Chapter 1 - PolyU Institutional Research Archive

Preface
2006
~Myopia Research
but not
Research Myopic ~
iii
Abstract
Both in terms of the economic and social health aspects, the impact of
myopia epidemic is high and far-reaching. It is believed that myopia
development is a multifactorial disease but despite the intensity of myopia
research in recent years, the molecular mechanism behind the myopia
development is still not known. Global protein profilings and protein
identifications have become possible with the new emerging proteomic
technology using high resolution two-dimensional gel electrophoresis (2DE) and
mass spectrometry (MS). Base on the previous ground works using chick as a
myopia model, the present study explored if the chick retina is good tissue model
for studying the molecular basis of myopia with proteomic technology. It is
hypothesized that the study of retinal protein expressions may provide new
insight on the downstream pathophysiological cascades in the myopic eye
growth.
In the first stage of the study, an animal model of compensated ametropia
with chicks wearing goggles for different period was established. The protein
extraction and the 2DE procedures from protein separation to protein staining
were optimized experimentally. With an optimized proteomic workflow, the first
chick retinal proteome database using the Matrix-Assisted Laser Desorption
Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) was built in
the second stage of the study. A total of 155 protein spots in the 2-D gels
covering the 3-10 pH range were identified with manual in-gel digestion or using
an automated robotic system. To allow for a global view of retinal proteins, the
proteins were further classified according to their subcellular locations as well as
their molecular functions. Most of the proteins (about 71%) were found to be
iv
presented in the cytoplasm. Others resided in the endoplasmic reticulum (7.2%),
mitochondrion (7.2%), nucleus (5.6%), Golgi (3.2%), extracellular (1.6%) and
plasma membrane (0.8%). There were remaining proteins (2.4%) returning with
unknown subcellular location. Based on the gene ontology information, over
80% of the identified proteins fell into three major functional categories which
were “catalytic activity” (39%), “binding” (33%) and “transporter activity”
(10%). In the third stage, the differential protein expression of normal growing
chick eyes at three time-points was studied and the capability of the established
workflow in identifying candidate proteins in the early postnatal retinal growth
was investigated. Four up-regulated and three down-regulated protein spots were
found during the study period in which five of them could be successfully
identified and their possible roles in the ocular growth were discussed. At the
final stage, differential protein expressions in the emmetropization of chick retina
were studied using both pooled and individual retinal samples. Using different
experimental conditions with -10D, +10D and occluders for various deprivation
periods, two candidate proteins were found to be differentially expressed in 2D
gels in response to the treatments. In myopic eyes, Apolipoprotein AI (Apo-AI)
was found to be down-regulated while destrin; actin depolymerising factor, ADF
(Destrin) was found to be up-regulated in the defocused eye. Since these two
proteins have yet to be related in the myopic growth, their functional roles in
regulating eye growth through fibroblasts remodelling were explored and
generally discussed. The information may provide an important link in the
cascade of molecular activity during the myopia development.
In addition, the feasibility of applying an emerging novel two-dimensional
fluorescence difference gel electrophoresis (2D-DIGE) technique in search for
v
differential protein expressions in chick myopia was explored. Using a reverse
fluorescent CyeDyeTM experimental protocol, a number of differential expressed
retinal proteins were detected and identified after the chicks were wearing -10D
lens for 7 days. The 2D DIGE technology has the advantage of overcome some
technical bottlenecks in the traditional 2DE and it offers a high level of
confidence in comparing protein profiles across multiple gels.
vi
List of selected presentation and publications:
Poster and paper presentation:
1. Thomas C. Lam, K.K. Li, and M.R. Frost, “Proteomic analysis of
emmetropisation in the chick”. Presented at the Association for Research in
Vision and Ophthalmology (ARVO), May 2002, United States.
2. Thomas C. Lam, K.K. Li, Samuel C.L. Lo, and C.H. To, “Proteomic analysis of
Emmetropization in the chick” Presented at 9th International Myopia Conference,
November 2002, Hong Kong & Guangzhou.
3. Thomas C. Lam, Samuel C.L. Lo, and C.H. To, “Documentation of the changes
in protein profiles in developing chick retina by a proteomic approach”
Presented at 3rd International Proteomics Conference, March 2004, Taiwan.
4. C.H. To, Thomas C. Lam, Samuel C.L. Lo and Q. Liu, “Proteomic identification
of human retina protein using a high- throughput automatic robotic system”
Presented at 3rd International Proteomics Conference, March 2004, Taiwan.
5. Thomas C. Lam, K.K. Li, Samuel C.L. Lo, and C.H. To, “Differential protein
expressions in the emmetropisation of chick eyes” Presented at 10th
International Myopia Conference, July 2004, United Kingdom.
6. Thomas C. Lam, K.K. Li, Samuel C.L. Lo, and C.H. To, “Differential protein
expressions in the emmetropization of chick retina by a proteomic approach”.
Presented at the Association for Research in Vision and Ophthalmology (ARVO),
May 2005, United States.
7. Thomas C. Lam, Rachel Ka-man Chun, K.K. Li, Chi-Wai Do, Samuel C.L. Lo,
Jeremy A Guggenheim,and C. H. To, “A global retinal proteins expressions
involving compensated myopia by proteomic approach” Presented at 11th
International Myopia Conference, August 2006, Singapore.
vii
Publication:
Lam, T. C., Li, K. K., Lo, S. C., Guggenheim, J. A. and To, C. H. (2006). "A chick
retinal proteome database and differential retinal protein expressions during early
ocular development." J Proteome Res 5 (4): 771-84.
viii
Acknowledgements
I would like to express my very sincere thanks to my supervisors Professor
Chi-Ho To, Professor Chun-lap Lo and Dr. Jeremy Guggenheim. The idea,
advice, and patience I received have been and will continue to be invaluable to
me. My special thanks to my chief supervisor, Professor Chi-Ho To who have
demonstrated his enthusiasm and wisdom in research, encourage and trust me
unfailingly throughout these years.
I am eternally grateful for the friendship and sharing from my lab-mates and
colleagues KK, Rachel, Dennis, Marco, Sing, Forrest and Wing. They have given
me tremendous support and advices without which this project could not have
been possible. To Dr. Mike Frost, his guidance to my study during his time in
Hong Kong was a wonderful “gift” to my study and his efforts and contributions
to our laboratory are greatly appreciated.
I owe a deep thanks to Rita for her endless care and understanding during the
course of my postgraduate life. She sacrifices her planning and allows me to
pursue mine, and I am forever grateful for that from the bottom of my heart.
Finally to my dearest Mom, Dad and brother who have given me the utmost
love and support throughout the different stages of my study that could ever be
sufficiently repaid. You have all been great blessings to me.
ix
TABLE OF CONTENTS
Title page…………………………………………………………………….i
CERTIFICATE OF ORIGINALITY……………………….……………….ii
Preface……………………………………………………………………...iii
Abstract……………………………………………………………………..iv
List of selected presentation and publication……………………….……. vii
Acknowledgement……………………………………………………..…...ix
Table of Contents………………………………………………………...….x
List of Figures………………………………………………………….… xvi
List of Tables………………..…………………………………………...xxiii
Abbreviations…………………………………………………………....xxiv
Chapter 1: Literature review ............................................................1
1.1
The mystery of myopia ................................................................1
1.1.1
Definition of myopia ..............................................................1
1.1.2
Classifications of myopia.......................................................1
1.1.3
Myopia is an epidemic disease...............................................2
1.1.4
Current methods of myopia management ..............................4
1.1.4.1
Non-surgical methods ....................................................4
1.1.4.2
Surgical methods............................................................4
1.1.5
The impacts of myopia...........................................................5
1.1.6
Risk factors of myopia development......................................6
1.1.7
Causes of myopia ...................................................................8
1.1.7.1
Normal eye growth (emmetropization)..........................8
1.1.7.2
Disruption of emmetropization ......................................8
1.1.7.3
The genetic factor and myopia.......................................9
1.1.7.4
The environmental factor involved in myopia
development .................................................................................10
1.1.7.5
1.2
Myopia is a multifactorial condition ............................12
Animal studies in myopia development ...................................12
1.2.1
Chick as a primary animal model.........................................13
1.2.2
Other animal models in myopia research.............................17
1.2.3
Acquired myopia in humans ................................................18
x
1.3
Retina: the source of signal .......................................................18
1.3.1
The anatomy of retina ..........................................................18
1.3.2
Local retinal control: a sensorimotor centre.........................20
1.3.3
Possible molecular candidates and pathways in
emmetropization...................................................................................22
1.4
Proteomic technology review.....................................................25
1.4.1
A novel molecule: protein ....................................................25
1.4.2
Step towards the new “-omics” science ...............................25
1.4.3
2DE - classical proteomic approach.....................................26
1.4.4
Non-2DE proteomic approach .............................................28
1.4.5
Protein identification and databases.....................................29
1.4.5.1
Mass spectrometry .......................................................29
1.4.5.2
Bioinformatics: protein databases ................................32
1.4.6
1.5
Challenges in proteomic study .............................................34
Applications of proteomics ........................................................35
1.5.1
In general research ...............................................................35
1.5.2
In eye research......................................................................36
1.6
1.5.2.1
An overview .................................................................36
1.5.2.2
Retina Pigment Epithelium (RPE) ...............................37
1.5.2.3
Retina ...........................................................................38
1.5.2.4
Ocular diseases.............................................................41
Objectives....................................................................................43
Chapter 2: Experimental Methods and Materials........................45
2.1
Animals .......................................................................................45
2.1.1
Eggs, supply and breeding ...................................................45
2.1.2
Goggles application..............................................................46
2.1.3
Refraction and growth measurement ...................................47
2.1.4
Dissection of retina and sample collection...........................48
2.2
Equipment and reagents............................................................49
2.3
General experimental workflow ...............................................49
xi
Chapter 3: Results of chick basal data measurement...................51
3.1
Statistical calculation .................................................................51
3.2
Refraction and body weight changes........................................51
3.2.1
Normal emmetropization .....................................................51
3.2.2
Astigmatic changes ..............................................................52
3.2.3
Compensated myopia ...........................................................53
3.2.4
Compensated hyperopia .......................................................56
3.2.5
Form deprivation myopia.....................................................58
3.2.6
Body weights........................................................................59
3.3
Discussion....................................................................................60
3.3.1
Refraction.............................................................................60
3.3.2
Body weight change.............................................................62
Chapter 4: Optimisation of experimental procedures…………..64
4.1
Introduction ................................................................................64
4.2
Retinal proteins extraction ........................................................64
4.2.1
Aims .....................................................................................64
4.2.2
Sequential extraction............................................................65
4.2.2.1
Buffer solution .............................................................65
4.2.2.2
Procedures ....................................................................65
4.2.2.3
Result and comment.....................................................66
4.2.3
Single buffer (EB5) extraction .............................................68
4.2.4
Discussion ............................................................................68
2D gel staining ............................................................................70
4.3
4.3.1
Coomassie blue stain............................................................70
Background and aims...................................................70
4.3.1.2
Procedures ....................................................................71
4.3.1.3
Results and comments..................................................73
4.3.1.4
Conclusion ...................................................................77
4.3.2
4.3.1.1
Silver staining ......................................................................78
4.3.2.1
Background and aims...................................................78
4.3.2.2
Procedures ....................................................................79
4.3.2.3
Results ..........................................................................81
xii
4.3.2.4
Conclusion ...................................................................87
Chapter 5: Assembly of chick retinal protein database................89
5.1
Introduction ................................................................................89
5.2
Experimental procedures ..........................................................89
5.2.1
Retinal samples ....................................................................89
5.2.2
2D gel electrophoresis..........................................................90
5.2.3
Protein detection and image analysis ...................................90
5.2.4
Protein identification............................................................91
Manual processing .......................................................91
5.2.4.2
Processing using the robotic system ............................94
5.3
5.2.4.1
Results and discussion ...............................................................96
5.3.1
Protein identification result ..................................................96
5.3.2
Protein classifications.........................................................102
5.3.2.1
Subcellular locations ..................................................102
5.3.2.2
Molecular functions ...................................................103
5.3.2.3
Biological functions ...................................................105
Building the chick proteome database ...............................105
5.3.3
5.4
Conclusion.................................................................................108
Chapter 6: Normal chick retinal protein expression ..................110
6.1
6.2
An intra- vs. inter animal comparison ................................... 110
6.1.1
Introduction ........................................................................ 110
6.1.2
Experimental procedures.................................................... 110
6.1.3
Results ................................................................................ 112
6.1.4
Discussion .......................................................................... 117
6.1.5
Conclusion .........................................................................120
Developmental retinal profiles changes..................................121
6.2.1
Introduction ........................................................................121
6.2.2
Experimental procedures....................................................121
6.2.3
Results and discussion .......................................................123
6.2.3.1.
Animal growth ...................................................123
6.2.3.2.
Different protein expressions .............................123
xiii
6.2.3.3.
Protein identification..........................................126
PMF result..................................................................................126
Protein expressions in the retinal growth process ......................129
6.2.4
Conclusion .........................................................................132
Chapter 7: Differential protein expression in the emmetropization
of chick retina .................................................................................133
7.1
Experimental procedures ........................................................133
7.2
Results .......................................................................................135
7.2.1
Experiment 1: (7 days -10D, pH 3-10)...............................135
7.2.2
Experiment 2: (5 days -10D, pH5-8 and pH 3-6)...............137
7.2.3
Experiment 3: (3 days -10D, pH 5-8).................................140
7.2.4
Experiment 4 (3 & 5 days -10D, pH 5-8; sequential
extraction ) .........................................................................................143
7.2.5
Experiment 5: (3 hours & 7 hours of -10D lens wear, pH 5-8)
145
7.3
7.4
7.2.6
Experiment 6 (4 days of +10D lens wear, pH 5-8) ............149
7.2.7
Experiment 7 (3 days form deprivation, pH 5-8)...............152
7.2.8
Protein identifications of spot A and spot B.......................153
Discussions ................................................................................154
7.3.1
Apolipoprotein AI, Destrin and myopia: a possible link?..154
7.3.2
Nutrition and myopia regulation ........................................163
Conclusion.................................................................................167
Chapter 8: An initial test of DIGE application in the study of
differential protein expression of chick retina.............................168
8.1
Background...............................................................................168
8.2
Experimental procedures ........................................................169
8.3
Results and Discussion.............................................................175
8.3.1
Refractive errors changes in chick eyes .............................175
8.3.2
Protein Profiles of CyDyesTM labelled retinal proteins....175
8.3.3
Image analysis by DeCyder DIA .......................................178
8.3.4
Image analysis by DeCyder BVA ......................................180
xiv
8.4
8.3.5
Effect of CyDyesTM reciprocal stain ..................................182
8.3.6
Decyder analysis after the second phase electrophoresis...183
8.3.7
Protein identification by MALDI-TOF MS .......................191
Conclusion.................................................................................204
Chapter 9: Summary and conclusions .........................................206
APPENDIX 1. .................................................................................209
APPENDIX 2. .................................................................................227
APPENDIX 3. .................................................................................241
REFERENCES...............................................................................254
xv
List of Figures
Figure 1. Schematic diagram of images focused in emmetropic and myopic
eyes. Modified from URL: http://www.webbandlucas.co.uk [accessed
2005 Oct 15th]...........................................................................................1
Figure 2. Changes in prevalence of myopia (≤-0.25 D) in school-age children
in Taiwan from 1983 to 2000. (Adapted from Morgan and Rose, 2005)
....................................................................................................................3
Figure 3. Schematic representation of the typical ten retinal layers in
vertebrate eye. Visual stimuli are detected in the (1.) photoreceptors
(rod and cone cells) and then transmitted through (2.) bipolar cells to
the (3.) ganglion cells where the signals are sent to the visual cortex in
the brain through the axons / nerve fibres converging at the optic
nerve head. Horizontal cells, amacrine cells and interplexiform cells
form the “lateral” pathways (Adapted from the teaching material of
e-learning team, school of optometry, the Hong Kong Polytechnic
University)...............................................................................................19
Figure 4. Schematic diagrams showing the structures of the (1.)
photoreceptor cells (cone and rod cells which convert visible light into
action potentials) and different types of (2.) bipolar cells (which
synapse with the photoreceptors and ganglion cells and transmit
signals) and (3.) ganglion cells (which serve as the final output
neurons to forward the signals in term of action potentials to the
brain). Ganglion cells are classified into different types according to
their morphological characteristics (Adapted from the teaching
material of e-learning team, school of optometry, the Hong Kong
Polytechnic University)..........................................................................20
Figure 5. Compensated emmetropization was unilaterally induced in young
chicks. The Velco-goggle devices were positioned on chick eyes and
the optical centre of the lens aligned with the pupil centre. ...............47
Figure 6. The posterior eye cup was hemisected for harvesting retinal tissue.
..................................................................................................................48
Figure 7. A typical experimental proteomic workflow in this study..............50
xvi
Figure 8. The mean refractive error changes in both eyes of chicks during
the first 20 days post-hatching. Error bars, SEM. ..............................52
Figure 9. The number of refractive astigmatism (against-the-rule,
with-the-rule) and spherical error in normal growing chicks............53
Figure 10. The effects of -10D lens wear on refractive development at
different onset of lens wearing. Group A, B, C and D represented lens
wearing age (onset) at 1-day old, 3-day old, 4-day old and 14-day old
respectively. The data plotted are the mean paired initial and final
refractive errors between the experimental eyes and the control eyes.
Error bars, SEM with number of animals were shown in parentheses.
The refractive errors were significantly different (p<0.01, paired
t-test) between the treatment and control eyes in all treatment
periods. ....................................................................................................55
Figure 11. The amount of refractive error difference between the
experimental eyes and paired control eyes (defocus-control) at the
end of lens treatment. Day 1 to 14 were the onset days of lens
application. Values are mean ± SEM (error bars) with number of
animals in parentheses...........................................................................56
Figure 12. The effects of +10D lens wear on refractive development at
different starting age of lens wearing. Group A and B represented
treatment onset of 3-day old and 4-day old respectively with number
of animals in parentheses. The data plotted are the mean paired
initial and final refractive errors between the experimental eyes and
the control eyes. Error bars as SEM were shown. The refractive
errors were significantly different (p<0.01, paired t-test) between the
treatment and control eyes in all treatment periods. ..........................57
Figure 13. The refractive development of light-proof black goggles wear on 1
day old chicks for periods of 3 days, 5 days and 7 days with number
of animals in parentheses. The data plotted are the mean paired
initial and final refractive errors between the experimental eyes and
the control eyes. Error bars as SEM were also shown. The refractive
errors were significantly different (p<0.01, paired t-test) between the
treatment and control eyes in all treatment periods. ..........................58
xvii
Figure 14. The final refractive errors of the experimental eyes and paired
control eyes after 3, 5 and 7 days of form deprivation. Values are
mean ± SEM (error bars) with the number of animals in parentheses.
..................................................................................................................59
Figure 15. The body weights (in grams) of normal (solid line) and treatment
chicks (broken line). Error bars as SEM was shown. .........................60
Figure 16. Daily changes in the weight of developing white leghorn embryo.
(Data based on A. L. Romanoff, Cornell Rural School Leaflet,
September, 1939). ...................................................................................63
Figure 17. Diagrams showing the Micro-Dismembrator unit (A), the teflon
chambers (B) and the different types of grinding balls (C)................66
Figure 18. The sensitivity of nine different coomassie blue staining methods.
A serial dilution of 400, 200, 100 ng of total marker proteins per lane
was separated by 12% mini-gels...........................................................73
Figure 19. The staining performance of four selected coomassie blue staining
methods (N1, N4, R and hot R350 as descried in (Table 4). Protein
profiles of 200μg of EB5 soluble retinal proteins were separated by
two-dimensional
gel
electrophoresis.
Isoelectric
focusing
was
performed using 11 cm (pH 5-8) IPGs followed by separation on 12%
mini polyacrylamide gels in the second dimension of electrophoresis.
..................................................................................................................75
Figure 20. The peptide peaks of two different protein spots (spot A and spot
B) detected by MALDI-TOF MS. For each protein, the upper (in blue)
peak profile was from gel stained by the hot R350 protocol while the
lower (in red) peak profile was from gel stained by the colloidal R
protocol. The same protein ID could be correctly identified by PMF
regardless the different staining protocols for each spot. ...................77
Figure 21. The detection sensitivity of the optimized silver stain protocol. A
serial dilution of the Perfect Protein™ Markers was separated on a
12% 1-D mini gel. The protein amount per each band was 25 ng,
12.5ng, 6.3ng, 3.1ng and 1.6 ng respectively for lanes 1 to 5 except for
the 2x band which has double amount of proteins..............................87
xviii
Figure 22. The workflow of a robotic system for MALDI-TOF MS protein
identification. ..........................................................................................96
Figure 23. 2-D chick retinal proteins profile resolved in 12% acrylamide gel
of pH 3-6. The annotated spots were excised and the proteins were
identified by PMF using MALDI-TOF MS..........................................97
Figure 24. Computer merged 2-D chick retinal proteins profile resolved in
12% acrylamide gel between pH 5-8 with a separated section
covering pH 8-10. The annotated spots were excised and the proteins
were identified by PMF using MALDI-TOF MS. ...............................98
Figure 25. Classification of retinal proteins identified by MALDI-TOF MS
according to their predicted subcellular locations. ...........................103
Figure 26. Classification of retinal proteins identified by MALDI-TOF MS
according to their molecular functions based on the Gene Ontology.
................................................................................................................104
Figure 27. Further classification of retinal proteins (of Figure 23) according
to their catalytic functions. ..................................................................104
Figure 28. The protein profiles of three pairs of normal retinae separated
with pH5-8 IPG strips and 12% SDS-PAGE in a Dodeca cell are
shown. The gels were stained with Biosafe Colloidal Coomassie blue
G250 premixed solution. (IEF: isoelectric focusing; Da: Dalton; RE:
right eye; LE: left eye.) ........................................................................ 113
Figure 29. Scatter plots of the matched spots according to the Od (optical
density). A.: A typical intra-animal protein profile comparison
between the right and left retinae of chick #2. B.: A typical
inter-animal protein profile comparison between the right retinae of
chick #2 and chick #3. (Higher false up-regulation as indicated in
arrow). ................................................................................................... 116
Figure 30. Enlarged panels showing intra- and inter- animal differences in
the 2D gels of chick #2 and #3. Gel spots were converted to greyscale
and the spot boundaries were detected by Melanie 4 software. A.: The
spot intensities (Od) were represented as numeric values according to
the automatic gel analysis data. (t: test spot, ref: reference spot). B.:
Two-dimensional and corresponding three-dimensional spot patterns
xix
comparison for both eyes of chick #2 and #3..................................... 119
Figure 31. Two-dimensional maps of pooled chick retinal proteins at 3 time
points of 3-day old (PN3), 10-day old (PN10) and 20-day old (PN20).
A total of 60 μg (20 μg from each individual, 3 chicks in each group)
soluble proteins in each time point were separated on the IPG strips
covering pH 3-10, followed by 12% SDS-PAGE. The gels were
stained with MS-compatible silver stain (2-D gels for the left eye were
shown as an example). Differentially expressed protein areas were
shown in blocks. (B) Relevant gel sections in blocks were magnified
and the differentially expressed proteins were marked in arrows or
circles. Two spots were found to be down-regulated (#D1 & #D2)
whereas 4 spots were found to be up-regulated (#U1, #U2a, #U2b &
#U3). (C) Protein changes were expressed in term of spot volume
(mean ± SEM, n=2 for right and left eyes, each consists of a pool of 3
chicks) which is the integration of optical density over the spot area,
for the 6 differentially expressed spots...............................................125
Figure 32. Enlarged panels showing the differential retinal protein
expressions (in arrows or circles) during normal postnatal retinal
growth in both eyes between PN3 and PN20. Two-dimensional gels
were
generated
using
narrower
pH
5-8
IPG strips.
Two
down-regulated proteins (#D1 & #D2) and 4 up-regulated proteins
(#U1, #U2a, #U2b & #U3) were found similar to the findings in
Figure 31. Three new and additional differentially expressed proteins
(#D3, #U4 and arrows indicated in #U1) were found with narrow pH
range (5-8).............................................................................................126
Figure 33. Biotools PMF data (left) and matrix science Mowse score (right)
for the identified retinal proteins spots (#D1, #D3, #U2a, #U2b, #U1,
#U3) involving in the normal ocular growth. The red peaks in PMF
data represented peptides that were matched to the specific NCBI
protein database. ..................................................................................130
Figure 34. Proposed cascades of myopia regulation by Apolipoprotein AI
and Destrin/ADF proteins. ..................................................................166
Figure 35. A schematic diagram outlines the logics of the DIGE experimental
setup and the data analysis by DeCyder Differential Analysis
xx
Software. The three image profiles of pre-labelled proteins were
individually scanned at their excitation wavelengths by a Typhoon
fluorescence scanner. Detection and quantitation of protein spots
(expressed as a ratio relative to the internal pool standard) were
performed by co-detection algorithms in the DIA (differential in-gel
analysis) module in the same gels. The spots’ profiles across multiple
gels were compared by matching all protein spots amongst different
pool standards to the master standard (in which the highest number
of protein spot was detected) using the BVA (biological variation
analysis) module. ..................................................................................174
Figure 36. Typical fluorescent protein profiles of the pre-labelled retinal
tissues by different CyDyes (Cy3 for treated eyes; Cy5 for control
eyes; Cy 2 for the pooled standard). The labelled retinal samples of
each animal were mixed prior to 2-D PAGE. Each gel contained 50μg
total protein separated by a pH 5-8 IPG strip in the first dimension
and 12% linear polyacrylamide gel in the second dimension
electrophoresis. Relevant images were captured by excitation with
different lasers using the Typhoon 9400 Variable Mode Imager. ....177
Figure 37. Histograms of the normalized spot volumes within a co-detected
image pairs using DIA module for two animals. The diagram showed
the total number of spots against log volume ratio simulated a
normal distribution (indicated by the red line). By applying the ±
2SD filter (the black vertical lines), most of the spots (green spots) fell
within the constraint (ratio = 1, or log [volume ratio] = 0) while the
blue spots indicated a volume increase and the red spots indicated a
volume decrease in the treatment eyes. ..............................................179
Figure 38. A typical retinal DIGE gel image showing the annotations and
locations of differential protein expressions in response to -10D lens
wearing. The treatment and control samples were labelled with
different CyDyes and mixed in 50:50 ratio and separated in 12%
linear gels. Image analysis was performed with the DeCyder BVA
module to identify the changes in protein amount. The up-regulated
proteins were marked in blue colour while the down-regulated
proteins were marked in red colour....................................................181
xxi
Figure 39. examples of the Cy3 and Cy5 dyes reciprocal labelling effect for
the 22 filtered differentially expressed protein spots (indicated by
arrows) between Gel 1 (treated sample was labelled by Cy3) and Gel
3 (treated sample was reciprocally labelled by Cy5). All gel sections
were captured by the ImageMasterTM 5 image analysis software using
the gel stacking function in which up-regulated proteins were
simulated as blue colour while down-regulated proteins were
simulated as red colour. Similar protein amount between the
defocused and control eyes were shown in dark colour. The
differential expressions were found to be consistent when using either
CyDyes...................................................................................................183
Figure 40. The DIGE gel image after a second phase electrophoresis to
resolve the higher molecular weight proteins. Proteins with molecular
weight less than about 25 kDa ran off the gel. Comparing to Figure
38, four additional spots (in circles) were found which have
significant differential protein expressions. The up-regulated proteins
were marked in blue colour while the down-regulated proteins were
marked in red colour............................................................................185
Figure 41. The comparative individual data (with fold changes and paired
t-test values) for those filtered spots by Decyder software.
Up-regulated proteins were shown in panel (a) while down-regulated
proteins were shown in panel (b). Graphical views showed the
standardized log abundance of spot volume (y-axis) against the
changes of proteins between the control and treatment groups (x-axis)
in all 4 gels. Typical 3-D views were also shown for each spot pair. 190
xxii
List of Tables
Table 1. A list of chromosomal localisations / candidate genes and their
involvements in human myopia. ...........................................................10
Table 2. A List of publicly accessible peptide-mass fingerprinting servers...32
Table 3. The procedure of sequential extraction and recovery of retinal
protein samples. Solution 1 to solution 4 represent Tris buffer, urea
containing cocktail, urea and thiourea combination cocktail and SDS
buffer respectively. R1 was soluble proteins in solution 1 while R1.1
and R1.2 were proteins remained after two consecutive washes.
R2-R4 were soluble proteins collected from solution 2 to solution 4. 67
Table 4. A list of coomassie blue staining protocol. .........................................72
Table 5. A common silver staining procedure with the functions of each step.
..................................................................................................................79
Table 6. The working protocol of an optimized MS compatible silver stain.86
Table 7. A reference mass list of known peptides contamination which were
excluded in PMF. ....................................................................................93
Table 8. Brief functions of the ten abundant chick retinal proteins identified
by MALDI-TOF MS. ...........................................................................100
Table 9. Brief functions of the five differentially expressed proteins (six spots)
in the normal postnatal chick retinal growth. ...................................128
Table 10. The experimental design of CyDyes minimal labelling for each
retinal sample in the DIGE study. A total of 150 μg labelled proteins
were loaded on each gel for 2D electrophoresis. #1 and #2 represented
two individual chicks. ..........................................................................171
Table 11. A list of differentially expressed chick retinal proteins after 7 days
-10D lens treatment. The proteins were detected by DecyderTM
analysis software using DIGE approach and were identified by
MALDI-TOF MS..................................................................................201
xxiii
Abbreviations
o
C
degrees in Celsius
2D PAGE
two-dimensional polyacrylamide gel electrophoresis
2DE
two-dimensional gel electrophoresis
ASB14
myristic amidosulphobetaine
BSA
bovine serum albumin
CHAPS
3-[(3-cholamidopropyl)-dimethylammonio]-1-propanesulfonate
CNS
central nervous system
D
dioptre
DHB
2,5-Dihydroxybenzoic acid
DIGE
Fluorescence 2-D Difference Gel Electrophoresis
DTT
Dithiothreitol
EB
extraction buffer
ESI
electrospray ionization
EST
expressed sequence tag
FDM
form-deprivation myopia
g
grams
GI
GenInfo Identifier
HCCA
α-Cyano-4-hydroxycinnamic acid
HDL
high-density lipoprotein
HUGO
Human Genome Organisation
HPLC
high performance liquid chromatography
HUPO
Human Proteome Organisation
IEF
isoelectric focusing
IOP
intra-ocular pressure
IPGs
immobilized pH gradients
LE
left eye
LIH
lens-induced hyperopia
LIM
lens-induced myopia
M
molar
MALDI-TOF
matrix-assisted laser desorption/ionization time of flight
mRNA
messenger ribonucleic acid
MS
mass spectrometry / mass spectrometer
xxiv
MW
molecular weight
m/z
mass-to-charge ratio
NIH
National Institute of Health
OD
optical density
pIs
isoelectric points
ppm
part(s) per million
PIR
Protein Information Resource
PMF
peptide mass fingerprinting
PN
postnatal
PSD
post source decay
PTMs
post-translational protein modifications
RA
retinoic acid
RE
right eye
RPE
retinal pigment epithelium
RT-PCR
reverse transcription polymerase chain reaction
SB3-10
caprylyl sulphobetaine
SDS-PAGE
sodium dodecylsulfate polyacrylamide gel electrophoresis
S.E.
equivalent sphere
S/N
signal to noise ratio
TCA
Trichloroacetic acid
TFA
Trifluoroacetic acid
TIF
tagged image file format
TM
trabecular meshwork
Tris
tris (hydroxymethyl) aminomethane
UniProt
Universal Protein Resource
VIP
Vasoactive intestinal peptide
xml
Extensible Markup Language
m
milli-
(10-3)
μ
micro-
(10-6)
n
nano-
(10-9)
p
pico-
(10-12)
xxv
Chapter 1: Literature review
1.1 The mystery of myopia
1.1.1 Definition of myopia
Myopia, or better known as near-sightedness or short-sightedness, is the most
common refractive defects of the eye. It is a spherical error of refraction in which
the image of distant object was formed in front of rather than on the retina (focal
plane) when the eye is in a relaxed or unaccommodated state (Heron and
Zytkoskee 1981; Curtin 1985) (Figure 1). The extent of blurred vision is
measured in dioptre (D) which is the power of the concave (negative) lens
required to focus the images. In humans, 0.3mm discrepancy between retina and
projected image focal plane results in about 1 D of refractive error (Hirsch and
Weymouth 1991).
Figure 1. Schematic diagram of images focused in emmetropic and myopic eyes.
Modified from URL: http://www.webbandlucas.co.uk [accessed 2005 Oct 15th].
1.1.2 Classifications of myopia
Myopia can be broadly classified according to the severity of refractive error
as low myopia (<3.00 D), medium myopia (3.00 D-6.00 D) and high myopia
1
(>6.00 D). It can also be classified by clinical entity as simple myopia, nocturnal
myopia (Leibowitz and Owens 1975), pseudomyopia (Koyama 1970),
degenerative myopia (Curtin 1985), In addition, it can be described as induced
(acquired) myopia due to exposure to various external stimuli such as
pharmaceutical agents (Amos 1987). Grosvenor categorized the myopia into four
groups based on the age of onset of myopia (Grosvenor 1987):
i)
Congenital myopia starts at birth and remains through infancy and
childhood.
ii)
Youth-onset myopia starts from about five years of age to teenage
years.
iii)
Early adult-onset myopia starts between the ages of 20 to 40.
iv)
Late adult-onset myopia starts after 40 years.
It is important to note that the distinctions among different categories are far
from clear-cut and they may be classified differently upon different perspectives.
1.1.3 Myopia is an epidemic disease
The prevalence of myopia varies among different populations/races and also
varies according to the diagnostic criteria used. In general, myopia has been and
is continuing to be a global epidemic problem. The prevalence of myopia in
studies among different age groups was found to be about 30%, 50%, 49.7% and
19.4% in the United States (Sperduto et al. 1983), Britain (Logan et al. 2005),
Sweden (Villarreal et al. 2000) and France (Berdeaux et al. 2002) respectively.
Myopia is more severe in the South East Asia regions. It affected about 74% of
high school students in Singapore (Quek et al. 2004), 66% of teenagers in Japan
(Matsumura and Hirai 1999), 71% of the population (Goh and Lam 1994) and up
2
to 88% of teenagers in Hong Kong (Lam et al. 2004).
More importantly, this refractive anomaly has been increasing in a wide range
of ages (Edwards and Lam 2004). Morgan and Rose have recently reviewed the
myopia prevalence in different populations of different age groups. They have
found an increase in the prevalence of common myopia as well as high myopia
worldwide (Morgan and Rose 2005). An example is shown in Figure 2 which
indicates the marked increase in the myopia prevalence in the early school years,
in addition to the general increase in prevalence within the population
.
Figure 2. Changes in prevalence of myopia (≤-0.25 D) in school-age children in
Taiwan from 1983 to 2000. (Adapted from Morgan and Rose, 2005)
It is estimated that the number of myopes in the world will grow from 1.6
billion presently to a staggering 2.5 billion by 2020 (data obtained from The
Vision Cooperative Research Centre. www.visioncrc.org). The global escalating
prevalence of myopia is alarming and warrants concern.
3
1.1.4 Current methods of myopia management
1.1.4.1
Non-surgical methods
The use of optical devices such as spectacles (single vision, bifocal or
multifocal lenses) or contact lenses (soft contact lens or rigid gas permeable,
RGP lens) remains the most common method of myopia management.
Non-surgical method of corneal reshaping by orthokeratology (ortho-k lens)
(Kerns 1978; Cho et al. 2005) has been another popular approach recently. It is a
FDA (Food and Drug Administration, US) approved procedure for the temporary
reduction or control the progression of low to moderate myopia using special
design RGP lens. The new generation of overnight lens-wearing protocol
provides a reversible alternative to refractive surgery. Besides, medical
(pharmaceutical) management by topical administration of cycloplegic agents
such as atropine (Shih et al. 1999; Kennedy et al. 2000) or cyclopentolate (Yen et
al. 1989) to relax accommodation has also been proposed to retard myopia
progression. In addition, various vision training has been proposed to control
myopia by reducing accommodation in myopia (Ciuffreda and Ordonez 1998).
(Friedman 1981) but conclusive data on its effectiveness has yet to be produced.
On the other hand, psychological strategies such as hypnotic treatment or
behavioral manipulations (Raz et al. 2004) have also been explored but the effect
is still controversial.
1.1.4.2
Surgical methods
Radial keratotomy (RK) is the first generation of refractive surgeries to
correct myopia. It applies spoke-like radial pattern of incisions by a
diamond-tipped instrument at the paracentral cornea in order to flatten the central
cornea (Hanczyc 1991). This approach is later replaced by excimer laser
4
photorefractive keratectomy (PRK). It is a computer-assisted procedure in which
the corneal power is decreased after excimer laser incision and healing (Flowers
et al. 2001). Another similar approach is automated lamellar keratomileusis
(ALK) which flattens the central cornea by removing a thin layer of anterior
cornea using a microkeratome (Price et al. 1996). In recent years, laser in situ
keratomileusis (LASIK) has become the most popular surgical treatment due to
its high successful rate. The theory is similar to ALK but the corneal stromal
tissue is removed by laser beam after creating a corneal flap using a mechanical
microkeratome (Pietila et al. 1999). Another relatively new refractive surgery
after LASIK is named Laser-assisted subepithelial keratectomy (LASEK). The
procedure is similar to the combination of the corneal surface treatment of PRK
with the added comfort of LASIK (Dastjerdi and Soong 2002). Although the
surgical procedure is less invasive the recovery time takes longer. Moreover,
phakic IOL (intraocular lenses) is an alternative surgical treatment to corneal
modification in which an artificial lens is implanted into the anterior chamber in
order to correct the myopia. However, its potential application is still under
investigation (Menezo et al. 2004).
While there are many options for managing myopia, the suitability of specific
procedure varies according to individuals. Considerations such as motivation,
degree of myopia, occupation, age, cost, safety may determine the choice and
outcome of the treatment.
1.1.5
The impacts of myopia
Myopia problem carries significant financial implications for both the
individuals and community. The costs that result include those of visual aids,
5
social services and public education. Significant social cost is inflicted by
myopia induced visual impairments which include human cost of quality of life,
impairment of personal image and loss of productivity or workforce. According
to the Health Care Financing Administration, the United States spent about US$
8.1 billion on vision products and required a total of 50 million eye examinations
in 1990 (Levit et al. 1991). Globally, myopia treatment with PRK costs about
US$ 4.6 billion (Javitt and Chiang 1994). Apart from the financial implications,
myopia-related retinal degeneration and impairments are also serious health
concerns. Pathological myopia is progressive in nature and commonly includes
myopia of more than 6D or with a long axial length (>26-27 mm) (Miller and
Singerman 2001). Pathological myopia is also associated with a number of
sight-threatening ocular diseases such as cataract (Lim et al. 1999), posterior
vitreous detachment (PVD) (Akiba 1993), glaucoma (Jonas and Budde 2005),
retinal detachment (Burton 1989; Banker and Freeman 2001) and these
conditions can be sight-threatening (Cedrone et al. 2005). With the increasing
prevalence of myopia, a higher prevalence of its related complications will be
anticipated in the near future. Therefore, myopia is not merely a simple refractive
condition that brings minor inconvenience, it can also be a severe
sight-threatening condition that has significant social and clinical implications.
1.1.6
Risk factors of myopia development
Many previous studies have looked for the risk factors in myopia
development. One of the most well known risk factors is the family history of
myopes. Data have showed that there is a higher prevalence of myopia in
children with myopic parents and their myopia was evident even in their first few
6
years of schooling (Zadnik et al. 1994). Study also suggested there is a high risk
of myopia progression in children with against-the-rule astigmatism (Mutti and
Zadnik 1995) or if they have myopia at early age (Grosvenor and Goss 1999).
Besides, a steep corneal curvature and a high ratio of axial length to corneal
radius (AL/CR) could also be important risk factors (Grosvenor 1988;
Yebra-Pimentel et al. 2004). More recently, the ocular accommodative and
vergence systems were also found to be associated with myopia development.
These include near esophoria (Goss and Jackson 1996), low positive relative
accommodation, decreased accommodative response at near (McBrien and
Millodot 1986) and a more convergent blur position of the “zone of clear single
binocular vision” in the fusional vergence reserve test at near (Goss and Jackson
1996).
Another well known risk factor is the amount of near work either in
children during school age or in adult exposed to a high education level. (Kinge
et al. 2000; Hepsen et al. 2001). It was previously thought that the extraocular
muscles (EOMs) tension on the eyeball during reading may play a role in myopia
development. The horizontal scanning movement which imposes constant
pressure on the oblique muscles and in turn on the globe over time might
somehow cause eye elongation (Greene 1980; Doonan 1984). Similar
phenomenon was later found using the wavefront measurements during
accommodation in which the central lens curvature steepened while the
peripheral curvature flattened (Roorda and Glasser 2003). Therefore, it was
concluded that youngsters who were involved in intensive professional studies
such as engineering and law might be more myopic (Zadnik and Mutti 1987;
Kinge et al. 2000).
7
The effect of accommodation during reading on myopic changes has been
well characterized. A phenomenon called Nearwork-Induced Transient Myopia
(NITM) which is defined as the short-term myopic shift in the far point
immediately following a sustained near visual task, has recently been associated
with myopia development (Ong and Ciuffreda 1995; Wolffsohn et al. 2003). The
cumulative effect of NITM in promoting myopia progression has yet to be
ascertained.
1.1.7
Causes of myopia
1.1.7.1 Normal eye growth (emmetropization)
Emmetropization is a developmental process by which the eye grows
towards a condition that is free of refractive error (Sorsby and Leary 1969). This
process starts soon after birth and results in a leptokurtotic distribution of
refraction at about emmetropia (Rabin et al. 1981). Longitudinal data has
demonstrated coordinated changes in a number of refractive components (cornea,
lens, axial length, etc) that eventually focus the distant image onto the retina.
However, the emmetropization process may fail sometime.
1.1.7.2 Disruption of emmetropization
Myopia was originally thought to be caused by high IOP that leads to
ocular expansion but later study disputed this association (Edwards and Brown
1996). It is now known that myopia occurs when the refractive power of the eye
is too much (refractive myopia) or the eyeball is too long (axial myopia) to allow
the refracted images to focus on the retinal photoreceptors layer. The refractive
error can be due to steepened curvatures of the cornea and/or the lens, or it can
be due to the change in the refractive indices of the anterior humor chamber, the
8
crystalline lens and the vitreous body. However, axial myopia is by far the most
common type of myopia which is due to an elongation of the posterior vitreous
chamber (or a long axial length) predominantly (van 1961). The exact cause of
the elongation of the eyeball in myopia remains unknown.
1.1.7.3 The genetic factor and myopia
Myopia development has long been thought to be determined by genetic
factors. The most widely held hypothesis is hereditary. Evidence for genetic
association has been documented in studies of familial inheritance for high
myopia (Guggenheim et al. 2000; Saw et al. 2001; Rose et al. 2002; Liang et al.
2004). It is believed that the chance of developing myopia in offspring is higher
if both parents are myopic. Good research evidence from classical twin study
also indicated that genetic factor could influence the development of myopia.
Statistically significant difference in refractive errors was found in the pair-wise
intra-class correlation coefficient between monozygotic twins and dizygotic
twins, and the correlation between monozygotic twins was higher than that of
dizygotic twins (Hammond et al. 2001). Clinically, almost all recent data show
clear difference in myopia prevalence and progression according to different
ethnic groups with different gene pools; eg. myopia is a more severe problem in
the Asian than Western communities (Au Eong et al. 1993; Yeow 1994;
Kleinstein et al. 2003; Lam et al. 2004).
Nowadays, myopia is regarded as a complex (heterogeneous) disease in
terms of genetics. Several chromosomal loci for inherited nonsyndromic high
myopia have been reported in genome-wide scans. Recent genetic studies have
also suggested several candidate genes and identified several loci that may
contribute to certain variants of pathological myopia. A brief summary of these
9
findings is given in Table 1. However, these forms of high myopia can only
account for a limited number of myopia populations. Few attempts have been
made to define genes associated with the non-syndromic or common myopia.
Table 1. A list of chromosomal localisations / candidate genes and their
involvements in human myopia.
OMIM Myopia Chromosomal
no.*
loci
locations
Candidate genes Related eye diseases
Inheritance
Publication
(year)
310460 MYP1 Xq27-28
OPN1LW
Myopia; Bornholm eye disease X-LINKED
1990
160700 MYP2 18p11.3
TGIF
Myopia, high grade
autosomal dominant
1998
12q13;
KERA;
Myopia, high grade; Cornea
12q21-q23
LUM,DSPG3
plana congenita
autosomal dominant
1998
608367 MYP4 7q36
-
Myopia, high grade
autosomal dominant
2002
608474 MYP5 17q21-q22
COL1A1;RARA Myopia, high grade
autosomal dominant
2003
608908 MYP6 22q12-q13.1
-
-
2004
609256 MYP7 11p13
PAX6
-
2004
609257 MYP8 3q26
-
Myopia, high grade
-
2004
609258 MYP9 4q12
-
Myopia, high grade
-
2004
609259 MYP10 8p23
EGR3
Myopia, high grade
-
2004
603221 MYP3
mild/moderate myopia
Myopia, high grade; aniridia,
keratitis
*Online Mendelian Inheritance in Man (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=OMIM)
Apparently, heredity plays a significant role in human myopia development.
A vast number of studies have been carried out to map the inheritance patterns or
the genetic origin of myopia. However, these explorative activities are only
beginning and a clinical gene therapy solution is unlikely to be at hand in the
near future.
1.1.7.4 The environmental factor involved in myopia development
In addition to the genetic input, there is growing evidence to suggest that
myopia is not merely an inherited condition and environmental factors may also
contribute to its development. For example, a higher prevalence or higher
10
myopia was found:
i)
the geographic location was closer to seacoast or with less
sunshine (Daubs 1984);
ii)
people live in urban area (Saw et al. 2001);
iii)
there are more rigorous schooling with advanced technology
(Garner et al. 1999);
iv)
students experienced longer near work demand during term-time
(seasonal variation in refractive error) (Fulk et al. 2002);
v)
occupations involving intensive close work (Simensen and
Thorud 1994; Ting et al. 2004), and
vi)
people having “professional” occupations (Parssinen et al. 1985).
A classical study by Young et al. adds further weight to the notion that the
environmental factor is important in myopia development. They reported a
dramatic increase in myopia in the generation of Alaskan Eskimos when they
were exposed to western-style education system in their childhood (Young et al.
1969). Other studies showed that such rapid increase in myopia in recent years
could occur even in the same population due to unidentified reason (Wong et al.
2000; Edwards and Lam 2004). Although the exact reason for the recent increase
in myopia is unknown, these studies have highlighted that the process of
emmetropization towards a “refractive-error-free” status appears to fail in many
circumstances. It has been repeatedly shown in laboratory experiments with
young animals that the emmetropization process to emmetropic state could be
readily altered by manipulation of the visual environment or stimuli (Norton and
Siegwart 1995).
11
1.1.7.5 Myopia is a multifactorial condition
Although the nature versus nurture debate on myopia development
continues, it is experimentally difficult to clearly categorize myopia as purely
genetic or environmental. To complicate the issue further, individuals might be
genetically more liable to develop myopia if they are exposed to certain
environments. Some may become myopic at a younger age or have a rapid
progression of myopia. The modern theory of gene-environment interaction also
argues against a clear-cut dichotomy and suggests that both genetics and
environment are playing important roles in human development. Therefore it is
likely that both heredity and the environment contribute to myopia development
(so called a multifactorial disease) (Mutti et al. 1996) although to what extent the
genetic and environmental factors actually contribute to myopia is not clearly
defined.
1.2 Animal studies in myopia development
Relevant animal models are important experimental platforms to study
disease processes. These animal data enhance our understanding of similar
disease in human and provide insights on developing effective clinical treatment.
Previous animal studies have shed important light on the mechanism and
pathogenesis of myopia development. It was found that many neonate animals
demonstrated similar emmetropization process to humans so that the eye grows
towards a plano (zero dioptre, D) refractive status. This process of gradually
changing the higher refractive error at birth to emmetropia in the early growth
phase is very similar to the emmetropization process observed in human (Walls
1942).
12
1.2.1
Chick as a primary animal model
The chick embryo has long been a classical model in developmental
biology studies (Stern 1994; Dupin et al. 1998). Chick is one of the premier
vertebrate models for biological research (Langman and Cohn 1993; Wolburg et
al. 1999; Okano and Fukada 2001; Wong et al. 2003). In myopia research, the
white Leghorn chick (Gallus gallus domesticus) is the most widely used
non-mammalian animal model. The reasons for their popularity include:
z
Their eyes have excellent optical quality and good visual acuity shortly
after hatching (Over and Moore 1981) and they are able to compensate
rapidly to applied defocus or occlusion.
z
They have laterally displaced eyes with independent accommodation
which allow intra-animal comparative studies be readily carried out.
z
The rearing and maintenance costs are relatively low and chicks are
available all year round.
z
Their embryogenes are short and a large number of animals can be
obtained within a relatively short time.
z
Their postnatal parental care is minimal.
In terms of physiological and visual functions, chick eyes were also similar
to other mammals such as rabbits and guinea pig (Crewther 2000) and their
normal refractive development and emmetropization have found to be similar to
that of humans, but at a much faster rate (Wallman et al. 1981).
It has been shown that chick eyes demonstrate compensatory ocular
growth with ophthalmic lenses of different powers (Schaeffel et al. 1988; Irving
13
et al. 1992; Beresford et al. 2001) under normal light/dark cycle. That is, in
addition to the normal growth of the cornea and lens, the growth of axial length
is retarded and the eye becomes hyperopic with positive lens (lens-induced
hyperopic or LIH). Conversely, the axial length increases and the eye becomes
myopic with negative lens (lens-induced myopic or LIM). These induced
changes could be recovered if clear vision was restored without the ophthalmic
lens (Wallman and Adams 1987). In addition to lens treatment, the eyes also
elongate when wearing diffusers or occlusion (form-deprivation myopia or FDM)
to deprive the retina of clear images (Wallman et al. 1978). Although the induced
responses
in
these
two
approaches
were
similar,
lens-induced
and
deprivation-induced refractive errors were reported to differ in the time course as
well as the underlying biochemical changes (Schaeffel et al. 1995; Kee et al.
2001).
i)
Change of refractive error
Similar to human, the chick’s eyes are slightly hyperopic upon hatching and
they progress to emmetropia during normal development (Wallman et al. 1981).
The effect of lens-induced ametropia in chick eyes was found to be quite linear
for inducing lens powers between –10D to +15D (Irving et al. 1992). Hyperopic
defocus tends to have a stronger effect while myopic defocus seems to have a
relatively weaker effect on ocular growth. Typically, one week is enough for
complete refractive compensation for the power induced and the resulting
refractive errors were due mainly to the changes in axial length. (Schaeffel and
Howland 1991; Irving et al. 1992; Schmid and Wildsoet 1996). Compared to lens
treatment, form deprivation generally results in higher myopia (Beresford et al.
2001).
14
However, it is interesting to note that binocular form deprivation causes a
different effect. Yinon et al. experimented with 3 months of binocular lid suture
in chick, it was surprising to find that 7 days binocular occlusion and
dark-rearing (Yinon and Koslowe 1986) produced hyperopia rather than myopia
as reported in other studies (Schaeffel and Howland 1991). It was found that
significant corneal flattening (due to lack of daily photoperiod) has overridden
the effect of axial length increase (Gottlieb et al. 1987) and rendered the eye
hyperopic.
ii)
Changes of corneal power
Normal hatching chicks exhibited significant against-the-rule astigmatism
of which 60-90% was corneal. The decrease in astigmatism during normal
corneal development has been suggested as part of the emmetropization
process (Schmid and Wildsoet 1997). The corneal radius is constant for the first
four days of development and increases linearly similar to the other ocular
parameters (Irving et al. 1996). Irving et al also found that there was corneal
flattening with high plus lens wearing but not with minus lens wearing (Irving et
al. 1992).
iii)
Changes of the crystalline lens
It is generally believed that the focal characteristics of crystalline lens
remain constant during the eye growth despite its change in size, shape and
refractive index. It seems to contribute little to the refractive change in induced
ametropia studies (Troilo et al. 1987). There was also no significant change in
lens morphology, soluble protein content, thickness, weight or diameter after 7
days lens wear (Irving et al. 1992; Priolo et al. 2000). It was suggested that the
change in refractive power of lens may be genetically predetermined rather than
15
visually guided.
iv)
Changes of the ocular tissue in the posterior eye
The trend of thickness changes in the posterior chick eyes is very similar in
form-deprivated myopia and lens-induced myopia. However, the time course of
the axial length change is significantly faster in LIM than in FDM (Kee et al.
2001). There is general thickening in the cartilaginous sclera suggesting an
increase in extracellular matrix production, together with significant thinning in
the fibrous scleral layer (Christensen and Wallman 1991; Beresford et al. 2001).
Moreover, histological examination also found that there was about 20-25%
thickness reduction in the deprivated myopic retina accompanied by about
20-40% surface area increase (Liang et al. 1995). Further studies showed
significant chorodial thinning even within a few hours of induced myopia.
Choroidal thickening on the other hand was found in induced hyperopia or eye
recovering either from FDM or LIM (Wallman et al. 1995; Junghans et al. 1999;
Troilo et al. 2000).
v)
Change of eye size and dry weight
In a form-deprivated chick eye, there was a 65% increase in scleral dry
weight plus the enlargement in the eye size which implied an increase in
synthesis of the extracellular matrix (Christensen and Wallman 1991). The
change in the axial length of lens-induced eye was found to be linear
between –10D and +20D lenses. The eye was longer in myopic treated eye but
shorter in hyperopic treated eye (Irving et al. 1992). These refractive changes
have been explained by two mechanisms: (1) there are chorodial thickening and
reduced axial elongation in the myopic defocus compensation; whereas (2)
ocular elongation and scleral remodelling are taken place in the hyperopic
16
defocus compensation (Wildsoet and Wallman 1995).
vi)
Protein concentration
Cellular and protein changes were compared between the experimental
myopic and control eyes. No significant difference in the soluble protein content
in the sclera and cornea was found in some studies (Pickett-Seltner et al. 1988;
Pickett-Seltner et al. 1992) while moderate increase (15%) in soluble proteins in
7 days deprivated eye was observed in another study (Christensen and Wallman
1991). Furthermore, the protein concentration of the liquid component was found
to decrease but that of the gel component in vitreous was found to be increased.
Increased synthesis of proteoglycans in sclera had also been seen in
deprivation-induced eye growth (Rada et al. 1994). Recently, the protein
concentration of suprachorodial fluid was found significantly lower in the
induced myopic eye than control eye. Interestingly, it increased dramatically in
recovering myopic eyes (Pendrak et al. 2000). It is noted that although very
similar ocular growth responses to optical lenses and diffusers were found in
different studies, the eye growth response to visual deprivation seemed to vary
with different strains of chicken (Troilo et al. 1995).
1.2.2
Other animal models in myopia research
It is of interest that similar findings to induced ocular changes were also
seen in other animals. Studies in cats (Wilson and Sherman 1977), monkeys
(Wiesel and Raviola 1977), marmosets (Graham and Judge 1999), tree shrews
(Norton et al. 1977), pigeons (Bagnoli et al. 1985), Kestrels (Andison et al. 1992)
and recently mouse (Schaeffel et al. 2004) have all found that either lens-induced
defocus or form deprivation could lead to significant increase in myopia during
17
the postnatal eye growth. Moreover, similar compensated ocular growth was also
observed in lower vertebrates, such as fish (Kroger and Wagner 1996; Shen et al.
2005). The fact that this compensated eye growth occurs in many species
suggests that the emmetropization process is very conserved.
1.2.3
Acquired myopia in humans
In humans, excessive eye growth with axial elongation was found in
patients with congenital eyelid closure (O'Leary and Millodot 1979), ptosis
(Gusek-Schneider and Martus 2001), cataract (Rasooly and BenEzra 1988) or
vitreous hemorrhage (Mohney 2002), where some forms of visual deprivations
were incurred. However, it is unclear whether these forms of deprivation share
the same mechanism in the above animal models.
1.3 Retina: the source of signal
As shown above, there is substantial evidence that the eye can somehow
recognise the visual signals for eye growth. Growing evidences have shown that
the ocular growth mechanism may likely originate from within the eye itself.
1.3.1
The anatomy of retina
Retina is part of the central nervous system (CNS). It is a complex and
important component of the vertebrate’s visual system. Retina in all vertebrate is
composed of three layers of nerve cell bodies and two layers of synapses. It is an
easily visible neural extension of the brain which consists of a complex neural
network and different cellular microcircuits (Figure 3 and Figure 4). The
organization and signaling pathways involve precise interconnections vertically
18
through photoreceptors, bipolar to ganglion cells and laterally between amacrine
and horizontal cells. Functionally, the retina serves as the first site of image
reception and signal processing in the visual pathway.
Figure 3. Schematic representation of the typical ten retinal layers in vertebrate
eye. Visual stimuli are detected in the (1.) photoreceptors (rod and cone cells) and
then transmitted through (2.) bipolar cells to the (3.) ganglion cells where the
signals are sent to the visual cortex in the brain through the axons / nerve fibres
converging at the optic nerve head. Horizontal cells, amacrine cells and
interplexiform cells form the “lateral” pathways (Adapted from the teaching
material of e-learning team, school of optometry, the Hong Kong Polytechnic
University).
19
Figure 4. Schematic diagrams showing the structures of the (1.) photoreceptor
cells (cone and rod cells which convert visible light into action potentials) and
different types of (2.) bipolar cells (which synapse with the photoreceptors and
ganglion cells and transmit signals) and (3.) ganglion cells (which serve as the
final output neurons to forward the signals in term of action potentials to the brain).
Ganglion cells are classified into different types according to their morphological
characteristics (Adapted from the teaching material of e-learning team, school of
optometry, the Hong Kong Polytechnic University).
1.3.2
Local retinal control: a sensorimotor centre
In both chick and tree shrew models, experimental data have gradually
indicated the existence of a local control mechanism in the posterior eye. When
translucent occluders or minus-lenses were applied to selectively block either
nasal or temporal visual field, the corresponding area under deprivation became
myopic with local vitreous chamber enlargement and axial elongation while the
opposing area was unchanged (Hodos and Kuenzel 1984; Wallman et al. 1987;
Norton and Siegwart 1995; Diether and Schaeffel 1997). In addition, chicks
20
raised in cages with lower roof were found to produce corresponding myopic
shift in the inferior retina (Miles and Wallman 1990). Findings from avian’s eyes
showed that the compensated eye growth persisted even after accommodation
was impaired by removing the Edinger Westphal nuclei (E-W) (Schaeffel et al.
1990). In addition, disrupting the afferent nerve to the brain either by optic nerve
section or using intraocular tetrodotoxin (TTX) injection to block ganglion cell
activity failed to stall the emmetropization process although larger variation in
refraction was found (Troilo et al. 1987; Wildsoet and Wallman 1995; Wildsoet
and Schmid 2000).
Posterior to retina is an important vascular tissue, the choroid, which is
heavily innervated by the ciliary ganglion, superior cervical ganglia, ocularmotor,
trigeminal and facial nerves (Bill and Nilsson 1985). This choroidal vasculature
is essential to support metabolic needs for normal retinal function, especially in
species without the retinal vasculature as in the chicks. It was found that the
choroid changed its thickness in response to induced visual defocus dramatically.
The choroidal thickness appeared to adjust itself to meet the induced focal plane,
either by thickening in response to LIH or by thinning in response to LIM in
chicks (Wallman et al. 1995), tree shrews (Siegwart and Norton 1998) and
monkeys (Hung et al. 2000). Therefore, an intimate inter-relationship for signal
transfer towards sclera from the retina might be expected.
The evidence derived from both human clinical observations and animal
experiments suggest that retina may be the sensorimotor organ that plays a
critical role in controlling the compensated eye growth. The next question is how
the retinal images are analyzed and what specific neural signals set off the
cascade to regulate the axial eye growth and myopia development.
21
1.3.3
Possible
molecular
candidates
and
pathways
in
emmetropization
Although the underlying mechanism for regulating eye growth is unknown,
a number of possible “candidate compounds” are suggested to directly or
indirectly involve in the myopic growth in animal studies. These candidates
include diurnal oscillators such as Dopamine and Melatonin, Serotonin; others
include vasoactive intestinal peptide, retinoic acid and ZENK factor.
One of the earliest candidates that was studied extensively is Dopamine
(4-(2-aminoethyl)benzene-1,2-diol). It is a neurotransmitter and neurohormone
mainly found in nervous tissue. It was found to be reduced in amount and
decreased in its biosynthesis rate when the eye was form-deprived in chicks and
monkeys (Stone et al. 1989; Laties and Stone 1991). It was further shown that
dopamine agonists decreased the FDM and LIM (Stone et al. 1989; Schmid and
Wildsoet 2004) while dopamine antagonist increased the FDM (Iuvone et al.
1991; Schaeffel et al. 1995). It may seem that the level of dopamine is negatively
correlated to myopia development. However, conflicting data have shown that
dopamine concentration did not generally correlate well with positive or negative
lens treatments in chicks (Bartmann et al. 1994; Schaeffel et al. 1994). In
addition, it was found that the LIH and LIM could not be prevented even when
dopamine was completely depleted in fish. Therefore this study speculated that
the changes in the retinal dopamine might not be directly involved in
emmetropization (Kroger et al. 1999) and the role of dopamine in myopia
development is still unclear.
Serotonin (5-hydroxytryptamine) is a monoamine neurotransmitter
22
synthesised in the serotonergic neurons of retinal amacrine cells and the central
nervous system. Previous work has suggested a possible role in myopia
development for serotonin as it can interact with other neurotransmitters, such as
dopamine (Zifa and Fillion 1992). Serotonin in rat can cause vasoconstriction in
both the retina and choroid (Boerrigter et al. 1992) and incidentally there is also
decreased choroidal blood flow in myopic chick (Fitzgerald et al. 2002). More
direct evidence came from recent chick compensated myopia experiments where
serotonin stimulates LIM but not FDM but too high doses of serotonin were
found inhibitory in LIM (George et al. 2005). However, in another study, there
was no change in the retinal serotonin levels in inducted of myopia (Bartmann et
al. 1994). The effect of serotonin on myopia is far from clear.
Vasoactive intestinal peptide (VIP) is a hormone found in the brain and
some autonomic nerves. It is also a retinal neurotransmitter involved in the
development of FDM since intravitreal injection of VIP reduced FDM while
antagonists completely abolished FDM (Seltner and Stell 1995). However, FDM
in monkeys triggered a marked increase in VIP (Stone et al. 1988; Raviola and
Wiesel 1990). There has been little systematic follow up since then and the role
of VIP remains to be determined.
Two other mediators were thought to be involved due to their
corresponding responses to the signs of defocus. The first one is all-trans
retinoic acid (RA). In guinea pigs, the level of retinoic acid increased in LIM
(which enhance ocular elongation) and decreased in LIH (which suppress ocular
elongation), although different extends of effect were found in the two treatments
(McFadden et al. 2004). Similar to LIM, FDM in chicks was also associated with
elevated retinal retinoic acid. The induced myopia can be reverted by inhibiting
23
retinoic acid synthesis by intravitreal injection of a RA inhibitor. Furthermore,
the mRNA level of both the retinoic acid receptor and aldehyde dehydrogenase-2
(an enzyme involved in RA synthesis) could be modulated by different lens
treatments (Seko et al. 1998; Bitzer et al. 2000). Since the choroid actively
synthesizes retinoic acid during growth, it is concervable that retinoic acid may
play an important role in regulating ocular elongation (Mertz and Wallman
2000).
Contrary to retinoic acid, ZENK synthesis (the immediate early gene of
glucagon) in glucagon amacrine cells was increased in LIH or during recovery
from lens wear and was decreased in LIM or FDM. The changes could be
induced in less than an hour after lens wear (Fischer et al. 1999; Bitzer and
Schaeffel 2002). Furthermore, The LIH and LIM could be inhibited by local
injection
of
glucagon
antagonist
and
glucagons
agonist
respectively
(Feldkaemper and Schaeffel 2002). It was therefore suggested that glucagon may
act as an inhibitory signal in eye growth. Furthermore, the glaucagon mRNA
levels were increased significantly after a few hours of positive lens wear and
decreased after negative lens wear (Feldkaemper et al. 2000). However, a
transient increase in glucagon receptor mRNA levels was found after both
positive and negative lens wear in another study (Buck et al. 2004). Although it
was significantly down-regulated in negative lens wear while up-regulated in
positive lens wear, the results were not repeatable throughout all time points and
similar changes in the gene expression were also observed in the control eyes
(Buck et al. 2004). In addition, other study has casted doubts on the presence of
glucagon in the mammalian retina since it failed to detect glucagon neurons in
the retina of rats, rabbits and cats (Tornqvist and Ehinger 1983). Further
24
investigations with other mammalian models will be required to fill the gap of
knowledge on glucagon’s involvement.
1.4 Proteomic technology review
1.4.1
A novel molecule: protein
Proteins are the cellular building blocks that constitute most of the dry
mass of in our body and they are also the essential molecules for executing
nearly all of the cellular functions. They may act as enzymes, chemical
messengers, signal integrators, antibodies, hormones and toxins (Bruce et al.
1998). Their influences extend to every cellular processing in a living organism.
Visualizing and characterizing of the proteins may help to advance biological
research and understand cellular functions.
1.4.2
Step towards the new “-omics” science
“Proteome” is defined as the protein complement expressed by the genome
of an organism or cell type (Wilkins et al. 1996). “Proteomics” refer to a wide
field of study that involve the separation of complex protein mixtures into their
individual polypeptide components, comparison of protein expression profiles of
sample pairs (e.g. normal versus transformed cells) or studying post-translational
modifications with addition of a drug or other stimulant. It is also called
“functional genomics” because it deals with the global analysis of gene
expression and their functions at the protein level (Celis and Gromov 1999).
Biological information flows from DNA to protein. The completion of the
human genome project is a landmark achievement which has created an
important platform for modern biological research. Genomic data provide a
25
databank which helps to predict the characteristics of DNA replication,
transcription and translation machinery. However, it is not a key to answer all
biological questions. For example, not every gene is expressed and the time and
rate of its expression as well as turnover are still difficult to predict. It is now
generally agreed that only a fraction of genes are switched on in a given cell
type (Celis et al. 1991). Besides, study on differential mRNA expression has
yielded a lot of novel and important biological information (Laub et al. 2000).
However, a growing number of studies have also pointed out there is a poor
correlation between mRNA level and protein expression (Tew et al. 1996;
Anderson and Seilhamer 1997; Haynes et al. 1998). It is plausible once the
cascade of any biochemical signal starts off, it may not require the continuous
presence of mRNA information. Although the advance in genomic DNA and
mRNA research has aided our understanding of cell regulation, they cannot
depict accurately the physiological state of a living cell, especially its
modification at a functional level.
As protein physiology is closely related to cellular functions, the expressed
protein profile as well as their isoforms is likely to involve in the key pathways
that characterize biological systems and their regulations. With the advent of
proteomic technology, complex biological systems can now be better studied in a
global manner.
1.4.3
2DE - classical proteomic approach
The classical proteomic technique of two-dimensional polyacrylamide gel
electrophoresis (2D PAGE) is being widely used but it is not new. The
combination of the first step isoelectric focusing (IEF) and the second step
26
sodium dodecylsulfate polyacrylamide gel electrophoresis (SDS-PAGE) were
described by O’Farrell (O'Farrell 1975) and Klose (Klose 1975) back in 1975 for
the study of Escherichia coli and mouse tissue protein profiles respectively.
Electrophoresis is one of the key separation techniques used nowadays in
biological and biochemical research, protein chemistry, pharmacology, forensic
medicine, clinical investigations, verterinary science as well as molecular
biology (Westermeier 1997).
At present, a new technical improvement involving the use of immobilized
pH gradients (IPGs) strip in 2D PAGE is the choice of technique in proteomic
study as it offers high resolution of protein separation (Gorg et al. 2000). It is
capable of resolving over thousands of denatured proteins in a single 2D gel
(Choe and Lee 2000). After electrophoresis, proteins separated on a gel have to
be stained for visualization and comparison. Coomassie blue R250 (Red hue) is
most common method for general proteins staining in polyacrylamide gels while
a more recent dye, coomassie brilliant blue G250 (green hue), a dimethyl
substitute of R250, is claimed to have better sensitivity with low background
stain (Blakesley and Boezi 1977). Further progress came later with the
development of silver stain, the reduction of silver ionic with an alkaline
reductant, formaldehyde to form an insoluble brown precipitate of metallic silver,
which had sensitivity down to nanogram level (Switzer et al. 1979). Recent
development of fluorescent dyes such as Sypro Ruby, provide additional benefits
such as higher sensitivity, improved simplicity and wider dynamic range (Lopez
et al. 2000). Image acquisition is commonly achieved by using charge-coupled
device (CCD) equipped with commercial flatbed scanners or using scanning
densitometers whereas successive measurements of optical density (OD) are
27
made on small areas of the gel image. The digitalized gel images can be
compared and analyzed using computing software. One major goal in proteomic
study is to identify the proteins of interest. From the 1980s, techniques of direct
N-terminal and internal peptide sequencing of gel separated proteins were
developed (Aebersold et al. 1986; Aebersold et al. 1987; Matsudaira 1987;
Rosenfeld et al. 1992). Automated Edman degradation has once been the most
widely used method since only as little as picomolar concentration is enough for
analysis.
In
1988,
two
new
methods,
namely
matrix-assisted
laser
desorption/ionization time of flight mass spectrometry (MALDI-TOF MS)
(Karas and Hillenkamp 1988) and electrospray ionization mass spectrometry
(ESI-MS) (Fenn et al. 1989) were developed. These have enabled rapid and
reliable protein identification and continuous growth in the protein sequence
database.
Two-dimensional PAGE in combination with various staining techniques,
digital imaging system, mass spectrometry, computerized analyzing system and
database queries have formed the current approach in the field of proteomic
study.
1.4.4
Non-2DE proteomic approach
Along with the popular use of 2D PAGE for protein separation, some other
technologies are also being developed to serve this purpose. The most common
one is the chromatographical method which usually employs sample separation
in two immiscible phases; namely a mobile phase (which may be a gas, a liquid
or a supercritical fluid) and an immobile, immiscible stationary phase. The
choice of the different phases is based on the differing solubilities of the sample
in each phase. Some examples recently reviewed include: high-performance
28
size-exclusion chromatography (HPSEC) (Irvine 2003), reverse-phase high
performance liquid chromatography (RP-HPLC) (Rahbar et al. 1986),
hydrophobic interaction chromatography (HIC) (Maruska and Kornysova 2004).
Column chromatography includes ion-exchange chromatography (IEX) (Fritz
2004), gel-filtration chromatography (GFC) (Bollag 1994) and affinity
chromatography (AC) (Lee and Lee 2004). Other approaches based on
electrophoresis include free-flow electrophoresis (FFE) (Kobayashi 2004) and
capillary zone electrophoresis (CZE) (Dolnik 1999). Different from gel-based
electrophoresis, FFE separates preparatively charged particles according to their
electrophoretic mobilities (EPMs) or isoelectric points (pIs) by continuously
injecting the sample into a thin buffer film without the support of a stationary
phase, such as a gel. CZE separates analyses according to their relative ionic
mobilities under an electric field in narrow tubes.
Since proteins are diverse in nature, many separation techniques mentioned
here are developed for isolate only one sub-type or sub-group from a protein
mixture. Incorporating these different techniques with 2D PAGE for sample
pre-treatment and pre-concentration may benefit proteomic analysis further.
Those applications entail the removal of a sub-group of proteins or a class of
proteins that might interfere with 2DE resolution, and also help concentrate low
abundant proteins for better detection in the 2D gel.
1.4.5
Protein identification and databases
1.4.5.1
Mass spectrometry
The principle of mass spectrometry is to measure the mass (m) to charge
(z) ratio of ions for an analyte in gas phase. The design of all spectrometers has
29
three essential components: an ion source, a mass analyzer and a detector. Mass
spectrometry became a viable technique in protein analysis and in other
biological macromolecules study as a result of the development of two new
ionization methods, MALDI and electrospray that allow the routine analysis of
proteins at an affordable cost. The development of these soft ionization
techniques allows the production of primarily intact protonated molecular ions of
peptides and proteins. (A summary of historical development in the mass
spectrometry can be obtained from the webpage of the Scripps Center for Mass
Spectrometry: http://masspec.scripps.edu/MSHistory/timeline.php).
MALDI-TOF MS
MALDI was introduced by Tanaka (Japan) as well as by Franz
Hillenkamp and Michael Karas (Germany) as an improvement to the laser
desorption/ionization method in 1987. Analyte is dissolved and co-crystallized
with a matrix on a probe surface. The mixture is then irradiated by nitrogen laser
pulses typically at wavelength of 337 nm. The high laser energy evaporates and
converts analyte into gas phase at the ion source. The ionized analyte is then
directed and separated by the time-of-flight (TOF) analyzer which is commonly
employed for MALDI-MS. The detector records the flight time of all ions and
the results are presented as mass spectra.
ESI MS
A quadrupole mass filter is typically combine with ESI-MS. Different
from MALDI-TOF ionization on a solid phase matrix, ESI ionization analyses
compounds directly from aqueous or aqueous/organic solutions without
denaturation. Highly charged analyte droplets from a fine spray outlet are ionized
at atmospheric pressure in the presence of a strong electric field so as to generate
30
a series of charged gas-phase ions. The charged ions are then emitted and focused
into the high-vacuum region of mass analyzer. The spectra are presented as
various charge states of the molecule separated according to their mass-to-charge
ratio (m/z) (Veenstra 1999). Apart from protein identification, ESI-MS has also
contributed to the determination of higher order structure of proteins and in the
study of noncovalent complexes such as protein/DNA interactions (Rostom and
Robinson 1999).
Peptide Mass Mapping
Protein gel plug is first excised from a 2D gel and the proteins embedded are
digested by chemicals or specific proteases with high sequence specificity such as
trypsin (or other proteases with specific cleavage sites). The eluted analyte is
co-crystallised with a ultra-violet (UV) absorbing matrix on a target plate, mass
spectra which represent the peptide fragments can be directly obtained by high
energy laser in a mass spectrometer (MS) at vacuum. The MS then generates
experimental peptide mass profile specific to the protein. This experimental
profile is then compared to the theoretical masses derived from the in silico
digestion at the same enzyme cleavage site(s) of all protein in the available protein
database for a match. A significant match is either based on calculated scoring
scheme or based on a random probability algorithm. This process is called peptide
mass fingerprinting (PMF) (Pappin et al. 1993). Some common PMF search
engines are listed in Table 2.
31
Table 2. A List of publicly accessible peptide-mass fingerprinting servers
Search
Database web link
Source
engine
http://www.matrixscience.com/search
Mascot
Matrix Science
_form_select.html
MS-Fit
ProFound
http://prospector.ucsf.edu/ucsfhtml4.
UCSF Mass
0/msfit.htm
Spectrometry Facility
http://prowl.rockefeller.edu/
ProteoMetrics and
Rockefeller University
(PROWL)
PepIdent
http://www.expasy.ch/tools/peptident.
Swiss Institute of
(ExPASy)
html
Bioinformatics
Tandem MS
Even though traditional peptide mapping has demonstrated powerful
capability in protein identification, its usage is limited by availability of the
database and the complexity of the protein mixtures. Newly developed tandem
mass spectrometry provides an alternative solution to these shortcomings. This
involves two consecutive stages of mass analysis where secondary fragment ions
that are formed from a particular precursor ion can be detected (referred to
MS/MS). These include MALDI or ESI ionization sources coupled to a
combination of two TOF analysers (MALDI TOF-TOF (Medzihradszky et al.
2000) to, an ion trap (Laiko et al. 2000), a Fourier transform ion cyclotron
resonance
analyser
(FTICR)
(Hendrickson
and
Emmett
1999)
or
a
quadrupole-TOF hybrid mass analyser (Loboda et al. 2000). Proteins can be
identified by tandem MS as the peptide sequences rather than only peptide
masses.
1.4.5.2
Bioinformatics: protein databases
With the enormous growth in biological data during the genomic era,
bioinformatics is becoming very crucial to the development of modern proteomic
32
research. The application of bioinformatics in MS based proteomic study
generally refers to the integration of downstream protein databases. There are
many public and private annotated protein databases targeting from sequences to
functions. Three major publicly accessible sequence databases included
SWISS-PROT (Watanabe and Harayama 2001), TrEMBL (Boeckmann et al.
2003) developed in collaboration between the Swiss institute of Bioinformatics
and the European Bioinformatics Institute, and Protein Information Resource
(PIR) provided by Georgetown University Medical Center (Wu et al. 2003).
Supported by National Institutes of Health (NIH), a comprehensive catalogue of
proteins information UniProt (Universal Protein Resource) (Apweiler et al. 2004)
was formed in 2002 by unifying these three databases.
In recent years, integrated resource portals are available to serve as
frameworks for data integration which provide comprehensive protein
information as well as updated cross references. They usually allow worldwide
internet access (through www, ftp or email) with data retrieval function
distributed in cross-platform Extensible Markup Language (XML) for further
data mining. These recently introduced databases include Entrez (Geer and
Sayers 2003); iProClass (Wu et al. 2004); InterPro (Mulder et al. 2005) and SRS
(Zdobnov et al. 2002). They provide one-stop libraries for information such as
redundant and non-redundant protein sequence data, protein family data structure
and domains information, post-translational modifications and literature
cross-referencing. These bioinformatics resources will aid scientific data access
and exchange but the mastering of bioinformatics is a challenge for scientists to
meet in the current data explosion era.
33
1.4.6
Challenges in proteomic study
Proteomics study is understandably complicated. The total number of
proteins in the human body is known to be many times more than that of genes,
and in fact a single gene can contribute to the synthesis of a number of proteins.
It is generally accepted that proteomic analysis is more complicated than
genomic analysis due to the physical and chemical diversities of proteins within a
biological system. Proteins do not only have an amino acid sequence but also
have different structures and 3D conformations that characterize their functions.
Furthermore, there are post-translational modifications such as phosphorylation,
alkylation, glycosylation. The genome of a cell is relatively static but the
proteome is much more dynamic in nature. Protein expression is sometimes
markedly fluctuating with diurnal variation and stress. Proteomic study not only
aims to address protein identification and its abundance but also the specific time
frame that the protein profile is expressed. Proteins’ localization, modifications,
interactions and expressions vary significantly under different environmental
stimuli
and
experimental
design.
Therefore,
a
universally
applicable
experimental protocol for all samples or tissues is difficult to achieve.
Well-established technologies such as high-throughput sequencing technology,
reverse transcription polymerase chain reaction (RT-PCR) and bioinformatics
resources have contributed the completion date of the Human Genome Project.
Yet, similar platforms and tools have yet to be invented to advance protein
research.
Proteomics is a useful research too but it is still at its infancy. The scope of
protein work is immense and it requires not only technological advances but also
cooperation and communication between different disciplines in order to meet
34
the challenges. In recent years, researchers have formed a worldwide
organization in 2001: the Human Proteome Organisation (HUPO) (Hanash and
Celis 2002) which is analogous to The Human Genome Organisation (HUGO). It
aims to consolidate the development of proteomic research and to encourage the
spread and exchange of proteomic technologies.
1.5 Applications of proteomics
1.5.1
In general research
In view of recent exponential growth in scientific publication using
proteomic related approach, it is not surprising to see the extensive applications
of proteomic techniques in a wide range of research areas included physiology,
pathophysiology and biomarker discovery.
The gel based proteomic approach was initially used for studying the
bacterial proteome under different growth conditions (Linn and Losick 1976;
Reeh et al. 1977). It was only after 1995 that a dynamic change of bacterial
protein expressions could be efficiently studied because of the completion of the
first genome sequence of Haemophilus influenzae (Fleischmann et al. 1995). The
technological advances in proteomics have enabled new directions of basic
studies of antibodies (Visintin et al. 2004), apoptosis (Senderowicz 2004), signal
transduction (Graves and Haystead 2003), the immune response (Purcell and
Gorman 2004) and neuroscience (Wilson et al. 2004) which have wide
applications in plant (Kersten et al. 2002), food industry (Pineiro et al. 2003),
toxicology (Kennedy 2002), evolution and genetic epidemiology (Sellers and
Yates 2003; Navas and Albar 2004).
The major focus of proteomic application has aimed to understand human
35
diseases such as tuberculosis (Jungblut et al. 2001), acquired immunodeficiency
syndrome (AIDS) (Dixon et al. 2005), malaria (Johnson et al. 2004), Alzheimer's
disease (Butterfield 2004), and systematic diseases such as diabetics (Sparre et al.
2003), multiple sclerosis (Hammack et al. 2004) and cardiovascular diseases
(Macri and Rapundalo 2001). Probably the most frequent proteomic application
is in cancer research, such as bladder carcinoma (Iwaki et al. 2004), renal cell
carcinoma (Rogers et al. 2003), breast cancer (Somiari et al. 2005), ovarian
cancer (Posadas et al. 2004), lung cancer (Granville and Dennis 2005), colorectal
cancer (Steinert et al. 2002) and brain tumours (Zheng et al. 2003). In addition,
this novel technological approach is also contributing to studies of new fatal
diseases such as Severe Acute Respiratory Syndrome (SARS) (Ren et al. 2004;
Yip et al. 2005). The main theme in the proteomic analysis is to identify proteins
and related pathways of therapeutic or diagnostic value. A great deal of interest
has gravitated around the development of new biomarkers for early disease
detection and drug development (Hale et al. 2003; He and Chiu 2003; Jeffery and
Bogyo 2003).
1.5.2
In eye research
The application of proteomics in eye research is relatively new but
growing. A brief summary of proteomic studies of different ocular tissues are
described below.
1.5.2.1
An overview
The tear film is rich in soluble proteins. Tear protein such as lactoferrin,
lysozyme, albumin, lipocalin, lipophilin and beta2-microglobulin, were identified
using RP-HPLC and ESI-MS (Zhou et al. 2003) whereas proline-rich proteins
36
could be identified in human tears using MALDI-TOF MS (Fung et al. 2004).
Using rat cornea, differential protein expressions at various stages of
angiogenesis were demonstrated and over 100 differentially expressed proteins
could be identified using the proteomic approach (Thompson et al. 2003).
Recently, the first normal human cornea proteome was established for studying
corneal diseases and corneal bioengineering (Karring et al. 2005). The balance of
aqueous humour (AH) transport is important to the normal intra-ocular pressure.
Using 2DE approach, a number of proteins were found to be significantly
increased in the AH from patients having corneal transplant rejection (Funding et
al. 2005). Also, changes in extracellular matrix and alterations in cytoskeletal
proteins were found as a result of increased TGF-beta which were similar to the
changes observed in glaucoma patients (Zhao et al. 2004). The lens is one of the
most widely studied ocular tissues in proteomic investigation. Human lens
proteome at different ages (Russell 1991; Datiles et al. 1992; Wu et al. 1999) and
its post-translational protein modifications (Yang et al. 1994; Kamei et al. 2000;
Ball et al. 2004) were reported in a number of studies. One of the early proteomic
studies in human vitreous has identified of synthesis of Transferrin in the eye
(Laicine and Haddad 1994). More recently, human vitreous humour proteins
were catalogued by several groups using different proteomic approaches
(Nakanishi et al. 2002; Koyama et al. 2003; Yamane et al. 2003; Wu et al. 2004).
In addition, the difference between the vitreous humour in pseudophakic and
phakic eyes was recently studied (Neal et al. 2005).
1.5.2.2
Retina Pigment Epithelium (RPE)
The retinal pigment epithelium (RPE) is a single cell layer adjacent to
photoreceptors. It plays key roles in retinal physiology and the biochemistry of
37
vision. Proteomic comparison of cultured rat RPE cells during differentiation has
been studied. The majority of the protein change were found to be associated to
stress response genes (West et al. 2001). In another similar study to compare
native and cultured human RPE cells, up-regulation of proteins associated with
cell shape, cell adhesion, and stress fiber formation was found (Alge et al. 2003).
More specifically, proteome expressions and a catalogue of protein components
of human ocular lipofuscin granules (a fatty by-product of metabolism that
accumulates within RPE related to aging) were built using 2D PAGE platform
coupled to MS (Schutt et al. 2002). The human RPE proteome has been studied
and 278 of the cellular proteins were identified (West et al. 2003). Using mouse
RPE, the molecular composition of apical microvilli of was studied and novel
proteins were identified at the cell surface which may contribute to epithelial
function (Bonilha et al. 2004). Proteomic study has also been carried out to
localize the cellular retinaldehyde-binding protein in the apical membrane of the
RPE which may help understand retinoid processing and trafficking (Nawrot et al.
2004). Recently, by combining metabolic labelling and proteomic approach,
differentially expressed proteins which involved in cell proliferation, protein
synthesis, actin-remodelling and differentiation in human RPE could be found.
(Hathout et al. 2005).
1.5.2.3
Retina
Retina plays a central role in human vision. Early attempts have been
made to profile proteins of retinal cones and rods in ox and chicken using 2D
PAGE (Hildebrandt et al. 1985; Schlosshauer 1985). The capability of being able
to profile and characterize specific protein targets of the retina can provide new
knowledge related to retinal physiology. For example, the presence of functional
38
heterogeneity of rod outer segments has been demonstrated among the eyes of
human, ox and frog. This implied subtle physiological differences in related
retinal functions (Balsamo et al. 1986). Similarly, heterogeneity was also found
with IEF and 2DE analysis of highly purified S-antigen from human, bovine,
porcine and rat retina (Banga et al. 1987). Combined with immunohistochemistry
and immunoblotting, a previously unidentified goldfish visual-pathway of
intermediate-filament proteins could be studied using the gel-based proteomic
approach (Jones and Schechter 1987). In addition, the in vitro phosphorylation of
horizontal cells of the fish retina as well as multiple phosphorylated variants of
high molecular subunit of retinal neurofilaments were successfully identified
using SDS PAGE and radiolabeling (Lewis and Nixon 1988; Janssen-Bienhold et
al. 1993). Apart from the studying of specific targets, 2DE analysis can allow for
mass screening of a protein population in a high-throughput manner. Crystallins
is one of the major compounds involved in maintaining the transparency of the
crystalline lens in vertebrates. Using 2DE and immunochemical approaches, both
alpha A- and alpha B-crystallins were found and identified at approximately
equimolar concentrations in frog retinal cells for the first time (Deretic et al.
1994). Besides, differential regulation of 23 radiolabeled transported ganglion
proteins in response to axotomy could be studied simultaneously using 2DE
(Wodarczyk et al. 1997).
New methods for neural tissue proteins analysis such as the
development of more tissue-specific experimental protocols for retina and brain
samples have gradually emerged. An effort was made to improve protein
solubility and sample application in 2DE for the analysis of total proteins
extraction (Semple-Rowland et al. 1991). Fractionation protocols were modified
39
in order to achieve greater purity of the isolated post-Golgi carrier membranes
for the analysis combining 2DE, immunoblotting and microsequencing
techniques (Morel et al. 2000). A new chemical derivative of SDS PAGE was
also tested for the improvement of low abundant peptide recovery on rat retina
and mouse brain (Konig et al. 2003). There was growing interest to produce a
catalogue for all retinal proteins in different species using generalized 2DE and
MS based identification (Nishizawa et al. 1999; Matsumoto and Komori 2000).
Proteomic studies of the retina have become more diversified with
recent advances in IPGs and MS based protein identification techniques. In
addition to photoreceptor structure or transduction investigations (Wohabrebbi et
al. 2002; Clack et al. 2003; Martin et al. 2005), their phosphorylation patterns
(Sineshchekova et al. 2004), oxidative modifications (Miyagi et al. 2002),
melatonin production (Wiechmann et al. 2002) or crystallin content (Sakaguchi
et al. 2003) in response to stimuli such as light, were studied. Other specific
retinal tissues such as ganglion cells, Muller glia cells and retinal axon have also
been studied as they subserve many important neuronal and signaling functions
(McFarlane et al. 2000; Mulugeta et al. 2000; Lund and McQuarrie 2001; Hauck
et al. 2003). In addition, the aging process of the neural retina in term of protein
profile change or altered expression of specific protein was studied.
Post-translational modifications and down-regulation of alpha A crystallin were
found in the aging retina (Kapphahn et al. 2003). On the other hand, dietary
caloric restriction was shown to retard age-related degeneration as found by
studying the protein profile changes of rat retina (Li et al. 2004).
There has been limited attention proteomics in myopia development.
Recently, I have devised the working protocols and identified proteins which
40
may be involved in the normal emmetropization of chick eyes using a proteomic
approach (Lam et al. 2006). Bertrand et al have also suggested candidate proteins
which may regulate emmetropization in a recent study using the 2DE approach
(Bertrand et al. 2006). The detailed discussion will be given in Chapter 7.3.
1.5.2.4
Ocular diseases
Proteomic technology has also been applied to the study of a number of
eye diseases. By comparing the protein changes in diseased and healthy tissues,
target or candidate proteins that may contribute to the disease process can be
profiled and characterized. For example, the changes in tear proteins in
pathological conditions such as blepharitis was studied and compared with
controls using the 2D PAGE technique (Koo et al. 2005). Using the same logic,
the differentially expressed corneal proteins between keratoconus and normal
epithelial samples were analyzed with the electrophoretic approach and three
differentially expressed proteins (gelsolin, alpha enolase, and S100A4) were
found to involve in the pathogenesis of keratoconus (Meek et al. 2005; Nielsen et
al. 2005). Proteomic evaluation has also been extended to involve a new protein
chip array in an effort to find diagnostic markers for uveal melanoma patients
(Missotten et al. 2003).
Cataract is the leading cause of vision impairment among the elderly
worldwide. Age-related changes in the human lens were studied by 2D PAGE
and MS (Lampi et al. 1998). Specific structural changes in lens proteins
“BetaB2-crystallin” and covalent multimers during aging was later observed
(Srivastava and Srivastava 2003; Srivastava et al. 2004).
Age-related macular maculopathy (ARM) is the most common cause of
blindness in the elderly in the western world. Kliffen has found five
41
glycoproteins specifically present in human ARM and up-regulation of
glycosaminoglycans in drusens of ARM using a proteomic approach (Kliffen et
al. 1995; Kliffen et al. 1996). Another two groups also studied drusen formation
in ARM using liquid chromatography tandem MS for protein identification and
modification (Crabb et al. 2002; Hollyfield et al. 2003). Their data strongly
supported an oxidative role in the pathogenesis of ARM and they proposed a
critical role of oxidative protein modifications in the drusen formation.
The ocular manifestation of systematic disease such as diabetic
retinopathy (DR) can be indirectly studied through protein analysis of vitreous
humor. An increase in the serum-like protein which indicated blood-retinal
barrier breakdown in DR was noted using differential protein profile comparison
(Bresgen et al. 1994). With the help of MS technology, the proteins in the
vitreous with proliferative angiogenesis was identified (Nakanishi et al. 2002).
Similarly, using vitreous samples from patients with pre-proliferative diabetic
retinopathy, differential protein expressions could be investigated. Chemical
mediators were identified for the first time and it is suggested that they may
trigger diabetic macular edema. In the cat model, an increase in cytoskeletal
proteins during retinal detachment (Lewis et al. 1994; Lewis et al. 1995) or
retinal dystrophy (Maeda et al. 1999) was found.
Glaucoma is another leading cause of blindness. It is known to involve
pathological changes in the trabecular meshwork, retinal ganglion cells and optic
nerve head. Proteomics analysis has also provided new insights as to its
pathogenesis in recent years. For example, differential protein expressions were
observed in human trabecular meshwork (TM) cultured cells in simulated
glaucoma condition (Zhao et al. 2004). Cochlin protein was identified as a key
42
element in disrupting the TM architecture which resulted in elevated IOP in
glaucoma (Bhattacharya et al. 2005). Besides, 2D PAGE and Edman sequence
techniques revealed the possible involvement of gamma-enolase in retinal
ganglion cell death in glaucoma patients (Maruyama et al. 2000). Another study
confirmed the expression of myocilin (the first glaucoma gene discovered)
protein isoforms in the optic nerve head using 2D PAGE and Western
immunoblot analysis (Clark et al. 2001). In addition, the remarkable similarity
observed in the protein profiles between human TM and the lamina cribrosa in
optic nerve head suggested that these tissues may react similarly during the
pathogenesis of primary open-angle glaucoma (Steely et al. 2000). Furthermore,
proteomic study has also provided new evidence to support the association of
oxidative damage with neurodegeneration in glaucoma. Oxidative modification
of many retinal proteins in ocular hypertensive eyes has recently been found in a
glaucoma rat model (Tezel et al. 2005).
1.6 Objectives
Since the retina is the primary site of image perception and signal
generation that induce choroidal and scleral changes in myopia, the present study
aims to characterize these retinal signals using a proteomic approach. The study
particularly examined the differential retinal protein expression in normal
growing and ametropic eyes using the chick myopia model. The present work
also aimed to lay a foundation for comparative proteomic applications in myopia
research. It is the first step towards the elucidation of key biochemical pathways
in human myopia which may shed light on the control of myopia in the future.
This research study has four objectives and stages. The objective of the first
43
stage was to establish of the chick model and to optimize the proteomic
technique.
The second objective was to identify proteins with MALDI-TOF MS, either
manually or automatically using a robotic system in order to build the first chick
proteome database.
The third stage was to study differential protein expression in the normal
growing chick eye and the capability of the workflow in picking up protein/s of
interest was also tested.
Lastly, differential retinal protein expression in lens-induced and
form-deprived compensated growth were studied using the optimised proteomic
approach. The retinal protein expression was further explored using a new
Fluorescence 2-D Difference Gel Electrophoresis (2D DIGE) technique.
44
Chapter 2: Experimental Methods and Materials
All proteomic studies from sample homogenization to protein identifications
were carried out at the School of Optometry, The Hong Kong Polytechnic
University while animal breeding and refractive measurement were performed at
the Shanghai Fraternity Association Services Centre, The Chinese University of
Hong Kong (http://www.lasec.cuhk.edu.hk/).
2.1 Animals
2.1.1 Eggs, supply and breeding
Specific Pathogen Free (SPF) eggs were directly imported from Jinan Spafas
Poultry Co., Ltd, China (http://www.spfegg.com/english.html) or obtained
through a local government farm, Tai Lung Experimental Station, maintained by
Agriculture, Fisheries and Conservation Department, Hong Kong Special
Administrative Region (HKSAR) (http://www.afcd.gov.hk). The SPF eggs were
kept in an incubator (Grumbach, Germany) upon arrival at the animal centre.
After hatching, the white leghorn chicks were transferred to stainless steel
brooder cages where foods (Glen forrest stockfeeders, Australia) and water were
given ad libitum during the experiment period. Brooders temperature was
maintained above 28oC using electric heating lamps while the breeding room was
maintained at a stable indoor temperature at about 25oC. The fluorescent lighting
in the room was controlled to provide ambient 12 / 12 hours light /dark cycle
(lights on at 07:00). Care and use of the animals in these experiments was in
accordance with the ARVO resolution on the Use of Animals in Research and in
compliance with university guidelines set-furth by the Animal Subjects Research
45
Ethnic Subcommittee (ASEC), The Hong Kong Polytechnic University.
2.1.2 Goggles application
Ametropias were induced using a Velcro-goggle combination. The goggles
(11 mm in optical zone diameter with 6.7 mm base curve) were manufactured by
Poly methyl methacrylate (PMMA) cast moulding (Ultra-precision machining
centre, Hong Kong). One ring-shape Velcro (about 15-20 mm in diameter
according to the age of chicks) was glued to the flange around the base of the
goggle using epoxy resin. A corresponding Velcro ring was cut to attach around
the eye using non-fogging instant glue. A small notch was also cut on the Velcro
to avoid covering the chick’s beak and it also allowed good ventilation and
reduced the amount of condensation inside the goggle. The goggle glued on
Velcro was then attached onto the eye. The lens could be easily detached for
daily cleaning and refractive error measurement. In all experiments, chicks were
unilaterally fitted with the treatment lens while the other eye was fitted with
plano lens as contralateral control. Form-deprivation myopia was induced using
an opaque goggle. The goggles were unilaterally applied and a plano lens was
placed over the other eye as control. The duration of goggle manipulation varied
in different experiments and was described in details in each experiment (see
later). These Velco-goggle applications were shown in Figure 5. Chicks adapted
well to the Velco-goggle system in about an hour and no abnormal activity was
observed after the adaptation period. The body weights of the chicks were also
monitored to ascertain whether growth was healthy.
46
Figure 5. Compensated emmetropization was unilaterally induced in young chicks.
The Velco-goggle devices were positioned on chick eyes and the optical centre of
the lens aligned with the pupil centre.
2.1.3 Refraction and growth measurement
The refractive status of each chick was measured using a streak retinoscope
(Heine, AWC34.10.118. Beta 200 Streak Retinoscope Set 2.5v) and a trial lens
bar (with ± 0.5D to ± 16.00D) by the same examiner in all studies. The
Refractive status was measured to the nearest ± 0.5D, both before the lens
wear/occlusions and immediately after the treatment period. The measurement
was taken under dim light with the lens removed and the process usually took
less than 3 minutes for each eye. The resultant equivalent sphere (S.E. =
spherical power + 1/2 cylindrical power) was calculated based on the two powers
along vertical and horizontal meridians.
It was suggested that the chicks were fixating beyond the plane of examiner
and the retinoscope (Pickett-Seltner et al. 1988; Irving et al. 1992). To avoid drug
47
induced protein changes, no cycloplegic drug was used in the refraction
procedure. It has been shown that there was only little difference between
cycloplegic and non-cycloplegic refraction in chick eyes (Wallman and Adams
1987). However, care was taken not to include refraction data with a fluctuating
pupil which may indicate unsteady accommodation.
2.1.4 Dissection of retina and sample collection
After the treatment period, chicks were sacrificed by CO2 asphyxiation and
the eyes were enucleated promptly within 5 minutes. After removing the
extraocular tissues, the eyes were hemisected equatorially using a single-edge
straight razor blade. The anterior segment and vitreous were discarded. The
retinal layer was carefully peeled off from the posterior hemisphere (Figure 6)
and any RPE cells attached were either isolated from the retinal tissue or blotted
away using Kimwipes (Kimberly Clark Corp. USA). The whole dissection
process was carried out on a cold aluminium platform containing a frozen
ice-pack. Tissues were immediately frozen in liquid nitrogen and then stored
at –80oC for later protein analysis.
Figure 6. The posterior eye cup was hemisected for harvesting retinal tissue.
48
2.2 Equipment and reagents
Frozen retinal sample was routinely homogenized in a liquid nitrogen
cooled Teflon freezer mill (Mikrodismembrator; Braun Biotech, Germany). IPG
strips for isoelectric focusing and the 2D PAGE systems including Protean IEF
Cell (for 1st dimension separation) and mini-Protean II tank / Protean II XL cell /
Dodeca tank electrophoresis system (for 2nd dimension separation) were obtained
from BioRad (USA). Image acquisition was done with a flatbed scanner
“ScanMaker 4600” from Microtek (Taiwan). The automatic protein spot cutter
and sample preparation robots (PROTEINEER series) as well as the
MALDI-TOF MS (Autoflex) were from Bruker Daltonics (Germany).
Unless otherwise stated, chemicals of the highest purity available or at least
HPLC grade were used. Molecular weight markers and most reagents for 2D
PAGE were purchased either from BioRad (USA) or Amersham Biosciences
(USA). Chemicals and solvents used for MALDI-TOF MS were either from
Fluka (USA), Sigma-Aldrich (USA) or Bruker Daltonics (Germany) while
trypsin for in-gel protein digestion was from calbiochem. Deionized/distilled
Milli-Q water was used in all experiments. Other specific reagents used were
further described in individual experiment.
2.3 General experimental workflow
The general proteomic workflow in the study comprises several steps. First
of all, the retinal tissues were homogenized in the dismembrator with lysis buffer.
Soluble proteins were extracted and quantified using protein assay. In 2D PAGE,
the analyte protein samples were separated in IPG strips according to their
isoelectric points in the first dimension and were further separated in SDS
49
polyacrylamide gels according to their molecular weights. Protein profiles were
visualized by different staining methods. After scanning the images in digital
format, 2D profiles could be compared and analyzed using ImageMasterTM 5 gel
analysis software. For protein identification purpose, spots of interest were
excised and trypsin in-gel digested. Fragmented protein peptides were mixed
with matrices and spotted onto a target plate. Mass spectra were acquired from
the MALDI-TOF MS and the resulting peptide maps were searched against the
PMF databases via online search engines or the MS bundle software (Figure 7).
Figure 7. A typical experimental proteomic workflow in this study.
50
Chapter 3: Results of chick basal data measurement
3.1 Statistical calculation
The differences in refractive errors between the eyes of a normal chick were
compared at each time point using unpaired two-tailed student t-test. To show the
compensated eye growth during the experimental periods, the refractive error
changes in both eyes before and after treatments were plotted. Statistical
differences between treatment eyes and fellow control eyes were assessed using
paired one-tailed student t-test for each treatment period. All raw data were listed
in appendix 1.
3.2 Refraction and body weight changes
3.2.1 Normal emmetropization
To examine the refractive development of untreated normal eyes, a total of
190 chick eyes were studied and refracted at different time points from 1 day
(day-1) to 20 days post-hatching (day-20). Young chicks were usually born with
hyperopic error which gradually decreased toward emmetropia over time (Figure
8). The chicks had a mean refractive error of +2.34D (RE) and +2.62D (LE) at
day-1 and both eyes emmetropized to +0.70D (RE) and +0.80D (LE) at day-20.
The rate of hyperopic reduction was greater at the younger age. The refractive
errors between two eyes of the same animal were not statistically different at all
time points (P>0.05, two-tailed individual t-test)
51
3.00
RE
LE
Refractive error (D)
2.50
2.00
1.50
1.00
0.50
0.00
0
5
10
15
20
25
Age (days)
Figure 8. The mean refractive error changes in both eyes of chicks during the first
20 days post-hatching. Error bars, SEM.
3.2.2 Astigmatic changes
The astigmatism of the normal growing chicks were studied and were
classified into against-the-rule astigmatism, with-the-rule astigmatism or
spherical (no astigmatism) error (Figure 9). Astigmatic power with -0.50D or
more was included and chicks developed more than -3.00D, oblique or irregular
astigmatism were excluded. It was shown that chicks exhibited substantially
against-the-rule astigmatism in the experimental period. Out of the totally 190
eyes studied, the majority, more than half (67.9%) of them had against-the-rule
astigmatism (mean = -0.87D) while only 7.9% had with-the-rule astigmatism
(mean = -0.57D). The rest (24.2%) of them had spherical refractive error.
52
140
chicks number
120
100
80
60
40
20
0
against the rule astigmatism
with-the-rule astigmatism
spherical error
Types of refractive errors
Figure 9. The number of refractive astigmatism (against-the-rule, with-the-rule)
and spherical error in normal growing chicks.
3.2.3 Compensated myopia
Lens-induced myopic (LIM) chicks were induced by wearing -10D optical
lenses. Their initial and final mean refractive errors in both treated and control
eyes were plotted in Figure 10. The duration of lens wear varied from 1 to 9 days
in groups of chicks of different ages (from 1-day old, 3-day old, 4-day old and
14-day old respectively for group A to group D). Significant difference (P<0.01,
one-tailed paired t-test) in refractive errors were seen in the eye wearing -10D
lenses in all groups when compared to the control eyes. This difference was
evident after 1 day of lens wear and it continued to increase with the lens
wearing time. The treatment eyes almost compensated fully to the -10D lens after
7 days. In addition, those chicks received earlier treatment starting from 1-day
old generally gave a stronger response than those started later seen from their
slopes of both 3 days and 4 days lens wearing.
The final refractive errors (the difference between the defocused and control
eyes per chick) in different treatment groups were shown in Figure 11. The
53
refractive errors generally increased with the duration of lens wear in all groups.
The most significant difference between two eyes was seen after 7 days of lens
wearing.
A.
4.00
3.00
2.00
1.00
3-day defocus (8)
0.00
3-day control
Refractive error (D)
-1.00
5-day defocus (9)
-2.00
5-day control
-3.00
7-day defocus (8)
-4.00
7-day control
-5.00
-6.00
9-day defocus (4)
-7.00
9-day control
-8.00
-9.00
-10.00
-11.00
-12.00
initial
B.
final
5.00
4.00
3.00
1-day defocus (4)
2.00
1-day control
1.00
3-day defocus (4)
Refractive error (D)
0.00
-1.00
3-day control
-2.00
5-day defocus (4)
-3.00
5-day control
-4.00
7-day defocus (4)
-5.00
7-day control
-6.00
-7.00
-8.00
-9.00
-10.00
-11.00
-12.00
initial
final
54
C.
5.00
4.00
3.00
1-day defocus (4)
2.00
1-day control
1.00
3-day defocus (14)
Refractive error (D)
0.00
-1.00
3-day control
-2.00
5-day defocus (10)
-3.00
5-day control
-4.00
7-day defocus (6)
-5.00
7-day control
-6.00
-7.00
-8.00
-9.00
-10.00
-11.00
-12.00
initial
D.
final
4.00
3.00
2.00
1.00
3-day defocus (4)
0.00
Refractive error (D)
-1.00
3-day control
-2.00
-3.00
5-day defocus (4)
-4.00
-5.00
5-day control
-6.00
-7.00
-8.00
-9.00
-10.00
-11.00
-12.00
initial
final
Figure 10. The effects of -10D lens wear on refractive development at different
onset of lens wearing. Group A, B, C and D represented lens wearing age (onset)
at 1-day old, 3-day old, 4-day old and 14-day old respectively. The data plotted
are the mean paired initial and final refractive errors between the experimental
eyes and the control eyes. Error bars, SEM with number of animals were shown
in parentheses. The refractive errors were significantly different (p<0.01, paired
t-test) between the treatment and control eyes in all treatment periods.
55
Figure 11. The amount of refractive error difference between the experimental
eyes and paired control eyes (defocus-control) at the end of lens treatment. Day 1
to 14 were the onset days of lens application. Values are mean ± SEM (error bars)
with number of animals in parentheses.
3.2.4 Compensated hyperopia
Lens-induced-hyperopia (LIH) was induced with +10D lenses. Their paired
initial and final mean refractive errors in both defocused and control eyes were
plotted in Figure 12. There were two different treatment times in the
compensated hyperopia with lens wearing started either from 3-day (group A)
old or 4-day old (group B). Again, there was significant difference (P<0.01,
one-tailed paired t-test) in the refractive errors between the treatment and control
eyes in all groups. Similar to that of -10D treatment, higher refractive errors in
the treated eyes were seen with longer lens wear while the control eyes remained
fairly constant over the treatment period. However, it seemed that the chick eyes
responded comparatively quicker to +ve than –ve lenses of the same absolute
56
dioptric power. A full compensation was obtained after 4 to 5 days of +10D lens
wear whereas it took about 7 days for the -10D group to compensate.
A.
12.00
11.00
10.00
Refractive error (D)
9.00
8.00
7.00
3-day defocus (6)
6.00
3-day control
5.00
4-day defocus (10)
4.00
4-day control
3.00
2.00
1.00
0.00
initial
final
B.
12.00
11.00
10.00
Refractive error (D)
9.00
8.00
4-day defocus (5)
7.00
4-day control
6.00
5-day defocus (4)
5.00
5-day control
4.00
3.00
2.00
1.00
0.00
initial
final
Figure 12. The effects of +10D lens wear on refractive development at different
starting age of lens wearing. Group A and B represented treatment onset of 3-day
old and 4-day old respectively with number of animals in parentheses. The data
plotted are the mean paired initial and final refractive errors between the
experimental eyes and the control eyes. Error bars as SEM were shown. The
refractive errors were significantly different (p<0.01, paired t-test) between the
treatment and control eyes in all treatment periods.
57
3.2.5 Form deprivation myopia
The form deprivation myopia (FDM) in this group was induced one day after
hatching. Light-proof black goggles were worn for 3, 5 and 7 days. Their paired
initial and final mean refractive errors in both deprived and control eyes were
plotted in Figure 13. The final refractive errors after different treatment periods
were shown in Figure 14. Again, a significant difference (P<0.01, paired t-test) in
refractive error between the two eyes was evident as expected. Comparing to
-10D lens wear, the induced myopic growth in FDM was much more rapid for
the same wearing period. Moreover, there was larger variation in refraction in the
FDM than the control eyes.
5.00
3.00
1.00
-1.00
initial
final
-3.00
Refractive error (D)
-5.00
3-day defocus (4)
-7.00
3-day control
-9.00
5-day defocus (4)
5-day control
-11.00
7-day defocus (8)
-13.00
7-day control
-15.00
-17.00
-19.00
-21.00
-23.00
-25.00
-27.00
Figure 13. The refractive development of light-proof black goggles wear on 1 day
old chicks for periods of 3 days, 5 days and 7 days with number of animals in
parentheses. The data plotted are the mean paired initial and final refractive
errors between the experimental eyes and the control eyes. Error bars as SEM
58
were also shown. The refractive errors were significantly different (p<0.01,
paired t-test) between the treatment and control eyes in all treatment periods.
5.00
3.00
1.00
-1.00
-3.00
Refractive error (D)
-5.00
(4)
(4)
-7.00
-9.00
(8)
-11.00
control
defocus
-13.00
-15.00
-17.00
-19.00
-21.00
-23.00
-25.00
-27.00
3
5
7
deprivation period (days)
Figure 14. The final refractive errors of the experimental eyes and paired control
eyes after 3, 5 and 7 days of form deprivation. Values are mean ± SEM (error
bars) with the number of animals in parentheses.
3.2.6 Body weights
The growth rate of chicks was monitored by their body weights, with a spring
balance. The changes of body weights over the experimental period were shown
in Figure 15. The average body weight was about 40g at the 3rd days
post-hatched. It gradually grew to over 110g at day-20. The body weights of the
treatment groups (70 chicks in total) at three experimental time points were
similar to that of control chicks. There was no retardation of growth in terms of
body weight after goggles wearing.
59
Body weight (grams)
120.00
115.00
110.00
105.00
100.00
95.00
90.00
85.00
80.00
75.00
70.00
65.00
60.00
55.00
50.00
45.00
40.00
35.00
30.00
1
3
7
10
14
20
Age (days)
Figure 15. The body weights (in grams) of normal (solid line) and treatment
chicks (broken line). Error bars as SEM was shown.
3.3 Discussion
3.3.1 Refraction
The present study employed days-old up to 3-week old young chicks when
the ocular growth is most rapid during this sensitive period (Pickett-Seltner et al.
1988). The chicks were closely monitored in the study and those with goggle
displacement or detachment during the experiment were excluded. Occasionally,
chicks which developed extreme astigmatism due to improper goggle application
were also excluded.
Similar to previous findings, chicks were found to be slightly hyperopic
(varied from +1.00 to +3.00D) upon hatching (Wallman et al. 1981; Priolo et al.
2000). It had also been shown that normal eye growth is almost linear during the
first 3 weeks of life (Schaeffel et al. 1986). The young chicks were able to
compensated fully for imposed refractive errors up to +20D and -15D as reported
60
in previous study (Irving et al. 1992). Three typical visual manipulations and
produced compensated refractive changes in young chicks were successfully
established: (a) Both negative lenses (-10D) and occlusion treatments in general
caused myopic compensation (LIM and FDM), but the total amount of myopia in
occlusion treatment was comparatively higher. Moreover, similar to other studies,
it was evident that compensated myopia response to negative lens developed
faster in younger chicks (Wallman and Adams 1987; Papastergiou et al. 1998).
Furthermore, the larger variability of final refractive error in occlusion treatment
also agreed with previous reports. It was explained by the gain function in
individual chicks driven by its genetic makeup under an open-loop treatment
without visual feedback The external visual guidance was completely lost under
the opaque occluders (Schaeffel and Howland 1988; Schaeffel and Howland
1991). (b) Positive lenses (+10D) caused hyperopic compensation (LIH) but the
rate of refractive change was more rapid than when using -10D lens during the
same treatment period. This trend was in agreement with previous observations
(Schaeffel and Howland 1988; Wildsoet and Wallman 1995). (c) Although
equivalent spherical errors were usually taken to simplify analysis, it was
observed from dioptre powers (raw data) along the two principle meridians (x90
and x180) that the astigmatic errors developed were mainly against-the-rule
astigmatism (where the cylinder axis is vertically close to 90 degrees). The data
was most significant in chicks at hatching where >90% of them were born with
against-the-rule astigmatism and the astigmatism decreased in magnitude with
development. The result in general agreed well with previous study of natural
and induced astigmatism in young chick (Schmid and Wildsoet 1997) except
lesser amount of initial astigmatism was found in the present study. Breed and
61
strain differences together with measurement protocol could have contributed to
the disparity.
3.3.2 Body weight change
Since chicks from different batches were used in a number of different
experiments, their ages and growth rates among these different batches were
recorded so that meaningful comparison of data can be made. In addition, the
time of hatching (normally after 21 days incubation) was also important in the
protein studies as the growth process involves dynamic changes of protein
expressions with time. It was thus important to hatch the chicks in our laboratory
in order to ensure the hatching time of each batch did not differ significantly.
Chicks that were not fully developed upon hatching were excluded. Chicks that
were delayed in hatching for more than 1 day in the same batch were also not
used.
The embryonic development of the leghorn chick has been well documented
(Figure 16). The body weight upon hatching was averaged at about 30 grams
which was similar to the 1-day post-hatching chicks in the present study. The
body weights of chicks in the normal and lens treated groups matched closely
with the averaged norm. The body weight of chicks between normal growth and
lens treatment groups exhibited linear growth rate from 3 days onward. To
minimize the effect of growth variation (or metabolic rate) within the same batch
(Fyhn et al. 2001), tissues used in later proteomic studies were selected from
chicks of similar body weights so that the optimal matching and comparison
could be performed.
62
Figure 16. Daily changes in the weight of developing white leghorn embryo. (Data
based on A. L. Romanoff, Cornell Rural School Leaflet, September, 1939).
63
Chapter 4:
Optimisation of experimental procedures
4.1 Introduction
Despite the recent rapid advancement of proteomic technology, there is still
no “universal” experimental protocol that can be applied to all tissue types. The
lack of standardization is partly due to the fact that proteomic research is an
emerging new technology and also that biological samples are too diverse for
simple generalization. The reason for optimizing the experimental protocol is to
ensure good profiling of cellular proteins (Rabilloud 1999; Santoni et al. 2000).
Two dimensional polyacrylamide gel electrophoresis (2D PAGE) has been
introduced for almost 30 years and it remains as one of the key protein separation
techniques in proteomic research. The technique has been further popularized in
recent years because of the advancement of analytical chemistry and downstream
protein identification using mass spectrometry. The success of 2D gel
comparison as well as protein characterization hinge on optimised working
protocols in each analytical step from protein extraction, protein separation to
protein fragmentation for MS identification (Gorg et al. 2004).
4.2 Retinal proteins extraction
4.2.1 Aims
Sample preparation is the first-step in the proteomic study and it is the key to
the success for later protein identification. One of the major purposes of sample
preparation is to solubilize cellular proteins, especially hydrophobic proteins,
from tissue sample into a solution of individual polypeptides (Molloy 2000;
Santoni et al. 2000). It aims to break down the molecular forces between the
substances in the sample mixture, eliminate the interfering substances and
64
prevent secondary reaggregation of the analytes during electrophoresis
(Rabilloud 1996) so as to ensure that each spot on the 2D gel represents a single
polypeptide (Manabe 2000). At the same time, there ia a need to optimize the
protein yield as much as possible but minimize protein degradation during the
sample preparation. A series of preliminary experiments, have been carried out to
devise an optimal method for solubilizing retinal proteins using various
detergents
4.2.2
Sequential extraction
4.2.2.1
Buffer solution
Bio-Rad ReadyPrep™ Sequential Extraction Kit was used in this
experiment in order to study the effect of fractionation on the retinal proteins.
The procedure was adopted according to the manufacturer’s recommendation.
There were totally 3 solutions provided which differed in their concentrations of
detergents and chaotropes. Solution 1 consisted of 40 mM Tris base buffer.
Solution 2 contained 8 M urea, 4% (w/v) CHAPS, 40 mM Tris, 0.2% (w/v)
Bio-Lyte 3/10 ampholyte and 1% (v/v) TBP. Solution 3 contained 5 M urea, 2 M
thiourea, 2% (w/v) CHAPS, 2% (w/v) SB 3-10, 40 mM Tris, 0.2% (w/v)
Bio-Lyte 3/10 and 1% (v/v) TBP. In addition to the three solutions, there was
solution 4 which was a strong denaturing solution made up of 1% sodium
dodecyl sulphate (SDS) and 100mM Tris base.
4.2.2.2
Procedures
All tissues were homogenized by a Micro-Dismembrator unit
(Mikrodismembrator; Braun Biotech, Germany) (Figure 17A). Two normal
retinae from a normal growing 10 day-old chick were dissected and
65
homogenized in the dismembrator at 1600 rpm with 200 μl of solution 1 for 4
min. Both the tissues and Teflon chamber (3 ml) (Figure 17B) were cooled in
liquid nitrogen before being assembled for homogenization. A tungsten carbide
(9 mm) grinding ball (Figure 17C) was placed inside the chamber to help shatter
the tissues into powder form at low temperature as the dismembrator shook.
Another 300 μl buffer was added to the tissue powder and the mixture was
further homogenized for another minute. Finally, 100 μl buffer solution was
added to help recover all of the solution. The sample was vortexed briefly and
then centrifuged at 16,000g for 30 min. The supernatant was collected and the
pellet was washed twice with solution 1 before sequential protein extraction with
buffers of increasing solubilization power in solutions 2 to 4. Modified Bradford
protein assay according to Ramagli (Ramagli 1999) was used to quantify the
protein concentrations and yield in each solution and also in their “washes”.
Figure 17. Diagrams showing the Micro-Dismembrator unit (A), the teflon
chambers (B) and the different types of grinding balls (C).
4.2.2.3
Result and comment
The sequential extraction cycle and protein recovery results were
66
summarized in Table 3. This approach mainly provided a general picture of
aqueous tris-soluble proteins and aqueous tris-insoluble proteins. The data
showed that increasing protein amount could be extracted using stronger buffer
solutions. About 14% of the total retinal protein, which represented the
water-soluble proteins, was recovered in Tris solution (solution 1) while most
proteins could be effectively extracted in solution 2. In other words, more than
90% of the total protein was extracted without using charged detergent SDS
which may interfere with the subsequent isoelectric focusing. However, there
was detectable protein in the “washes” which were proteins being carried over
from one buffer to another during sequential extraction. This problem may
complicate the highly sensitive differential protein profiles comparison.
Table 3. The procedure of sequential extraction and recovery of retinal protein
samples. Solution 1 to solution 4 represent Tris buffer, urea containing cocktail,
urea and thiourea combination cocktail and SDS buffer respectively. R1 was
soluble proteins in solution 1 while R1.1 and R1.2 were proteins remained after
two consecutive washes. R2-R4 were soluble proteins collected from solution 2 to
67
solution 4.
4.2.3 Single buffer (EB5) extraction
Subsequent to the retinal fractionation experiments, an all-in-one lysis buffer
cocktail (EB5) was also tried. It was made up of 7M urea, 2M thiourea, 40 mM
Tris, 0.2% (w/v) Biolyte, 1% (w/v) DTT, 2% (w/v) CHAPS, 1% (v/v) ASB14
and 1% (v/v) Protease Inhibitor Cocktail (Sigma-Aldrich, USA).
Although the above fractionation approach (Section 4.2.2) could reduce
the complexity of the protein mixture, use of the all-in-one lysis buffer cocktail
for the retinal proteomic analysis was preferred in order to keep the protein
extraction procedure as simple as possible. This would speed up the tissue
homogenization process and enhance the repeatability of 2D gel profiles.
Secondly, a strong single buffer would minimize sample loss and protein
degradation with time. Thirdly, good 2D profile with high resolution with large
2D gels could be achieved. Finally, according to the protein extraction data, this
single EB5 cocktail was efficient in recovering at least 95% of the total soluble
retinal proteins. It was tested to be compatible with the 2D electrophoresis
protocol. Therefore, this one-step single lysis buffer cocktail was adopted in
these experiments.
4.2.4 Discussion
Lysis buffer is a formulated mixture of selected chaotropic agents, detergents,
reducing agents, buffers, and ampholytes. Many new reagents have been
suggested and adapted for use in IEF (Gorg et al. 2004). They act differently but
serve the same purpose, which is to facilitate protein solubilization for the
gel-based electrophoresis.
68
The combinations of reagents in the present buffer serve a number of
solubilization purposes. Since the strongest covalent bond in proteins is the
disulfide bond between thiol groups of cysteine amino acid, the thiol reducing
agent, Dithiothreitol (DTT) can be used to disrupt disulfide bonds in protein
mixture and maintain all proteins in fully reduced state. Chaotropes including
urea and thiourea can break down all types of non-covalent interactions such as
disrupting hydrogen bonds, unfolding hydrophobic cores of a protein and
decreasing ionic bonds between proteins. Detergents such as CHAPS and more
recently developed sulphobetaine surfactant, ASB14 (Chevallet et al. 1998;
Molloy 2000), are important in preventing hydrophobic interactions and
minimizing protein aggregation especially in membrane proteins. IPG buffer
with carrier ampholytes mixture enhances sample solubility and produces
uniform conductivity during IEF.
The optimal choice of homogenization method largely depends on the type
and amount of sample. Since proteins are susceptible to external stimuli such as
temperature and pH or internally to proteases, it is critical to devise a
well-controlled protocol for tissue homogenization that can give consistent
material recovery and minimise protein degradation. Considering other
commonly available methods (such as osmotic lysis, freeze-thaw method, motor
and pestle grinding, mechanical Potter-Elvehjem homogenization, glass bead
homogenization and the vigorous sonication method), the Micro-Dismembrator
unit is advantageous in the sense that it is clean, safe and efficient for
homogenizing retinal tissues. Frozen retinal tissues could be contained in a liquid
nitrogen cooled Teflon chamber with lysis buffer and the samples can be
homogenized by the tungsten carbide grinding ball in the chamber with digitally
69
programmed shaking frequency and duration.
4.3 2D gel staining
Another important feature of proteomic research is the ability to visualize
and analyze proteins separated by 2-D PAGE. Several approaches have been
previously developed for protein detection. For most proteomic study,
non-fluorescent staining is the most popular and convenient method which is
compatible with subsequent MS analysis. The two typical non-fluorescent
methods are coomassie blue and silver staining.
4.3.1 Coomassie blue stain
4.3.1.1
Background and aims
Coomassie blue organic dye has been widely used since the early 1960s
(Meyer and Lamberts 1965). Despite its relatively low sensitivity in detecting
microgram level of protein, it is the most popular technique in proteomic study
due to a number of advantages. It can stain a broad spectrum of proteins
(virtually non-specifically bound to all proteins) when compared with other
staining methods. Also, it is relatively cheap in cost, easy to use, safe and
provides good reproducibility. More importantly, the proteins are not chemically
fixed in the polyacrylamide gel matrix after staining and it is therefore fully
compatible with subsequent protein identification either by Edman degradation
or by MS.
With the wide application of coomassie blue staining in proteomic
research, there have been several modifications on colloidal coomassie brilliant
blue staining protocols aiming to improve its overall performance. A number of
70
the modifications and modified staining methods were studied and compared
with respect to the sensitivity and ease of use.
4.3.1.2
Procedures
A total of eight coomassie stain protocols were tested. They were named
as Neuhoff protocol (Neuhoff et al. 1988) (N1); Modified Neuhoff A (N2);
Modified Neuhoff B (N3); Neuhoff with stabilization (N4); Reisner protocol
(Reisner et al. 1975) (R); commercial available kit solution form BioRad
(Biosafe); standard R250 (R250); PhastGel™ Blue R from Amersham
Biosciences (R350); modified R350 (hot R350). Their preparations were listed
in Table 4.
In the first part of optimization, a broad range SDS-PAGE protein
standard mixture, the Perfect Protein™ Markers which cover molecular weight
from 10 kDa to 225 kDa (9 proteins mixture, Novagen) was used for the
sensitivity tests. One-dimensional gel electrophoresis was performed with a serial
dilution of 400, 200, 100 ng of total marker proteins per lane using a
mini-Protean II tank with 12% polyacrylamide gels. Generally, the gels were
soaked in fixating solution for 60 min and then stained overnight according to
different protocols. For hot R350 protocol, the gel was stained with hot staining
solution in a microwave for 10min and then destained overnight.
In the second part of the test, the performance of four colloidal
coomassie stains (N1, N4, R and hot R350) were compared using chick retinal
tissues separated by 2-DE. The soluble proteins were extracted using EB5 lysis
buffer. Each 200 μg retinal protein sample was separated by 11 cm IPG (pH 5-8)
in the first dimension and then further separated in 12% polyacrylamide gels in
the second dimension. Upon completion of SDS-PAGE, the gels were stained
71
according to their respective protocols as listed in Table 4.
Table 4. A list of coomassie blue staining protocol.
Method:
N1
Fixation solution
Staining solution
Destain solution
12% trichloroacetic 0.1% (w/v) G250, 1.6% DDH2O
acid
(TCA)
(v/v) perchloric acid,
8% (w/v) ammonium
sulfate, 20% methanol
N2
1.3 % perchloric 0.1% (w/v) G250, 1.6% DDH2O
acid
(PA),
10% (v/v) perchloric acid,
methanol
8% (w/v) ammonium
sulfate, 20% methanol
N3
40%
methanol, 0.06%
10% acetic acid
(w/v)
G250, DDH2O
8.5% (v/v) perchloric
acid
N4
12% trichloroacetic 0.1% (w/v) G250 1.6% Stabilized in 20%
acid
(TCA)
(v/v) perchloric acid, (w/v) ammonium
8% (w/v) ammonium sulfate
sulfate, 20% methanol
R
40%
methanol, 0.04%
10% acetic acid
(w/v)
for
4hrs
before DDH2O
G250, DDH2O
3.5% (v/v) perchloric
acid
Biosafe
briefly
DDH2O 100mL kit solution for DDH2O
rinse (30 sec)
R250
40%
mini-gel
methanol, 0.1% (w/v) R250, 40% 30%
10% acetic acid
methanol,
methanol, 10% acetic 10% acetic acid
acid
R350
40%
methanol, 0.1% (w/v) R350, 30% 30%
10% acetic acid
methanol,
methanol, 10% acetic 10% acetic acid
acid
Hot R350
Nil
0.025% (w/v) R350
10% acetic acid
72
10% acetic acid
4.3.1.3
Results and comments
The staining results of the different coomassie blue protocols using molecular
weight marker were scanned and showed in
Figure 18.
400ng
400ng
200ng 100ng
N1
400ng
200ng 100ng
200ng 100ng
400ng
N2
400ng
Biosafe
200ng 100ng
R250
200ng 100ng
400ng
N3
400ng
200ng 100ng
R350
200ng 100ng
R
400ng
200ng 100ng
Hot R350
400ng
200ng
N4
Figure 18. The sensitivity of nine different coomassie blue staining methods. A
serial dilution of 400, 200, 100 ng of total marker proteins per lane was separated
by 12% mini-gels.
73
In contrast to previous observation that the traditional coomassie blue stain
was better in detection limits compared to the colloidal coomassie blue stains
(Patton 2002), the present data showed that the traditional R250 and R350
standard coomassie staining methods were not as sensitive as the other colloidal
modifications. Both Neuhoff (N1 to N4) and Reisner (R) staining protocols
achieved similar sensitivity. They were able to detect a 10 ng band as their
sensitivity limits of the modified colloidal coomassie blue stains. The gels
stained with N3 protocol showed much more coomassie precipitation and
contamination which caused prominent smearing of gels. The dye contamination
could not be removed without compromising the sensitivity after the destaining
step. As reported previously, it was observed that the colloid formation would
require sufficient time resulting in prolonged staining time (Neuhoff et al. 1988).
The relatively unpopular but simple hot R350 protocol, although having a
different colour hue, showed comparable sensitivity to N or R protocols even
without a gel fixation step. In addition, it also gave very clear gel background.
The commercially available Biosafe premixed staining solution
achieved staining sensitivity at about 20 ng per band, as claimed by the
manufacturer. However, its performance was slightly inferior to all N & R
variations. On the other hand, this ready-to-use solution was safer and much
easier to use. It was also the only protocol which did not cause gel shrinkage as
no methanol or acid was used in the protocol.
In consideration of the overall staining performance using the protein
standard markers, four staining protocols (N1, N4, R and hot R350) were chosen
and applied to the retinal proteins. The coomassie stained retinal 2-DE protein
profiles were shown in Figure 19.
74
N1
N4
R
Hot R350
Figure 19. The staining performance of four selected coomassie blue staining
methods (N1, N4, R and hot R350 as descried in (Table 4). Protein profiles of
200μg of EB5 soluble retinal proteins were separated by two-dimensional gel
electrophoresis. Isoelectric focusing was performed using 11 cm (pH 5-8) IPGs
followed by separation on 12% mini polyacrylamide gels in the second
dimension of electrophoresis.
ImageMasterTM 5 gel analysis software was employed to study the
detection sensitivity of these four 2-DE gels in terms of the number of spots
detected. By applying the same automatic detecting algorithm to all gels, the
highest number of detectable spot was found with the gel stained by the “N4”
75
protocol (461 spots) while a comparatively less sensitive protocol was the “R”
method (417 spots). “N1” and “hot R350” both shared the same number of
detectable spots (450 spots) which was only 2% less than the most sensitive N4
protocol.
In view of the above findings and in consideration of the ease of use, the
hot R350 was chosen as the preferred coomassie stain protocol. This protocol is
not only economical but also avoids the use of hazardous perchloric acid which
is necessary in all other N and R modifications. It was noticed that the protein
spots would be destained completely with a clear gel background after overnight
destaining. This was not observed in the hot R350 protocol which probably due
to the strong aggregation of R350 dye molecules under a hot and acidic staining
environment.
Apart from the sensitivity issue, another key consideration is the
compatibility of the staining method to the later MS analysis. While colloidal
G250 was well known to be compatible to MALDI-TOF MS, the compatibility
of the hot R350 protocol was unknown at the time when this study was carried
out. Therefore, a comparison on the in-gel digestion and PMF for randomly
selected proteins spots have also been performed, two from each gel of colloidal
R and hot R350 protocols. It can be seen from Figure 20 that the protein spots
stained by the hot R350 achieved very similar peptide profiles as that from the
colloidal R. Therefore, both in-gel enzymatic digestion and MALDI-TOF MS
was confirmed not to be significantly altered by the hot R350. The same protein
was matched for both protocols according to the PMF result. Spot A was
identified as “Guanine nucleotide binding protein (G protein)” while spot B was
identified as “Aldolase C”
76
Spot A
Hot R350
Colloidal R
Spot B
Hot R350
Colloidal R
Figure 20. The peptide peaks of two different protein spots (spot A and spot B)
detected by MALDI-TOF MS. For each protein, the upper (in blue) peak profile
was from gel stained by the hot R350 protocol while the lower (in red) peak
profile was from gel stained by the colloidal R protocol. The same protein ID
could be correctly identified by PMF regardless the different staining protocols
for each spot.
4.3.1.4
Conclusion
Detection of proteins in SDS-PAGE is an essential step to make
quantitative comparison in proteomic study. The goal of various modifications
has been directed at improving the overall protein detection sensitivity. Neuhoff
et al. have successfully increased the colloidal coomassie staining using
77
ammonium sulfate in an acidic alcoholic media. Recently, a novel coomassie
staining method claimed to have achieved even better detection sensitivity by
incorporating aluminium sulfate and ethanol to coomassie blue dye (Kang et al.
2002). Therefore, newer and better staining will be developed over time. The
simple hot R350 protocol was preferred as a coomassie stain for routine staining
procedure and downstream MS analysis.
4.3.2 Silver staining
4.3.2.1
Background and aims
Silver stain was first introduced by Switzer et al (Switzer et al. 1979) for
protein staining in polyacrylamide gels. There have been a vast number of
published modifications since then for different protein samples (Porro et al.
1982; De Moreno et al. 1985; Chaudhuri and Green 1987; Nesterenko et al. 1994;
Swain and Ross 1995; Yan et al. 2000; Mortz et al. 2001). A common silver stain
protocol is shown in Table 5. Common silver staining procedures relies on the
reduction of silver ions to its visible metallic form but the precise mechanism has
not been fully established. Silver staining of 2-DE gels was reviewed (Rabilloud
1999) and although there is no standardized silver staining procedure, all silver
staining protocols are claimed to be more sensitive than the coomassie stain and
offers protein detection sensitivity down to nanogram range.
However, due to the variability in staining, it is known that
inter-laboratory comparison of silver staining sensitivity even with the same
staining protocol is difficult. Most importantly, only a few of the silver stain
protocols were compatible with MS analysis due to the protein modifications in
gel (Shevchenko et al. 1996; Yan et al. 2000; Mortz et al. 2001). In order to
78
identify an optimized protocol in term of detection sensitivity and MS
compatibility, several silver staining methods were investigated based on
published protocols (Schleicher and Watterson 1983; De Moreno et al. 1985;
hMoreno et al. 1985; Chaudhuri and Green 1987; Swain and Ross 1995;
Shevchenko et al. 1996; Scheler et al. 1998; Yan et al. 2000; Mortz et al. 2001)
Table 5. A common silver staining procedure with the functions of each step.
Steps
1. Fixation
Function
To insolubilize proteins and reduce diffusion of separated proteins
from the 2-D gel, and remove interfering substances especially
those with lower molecular weight, such as Tris, SDS etc that may
affect the image development.
2. Sensitization
To enhance the contrast between stained proteins bands and
background by creating latent images and thus improve sensitivity. It
is an important step for developing a positive image.
3. Washing
To removes excess components in sensitization step so as to allow
more efficient cross-linking of proteins in gel.
To attach silver ions to protein spots in the 2-D gel.
4. Silver
impregnation
5. Washing
To remove excess free silver complexes from the gel or silver nitrate
solution before developing step so as to reduce the background
staining or surface deposition.
To reduce the silver ions to silver metal and develop the colour of
6. Image
development
protein spots.
7. Stopping
To stop the developing reaction.
8. Washing
To change the gel from acidic to neutral form to prevent cracking
during drying by film
9. a) Dry storage
b) Wet storage
4.3.2.2
To dry the gel in film for handling and long term storage.
To keep the gel in solution for further analysis such as MS.
Procedures
Two broad range SDS-PAGE protein standard markers covering
molecular weight from 6.6 kDa to 201 kDa (8 proteins mixture, BioRad) and
from 6.5 kDa to 205 kDa (11 proteins mixture, Pharmacia) were employed in the
79
silver sensitivity optimization experiment.
One-dimensional gel electrophoresis was performed using mini-Protean
II tank with 12% polyacrylamide gels for marker loading. For both markers, a
serial dilution of 100, 50, 25, 12.5 ng of total proteins was prepared for each well.
The gels were stained generally based on the recent MS compatible silver
staining protocol (Yan et al. 2000) published at the time of experimentation. The
effects of different staining variables could be evaluated with specific
modification for each staining test. Moreover, the first commercially available
MS compatible silver stain kit was also compared to the custom made silver stain
protocol used here. All incubations and washing were carried out at room
temperature with gentle agitation on a platform rocker except as otherwise
specified.
The experimental and control gels were processed and stained together
for side by side comparisons. A public domain Java image processing program,
ImageJ (Rasband, W.S., ImageJ, U. S. National Institutes of Health, Bethesda,
Maryland, USA, http://rsb.info.nih.gov/ij/, 1997-2005) was used to quantify the
faintest marker lanes (with 12.5 ng total protein load) when the gel images could
not be compared on screen.
At the end of of this study, the detection sensitivity of the optimized
silver stain was evaluated using The Perfect Protein™ Markers (Novagen, US).
This is a relatively new mixture proteins marker (molecular weight from 10 kDa
to 225 kDa) with known protein quantity of each band.
80
4.3.2.3
i.
Results
One-step (30 min) fixation vs. two-step (2 x 15 min) fixation
100ng 50ng 25ng 12.5ng
Both were similar on screen.
100ng 50ng 25ng 12.5ng
The one-step fixation was 15%
better than the two-step fixation
according
to
the
image
quantification on the last lane. The
one step 30 min fixation was
therefore preferred.
one-step
ii.
two-step
One-step overnight fixation vs. two-step overnight fixation
Both were similar on screen
although the two-step overnight
fixation (renewed fixation solution
after 1 hr initial incubation) was
3%
better
than
the
one-step
overnight fixation according to the
image quantification on the last
one-step
lane. The one step protocol was
two-step
preferred considering the time and solution consumed.
81
iii.
Acetone and TCA additives in fixation step
It was claimed that acetone
and TCA might help in fixing
protein spots in gel and thus
increase the detection sensitivity
(Encarnacion et al. 2005). It can
be clearly seen that the additives
of 50% (v/v) acetone and 1%
with additives
control
(v/v) TCA did not improve the
detection sensitivity but gave a yellowish gel background. No acetone and TCA
additives were therefore included in the optimized fixation step.
iv.
Coomassie blue pre-stain before fixation step
A
combined
coomassie blue-silver stain
procedure was reported to
improve
sensitivity
the
detection
that
was
superior to silver stain as
the coomassie blue dye can
with pre-stain
control
enhance the global silver
ions binding (De Moreno et al. 1985). It was observed that the coomassie blue
pre-stain step generally increased the visible detection area for each band but the
detection sensitivity was very similar in these two protocols.
82
v.
Glycerol additive in fixation step
Glycerol was thought
to
decrease
the
background staining and
artefactual protein spots
as
it
maintains
the
moisture of the gel during
the
with glycerol
control
whole
staining
procedure (Chaudhuri and
Green 1987). However, the staining of both lanes was similar on screen. Image
quantification on the last lane showed only 6% increase in sensitivity with 2%
(v/v) glycerol comparing to the control, therefore this step was not included in
the optimized protocol in considering of the amount of extra work and solution
used.
vi.
Sodium thiosulfate additive in development step
Thiosulfate has been claimed
to give less background staining
and thus improve contrast of the
protein spots when it is included
in
the
developing
solution
(Rabilloud et al. 1988). The
with thiosulfate
additive of 0.01% (w/v) sodium
control
thiosulfate did not only remove background stain, it also reduced the protein
signals significantly. Therefore, it was not included in the developing solution.
83
vii.
Sensitization step without sodium acetate
The removal of sodium
acetate (Shevchenko et al. 1996)
in typical silver stain protocol
significantly
improved
the
detection sensitivity in several
repeated experiments. Therefore,
this modification was adopted in
without sodium acetate
control
the optimized protocol.
viii.
Urea additive in silver impregnation step
Urea
additive
(2.5%)
was said to increase the
diffusion
of
both
electrolytes
and
non-electrolytes
and
facilitate their penetration
with urea
control
into proteins in gel. It was
also said to act as a protective action in suppressing the ionization of silver
nitrate (Chaudhuri and Green 1987). The additive of 2.5% (w/v) urea did not
improve the detection sensitivity at all protein concentrations. Therefore, urea
was not used in the silver impregnation step.
84
ix.
Low temperature in silver impregnation step
Oxidation of silver ions
was said to be minimized
under low temperature which
resulted in more free silver
ions available for protein
binding in the gel and thus
low temperature
control
enhanced
the
sensitivity
(Shevchenko et al. 1996; Scheler et al. 1998). Both gels appeared to be similar
on screen. According to the image quantification on the last lane, 4oC
incubation of silver nitrate solution increased the sensitivity by 10%. Therefore,
this simple step of keeping the staining solution cool in fridge was incorporated.
x.
BioRad silver stain plus kit and the tailor-made silver stain protocol
The staining kit was
simpler
in
however,
procedure,
the
present
tailor-made
protocol
showed
staining
better
sensitivity. The solidified
silver stain kit
tailor-made
black
precipitants
appeared
in
the
developing step using the kit also required much longer washing time prior to
image scanning. Therefore, the silver stain kit was not preferred.
85
xi.
Optimized silver stain protocol
According to the experiments on silver stain optimization in term of staining
sensitivity and ease of use, a customized MS compatible protocol was devised.
The staining procedure was shown in Table 6.
Table 6. The working protocol of an optimized MS compatible silver stain.
Steps
1. Fixation
components
time
10% (v/v) acetic acid, 40% (v/v) methanol, 50%
overnight
DDH2O
2. Sensitization
0.2% (w/v) sodium thiosulfate, 30% (v/v)
30 mins
methanol, 70% DDH2O
3. Washing
DDH2O
5 mins x 3
o
4. Silver impregnation
2.5% (w/v) silver nitrate in DDH2O, keeps at 4 C
20 mins
5. Washing
DDH2O
1 min x 2
6. Image development
2.5% (w/v) sodium carbonate, DDH2O, 0.04%
depends
(v/v) formaldehyde freshly added before use.
7. Stopping
5% acetic acid, 95% DDH2O
15 mins
Using an optimized silver stain protocol, the detection sensitivity was
studied Figure 21. At the time of the study, the Perfect Protein™ Markers were
the only set of recombinant proteins available for SDS-polyacrylamide gel with
known amount of each component protein band. According to the dilution, each
band in lane 4 (25 ng total load) contained approximately 3.1 ng protein except
the 2x band which contained twice as much protein. For some proteins, the
detection level of the present optimized staining protocol could be extended to
lane 5 which has only about 1.6 ng per band.
86
200ng
100ng
50ng
25ng
Lane 2
Lane 3
Lane 4
12.5ng
6.25ng
3.13ng
1.56ng
2x
Lane 1
Lane 5
Lane 6
Lane 7
Lane 8
Figure 21. The detection sensitivity of the optimized silver stain protocol. A serial
dilution of the Perfect Protein™ Markers was separated on a 12% 1-D mini gel.
The protein amount per each band was 25 ng, 12.5ng, 6.3ng, 3.1ng and 1.6 ng
respectively for lanes 1 to 5 except for the 2x band which has double amount of
proteins.
4.3.2.4
Conclusion
This research showed that most published silver stain modifications did
not show significant improvement in detection sensitivity. They remain as
experimental considerations at large and have not been popularized in general
silver staining protocol. A balance between detection sensitivity and simplicity of
staining workflow was the main goal in the optimization process. It was found
that staining time and amount of water used in washing steps could be the key
issues in achieving batch-to-batch reproducibility. Extensive water washing
procedure may reduce image contrast and cause proteins loss especially of those
low molecular weight proteins (Schleicher and Watterson 1983).
Applying the current optimized silver staining protocol, the threshold of
87
detection was showed to be at a low nanogram (femtomole) range which was
amongst the detection limit of published MS compatible silver stain protocol
(Mortz et al. 2001). The optimized protocol was also tested to be compatible with
the protein digestion and MALDI-TOF MS analysis used (refer to protein
identification in Chapter 5).
88
Chapter 5: Assembly of chick retinal protein database
5.1 Introduction
At present, there is no publicly available data on two-dimensional
polyacrylamide gel electrophoresis reference map of chick retina and its protein
profiles. This study attempted to establish a chick retinal protein database by
characterising retinal cell lysates electrophoretically and identifying related
proteins from the 2DE protein profiles. This information provides a foundation
for building up a comprehensive database for sharing scientific information
among researchers online (www.swissprot.com). It may also provide a platform
for studying and comparing the differential retinal protein expressions in chicks
and other animal species. In addition, the study also aimed to characterize the
proteomic protocols and procedures for studying retinal tissues and to identify as
well as classify predominate expressed retinal proteins.
5.2 Experimental procedures
5.2.1
Retinal samples
This study was aimed to build a proteome database for emmetropic chick
retina. Since the refractive errors in chicks were stabilized and nearly
emmetropic one week after hatching, 7 days old chicks were used for building
the 2D retinal proteome database. Retinal tissues were homogenized and
extracted by the lysis buffer (EB5) as described in Chapter 4. The total retinal
protein harvested was determined by the modified Bradford protein assay. A total
amount of 50 μg or 300 μg soluble proteins were used and electrophoresed for
analysis in silver stained or coomassie stained gels. Before 2DE, rehydration
buffer containing 7M urea, 2M thiourea, 0.2% (w/v) Biolyte, 1% (w/v) DTT, 2%
89
(w/v) CHAPS, 1% (v/v) ASB14 and a trace amount of bromophenol blue was
added to the retinal lysates to make up for a total volume of 300 μl.
5.2.2
2D gel electrophoresis
Isoelectric focusing was performed using linear 17 cm IPG strips of pH 3-6,
pH 5-8 and pH 3-10. The dry strips were actively rehydrated with the protein
sample by in-gel reswelling protocol under constant temperature (20oC) for 16
hrs to enhance protein uptake. The protein samples were focused for a total of
42,000 Vh using a linear voltage ramp: 100 V for 2 hr, 500 V for 1 hr, 100 V for
1 hr, 4000 V for 2 hr and finally 8000V for 6 hr in the Protean IEF Cell.
Following IEF, strips were incubated in the equilibration buffer (6M urea, 30%
glycerol, 50 mM Tris, 2% SDS) containing 2% DTT for 15 min and then 2.5%
iodoacetamide for an additional of 15 min. The focused IPGs were rinsed briefly
with Milli-Q H2O, and sealed with 0.5% agarose on the top of 12% continuous
SDS-PAGE gels. Separation of the proteins in the second dimension was
achieved by 1 mm thick, either 16 x 20 cm (for PROTEAN II XL vertical
electrophoresis cells) or 25 x 20 cm gels (Dodeca tank) running at constant
80mA or constant 200V respectively until completion.
5.2.3
Protein detection and image analysis
2DE gel with higher protein amount of 300 μg was stained with colloidal
coomassie blue stain while those gels with lower protein amount of 50 μg were
stained with the optimised MS compatible silver staining. Stained gels were
scanned as uncompressed “TIFF” images at 300 dpi (pixels per inch) resolution
with a flatbed scanner “ScanMaker 4600” from Microtek (Taiwan). The gel
90
images were then exported to the ImageMasterTM 2D Platinum software ver.5
(Swiss Institute of Bioinformatics) for protein spots detection, quantification and
annotation. Finally, the gels were stored in a 10% methanol solution for later
protein identification.
5.2.4
Protein identification
For the automated process, a robotic PROTEINEER Line (Bruker Daltonics,
Germany) platform was firstly employed to investigate the most abundant protein
spots on a colloidal coomassie blue stained 2D gel. In addition to the automated
process which was found to recover less protein, a number of silver stained 2D
gels were later prepared and used for manual in-gel tryptic digestion on spots
which failed to be identified in the robotic PMF run.
5.2.4.1
Manual processing
In-gel digestion of 2D protein spots
Protein gel plugs were excised manually from 2DE gels using a clean
pipette tip (the picking size was about 1-2 mm in diameter) and transferred to 1.5
ml eppendorf tubes. The protein spots were first washed with milli-Q water and
50 mM NH4HCO3/ACN (1:1, v/v) for 15 min respectively and then they were
washed with ACN. In the reduction-alkylation steps that followed, the gel plugs
were firstly incubated at 56oC in 10 mM DTT/25 mM NH4HCO3 for 45 min and
further incubated in the dark at room temperature in 55 mM iodoacetamide/25
mM NH4HCO3 for another 45 min. After removing the solution, ACN was used
to wash the gel plugs before they were dried in a vacuum SpeedVac. Finally, the
gel plugs were incubated in 10 ng/μl sequencing grade trypsin (Promega, USA)
in 25 mM NH4HCO3 at 37oC overnight. The supernatant was recovered and
91
placed in a 0.5 ml ACN pre-washed eppendorf tube. Peptide extraction from the
gel pieces was performed by adding 5 μl ACN/0.1% TFA (1:1 v/v) and the
mixture was sonicated in water bath for 10 min. The supernatant was collected
and added to the previous recovered extract. This extraction procedure was
repeated for 3 cycles. The collected extract was concentrated to about 3-5 μl in
vacuum centrifuge and then frozen for future analysis.
Protein identification by MALDI-TOF MS
Peptide samples of 0.5 μl were loaded into individual wells and allowed
to dry on an AnchorChipTM (Bruker Daltonics, Germany). The AnchorChipTM
have 384 positions of either 400 μm or 600 μm spot size. It has a prestructured
MALDI sample support which was proven to enhance the sensitivity of detection
(Schuerenberg et al. 2000; Johnson et al. 2001). After the sample was completely
dried and concentrated on the AchorChipTM at room temperature, 2 μl of CHCA
stock matrix solution [1 mg HCCA/500 μl ACN and then mixed with 0.2% TFA
(1:1, v/v)] was added and mixed with the peptide samples in each well. Mass
spectra were acquired using a Bruker Autoflex MALDI-TOF mass spectrometer
under the positive ion reflectron mode. The time of flight was measured using the
following parameters: 19KV Ion source 1 (reflector), 16.55KV Ion source 2
(reflector detector), 1400V detector gain voltage offset, 5Hz laser frequency,
80ns plused ion extraction. Nonlinear external calibration was done with a
calibrant mixture containing angiotensin II (m/z 1046.5418), angiotensin I (m/z
1296.6848), substance P (m/z 1347.7354), bombesin (m/z 1619.8223), ACTH
(fragment 1-17, m/z 2093.0862) and (fragment 18-39, m/z 2465.1983). The
spectra were further calibrated internally against the autoproteolytic trypsin
fragments of m/z 842.509 and m/z 2211.104. Before interpreting the mass
92
spectra, all known contaminant peaks (Table 7) were removed according to the
results experienced in the control experiments and the manufacturer
recommendation. The resulting peak lists from 800 to 3000 m/z for all samples
were generated by the FlexAnalysis 2.0 (Bruker Daltonik, Germany) and
searched against the SwissProt and NCBInr sequence database via the Mascot
search engine online (http://www.matrixscience.com) or through the Biotools 2.0
software (Bruker Daltonik, Germany). For database entry, the taxonomy was
restricted to Metazoa (Animals) and a maximum of 1 missed cleavage was
allowed. The protonated molecule ion “MH+” and “Monoisotopic” were defined
for the peak mass data input. The potential chemical modifications of the
alkylation of a cysteine group [Carbamidomethyl (C)] and the oxidation of a
methionine residue [Oxidation (M)] were also considered in the search. For all
mass lists, the peptide tolerance/error was at most 100 ppm and no restriction
was applied for both the protein isoelectric point and molecular weight.
Table 7. A reference mass list of known peptides contamination which were
excluded in PMF.
93
5.2.4.2
Processing using the robotic system
PROTEINEERTM SP and DP robots
Protein spots identification of coomassie stained gels were subjected to
automatic processing using a robotic PROTEINEER Line (Bruker Daltonics,
Germany). In brief, a 2DE gel was first rinsed with milli-Q water for 30 min. It
was then mounted on a glass plate and fixed by an aluminium frame to minimize
gel motion during picking and transport. The image of the 2DE gel was scanned
by embedded scanner equipped with a transluminating light bridge and the spots
subjected to protein identification were located and assigned on screen as a
picking list in the protein spot picking station. Relevant gel spots were then
excised automatically by a liquid handling robotic picker (PROTEINEER SP)
into a 96 wells microtiter plate using a 1 mm diameter size probe. Proteolytic
peptide fragments of the protein spots were generated by programmed protocol
in the temperature-controlled PROTEINEER DP Digest&Prep station where the
washing, in-gel digestion, incubation steps were sequentially performed. All
necessary buffers, enzyme, and matrix, for protein digestion and MALDI sample
preparation used in the automatic system were provided by the manufacturer’s
digestion kit. Upon the completion of trypsin in-gel digestion, the protein
samples and calibrants were subsequently spotted and dried on an Anchor target
plate (400 μm or 600 μm spot size) using the “thin-layer affinity preparation”
approach (Gobom et al. 2001) and the HCCA matrix solution was loaded on top
of the dried analytes.
Automatic peptide mass fingerprinting
Automatic MALDI-TOF peptide acquisition was carried out in the
Autoflex MS using the bundle FlexControl software (Bruker Daltonik, Germany)
94
based on a real-time Fuzzy logic feedback control engine according to an internal
pre-programmed SNAP algorithm. After summation of 500 shots with detectable
peptide peaks for each spot, all monoisotopic peaks were automatically annotated
and aligned against external calibration. Protein database searches were triggered
by ProteinScape using the generated peak lists as inputs for offsite Mascot
database search. The searching criteria were similar to that in the manual search
except 200 ppm peptide tolerance/error was allowed. A larger peptide tolerance
was applied in automatic search as only external calibration was performed for
the peptide calibration. Internal calibration of trypsin autolysis was avoided in
order to prevent any false assignment of trypsin peaks during the automatic
peptide acquisition. Protein identification was evaluated based on the predefined
matching criteria similar to that of manual search. The search reports were
generated by the bundle “Proteinscape” database management system (Bruker
Daltonik, Germany) and stored as HTML files for review. The workflow of this
robotic system was shown in Figure 22. After the automatic processing, a second
phase of manual examination and PMF was carried out to ensure that there was
no missing laser hit due to irregular matrix formation or system misalignment.
95
Figure 22. The workflow of a robotic system for MALDI-TOF MS protein
identification.
5.3 Results and discussion
5.3.1 Protein identification result
Master electronic gels (created using imaging software, Adobe Photoshop) of
2D chick retinal profiles covering the pH range from 3 to 10 were shown in
Figure 23 and Figure 24. Proteins spots identified from all 2D gels with silver
and coomassie staining methods were combined and assigned on these master
gels.
96
Figure 23. 2-D chick retinal proteins profile resolved in 12% acrylamide gel of pH
3-6. The annotated spots were excised and the proteins were identified by PMF
using MALDI-TOF MS.
97
Figure 24. Computer merged 2-D chick retinal proteins profile resolved in 12%
acrylamide gel between pH 5-8 with a separated section covering pH 8-10. The
annotated spots were excised and the proteins were identified by PMF using
MALDI-TOF MS.
A total of 350 distinct protein spots were detected and mostl (~71%) fell in
the pH 5-8 range. Out of 160 high abundant spots picked within this range, 105
proteins (66%) were identified by the robotic system and matched significantly
in the database search. For those unmatched spots, 32 of them (20%) failed
because three was no peptide spectrum generated after MALDI-TOF MS. This
problem could be due to insufficient trypsin in-gel digestion, uneven on-chip
analyte/matrix mixture formation or simply due to insufficient amount of sample
for identification. Therefore, these unidentified proteins were trypsin-digested
98
again manually using gel plugs from coomassie stained or silver stained gels. All
successful protein identification after MALDI-TOF MS were annotated on the
master gels. A total of 155 retinal protein identified were listed in appendix 2
with their associated information and cross references in protein sequencing
databases. As expected, average matched amino acid sequence coverage was
found to be higher for protein using gel plugs from coomassie stained gel (~36%)
when compared to that using silver stained gel plugs (~27%) because of higher
protein abundance per gel spot. Thirty-eight protein spots (~25%) got more than
one significant match in the NCBI database (The National Center for
Biotechnology Information search systems). Yet, these “parallel” matches were
either belong to the multiple species of the same protein or from the same protein
family.
Proteins highlight
In addition to common housekeeping proteins, such as heat shock proteins
or the actin related proteins, ten of the most abundant retinal proteins in the
retinal proteomic maps (Figure 23 and Figure 24) were identified. These included
tubulin (spots 39, 40) 21, 22; visinin (spot 33) 23; calretinin (spot 34) and
calmodulin (spot 146) 24-26; beta-synuclein (spot 145) 27, 28; glutamine
synthetase (spot 61) 29, 30; enolase (spots 64, 65, 67, 70, 108) 31; B-creatine
kinase (spots 66, 71, 82, 109) 32, 33; aldolase C (spots 63, 84, 98) 34 and
carbonic anhydrase II (spots 58, 59) 35. A brief description of these proteins was
given in Table 8.
99
Table 8. Brief functions of the ten abundant chick retinal proteins identified by
MALDI-TOF MS.
NCBI GI Protein name Predicted / known functions
Mascot Mascot
no.
pI.
M.W.
(da)
52138699 tubulin
It is a cytoskeletal protein which is the major 4.78
50377
constituent of microtubules and is found
highly expressed in neuronal cells.
86482
visinin
An abundant calcium-binding protein in the
5.01
22611
45384332, calretinin,
Both are calcium-binding proteins. They are 5.10,
31171,
45384366 calmodulin
homologous proteins which were located in 4.10
16842
eye. It is expressed in retinal cone cells for
phototransduction.
many neurons of the CNS.
45382773 beta-synuclein It is expressed primarily in neural tissue,
4.38
14054
6.38
42747
6.17
47617
5.78
42525
It is one of the ubiquitous glycolytic enzymes 5.79
39023
specifically in synapses around neurons, but
not in glial cells.
45382781 glutamine
synthetase
A retinal Muller glial-specific enzyme that
amidates glutamate, a well known retinal
neurotransmitter to glutamine. It is inducible
only when the Muller cells are closely
associated with retina neurons.
1706653
enolase
It is an essential glycolytic enzyme that
catalyses the interconversion of
2-phosphoglycerate and
phosphoenolpyruvate. There are 3 different
tissue-specific isoenzymes (alpha, beta and
gamma) currently known.
211235
B-creatine
It catalyzes the reversible transfer of high
kinase
energy phosphate from ATP to creatine,
generating phosphocreatine and ADP. It
plays a central role in energy transduction in
the brain and retina.
226855
aldolase
found in the brain for glycolysis
833606
carbonic
It is one of the cytosolic isozymes of
anhydrase II
carbonate dehydratase which is responsible
for the reversible hydration of carbon
dioxide. It is found widespread in brain tissue
100
6.56
28989
In the 2DE profile, Enolase, B-creatine kinase and aldolase C showed
several isoelectric variants. These may suggest the existence of a number of
physiological post-translational protein modifications (PTMs) such as protein
phosphorylation where the most basic spot was the dominant one
(non-phosphorylated). Since the most common modifications during sample
handling are amino acid oxidation (commonly detected in MS PMF) which
should not be resolved and detected by 2D gels, these repeatable
post-translational protein modifications may likely occur in vivo. The extent and
site of PTMs are not known with the existing identification platform. Future
protein sequencing using LC/MS/MS will be required to elucidate these
molecular changes. Interestingly, membrane associated proteins which are
important in cellular signal transduction were also found in the gels using the
existing buffer solution. These include ATPases (spot 74, 76) and ATP
synthetases (spot 38, 122).
Moreover, the present results may be complementary to the published
human RPE database (West et al. 2003) and allowing better understanding and
more complete picture of protein functions in the retina. In addition, the present
retinal database also provided a more global profile of total retinal proteins than
the previously published protein maps which were only focused specifically on
photoreceptors (Morel et al. 2000) and Muller glia cells (Hauck et al. 2003). In
view of the common embryological origin of the retina and CNS, it is not
surprising to see that the retinal tissue shared good similarity in term of protein
profile and protein identification with the published proteomes of brain or
cerebellum. For examples, similar to the present results, heat shock protein and
actin were highly abundant in the rat brain proteome and the catalytic activity
101
was found to be the major function among the 210 identified protein spots. Also,
the majority of the proteins from the human and rat brain tissues were located in
the cytoplasm and most of the human brain proteins were also located between
pH 5-8.(Fountoulakis et al. 1999; Langen et al. 1999; Beranova-Giorgianni et al.
2002).
5.3.2
Protein classifications
5.3.2.1
Subcellular locations
In order to have a global understanding of the 2D separated protein
nature, the classification of the chick retinal proteins according to their cellular
locations and predicted functions was attempted. Using the FASTA amino acid
sequence according to the annotated SwissProt database, the subcellular locations
of proteins were analyzed by the Proteome Analyst Specialized Subcellular
Localization Server V2.5 (http://www.cs.ualberta.ca/~bioinfo/PA/Sub/) (Lu et al.
2004). For particular protein spots having more than one SwissProt ID in the
proteome database, the one related to “gallus” was selected first or the one with
higher MASCOW score was input. Since some of the identified proteins had not
yet been updated in the SwissProt database, the subcellular localization
prediction was only performed on 119 proteins (about 77%) out of the total 155
identified proteins. The average peptide sequence length was 394 amino acids.
Most of the proteins were likely present in the cytoplasm (about 71%).
About 7.2% of the proteins reside in the endoplasmic reticulum and
mitochondrion while less than 1% identified proteins was found to be plasma
membrane bound. There were 2.4% of proteins returning with unknown
subcellular location. The complete classification was shown in Figure 25.
102
Figure 25. Classification of retinal proteins identified by MALDI-TOF MS
according to their predicted subcellular locations.
5.3.2.2
Molecular functions
The chick retinal proteome can also be classified according to their
molecular functions. The identified proteins were classified into ten groups
according to their molecular functions based on the Gene Ontology on amiGO
database (http://www.godatabase.org) (Ashburner et al. 2000) and the result was
shown in Figure 26.
103
Figure 26. Classification of retinal proteins identified by MALDI-TOF MS
according to their molecular functions based on the Gene Ontology.
Over 80% of the identified proteins fell into three major functional
categories which were “catalytic activity” (39%), “binding” (33%) and
“transporter activity” (10%). Further classification of the catalytic function was
made and shown in Figure 27. The major catalytic activity was related to
hydrolase which functions to hydrolyse various biomolecules.
Figure 27. Further classification of retinal proteins (of Figure 23) according to
their catalytic functions.
104
5.3.2.3
Biological functions
It was also observed that there were two dominating functional aspects
of the retinal proteins. Among the 100 annotated proteins (QuickGO database;
http://www.ebi.ac.uk/ego/), 30% of them were found to be involved in glycolysis
or cellular metabolism while 20% were related to transport or signal transduction.
These findings may show the distribution of the soluble protein machinery within
the retina and reflect the key physiological activities undertaking by the retina in
vivo. Other less abundant proteins were related to biological functions such as
protein folding, microtubule-based movement and cytokinesis.
5.3.3
Building the chick proteome database
Automation of MALDI-TOF MS functions not only speeds up the
experimental procedure but also minimizes potential manual contaminations.
However, its sensitivity in terms of protein identification is not as good as the
manual procedure. In addition, a major difficulty in automated PMF
identification using the robotic system has been the large peptide m/z error
encountered in using external spectra calibration. In the manual processing,
significant improvement in the database match during the second phase
examination was made by assigning the trypsin autoproteolytic fragments as
internal calibration. Sometimes due to low peptide recovery, the automated
process may not have obtained sufficient quality peaks for protein identification.
This problem may be resolved by manual laser hitting at the spot target so as to
generate additional peptide peaks of better resolution for PMF identification.
Such manipulation was difficult if not impossible with the automated system.
Failing this, those unmatched protein may require either later database searching
105
with more complete and updated sequence libraries or de novo microsequencing
approaches such as ESI-MS/MS.
“De novo PSD sequencing” in MALDI-TOF MS
A new MALDI-TOF MS system with delayed extraction mode and a
reflectron design such as Bruker Autoflex MS is capable of performing Post
Source Decay (PSD) analysis. It enables fragmentation of a metastable ion (by
mass analysis of daughter ions from in-flight fragmentation of the parent ion)
that has been fully accelerated in order to obtain structural information. Although
the procedure is more complicated and time-consuming than tandem mass
spectrometry, this approach is proposed as an alternative to MS/MS peptide
sequencing (Chaurand et al. 1999).
The PSD analysis was attempted in this study for some samples which had
peaks generated but failed in the PMF query. The hope was to increase the
specificity of the search by combining the peptide masses and partial sequence
data found by PSD. In theory, this method can allow identification of the proteins
which have only partial gene sequence information or represented only by the
expressed sequence tag (EST) databases (Mann 1996). However, the PSD
approach in this system was very difficult to operate and impractical to perform
at this stage. First of all, the laser power in PSD has to be increased well beyond
the threshold value that was required by usual MALDI spectrum. Secondly, ions
with lower kinetic energy in separate mass ranges are generated progressively
which build up the entire spectrum in a stepwise manner. This acquisition
procedure is very time consuming and each step must be individually calibrated
for a complete spectrum stacking. The success of PSD thus varies with the
sequence length of individual peptide, ease of sample ionisation, precise laser
106
power adjustment, and more importantly, the sample amount or sample depletion
rate. Moreover, an accurate interpretation of fragment ion spectra is complicated.
All of these intrinsic shortcomings have limited the application of PSD
technology in general proteomic studies. It has been reported that unambiguous
sequencing of unknown peptides by traditional PSD approach is not always
possible (Chaurand et al. 1999). In recent years, a new PSD approach using
nonlinear reflectrons, such as the curved field reflectron, has been developed to
address the problems by providing higher bandwidth, thus eliminating the need
for step-wise ion scanning (Cotter et al. 2004).
A chicken genome database
Mass spectrometry together with database searching has enabled efficient
and reliable protein identification that is not possible by traditional protein
analysis. However, the success of protein identification using the proteomic
approach relies heavily on the availability of genomic data. Therefore, a lack of
genomic information on a particular species can substantially limit the scope of
proteomic study in term of successful protein identification. Since a complete
chicken database was not available at the moment for this study, the PMF search
was performed using the vertebrate’s database.
The chicken has long been the primary model for studying embryology and
development. Due to the occurrence of avian flu, the need for a complete chicken
genome became urgent. A large scale chicken genome project was finally
underway by a consortium of scientists in early 2003 (press release available at
http://www.genome.gov/11510730). With the help of a whole genome shotgun
approach, the available genome data for chicken have rapidly grown from only 1
(complete mitochondrion) to 31 (chromosomes 1-28, 32 and sex chromosomes m
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& z) within a year. As a result, there is a huge increase in the information on
translated proteins in the database (from about 8,300 proteins in early 2004 to
more than 29,000 proteins in early 2005). By the end of September 2005, the
chicken database (about 3Mb genome size) was nearly complete and was at
“genome refinement” under National Human Genome Research Institute
(NHGRI)
sequencing
program
(http://www.genome.gov/19516773).
This
publicly accessible database is being continuously updated online at NCBI
(www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=9031). There has
been continuous improvement in the rate of successful identification of the
retinal proteins by PMF with the growth of the database. Currently, only a few
numbers of proteins (~ 5%) in the list were identified based on homology search
against other species. A complete chicken genome in the near future will thus
further enhance the success rate of protein identification by PMF and reduce the
need for more complicated PSD or tandem MS approaches.
5.4 Conclusion
The construction of a 2-D map is commonly the first step in studying the
proteome of a particular tissue. Among different MS systems, MALDI-TOF mass
spectrometry is the only technique that is fully compatible with automatic robotic
workflow capable of generating high throughput data.
In this study, the first 2D proteomic map of chick retina has been established.
These proteins were profiled using 2DE covering the 3-10 pH range. The existing
protocol was able to resolve hundreds of proteins of chick retina and 155 of those
were identified using the peptide mass fingerprinting method with manual and/or
robotic MALDI-TOF mass spectrometry. The majority of proteins are classified
108
as having catalytic activity and binding functions, and they are mostly involved
in glycolysis and signal transduction.
The study has outlined a feasible proteomic approach that can generate
quality retinal proteome data. The chick retinal proteome map has also provided
a necessary reference and platform for further investigation on the complex
protein functions of the retina in relation to myopia or other retinal diseases.
109
Chapter 6: Normal chick retinal protein expression
6.1 An intra- vs. inter animal comparison
6.1.1 Introduction
In the previous experiment, a workable proteomic procedure from proteins
extraction,
protein
separation
by
two-dimensional
polyacrylamide
gel
electrophoresis (2D-PAGE) to protein identification with Matrix-Assisted Laser
Desorption Ionization-Time of Flight mass spectrometry (MALDI-TOF MS) for
chick retina was devised. In this following experiment, an attempt to study the
protein profiles between eyes of the same and different animals by using gel
analysis software is made.
6.1.2 Experimental procedures
Unless specified differently below, the experimental procedures were similar
to that described in Chapter 5.2.
Retinal samples
Six retinae were isolated from three 10 day-old white leghorn chicks of
similar body weight and refractive status. The proteins were extracted by EB5
lysis buffer. The protein amount was quantified by modified Bradford protein
assay and 300 μg of soluble retinal proteins of each eye were electrophoresed in
2D gels.
2D gel electrophoresis
In the first dimension gel electrophoresis, the retinal proteins were loaded
with the ReadyStripTM Immobilized pH gradient (IPG) strips (11cm) of pH 5-8
and focused for a total of 36,000 Vh at constant temperature (20oC) under linear
110
voltage ramp in a BioRad PROTEAN IEF Cell. In the second dimension, the
proteins were separated in 12% continuous polyacrylamide gels (1 mm thick, 25
x 20 cm) at 30 mA /gel overnight until the dye front was 1cm from the bottom.
Two IPG strips were loaded with samples from the paired right and left eyes and
they were run side-by-side on a single SDS-PAGE gel. All three gels (from 3
chicks) were run in the BioRad Dodeca tank system simultaneously so as to
minimise variations in the running conditions.
Protein detection and image analysis
After the 2D-PAGE, the proteins in the gels were fixed overnight with
methanol /acetic acid solution. They were then stained together in the same
container with premixed Bio-safe colloidal Coomassie Blue G-250 satin (BioRad,
USA) on a rocking platform. After staining for 2 hours, the gels were destained
with deionized H2O for 30 mins. The gel images were scanned and exported to
the Melanie 4 software for protein spots matching and quantification without
prior editing. Twenty spots on each gel were randomly selected as references for
gel alignment. Automatic spot detection and spot matching were carried out so
that all software parameters were set identically across all six gel images.
Intra- and inter-animal protein profiles were matched and compared between
the paired retinal samples. In terms of the quantitation of spot intensity, the
program first calculated the optical density (Od) of the spot. It was based on the
highest calibrated pixel intensities of the spot from which the background was
subtracted. The background is defined as the minimum pixel value in the
neighbourhood of the spot. The spot volume was calculated as the total pixel
volume above the spot border which was equivalent to protein amount of the
spot.
111
6.1.3 Results
The variation of retinal protein profiles of the same and different animals was
investigated. Figure 28 showed the coomassie blue stained protein profiles of
three pairs of normal retinae.
IEF
IEF
#1 RE
#1 LE
KDa
112
#2 RE
#2 LE
#3 RE
#3 LE
Figure 28. The protein profiles of three pairs of normal retinae separated with
pH5-8 IPG strips and 12% SDS-PAGE in a Dodeca cell are shown. The gels
were stained with Biosafe Colloidal Coomassie blue G250 premixed solution.
(IEF: isoelectric focusing; Da: Dalton; RE: right eye; LE: left eye.)
113
Applying the same spot detecting algorithm to all gels, very similar numbers
of protein spots on each retinal profile using the Melanie 4 gel matching software
was observed. There were about 215 ± 7 (Mean ± SEM, n=6) distinct spots
detected in each gel. The overall matching percentages of spots between the right
and left retinae of the same animal ranged from 80 to 87% and averaged at 83.1
± 2.1% (Mean ± SEM, n=3). Of those matched spots, the spot volume (or the
total protein content per spot) correlated extremely well between eyes of the
same animal (correlation coefficient=0.98). Comparing the protein profiles
between eyes of different animals, lower percentages of spot matching were
observed in all three comparisons: #1 vs #2, #1 vs #3 and #2 vs #3, and the
values were 69.1%, 58.3% and 64.8% respectively, averaged at 64.1 ± 3.1%
(Mean ± SEM). The difference in the overall matching percentages between the
intra- and inter-animal comparisons (83.1% and 64.1% respectively) was
statistically significant (P<0.05 by paired t-test). Of those matched spots between
different animals, the spot volume correlations were also good, with a typical
value of 0.96. This was only slightly less than that in the same animal
comparison (0.98).
It was also noted that during the automated spot matching, some spots on one
gel may be mismatched to the nearby spots on the paired gel especially for those
closely packed spots. These mismatches could be corrected by manual
spot-to-spot checking. It was found that spot mismatches between different
animals (inter-animals) were higher than that of the same animal (intra-animal).
Therefore, the actual correct matching rate in the inter-animal comparison would
have been poorer if these mismatches were rectified. In other words, the protein
profiles of retinae from different animals were more dissimilar.
114
To further investigate the differences in intra-animal and inter-animal
comparisons, the scatter plots of the spot Od between eyes of the same animal
and also between animals were studied. In Figure 29, the number of proteins
matched was higher in the same animal than that between different animals (167
pairs vs. 156 pairs). Most interestingly, the Od value differed by 5.1 unit between
different animals whereas very slight difference of 0.49 unit was seen in the
intra-animal comparison (Figure 29, the regression lines). Enlarged gel sections
from both eyes of chick #2 and #3 were shown in Figure 30 as an example.
115
Chick #2 RE and LE
(intra-animal match)
0.95*x+0.49
Matched spots: 167
A.
LE
RE
(inter-animal match)
Chick #2 and #3
1.0*x+5.1
Matched spots:156
B.
#3
#2
Figure 29. Scatter plots of the matched spots according to the Od (optical
density). A.: A typical intra-animal protein profile comparison between the right
and left retinae of chick #2. B.: A typical inter-animal protein profile comparison
between the right retinae of chick #2 and chick #3. (Higher false up-regulation as
indicated in arrow).
116
6.1.4 Discussion
The proteomic approach aims at identifying differential protein expression by
comparing protein profiles between the control and experiment proteomes. For
example, in myopia research, the differences in protein expressions between the
control and myopic eyes of animals can be profiled and studied. These protein
changes could reflect the underlying physiological changes related to eye growth
and therefore may shed important light on the pathogenesis of myopia. For
meaningful comparison, the protein profiles of the samples must be sufficiently
repeatable and consistent.
The Coomassie blue stained protein 2DE profiles between the right and left
eyes of the same animal (intra-animal comparison) as well as eyes between
different animals of the same age (inter-animal comparison) were studied.
Coomassie blue staining was used because it can give good linearity in
quantifying protein concentration and a narrow pH range (5-8) was used to
separate protein spots optimally for spot detection and analysis.
These results have clearly shown that the inter-animal variation was
significantly (p<0.05) higher than the intra-animal variation in term of protein
spots matching under the same experimental conditions. Although this was an
expected finding, the present study has quantified the extent of similarity in these
comparisons. Furthermore, it was noted that if the presence of differential
expressed proteins was decided based solely on the Od values (Figure 29, the
regression lines) of the matched spot pairs, one might wrongly conclude that
there were protein changes between the apparently similar age-matched retinal
samples. It highlighted the potential risk of misinterpreting changes in protein
expressions when comparing samples from different animals.
117
One of the possible reasons of the protein variations between animals may
be that since very young and fast growing chicks were used in the experiment,
subtle differences in development or growth rates between chicks could produce
very different protein 2-D maps. This argument is consistent with the observation
in the 2D protein patterns from right eye (RE) and left eye (LE) of two animals in
Figure 30. Figure 30 A showed the comparison of the spot Od at two different gel
areas between chick #2 and #3 (inter-animal comparison). The spots being tested
(t) seemed to be “up-regulated” in both eyes of chick #3 by about 28.9% (SD ±
4.0, n=2) in area 1 and 52.6% (SD ± 8.5, n=2) in area 2. However, it was obvious
that the spots (t) between two eyes (RE vs. LE) of the same animal were similar
(intra-animal comparison) in both cases. Therefore, a false “up-regulation” of
protein (t) in the experimental eyes #3 may have been concluded if either eye of
another individual #2 is taken as a control. Similarly, in Figure 30 B, differential
protein expression between different animals may have been suggested, but those
apparently different spots were equally present in both eyes of animal #3 (as
indicated) while they were altogether missing in animal #2. These differences
between animals were very repeatable in all above cases and they cannot be
attributed to staining variations in different gels. It was clearly shown that the
intensity of a reference spot (ref), which was next to the test spots (t), remained
fairly unchanged in all cases as shown in Figure 30 A.
118
Area 1.
(A)
RE
Area 2.
LE
LE
RE
ref:9.6
t: 69.4
#2
ref: 120
t: 64.6
ref: 117
#2
t: 46.6
ref:10.4
t: 38.6
ref:11.4
t: 91.4
#3
ref: 120
t: 81.4
ref: 119
#3
t: 68.3
ref:10.2
t:61.2
(B)
Figure 30. Enlarged panels showing intra- and inter- animal differences in the 2D
gels of chick #2 and #3. Gel spots were converted to greyscale and the spot
boundaries were detected by Melanie 4 software. A.: The spot intensities (Od)
were represented as numeric values according to the automatic gel analysis data.
(t: test spot, ref: reference spot). B.: Two-dimensional and corresponding
three-dimensional spot patterns comparison for both eyes of chick #2 and #3.
Although not completely unexpected, it is important to note that protein
expressions varied significantly among different animals presumed to be the
same age but varied far less in eyes of the same animal. Schaeffel and Howland
suggested that the feedback loop controlling eye growth was genetically
119
determined in each individual. In binocular FDM, the refractive errors acquired
were highly correlated in both eyes of the same individual but high variations
existed among different animals (Schaeffel and Howland 1991). The present
finding highlights the caveat in comparing protein profiles of tissues from
different animals. Most importantly, it accentuates the advantages of comparing
eyes of a single animal in experimentation. It is particular applicable in
proteomic study where eyes of the animal can be manipulated separately and
compared, such as in the animal myopia research. Given that the background
variation of protein within animal is small, subtle differential changes in proteins
can be identified with more confidence.
6.1.5 Conclusion
The intra- and inter-animal variations of 2D-PAGE protein expressions in the
chick retina were compared using Melanie 4 gel matching software. In term of
protein profile and protein match, there were good similarities between eyes in
the intra-animal comparison but relatively more dissimilar in the inter-animal
comparison. The potential caveats in comparing protein profiles between
different animals where the apparently differential expressed protein could
actually be false positive signals have been documented. The findings
highlighted the potential usefulness of proteomic approach in basic eye research
where comparison between control and experimental tissues can be carried out in
the same animal.
120
6.2 Developmental retinal profiles changes
6.2.1 Introduction
The initial step of this proteomic approach to understanding the retinal
protein/s involving in the myopia development, has focused the previous studies
on optimizing a workable protocol with the normal chick retina and constructed a
2DE-based proteome reference database (Chapter 5). The advantages and
importance of intra-animal comparison between the left and right eyes have also
been characterized.
An early 2-DE study on cultured embryonic chick retina has reported changes
in only one protein - glutamine synthetase (Soh et al. 1982). The amount of data
produced is very limited possibly due to the technological limitations in
gel-based protein separation, plus a lack of MS based protein identification at the
time. Presently, there is still very little published information on the protein
changes related to post-hatching avian retinal growth. Since myopia is believed
to be an accelerated ocular growth process, it likely shares some common
physiology to the normal growth process. Therefore, the normal retinal growth of
young chicks was studied by profiling the retinal proteins at different ages in this
study.
6.2.2 Experimental procedures
Unless specified otherwise, the experimental procedures were similar to that
described in Chapter 5.2.
Retinal samples
Three normal chicks of similar body weight were used per each time point of
3-day old (PN3), 10-day old (PN10) and 20-day old (PN20) and their retinae
121
were harvested and used for studying the differential protein expression in early
eye growth. The protein concentration was determined by a commercially
available reagent compatible 2-D Quant Kit (Amersham Biosciences, China).
Equal amount of proteins from each chick at the same time point (20 μg each)
were pooled (total = 20 μg x 3 = 60 μg).
2D gel electrophoresis
The 2-DE separations were carried out as described previously (Chapter 6.1)
but longer 17 cm IPG strips of pH 3-10 were used and the proteins were focused
for 42,168 Vh for a global view of the protein profiles. To better visualize protein
spots, the differential protein expression study on PN3 and PN20 samples using
narrow 11 cm IPG strips of pH 5-8 was repeated. To minimize experimental
variations, samples to be compared were homogenized and run in the 2DE
systems at the same time (17 cm IPGs were run together in parallel while paired
11 cm IPGs were run side by side on a single gel).
Protein detection and image analysis
After the 2DE, all gels were stained with the optimized MS compatible silver
staining method and the gel images were immediately scanned. The digitalized
gel images were then exported to the ImageMasterTM 2D Platinum software ver.5
(Swiss Institute of Bioinformatics, Sweden) for spots matching and
quantification without prior editing. Only differentially expressed protein spots
detected on the paired gels were marked for protein identification.
Protein identification
Protein spots were excised manually from the 2D gels and underwent manual
in gel trypsin digestion and MALDI-TOF PMF as descried before in CH 5.2.
122
6.2.3 Results and discussion
6.2.3.1.
Animal growth
It is well known that chick’s eye, as well as many other vertebrates’ eyes,
are hatched hyperopic and they grow towards emmetropia during the early
postnatal period (Wallman et al. 1981; Irving et al. 1996). The present data
showed that young chicks grew at an approximately linear rate (where r2=0.99) at
the three selected study periods over the first 20 days in terms of body weight
(PN3=38.3 ± 1.9g; PN10=70 ± 1.3g; PN20=98.3 ± 0.9g. mean ± SEM where n=3
in each group). The mean refractive error (in equivalent sphere) of postnatal
growth approached emmetropia from +1.88 ± 0.30D at PN3 to +0.79 ± 0.28D at
PN20 (mean ± SEM where n=6 in each group). The above results on refractive
errors agreed well with previous findings of postnatal chick growth. It was
reported that eye growth during this experimental period was almost linear
(Schaeffel et al. 1988).
6.2.3.2.
Different protein expressions
The protein profiles of the pooled retinae from PN3, PN10 and PN20
chicks (n=3 in each group) using broad range pH 3-10 IPG strips were studied.
The gel images from the left eyes were shown in Figure 31 (A). The retinal
protein profiles amongst these 3 groups of chicks were very similar with most of
the proteins distributed within the pH5-8 range and this distribution was similar
to the earlier retinal proteome databases (Figure 23 and Figure 24). Using the
IM5 gel analysis software, there were over 500 (524 ± 31. mean ± SEM, n=3)
distinct protein spots detected within this range.
Six protein spots (#D1, #D2, #U1, two spots in #U2 and #U3) appeared
to be differentially expressed. The related gel image were enlarged and shown in
123
Figure 31 (B). Similar differential protein changes were also found in the
contralateral eyes and the overall findings were summarized in Figure 31 (C) The
estimation was based on the calculated “spot volume” of each specific spot
[“Spot volume” is the integration of optical density over the spot area where the
value is calibrated against the gel background value adjacent to the spot]. Most of
the protein spots of PN3 and PN20 were located at the center of the gel (between
pH 5-8). In order to improve the separation, the retinal protein samples were
further electrophoresed using pH 5-8 IP G strips (Figure 32). In addition to the
six differentially expressed spots detected previously, three more differentially
expressed spots were found in 2D gels with this narrow pH range.
PN 3
PN 10
PN 20
#D2
#D2
#D2
(A)
#U2
#D1
#D1
#D1
#U2
#U2
#U1
#U1
#U3
#U3
(B)
124
#U1
#U3
PN3
PN10
PN20
(C)
normalized spot volume
300
250
200
150
100
50
0
#D1
#D2
#U1
#U2a
#U2b
#U3
Spot numbers
Figure 31. Two-dimensional maps of pooled chick retinal proteins at 3 time
points of 3-day old (PN3), 10-day old (PN10) and 20-day old (PN20). A total of
60 μg (20 μg from each individual, 3 chicks in each group) soluble proteins in
each time point were separated on the IPG strips covering pH 3-10, followed by
12% SDS-PAGE. The gels were stained with MS-compatible silver stain (2-D
gels for the left eye were shown as an example). Differentially expressed protein
areas were shown in blocks. (B) Relevant gel sections in blocks were magnified
and the differentially expressed proteins were marked in arrows or circles. Two
spots were found to be down-regulated (#D1 & #D2) whereas 4 spots were found
to be up-regulated (#U1, #U2a, #U2b & #U3). (C) Protein changes were
expressed in term of spot volume (mean ± SEM, n=2 for right and left eyes, each
consists of a pool of 3 chicks) which is the integration of optical density over the
spot area, for the 6 differentially expressed spots.
125
Figure 32. Enlarged panels showing the differential retinal protein expressions (in
arrows or circles) during normal postnatal retinal growth in both eyes between
PN3 and PN20. Two-dimensional gels were generated using narrower pH 5-8
IPG strips. Two down-regulated proteins (#D1 & #D2) and 4 up-regulated
proteins (#U1, #U2a, #U2b & #U3) were found similar to the findings in Figure
31. Three new and additional differentially expressed proteins (#D3, #U4 and
arrows indicated in #U1) were found with narrow pH range (5-8).
6.2.3.3.
Protein identification
PMF result
Out of the 8 protein spots, 6 of them could be successfully identified by
MALDI-TOF MS while the other two protein spots gave very weak peptide
126
signals and failed to be identified. In Figure 31 (B & C), two spots showed
down-regulation during the retinal growth process. #D1 (Apolipoprotein AI)
showed a gradual decrease in protein amount. #D2 (not identified) showed very
rapid protein down-regulation with time and it could not be detected at PN20.
For the up-regulated proteins, there were four spots included #U1 (PREDICTED:
similar to glyoxylase 1; glyoxalase 1), two spots at #U2 (both were identified as
phosphoglycerate mutase type B subunit, PGM-B) and #U3 (destrin; actin
depolymerising factor, ADF) which showed increasing protein expressions with
time. The #U1 spot (PREDICTED: similar to glyoxylase 1; glyoxalase 1) was
undetectable at PN3 which might be due to the limited protein expression for this
particular protein at an earlier retinal growth phase.
With the pH range of 5-8, the six differentially expressed proteins were
also observed in these gels. In addition, an extra down-regulated spot #D3 (Fatty
acid-binding protein, retina. R-FABP) as well as another up-regulated spot #U4
(not identified) were found. Moreover, comparing the same region at #U1
(PREDICTED: similar to glyoxylase 1; glyoxalase 1) between gel separations
using IPG strips pH 3-10 (Figure 31 B) and pH 5-8 (Figure 32), an extra spot
(arrows) showed a shift in the horizontal location which could only be resolved
with the narrow IPGs. All differential expressions detected were at least having a
two-fold difference in the protein amount. From the above manipulation, it was
clear that a “zoom-in” gel was more powerful in resolving closely packed protein
spots in 2-D gel analysis. The general functions for all identified proteins were
documented in Table 9.
127
Table 9. Brief functions of the five differentially expressed proteins (six spots) in the normal postnatal chick retinal growth.
NCBI
Expression
GI no.
(Spot abbreviation)
227016
Down-regulation
Protein name
Predicted / known functions
Apolipoprotein AI
It is the major protein component of the serum high-density lipoprotein
(#D1)
(HDL). Plasma lipoproteins serve many functions in lipid metabolism &
cholesterol homeostasis in the CNS.
45384320 Down-regulation
(#D3)
50749899 Up-regulation
(#U2a and #U2b)
50740506 Up-regulation
Fatty acid-binding protein, It is responsible for the intracellular transport of hydrophobic metabolic
retina. R-FABP
Phosphoglycerate mutase It is the brain isoform of this enzyme for interconversion of
type B subunit. PGM-type 3-phosphoglycerate and 2-phosphoglycerate during glycolysis and
B
gluconeogenesis.
Glyoxalase I
It belongs to the glyoxalase system and can be found in the cytosol of all
(#U1)
45382979 Up-regulation
intermediates and acts as a carrier of lipids between membranes.
cells for detoxification purpose.
Destrin
(#U3)
It is a mammalian actin-binding protein which belongs to a superfamily
of “ADF/cofilin” that rapidly depolymerizes F-actin in a stoichiometric
manner.
-
(#D2, #U4)
-
Not identified
128
Protein expressions in the retinal growth process
The PMF data and matrix science z-score data for each protein was
summarized and listed in Figure 33 and their detailed information were attached
in appendix 3. The roles of these differentially expressed proteins in chick eye
growth are currently unknown and this was the first time that they are profiled by
a proteomic approach. Some of them have been implicated in various aspects of
growth and development in other tissues or species.
Ions score is -10*Log(P), where P is the probability that the observed match is
a random event. Protein scores greater than 72 are significant (p<0.05).
(#D1)
Ions score is -10*Log(P), where P is the probability that the observed match is
a random event. Protein scores greater than 72 are significant (p<0.05).
(#D3)
Ions score is -10*Log(P), where P is the probability that the observed match is
a random event. Protein scores greater than 71 are significant (p<0.05).
(#U2a)
129
Ions score is -10*Log(P), where P is the probability that the observed match is
a random event. Protein scores greater than 70 are significant (p<0.05).
(#U2b)
Ions score is -10*Log(P), where P is the probability that the observed match is
a random event. Protein scores greater than 72 are significant (p<0.05).
(#U1)
Ions score is -10*Log(P), where P is the probability that the observed match is
a random event. Protein scores greater than 72 are significant (p<0.05).
(#U3)
Figure 33. Biotools PMF data (left) and matrix science Mowse score (right) for
the identified retinal proteins spots (#D1, #D3, #U2a, #U2b, #U1, #U3) involving
in the normal ocular growth. The red peaks in PMF data represented peptides that
were matched to the specific NCBI protein database.
z
(#D1) Apolipoprotein AI (Apo-AI)
It is a primary protein constituent of high-density lipoprotein (HDL). It
was found that HDL concentration in chick liver and skeletal muscle increased
sharply around hatching and then decreased after 1 week of postnatal time
(Shackelford and Lebherz 1983; Tarugi et al. 1989). The Apo-AI mRNA level
and its synthesis showed similar trend (Ferrari et al. 1986; Ferrari et al. 1987).
130
Apo-AI was also found to be regulated in the development of chick sciatic nerve,
in parallel with the process of active myelination (Lemieux et al. 1996).
z
(#D3) Fatty acid-binding protein, retina (R-FABP)
It is the avian counterpart of murine brain FABP implicated in glial cell
differentiation and neuronal cell migration. A study on chick mRNAs level also
has confirmed the elevation of FABPs in undifferentiated retina from embryonic
day 3.5 and subsequent decrease (50-100 folds) upon tissue maturation through
day 7 to day 19. It was suggested that the encoded protein/s may play an
important role in the early retinal development (Godbout 1993; Godbout et al.
1995). Change in localization and expression of FABP in the neural tissue during
the early developmental age had also been found in brain and retina (Sellner
1994).
z
(#U2a and #U2b) Phosphoglycerate mutase-type B (PGM-typeB)
This protein has not been well characterized in chick tissue. Studies
have shown PGM’s involvement in muscle differentiation in human muscle
culture (Miranda et al. 1988) and rat facial development (Granstrom 1986). It
was shown to increase with age in the cultured dermal fibroblasts (Boraldi et al.
2003). Therefore, PGM is likely to be important in the growth of retina.
z
(#U1) Glyoxalase I
Glyoxalase I is vital in the earliest stages of embryogenesis, through
maturation and development, and it is also involved in the aging and death
process (Thornalley 1993). Although the developmental change of glyoxalase has
not been previously documented in the ocular system, its activity was increased
in liver, spleen and kidney of mice aging (Sharma-Luthra and Kale 1994).
Moreover, its role in the regulation of growth and differentiation in plant has
131
been documented (Deswal et al. 1993).
z
(#U3) Destrin / Actin depolymerizing factor (ADF)
It is important for a variety of cellular processes involving actin
remodelling (Bamburg 1999). Recently in the ocular system, a close relationship
between the mice destrin gene and the proliferation rate of the corneal epithelium
has been found (Ikeda et al. 2003). ADF were also believed to be the essential
regulator necessary for neurite outgrowth and it plays important roles in the
nervous system development (Gungabissoon and Bamburg 2003).
6.2.4 Conclusion
This study has showed the chick retinal protein changes in the first three
weeks after hatching when ocular growth is at its peak. With the proteomic
approach, not only those known proteins involved in the chick growth were
confirmed but new proteins that may play important roles in early retinal
development were also reported. The dynamic protein expression changes in the
2DE retinal proteins maps during early ocular development were demostrated.
These results showed the ability of the proteomic approach to identify a number
of changes in the retinal protein expressions with age.
In developmental biology, additional knowledge of the gene products as well
as their temporal change may shed light on the molecular mechanisms involved
in tissue maturation. Also, the ability to profile and identify key proteins changes
in a high-throughput manner has provided a number of clear protein targets for
further functional study.
132
Chapter 7: Differential protein expression in the
emmetropization of chick retina
According to previous established experimental protocols, the differential
protein expression(s) in response to the compensated ametropia were studied in
the study.
7.1 Experimental procedures
Retinal samples
The lens manipulations were usually started at 1- or 2-day after chick
hatching, except stated otherwise. Either right or left eyes were randomly chosen
to be the experimental eyes and plano lenses were mounted on the other eye as
control in all cases. The protein extraction and working protocols were similar to
that described in Chapter 5.2 and Chapter 6.2.
The paired protein amounts required for the 2DE was obtained according to
the quantitation result from either the modified Bradford protein assay or the 2-D
Quant Kit. The retinal tissues were used for pair comparison only if the total
protein difference between the defocused and control eyes were less than 50% in
order to ensure comparable protein profilings.
2D gel electrophoresis
To minimize experimental variations, all samples to be compared were
processed and run in the 2DE systems at the same time (17 cm IPGs were run
together in parallel while paired 11 cm IPGs were run side by side on a single
gel).
All gel images were analyzed using the ImageMasterTM 5 software.
133
Differential expressed proteins were represented by total normalized volumes (%
Vol) and fold differences between defocused and control samples. Although the
software was developed for robust spot detection with built-in compensation
functions for variables such as staining variation and gel distortion, significant
protein spot detection and matching errors between the defocused and control
eyes were still a major technical issue in the gel analysis. To secure the quality of
2DE gels for confident proteomic comparison and analysis, only those gels with
a spot match correlation better than 0.8 (the “correlation” in scatter plot analysis
indicates the goodness-of-fit for the matched spot pairs) were included. Also,
2DE gels with obvious streaking or staining problem in either the treatment or
control samples were excluded from analysis. Furthermore, although a
computerized master gel could be generated for gel comparison using individual
sample images, false positives were frequently seen when using merged master
gels for differential protein comparison. Therefore, rather than using a virtual
master gel, the approach of repeated 2-DE experiments using pooled sample
from individual animals to produce a real master gel was adopted.
Similar to the previous protein identification, the differentially expressed
protein spots were excised and subjected to tryptic digestion and subsequent
MALDI-TOF mass spectrometry and database matching.
134
7.2 Results
7.2.1 Experiment 1: (7 days -10D, pH 3-10)
Sample
Defocused eyes
final
protein
Rx
concentration
-7.25 D 13.2 μg / μl
7 days -10D
-8.0 D
13.4 μg / μl
lens wearing
-9.0 D
16.6 μg / μl
Chick
no.
027
031
034
manipulation
Control eyes
final
protein
Rx
concentration
+0.5 D 14.9 μg / μl
7 days plano
+1.5 D 14.0 μg / μl
lens wearing
+0.5 D 15.5 μg / μl
manipulation
2DE
Sample loaded:
Pool of 300 μg
(100μg x3 chicks)
1st dimension
17cm, pH 3-10
2nd dimension
12% gel in Protean II
XL cell
Protein stain
R-250 coomassie and
then silver re-stained
Protein profiles
z Part A. Coomassie staining result
300 μg pool defocus
spot
#
A
B
spot
area
1.59
2.11
Defocused eyes
%
%
intensity volume
0.076
0.047
0.160
0.132
300 μg pool control
spot
area
1.53
Control eyes
%
%
intensity volume
0.171
0.095
(not detected)
135
(Fold change for % volume)
protein regulation
-2.02j
i
% intensity scatter plot
% volume scatter plot
z Part B. silver staining result
300 μg pool defocus
spot
#
A
B
Defocused eyes
%
%
intensity volume
0.113
0.056
3.30
0.230
0.244
spot
area
1.78
300 μg pool control
spot
area
3.35
Control eyes
%
%
intensity volume
0.177
0.144
(not detected)
% intensity scatter plot
(Fold change for % volume)
protein regulation
(-2.57) j
i
% volume scatter plot
136
These first set of broad range 2DE gels gave an overview of protein
expression between pH3-10. As expected, the silver staining was more sensitive
than the Coomassie blue staining (about 1100 spots from silver stained gel vs.
400 spots detected with Coomassie blue). The scatter plots showed typical and
high correlation of those spots matched both in term of spot intensity (averaged
at 0.96) and spot volume (averaged at 0.84).
In response to the 7 days and -10D lens wearing, two most interesting
proteins (spots A and B) were found in between pH 5-8. Spot A was found to be
down-regulated for more than 2 folds in the defocused eyes in both Coomassie
blue and silver stained gels. Spot B, on the other hand, was found only in the
defocused eyes but was not in the control eyes. This may imply that either the
new protein (spot B) was expressed only in the defocused eye or the protein was
too low in abundance for detection in the control eye.
7.2.2 Experiment 2: (5 days -10D, pH5-8 and pH 3-6)
Sample
Chick
no.
216
217
219
Defocused eyes
final
protein
Rx
concentration
-6.5 D
6.25 μg / μl
5 days -10D
-7.0 D
3.80 μg / μl
lens wearing
-7.0 D
6.62 μg / μl
manipulation
Control eyes
final
protein
Rx
concentration
+2.5 D 6.65 μg / μl
5 days plano +2.25 D
4.95 μg / μl
lens wearing
+2.25 D 7.87 μg / μl
manipulation
2DE
Sample loaded:
Pool of 300 μg
(100μg x3 chicks)
1st dimension
17cm, pH 5-8
2nd dimension
12% gel in Dodeca tank
Protein staining
Hot R-350 coomassie
Sample loaded:
Pool of 60 μg
(20μg x3 chicks)
1st dimension
17cm, pH 5-8
2nd dimension
12% gel in Dodeca tank
Protein staining
silver
137
Sample loaded:
1st dimension
2nd dimension
Protein staining
individual of 60 μg
17cm, pH 3-6
12% gel in Dodeca tank
silver
Protein profiles
z Part A. pool pH 5-8 coomassie staining result
300 μg pool defocus
spot
#
A
B
spot
area
4.17
8.44
Defocused eyes
%
%
intensity volume
0.149
0.080
0.141
0.149
300 μg pool control
spot
area
6.15
11.58
Control eyes
%
%
intensity volume
0.211
0.140
0.106
0.110
(Fold change for % volume)
protein regulation
(-1.75) j
(+1.35) i
z Part B pool pH 5-8 silver staining result
60 μg pool defocus
60 μg pool control
138
spot
#
A
B
spot
area
5.76
7.80
Defocused eyes
%
%
intensity volume
0.137
0.104
0.093
0.106
spot
area
4.98
8.94
Control eyes
%
%
intensity volume
0.201
0.161
0.061
0.064
(Fold change for % volume)
protein regulation
(-1.55) j
(+1.66) i
z Part C. individual pH 3-6 silver staining result
60 μg individual defocus
Chick
no.
216
217
218
spot
area
7.37
4.95
5.95
Defocused eyes
%
%
intensity volume
0.699
0.605
0.375
0.269
0.379
0.235
60 μg individual control
spot
area
9.26
6.32
8.45
Control eyes
%
%
intensity volume
0.690
0.855
0.582
0.513
0.529
0.547
139
(Fold change for % volume)
protein regulation
(-1.41) j
(-1.91) j
(-2.33) j
Similar to the double staining approach in the experiment 1, the same
findings were confirmed using separated gels running with a different coomassie
stain protocol and silver stain. Spot A was down-regulated in the defocused eye
using the pooled samples. In additional, this finding was observed in all
individual animals using pH 3-6 IPGs.
Similary, the up-regulation of spot B could also be observed again.
Importantly, the spot B protein was found in the control eye, which was not seen
previously in Experiment 1 above. This implied that the previous absence of spot
B protein was due to low protein abundance rather than zero expression in the
defocused eye.
7.2.3 Experiment 3: (3 days -10D, pH 5-8)
Sample
Chick
no.
127
135
137
Defocused eyes
final
protein
Rx
concentration
-3.5 D
9.79 μg / μl
3 days -10D
-6.0 D
3.49 μg / μl
lens wearing
-6.0 D
4.07 μg / μl
manipulation
Control eyes
final
protein
Rx
concentration
+1.5 D 8.58 μg / μl
3 days plano +2.5 D
3.77 μg / μl
lens wearing
+4.0 D
2.9 μg / μl
manipulation
2DE
Sample loaded:
Individual 60 μg
1st dimension
17cm, pH 5-8
2nd dimension
12% gel in Dodeca tank
140
Protein staining
silver
Protein profiles
60 μg individual defocus
60 μg individual control
For spot A:
Chick
no.
127
135
137
spot
area
7.10
6.18
5.83
Defocused eyes
%
%
intensity volume
0.152
0.215
0.239
0.265
0.189
0.138
spot
area
5.95
7.69
7.29
Control eyes
%
%
intensity volume
0.103
0.081
0.292
0.357
0.409
0.474
141
(Fold change for % volume)
protein regulation
(+2.65) i
(-1.35) j
(-3.43) j
For spot B:
Chick
no.
127
135
137
spot
area
6.94
Defocused eyes
%
%
intensity volume
0.183
0.279
(not detected)
(not detected)
spot
area
8.82
Control eyes
%
%
intensity volume
0.066
0.083
(not detected)
(not detected)
(Fold change for % volume)
protein regulation
(+3.36) i
-
The differential protein expressions were generally repeatable amongst
individual animals. Incidentally, it was observed that the spot A in one of the
chicks showed up-regulation instead of expected down regulation. It was also
noted that the final refractive status of this chick (-3.5D) was significantly less
compensated to the -10D lens compared to the other two chicks (-6.0D and
-6.25D) within the same group. Although the exact reason for this discrepancy
was unclear, it may be a consequence to the unknown aberrant emmetropization
response of this chick.
For spot B, the up-regulation could be seen in one chick but not in the
other two chicks. Since insufficient protein amount could prevent the
visualization of protein spots as it was observed earlier, given that this protein
spot were missing in both the defocused and control eyes with relative low
protein concentration per gel, it was possible that the protein amount of spot B
may not too low to be detected in these gels. Furthermore, as seen in Chapter 6, a
large inter-animal difference (even using the same day-old chick) may have
contributed to the positive finding in the chick (# 127) of this group.
142
7.2.4 Experiment 4 (3 & 5 days -10D, pH 5-8; sequential extraction )
Sample
Defocused eyes
final
protein
Rx
concentration
3 days -10D -8.0 D
3.47 μg / μl
lens wearing
-8.0 D
5.96 μg / μl
Chick
no.
236
240
manipulation
Chick
no.
284
manipulation
285
Defocused eyes
final
protein
Rx
concentration
5.85 μg / μl
5 days -10D -9.5 D
lens wearing
from
14 -7.0 D
6.30 μg / μl
day-old chick
Control eyes
final
protein
Rx
concentration
+2.0 D 3.58 μg / μl
3 days plano
lens wearing
+1.5 D
5.40 μg / μl
manipulation
Control eyes
final
protein
Rx
concentration
+0.5
D
6.73 μg / μl
5 days plano
manipulation
lens wearing
from 14
day-old chick
+1.25 D
3.21 μg / μl
2DE
To better understand the two candidate proteins A and B, the retinal
tissues after 3 days and 5 days lens wear were harvested and the proteins were
extracted with the sequential proteins extraction protocol. This fractionation
procedure has been described in Chapter 4.2.2. Only the tris-soluble proteins
were collected for this 2DE study.
Sample loaded:
Pool of 60 μg
(30μg x2 chicks)
1st dimension
17cm, pH 5-8
2nd dimension
12% gel in Dodeca tank
143
Protein staining
silver
Protein profiles
z Part A. Pooled chick retinal samples after 3 days lens wear
60 μg pool defocus
spot
#
A
B
spot
area
6.85
Defocused eyes
%
%
intensity volume
0.093
0.071
(not detected)
60 μg pool control
spot
area
5.55
Control eyes
%
%
intensity volume
0.186
0.117
(not detected)
(Fold change for % volume)
protein regulation
(-1.67) j
-
z Part B. Pooled chick retinal samples after 5 days lens wear (from 14 day-old
chicks)
60 μg pool defocus
60 μg pool control
144
spot
#
A
B
spot
area
5.87
5.84
Defocused eyes
%
%
intensity volume
0.051
0.035
0.221
0.185
spot
area
6.02
5.69
Control eyes
%
%
intensity volume
0.087
0.054
0.137
0.093
(Fold change for % volume)
protein regulation
(-1.54) j
(+1.98) i
Using a different protein extraction protocol, spot A was once again
down-regulated in the defocused eye in both part A and part B experiments using
chick retinae from 3 days or 5 days. This differential expression was repeatable
in all individual animals of the same group (data not shown).
Expectedly, spot B was consistently not detected in both the defocused
and control eyes after 3 days treatment (similar to the results from Experiment 3).
Apart from the tris soluble extracts shown above, the protein was also not
detected in the sample recovered from the subsequent EB5 reagent (data not
shown). However, it showed an up-regulation again in the 5 days defocused eye.
From the above results, both spot A and spot B proteins appeared to be
water-soluble and their differential expressions could be readily studied with Tris
extraction buffer alone.
7.2.5 Experiment 5: (3 hours & 7 hours of -10D lens wear, pH 5-8)
Sample
Chick
no.
323
325
Chick
no.
331
332
333
334
335
Defocused eyes
manipulation final
protein
Rx
concentration
3 hours -10D +2.0 D 4.79 μg / μl
lens wearing +1.25 D 5.53 μg / μl
from 7
day-old chick
Defocused eyes
final Rx protein
concentration
+1.75 D 4.48 μg / μl
7 hours -10D
+1.50 D 3.65 μg / μl
lens wearing
+1.25 D 3.25 μg / μl
from 7 day-old
+0.50 D 5.89 μg / μl
chick
+1.75 D 5.28 μg / μl
manipulation
145
Control eyes
final
protein
Rx
concentration
3 hours plano
similar 4.85 μg / μl
lens wearing
similar 4.18 μg / μl
from 7
day-old chick
manipulation
Control eyes
final Rx protein
concentration
+1.75 D 5.47 μg / μl
7 hours plano
+1.75 D 3.52 μg / μl
lens wearing
+2.00 D 3.79 μg / μl
from 7 day-old
+0.50 D 5.62 μg / μl
chick
+1.00 D 3.41 μg / μl
manipulation
2DE
For 3 hours -10D lens wear:
Sample loaded:
Pool of 60 μg
(30μg x2 chicks)
1st dimension
17cm, pH 5-8
2nd dimension
12% gel in Dodeca tank
Protein staining
silver
For 7 hours -10D lens wear:
Sample loaded:
Pool of 60 μg
(12.5μg x5 chicks)
1st dimension
17cm, pH 5-8
2nd dimension
12% gel in Dodeca tank
Protein staining
silver
Sample loaded:
Individual of 50 μg
1st dimension
11cm, pH 5-8
2nd dimension
12% gel in Dodeca tank
(defocus and control IPGs
run on the same gel side by
side)
Protein staining
silver
Protein profiles
z Part A. Pooled samples after 3 hours -10D lens wear (pH 5-8 and silver
stained)
60 μg pool defocus
spot
#
A
B
spot
area
6.44
8.10
Defocused eyes
%
%
intensity volume
0.213
0.158
0.238
0.238
60 μg pool control
spot
area
5.18
8.94
Control eyes
%
%
intensity volume
0.232
0.177
0.188
0.225
146
(Fold change for % volume)
protein regulation
(-1.12) €
(+1.06) €
z Part B.
Pooled and individual samples after 7 hours -10D lens wear (pH 5-8
and silver stained)
60 μg pool defocus
spot
#
A
B
spot
area
3.84
8.03
Defocused eyes
%
%
intensity volume
0.207
0.135
0.299
0.410
individual
defocus
60 μg pool control
spot
area
4.53
7.13
Control eyes
%
%
intensity volume
0.233
0.182
0.312
0.419
individual
control
147
individual
defocus
(Fold change for % volume)
protein regulation
(-1.35) j
(-1.02) €
individual
control
For spot A:
Chick
no.
331
332
333
334
335
spot
area
7.39
7.73
6.37
8.34
3.45
Defocused eyes
%
%
intensity volume
0.075
0.067
0.456
0.496
0.390
0.272
0.174
0.165
0.224
0.126
spot
area
3.68
8.98
7.39
7.94
3.35
Control eyes
%
%
intensity volume
0.252
0.166
0.520
0.535
0.536
0.533
0.313
0.311
0.252
0.131
(Fold change for % volume)
protein regulation
(-2.48) j
(-1.08) €
(-1.96) j
(-1.88) j
(-1.04) €
For spot B:
Defocused eyes
Control eyes
Chick
spot
%
%
spot
%
%
(Fold change for % volume)
no.
area
intensity
volume
area
intensity
volume
protein regulation
331
6.05
0.380
0.437
6.13
0.303
0.349
(+1.25) €
332
11.1
0.633
1.020
11.7
0.573
0.915
(+1.11) €
333
12.4
0.637
0.998
16.2
0.679
1.301
(-1.30) j
334
7.48
0.277
0.292
6.27
0.302
0.279
(+1.05) €
335
7.82
0.503
0.531
6.58
0.386
0.426
(+1.24) €
It is known that choroid changes its thickness with negative lens
wearing in chicks and that this choroidal response can occur after a few hours or
even minutes of lens treatment (Wallman and Winawer 2004; Zhu et al. 2005).
The change in protein expression could also take place in retina after a brief
period of lens wear. Therefore, the retinal protein expressions after a short period
of -10D lens wear was studied. In addition, in view of the above findings on
time-course for spot B. lens manipulations were performed on 5 and 7 days old
instead of 1 or 2 days old chicks in order to extract enough protein amounts.
The first study was performed after only 3 hours lens wear. There was
no difference in the expressions of spot A and B in terms of spot volume
fold-changes. However, after 7 hours lens wear, spot A was significantly
down-regulated in three chicks whereas no obvious change (less than 10%
fold-change) was seen in another two chicks.
148
Larger variation was noted for spot B after 7 hours treatment. Although
4 chicks demonstrated up-regulation of spot B, one of the chicks showed
down-regulation. All differential expressions were less than 1.3 folds and the
effect of short term lens wearing on spot B remained inconclusive.
7.2.6 Experiment 6 (4 days of +10D lens wear, pH 5-8)
Sample
Chick
no.
306
307
308
298
299
Defocused eyes
final
protein
Rx
concentration
+5.5 D 7.14 μg / μl
+8.0 D 6.29 μg / μl
4 days +10D
+8.0 D 8.62 μg / μl
lens wearing
+7.75 D 6.25 μg / μl
+8.0 D 5.46 μg / μl
manipulation
Control eyes
final
protein
Rx
concentration
+0.5 D 7.86 μg / μl
+0.25 D 5.86 μg / μl
4 days plano
+1.0 D 6.76 μg / μl
lens wearing
+1.25 D 6.16 μg / μl
+1.0 D 6.81 μg / μl
manipulation
2DE
Sample loaded:
Individual of 50 μg
1st dimension
17cm, pH 5-8
2nd dimension
12% gel in Dodeca tank
149
Protein staining
silver
Protein profiles
50 μg individual defocus
50 μg individual control
150
For spot A:
Chick
no.
306
307
308
298
299
spot
area
6.98
6.45
6.77
6.25
6.81
Defocused eyes
%
%
intensity volume
0.090
0.077
0.186
0.178
0.107
0.097
0.164
0.109
0.086
0.064
spot
area
7.15
8.59
4.32
5.24
8.73
Control eyes
%
%
intensity volume
0.139
0.124
0.195
0.219
0.145
0.086
0.711
0.102
0.074
0.078
(Fold change for % volume)
protein regulation
(-1.61) j
(-1.23) €
(-1.13) €
(+1.06) €
(-1.22) €
For spot B:
Chick
no.
306
307
308
298
299
Defocused eyes
%
%
intensity volume
11.27
0.079
0.089
6.76
0.069
0.062
2.24
0.047
0.022
(not detected)
(not detected)
spot
area
spot
area
8.26
8.65
5.95
Control eyes
%
%
intensity volume
0.206
0.251
0.256
0.312
0.223
0.179
(not detected)
(not detected)
(Fold change for % volume)
protein regulation
(-2.82) j
(-5.03) j
(-8.14) j
-
In additional to the negative lens treatment, the effect of +10D was
studied in this experiment.
For the spot A, only one out of five chicks showed significant
down-regulation and the averaged differences were less than 1.3 folds.
Interestingly, it was the first time that spot B appeared to be significantly
down-regulated in response to the +10D lens treatment. Since up-regulation was
found in previous -10D lens experiments, these reverse lens response for spot B
might indicate its importance in the compensated myopia development. Further
studies are needed to draw a conclusion.
151
7.2.7 Experiment 7 (3 days form deprivation, pH 5-8)
Sample
Defocused eyes
manipulation final Rx
protein
concentration
-7.50 D
6.80 μg / μl
-7.00 D
5.74 μg / μl
-6.25 D
5.61 μg / μl
3 days
-7.50 D
6.25 μg / μl
occluder
-7.00 D
7.85 μg / μl
wearing
-12.0 D
8.14 μg / μl
-6.50 D
6.57 μg / μl
-7.50 D
5.77 μg / μl
Chick
no.
F3
F4
F6
F8
F10
F11
F12
F13
Control eyes
final
protein
Rx
concentration
+4.00 D 7.69 μg / μl
+4.00 D 5.39 μg / μl
+4.25 D 7.08 μg / μl
3 days plano +2.75 D 6.28 μg / μl
lens wearing
+2.00 D 7.18 μg / μl
+2.50 D 6.76 μg / μl
+2.50 D 5.22 μg / μl
+2.50 D 4.71μg / μl
manipulation
2DE
Sample loaded:
Pool of 60 μg
(7.5μg x8 chicks)
1st dimension
17cm, pH 5-8
2nd dimension
12% gel in Dodeca tank
Protein staining
silver
Protein profiles
60 μg pool defocus
spot
#
A
B
spot
area
10.3
7.19
Defocused eyes
%
%
intensity volume
0.027
0.026
0.121
0.106
60 μg pool control
spot
area
9.15
7.34
Control eyes
%
%
intensity volume
0.092
0.078
0.068
0.057
(Fold change for % volume)
protein regulation
(-3.00) j
(+1.86) i
Since considerable variation in the refractive response was anticipated
in the form deprivation model (Schaeffel and Howland 1988; Schaeffel and
152
Howland 1991), more chicks were used in this experiment. Interestingly,
down-regulation of spot A and up-regulation of spot B were also evident in the
form deprived myopic eyes as in the lens-induced model. This result may
indicate that the compensated eye growth in lens-induced myopia and
form-deprivated myopia may share certain common pathways.
7.2.8 Protein identifications of spot A and spot B
Although the protein identities of spot A and B could be readily matched
to the previous chick retinal database (Chapter 5), MS was carried out to confirm
their protein identifications in the above gels and all the PMF results gave the
same protein ID for spot A and B, namely Apolipoprotein AI and destrin
respectively. Typical MALDI-TOF MS data of a result using the 2D gels from
experiment 7 were shown.
(Spot # A): Apolipoprotein-AI
NCBI GI MOWSE intensity seq.
no.
score
coverage coverage
227016
110
56%
37.4%
Mascot Mascot Organism
SwissProt /
SwissProt /
pI.
M.W.
TrEMBL
UniProt entry
(da)
accession no. name
5.45
28790 Gallus Gallus
P08250
APA1_CHICK
153
(spot #B): Destrin; actin depolymerising factor, ADF
NCBI GI MOWSE intensity seq.
no.
score
coverage coverage
63516
87.1
55.6%
36.4%
Mascot Mascot Organism
SwissProt /
SwissProt /
pI.
M.W.
TrEMBL
UniProt entry
(da)
accession no. name
7.52
18920 Gallus Gallus
P18359
DEST_CHICK
7.3 Discussions
7.3.1 Apolipoprotein AI, Destrin and myopia: a possible link?
Two candidate retinal proteins, Apolipoprotein AI and destrin have been
identified, which were shown to vary in expressions in the compensated eye
growth. In a similar manner, these proteins were also apparently involved in the
early growth and development of the chick retina (Chapter 6.2). Typically, the
defocused myopic (or growing) eye showed down-regulation of Apolipoprotein
AI and up-regulation of destrin. These similarities in expressions in normal
growing and myopic retina suggested that myopic growth and normal eye growth
may share similar biochemical process or processes at least in terms of retinal
protein expression.
Although the exact roles of Apolipoprotein AI and destrin in myopia
development are still unknown at present, information related to their general
biological functions and interactions in the literatures may help to postulate
working hypotheses. Base on the published information, a working model of
their involvement in the compensated emmetropization is proposed (Figure 34).
154
z
Apolipoprotein AI (Apo-AI)
Apo-AI consists of 264 amino acids with theoretical pI and molecular
weight of 5.59 and 30680 Da respectively. However, its function in retina is not
yet characterized.
Apolipoprotein is well known of its regulatory role in the lipid
metabolism and cholesterol homeostasis as it is the major component of the
serum high-density lipoprotein (HDL). HDL is known as the "good" cholesterol
that it protects our body against Syndrome X (the description of a group of
metabolic imbalance conditions such as hypertension, diabetes, dyslipidemia,
cardiovascular disease, obesity, abnormal glucose tolerance, etc). Its therapeutic
use on atherosclerosis and cholesterol transport have also been explored recently
(Kaul and Shah 2005; Duffy and Rader 2006).
Apart from the classical function of reversing cholesterol metabolism,
components in HDL are found to involve in many other cellular functions in
recent years. For example, HDL possesses anti-oxidative and anti-inflammatory
properties as Apo-AI was found to directly scavenge oxidative seeding molecules
of the artery wall and provided arteriovascular protection (Calabresi et al. 2003).
Besides, Apo-AI was thought to play a regulatory role in development. During
the process of active myelination in chick sciatic nerve, both the mRNA and
protein expression of Apo-AI have been shown to increase during the rapid phase
in myelination (LeBlanc et al. 1989; Lemieux et al. 1996). Also, the Apo-AI and
Apo-AE (a functional homologue of avian Apo-AI) syntheses were found to
increase in the degenerated optic nerves of chick and rat (Dawson et al. 1986).
An increased in Apo-AI was also seen in optic nerve injury in fish (Harel et al.
1989) and CNS injury in macaques (Saito et al. 1997). In addition, recent studies
155
have proposed an intimate relationship between Apolipoproteins and aging
diseases. For examples, in the human retina, an increase in the expression of
Apo-AE was found which may be related to the reduction of photoreceptor
synaptic terminals in age-related macular degeneration (ARMD) (Johnson et al.
2005). Genetic study has also demonstrated the association of the Apo-E gene to
ARMD (Hamdi and Kenney 2003). Intriguingly, Apolipoprotein is also found to
be associated with age-related Alzheimer's syndrome (Blain and Poirier 2004).
These findings indicated the diverse roles of Apolipoproteins in the body in
addition to their classical functions as a HDL.
Considering
the
significant
roles
of
Apolipoprotein
in
the
neuro-physiology, it is possible that Apo-A1 may be involved in myopic retinal
growth although direct evidence is not yet available. A number of studies have
indirectly suggested the relationship between myopia and Apolipoprotein
expression. Firstly, in rhegmatogenous retinal detachment which is one of the
severe complications of high myopia, it was found that Apo-AI was
down-regulated in the subretinal fluid of the detached retina (Huerva et al. 1993).
Although the cause and effect of Apo-AI expression is not yet clarified in the
study, the Apo-AI was down-regulated in the human and chick myopic eyes.
Secondly, it is well known that retinal RA increases in both the lens-induced and
form-deprivated myopia in chicks and guinea pigs (Seko et al. 1998; Bitzer et al.
2000; McFadden et al. 2004). In human, it was also found that oral intake of
synthetic retinoids, isotretinoin (13-cis RA), for four months led to a decrease of
10% HDL (Zech et al. 1983) and a nearly linear dose-related effect was observed
in another study (Melnik et al. 1987). Since Apo-AI is the major component of
HDL, it is likely that RA treatment may also lead to a reduction of Apo-AI
156
concentration. In fact, it has been demonstrated that treatment of rat hepatocytes
with RA resulted in a decrease in Apo-AI mRNA levels (Berthou et al. 1998).
Therefore, these findings are also in agreement with the present finding of
Apo-AI down-regulation in the myopic chick retina. It is possible that Apo-A1 is
implicated in myopic growth but its exact involvement and interplay with various
molecular entities, such as retinoic acid, is unclear at present.
Furthermore, it has been documented that cAMP induced Apo-AI
binding activity and promoted cellular cholesterol efflux via ATP-binding
cassette transporter A1 (ABCA1) transporter protein in macrophages (Oram et al.
2000). cAMP also increased ABCA1 mRNA in mouse macrophages as well as
the Apo-AI-mediated cellular efflux in human fibroblasts. (Haidar et al. 2002).
Also, ABCA1 expression was found to mediate by cAMP signaling in cultured
human fibroblasts when induced by (22R)-hydroxycholesterol and 9-cis-retinoic
acid (Haidar et al. 2004). Therefore, in a similar way, RA and Apo-AI may be
involved in a cascade of reactions to promote growth via actions on the
fibroblasts of the eye.
The preceding experiments of protein expressions during normal
retinal growth (Chapter 6.2) showed that there was a decrease in Apolipoprotein
expression with growth (Lam et al. 2006). As the compensated myopic growth is
actually presented by an accelerated eye growth, the data provided a direct
evidence to suggest the involvement of Apo-AI in myopia. A similar
down-regulation of this protein in the defocused eye (comparing to the
contralateral normal developing eye) in response to the -10D lens treatment was
observed when accelerated growth occurred as in chick myopia. However, a clear
quantitative relationship between the Apo-AI concentration and the amount of
157
lens wearing was not observed. The reason is unknown but the fact that both the
normal emmetropization and compensated myopic growth took place at the same
time during the experimental period may have masked any quantitative
difference
in
Apo-A1
expression.
Interestingly,
there
was
significant
down-regulation of Apo-AI within hours of -10D lens treatment ahead of
changes in both the refractive error and physical eyeball size. Therefore, it is
plausible that the Apo-AI expression may be involved in the early signaling
process.
Concurrent with the present thesis, a study making complementary
observations was reported which also highlighted the importance of Apo-AI in
eye growth regulation (Bertrand et al. 2006). The expressions of Apo-AI were
found to be up-regulated in both chick retina and fibrous sclera in response to
LIH. Their findings using proteomic study are in line to the present results of
Apo-AI down-regulation in LIM and FDM found in this study. Besides, the
authors further showed that peroxisome proliferator-activated receptor alpha
(PPAR-alpha), which is known to promote Apo-AI, could reduce the LIM by
about 30% (Bertrand et al. 2006). Although the regulatory mechanism was not
suggested, it is found that the PPAR related pathways to control HDL and
Apo-AI expressions seem promising from the literature. In human subjects, as
PPAR-alpha activation has been demonstrated to increase plasma HDL, its
agonists are recently suggested clinically to reduce Syndrome X and to manage
hyperinsulinemia (Gervois et al. 2000; Han et al. 2005; Reaven 2005). Moreover,
a PPAR-alpha ligand, fenofibrate (or fibrates / fibric acid) was also found to
increase both the HDL concentration and insulin sensitivity. The use of these new
fibrate class of drugs was found to be beneficial for patients with metabolic
158
syndrome, inflammatory vascular disease, hypertriglyceridemia and high body
mass index (Idzior-Walus et al. 2000; Koh et al. 2004; Han et al. 2005; Xu et al.
2006). Furthermore, PPAR-alpha is mainly expressed in tissues exhibiting high
oxidative demand such as liver, kidney, heart and muscle. New data have
indicated PPAR as well as fenofibrate can increase epithelial nitric oxide
synthase (eNOS) phosphorylation and endothelium-derived nitric oxide (NO)
production. NO not only has a protective role in cardiovascular diseases and
inflammation condition, but has also been found to increase the HDL and Apo-AI
levels (Goya et al. 2004; Bulhak et al. 2006; Murakami et al. 2006; Zhu et al.
2006). This evidence corroborates well with the current working hypothesis for
the up-regulation of Apo-AI which results in myopia reduction.
On the other hand, recent studies have proposed another role of PPAR
in effecting eye growth through the regulation of matrix metalloproteinases
(MMPs) expression. For examples, PPAR ligands were demonstrated to inhibit
the expression of extracellular MMP-9 and MMP-2 (Liu et al. 2005). In guinea
pig model, PPAR agonist was found to significantly reduce the levels of
MMP-13 in the articular cartilage (Kobayashi et al. 2005). MMPs are neutral
proteinases for the degradation of collagens and other extracellular matrix
components. Since MMPs expressions have been well studied for their roles in
the scleral tissue degradation which results in myopic growth (Rada et al. 2006);
the MMPs inhibition is therefore thought to reduce the myopic growth. Although
the control mechanism of MMPs by PPAR is not yet available, it is proposed that
the up-regulation of Apo-AI levels (in line to the up-regulation of PPAR) may
share a common pathway to PPAR and eventually lead to a reduction of LIM
(PPAR pathway in Figure 34).
159
z
Destrin; actin depolymerising factor, ADF (Destrin)
Destrin consists of 164 amino acids with theoretical pI and molecular
weight of 7.52 and 18401 Da respectively. Its physiological function in the chick
retina is also not well characterized.
Destrin is an actin-binding protein which belongs to a superfamily of
“ADF/cofilin”. It was first isolated from the brains of chick embryo that
promotes the disassembly of actin filaments (Bamburg et al. 1980). It works by
binding the F-actin and cooperatively changes the twist of the actin filament and
severes the actin filaments. As a result, it enhances the turnover of actin by
regulating the rate constant of polymerization and depolymerization at the end of
filament (Bamburg 1999; Bamburg et al. 1999). This process was calcium
dependent since the depolymerization of actin filaments has been shown to
associate with calcium release (Wang et al. 2002) whereas actin polymerization
rates are enhanced by the presence of calcium (Harris and Weeds 1983). In short,
destrin is essential for recycling actin subunits to support the growth of new
filaments. In the present study, destrin was found to be up-regulated in the LIM
but down-regulated in the LIH. Its expressions seem agree very well to the
compensated eye growth in both directions. Again, similar to the identification of
Apo-AI involvement in the normal retinal growth, its expression was also found
to be growth-dependent according to the previous result (Chapter 6.2) (Lam et al.
2006). It is likely that destrin may also play a role in the myopic growth.
Although destrin expression was not previously found in myopia, it has
been well studied in tissue remodelling because of its dynamic biochemical
properties. Indeed, actin is a major cytoskeletal protein and its assembly is
important in cell motility, vesicle transport and membrane turnover. Abnormality
160
in its assembly by destrin will result in aberrant structural formation. ADF/cofilin
is found in regions of rapid actin dynamics. Increase in ADF/cofilin expression
has shown to enhance cell division, motility as well as membrane ruffling
(Aizawa et al. 1996). ADF/cofilin was also required for myofibril assembly (Ono
et al. 1999). Besides, the growth cone at the end of neuronal processes acts as a
pathfinder to direct the neurons during their outgrowth in the development of
nervous system. This motility of growth cones hinges on the rapid reorganization
of the actin cytoskeleton. It was found that the action of the retinal growth cone
filopodia was mediated through ADF/cofilin (Gungabissoon and Bamburg 2003;
Gehler et al. 2004). Therefore, ADF/cofilin is now believed to play a key role in
regulating the retinal growth.
Posterior to the retina, destrin may also play a critical role in the scleral
tissue changes during myopic growth. In search of the relationship between
destrin and myopia, some of the previous findings in the regulation of scleral
tissue thinning during the myopic growth are highlighted. McBrien et al have
demonstrated that there was loss of scleral tissue and subsequent scleral thinning
during the development of axial myopia in tree shrews (McBrien et al. 2001).
Short term or long term scleral thinning is actually a well recognized findings
across different myopic animal models as well as in humans (McBrien et al. 2001;
McBrien and Gentle 2003; Rada et al. 2006). The regulation of cell proliferation
involves a complex signal transduction in which destrin modulated actin
expression was said to play an important role (Boonstra and Moes 2005).
Although the mechanism is largely unknown at present, scleral remodelling in
myopia development is believed to be a dynamic process that involves the
continual synthesis and degradation of extracellular matrix. Until recently, the
161
scleral fibroblasts located between the scleral lamellae are said to be the key
player in regulating the scleral growth (Rada et al. 2006). It is suggested from
present work that two possible pathways are involved. Firstly, fibroblasts were
found to increase the MMPs production which will definitely enhance the scleral
tissue loss (McBrien et al. 2001; McBrien and Gentle 2003; Metlapally et al.
2006). This is in line to discussion of MMPs in the previous Apo-AI session.
Secondly, McBrien et al have shown the integrins subunits (a large family of cell
surface receptors facilitating cytoskeletal-extracellular matrix communication) of
fibroblasts to interact with actin filaments and thus involving in the regulatory
changes of myopic sclera (McBrien et al. 2001). In additional, ADF/cofilin has
been proposed to control cell polarity during fibroblast migration in filament
disassembly/severing (Dawe et al. 2003). Hence, the interplay of destrin and its
induced fibroblast in scleral remodelling expression is plausible. Besides, earlier
data have revealed a down-regulation of another structural glycosaminoglycans
(GAGs) in both of the myopic human (Avetisov et al. 1983) and tree-shrew
sclera (Norton and Rada 1995). Interestingly, apart from the interaction on actin,
integrins are also suggested to be one of the players in mediating the reduction of
GAGs for the scleral thinning (McBrien et al. 2001). Collectively, all of these
pathways lead to myopic growth and it is plausible that ADF/cofilin may initiate
the fibroblast activation and thereby produces subsequent scleral remodelling in
myopic development.
The reversal protein expressions of destrin in response to -10D and
+10D lens treatments is an interesting finding in this study. It is believed that the
destrin induced actin modification may play a major role in the eye growth
regulation. As actin filaments extension and their breakdown are based on the
162
continuous polymerizing and depolymerising process of individual actin
monomers (G-actin), the inherently unstable property of actin was said to
facilitate a rapid response of structural remodelling in developing chicken
muscles according to the external changing environments (Nagaoka et al. 1996).
In a similar manner, destrin as an actin depolymerising factor may efficiently
regulate the actin redistribution bi-directionally in myopic growth. In addition,
since up-regulation of both destrin and vimentin (Bertrand et al. 2006) are found
in the myopic eyes, the cytosketetal protein natures for both proteins are
suggested to share similar pathway in regulating the myopia growth.
7.3.2 Nutrition and myopia regulation
In addition to the above discussions of Apo-AI and destrin in Chapter 7.3, it
seems that previous findings in food nutrients on myopic development can
further give new insights to the proposed pathways as shown in Figure 34.
Supplements of the long-chain forms of Omega-3 polyunsaturated fatty
acids such as decosahexanoid acid (DHA) (a major structural lipid of retinal
photoreceptor outer segment membranes) and its substrate, eicosapentaenoic acid
(EPA), are well recognized as the vital components for normal brain development
and visual function. DHA and EPA have been reported to improve visual acuity
in myopes (Suzuki et al. 2001). Clinically, DHA/EPA are known to reduce
Syndrome X by elevating the general HDL levels (Horrocks and Yeo 1999; Das
2005) which may prevent myopia development in the theoretical proposed
pathway. Interestingly, breast-fed babies have shown to have lower risk in
developing myopia (Chong et al. 2005). Whether such an effect is mediated
through DHA or other HDL in milk remains to be confirmed. Since intake of
163
dairy products were found to elevate both of the HDL and Apo-AI levels in the
body (Maruyama et al. 1992; Onning et al. 1998; Kiessling et al. 2002), it is
plausible that the protective effect from the intake of milk may be mediated by
Apo-AI up-regulation. Moreover, DHA/EPA are capable to activate the
expression of PPAR-alpha either in the cultured cells of Xenopus laevis or in the
human neural retina (Keller et al. 1993; SanGiovanni and Chew 2005). This
activation of PPAR pathway is one of the possible signalling cascades for the
HDL up-regulation which can lead to myopia reduction (as described in the
Apo-AI session).
In contrast, high consumption of sugar / fructose was found to relate to high
myopia. It is said to cause either by immediate refractive power change due to
hyperglycemia (Furushima et al. 1999) or by long term calcium depletion which
weakens the structure of sclera (Hodos 1990) and thereby increases myopia
(Daubs 1984). Indeed, hyperglycaemia can cause hyperinsulinemia which in turn
up-regulates tissue growth. Recently, chronic hyperinsulinemia has been
proposed to play a key role in the pathogenesis of juvenile-onset myopia
(Cordain et al. 2002).
A high insulin levels is incidentally found to involve in the regulation of the
expression of transcription factor Pax-6 (Grzeskowiak et al. 2000) and recently
Pax-6 gene was found to be up-regulated in myopic eyes (Zhong et al. 2004).
This finding provides a plausible connection between the observation of high
sugar level and myopia development via insulin and Pax-6 gene expression.
Furthermore, hyperinsulinemia leads to an elevation of free insulin-like growth
factor-1 (IGF-1) and reduces the insulin-like growth factor-binding protein
(IGFBP) in serum (Cordain et al. 2003). Free IGF-1 was shown to stimulate
164
bodily growth (Juul et al. 1995) and may indirectly mediate eye growth since
body size / height can be correlated directly to axial length or myopes in a
number of studies (Saw et al. 2002; Saw et al. 2002; Ojaimi et al. 2005). In
addition, IGF can also stimulate the proliferation of scleral chondrocytes and
scleral fibroblasts in vitro (Seko et al. 1995) and effects myopic growth. Actually,
a significant increase of IGF was found in the sclera of FDM in chicks and IGF
has been proposed to play role at the fibrous sclera in chick myopia (Kusakari et
al. 2001). Furthermore, high carbohydrate diets were associated with an elevation
of insulin levels and a decrease in HDL (Coulston et al. 1983) which may lead to
accelerated eye growth via pathways triggered by Apo-AI down-regulation.
A theoretical framework to relate Apo-AI and destrin to myopic eye growth
is provided in the above discussions. It aims to provide new hypotheses for
testing so that the involvements of these two candidate proteins in the cascades
of visually regulated ocular growth and scleral remodelling can be elucidated in
the future.
165
Figure 34. Proposed cascades of myopia regulation by Apolipoprotein AI and Destrin/ADF proteins.
166
7.4 Conclusion
Using different experimental conditions, two candidate proteins, Apo-AI
and destrin, were found to be differentially expressed in the myopic eyes induced
by -10D or form deprivation. These two proteins were not the only protein which
showed differential expression in the experiments done in this study. However,
they were the most significant (in terms of “fold” changes) and consistent in all
of the experiments performed.
The Apo-AI protein was found to be down-regulated in the defocused eye
while destrin was found to be up-regulated in the defocused eye. Moreover, in
induced hyperopia using +10D lens, destrin was found to be down-regulated. In
view of the differential retinal protein expressions identified in the present study
as well as the findings from other studies, the cascades of Apolipoprotein AI and
destrin/ADF in the regulation of myopic eye growth were proposed.
167
Chapter 8: An initial test of DIGE application in the
study of differential protein expression of chick retina
8.1 Background
Two-Dimensional polyacrylamide gel electrophoresis (2-D PAGE) is
currently the key technique for profiling thousands of proteins of a given
proteome simultaneously. Despite the continuous advances in 2D PAGE
technique, including better solubility of the new lysis buffer, higher resolution
IEF with IPGs and improved detection agents, the gel-to-gel variations are
considerable and have rendered reliable quantitative comparisons between gels a
major challenge.
A novel Two-Dimensional fluorescence difference gel electrophoresis (2-D
DIGE) technique, first described by Unlu et al. and later marketed by Amersham
Bioscience as Ettan DIGE (Unlu et al. 1997; Tonge et al. 2001), targets to solve
these problems by providing a highly reliable and quantitative dimension to the
2-D PAGE technique. In the DIGE approach, two to three protein extracts can be
individually
pre-labelled
by
different
spectrally
resolvable,
size-
and
charge-matched fluorescent CyDye DIGE fluors. The labelled proteins are then
mixed together and separated by isoelectric focusing in the first dimension and
molecular size in the second dimension similar to the traditional 2-D PAGE
technique but on a single gel. Images of the protein profile on the gel are
acquired sequentially using lasers of appropriate excitation wavelengths. Since
the proteins from different extracts are separated under identical experimental
conditions within the same gel, comparisons of different protein profiles are
168
therefore free of gel running variations. The ratio of the differentially expressed
protein spots among different samples are normalized and derived by a analysis
software to further eliminate gel-to-gel variation.
At the later stage of this project, I had gained access to the Ettan DIGE
system for the study of its capability in identifying differential protein expression
in the emmetropization of chick retina. I also tried to conduct a multiplex study
based on some modifications of the current 2D PAGE protocol in order to test the
workflow as well as to investigate the additional benefits of the DIGE system in
profiling retinal proteins of chick eyes.
8.2 Experimental procedures
Retinal samples
To evaluate the DIGE system in studying the differential proteins
expressions in myopic chick eyes, two pairs of retinal tissues from age matched
chicks after 7 days, -10D monocular lens wear were isolated (procedure as
described in Chapter 5.2). The refractive errors of the myopic eyes were -10.5D
and -11.5D while mild hyperopia was found in the fellow control eyes. The
retinal proteins were extracted with a modified DIGE compatible EB5 lysis
buffer in which DTT, Biolyte, primary amines or thiols were omitted during
homogenization stage as they may react and affect the subsequent CyDyesTM
labelling. The protein concentrations of the four retinal extracts were determined
by the 2-D Quant Kit.
Proteins labelling with CyDyesTM
Lysine labelling protocol which referred as “minimal labelling” was utilized
in this study. Each dye (25nmol) was reconstituted with 25 μl anhydrous
169
N,N-Dimethylformamide (Aldrich chemical co.) as 1000 pmol /μl stock dye
which was stable in -20oC for at least 2 months time according to the
manufacturer’s recommendation. The stock dye was further diluted to be 400
pmol /μl. It formed the working dye solution for immediate use for the labelling
reaction. Tris-HCl (50mM) was used to adjust the pH of the samples to about 8.5
which is the optimal pH for cyanine CyDyes labelling. The soluble retinal
proteins were then labelled individually with dyes Cy3 and Cy5 while the pooled
retinal proteins from all samples were labelled with Cy2. According to the test
labeling result using E-coli as a standard protein mixture (data not shown), 50 μg
(about 8-9 μl) of each soluble protein extract and the pooled sample (12.5 µg x 4)
was mixed with 1 μl of working Cy2, Cy3 or Cy5 and incubated on ice for 30
mins in dark. The labelling reactions were quenched with 1 μl of 10 mM lysine
and incubated further on ice for 10 mins. Differentially labelled samples were
mixed with the pooled Cy2-labelled extracts and an equal volume of modified
EB5 lysis buffer with 2% (w/v) DTT and 0.4% (v/v) Biolyte was added for 10
mins proteins reduction at room temperature. The final volume for all
preparations was adjusted to a total of 300 μl with rehydration buffer (7M urea,
2M thiourea, 0.2% Biolyte, 1% DTT, 2% CHAPS, 1% ASB14 and a trace
amount of bromophenol blue).
The DIGE technology is a new technique and the labelling property of
CyDyesTM for retinal tissue has yet to be characterized. To further validate the
application of DIGE technique to the samples, a reciprocal labelling experiment
in which both the treatment and control groups were labelled by Cy3 and Cy5
was conducted in order to account for any preferential proteins labelling by
CyDyesTM. The labelling protocols for all 2-D gels prior to electrophoresis were
170
shown in Table 10.
Table 10. The experimental design of CyDyes minimal labelling for each retinal
sample in the DIGE study. A total of 150 μg labelled proteins were loaded on
each gel for 2D electrophoresis. #1 and #2 represented two individual chicks.
Gel no.
Gel 1
Gel 2
Gel 3
Gel 4
Cy3
Cy5
Cy2 (pool control)
#1 treated
#1 control
#1 and #2 treated & control
(50 μg)
(50 μg)
(25 μg #1 and 25 μg #2)
#2 treated
#2 control
#1 and #2 treated & control
(50 μg)
(50 μg)
(25 μg #1 and 25 μg #2)
#1 control
#1 treated
#1 and #2 treated & control
(50 μg)
(50 μg)
(25 μg #1 and 25 μg #2)
#2 control
#2 treated
#1 and #2 treated & control
(50 μg)
(50 μg)
(25 μg #1 and 25 μg #2)
Two-dimensional gel electrophoresis
Two-dimensional gel electrophoresis was performed similar to the
procedures described in Chapter 7.1. In order to have a better resolution, 17 cm
IPG strips of pH 5-8 were employed in the first dimension to study the area
where most of the soluble retinal proteins were located. The IPG strips were
placed in the equilibrium buffer containing 0.5% DTT first and in another buffer
in which the DTT was replaced by 4.5% iodoacetamide. The second dimension
electrophoresis was carried out in the Hoeffer SE600 (16 x 18 cm) vertical tank
(Amersham Biosciences) at constant 30 mA /gel. The polyacrylamide gels (12%)
were prepared with low fluorescent Pyrex glass plates in order to minimize the
background fluorescence and maximize the signal to noise ratio during the image
scan. All electrophoresis procedures were performed in dim light or in the dark.
After the image scanning, all gels were resembled to the SE600 tank for a
171
further second dimension separation run at 15 mA /gel overnight. The
electrophoresis process was stopped at the same time and the images were
scanned again for a better visualization of protein profiles at higher molecular
weight region.
Protein detection
After 2DE, the gels were scanned directly between the glass plates with the
provided Gel Alignment Guides using a TyphoonTM 9400 Variable Mode Imager
(Amersham Biosciences). All laser power adjustment and image acquisition were
done by the bundle Typhoon Scanner Control program. The Cy3 gel images were
scanned at an excitation wavelength of 532 nm (green laser) and at an emission
wavelength of 580 nm /BP 40 (maxima/bandwidth). The Cy5 gel images were
scanned at an excitation wavelength of 633 nm (red laser) and at an emission
wavelength of 670 nm /BP 30 nm while the Cy2 gel images were scanned at an
excitation wavelength of 488 nm and at an emission wavelength of 520 nm /BP
40. The BP emission filters were used to minimize possible cross-talk between
different fluorescence channels. Although an “Auto Link Mode” for a single pass
scan for all three channels was available, scanning of gel with different laser was
carried out individually to ensure a better sensitivity. Edge illumination was used
and the pre-scan laser power adjustment was performed with 1000 μm pixel size
to allow full utilization of the image dynamic range before saturation. The
resolution for final quantitative analytical scans was set at 100 μm and the final
laser powers for Cy3, Cy5 and Cy2 were set as 520 PMT, 488 PMT and 500
PMT respectively.
172
Image analysis
The scanned gels were saved as modified 16-bit tiff format as *.gel format
which allowed better representation of wide dynamic range gray-scale for protein
spots. Prior to analysis, all gel images were cropped to identical size by removing
areas extraneous to the proteins spots by the ImageQuantTM ver 5.0 (Amersham
Biosciences) and then they were transferred to the DeCyderTM Differential
Analysis Software ver 6.0 (Amersham Biosciences) for analysis.
Gel specific spot exclusion parameters were first determined to allow
artefacts removal (such as dust particles, scratches and protein streaks). A batch
processor without user intervention was later implemented to perform fully
automated background subtraction, spot co-detection, quantitation and matching
according to the experimental design in Table 10. The standardized spot volume
(the sum of pixel values within a detected spot boundary) was calculated as the
ratio between the absolute volume of the individual spot and the total volume of
the gel. The pooled gel images (Cy 2) on each gel were intrinsically linked to the
treatment and control gel images (Cy3 and Cy5) within the same gels and across
the pooled images of other gels. A DeCyder DIA (differential in-gel analysis)
module was performed for image analysis between samples within the same gel
while a DeCyder BVA (biological variation analysis) module was performed for
pair-wise image analysis amongst multiple gels. Ratios of differentially
expressed proteins were shown as “fold” changes between the treated myopic
eyes and the control eyes. An increase of protein abundance in the treated eye
was expressed as a positive value while a negative value denoted a decrease in
the protein abundance. Protein spot can be normalized using the corresponding
spot on the pooled internal standard on every gel, Student’s t-test on logged ratios
173
could be used to compare the average spot volume and significant differences of
protein abundance for all detectable pairs between the treatment and control
groups. The workflow was described in Figure 35.
Figure 35. A schematic diagram outlines the logics of the DIGE experimental
setup and the data analysis by DeCyder Differential Analysis Software. The three
image profiles of pre-labelled proteins were individually scanned at their
excitation wavelengths by a Typhoon fluorescence scanner. Detection and
quantitation of protein spots (expressed as a ratio relative to the internal pool
standard) were performed by co-detection algorithms in the DIA (differential
in-gel analysis) module in the same gels. The spots’ profiles across multiple gels
were compared by matching all protein spots amongst different pool standards to
the master standard (in which the highest number of protein spot was detected)
using the BVA (biological variation analysis) module.
To avoid any preferential CyDyes labelling of particular protein spots,
which may bias the differential protein expressions, images of the reciprocal dyes
labelling of gel 1 and gel 3 were exported and converted as tiff format for overlay
comparisons in the ImageMasterTM 5 gel analysis software. The differential
174
expressions could be observed visually by using different colour channels for the
treatment and control groups.
Protein identification and Mass Spectrometry
To allow MS protein identifications of spots of interest, preparative
traditional 2-D PAGE gels were re-run as individual gels for the four retinal
samples. Extracts of proteins (100µg) from each retinal sample were separated
on 17 cm IPG strips of pH 5-8 in the first dimension. The buffers and running
conditions were based on the DIGE protocol. The 2-D gels were stained with MS
compatible silver stain and the protein profiles were compared against the DIGE
images in the ImageMasterTM 5 gel analysis software to identify the differentially
expressed proteins. Gel spots were then excised manually and underwent in-gel
trypsin digestion and MALDI-TOF MS was performed as descried earlier in
Chapter 5.2. Peptide mass mapping was carried out using the NCBInr database
(NCBInr 20070120, 4462937 sequences) via the online Mascot search engine.
Biological variant of protein isoforms with the same score achieved were also
listed. All identified proteins had to be with more than 4 peptides matched and
sequence coverage of more than 10 %.
8.3 Results and Discussion
8.3.1
Refractive errors changes in chick eyes
Both animals developed significant myopia after the treatment period. The
final refractive errors of the myopic eyes were -10.5D and -11.5D respectively in
the two chicks while only mild hyperopia was found in their fellow control eyes.
8.3.2
Protein Profiles of CyDyesTM labelled retinal proteins
An overview of the fluorescent DIGE images of two individual animal (gel
175
1 for chick #1 while gel 2 for chick #2) were showed in Figure 36. The
fluorescent images generated by the typhoon system were relatively simple and
readily comparable to the traditional silver or coomassie dye stains. All three
passes of fluorescent scans with sufficient resolution for DIGE analysis could be
obtained within 30 mins. There were three individual images captured from each
gel (with 50μg protein). The Cy3 images represented the retinal profiles of the
treatment (defocus) eyes and the Cy5 images represented retinal profiles of the
control (normal) eyes. The Cy2 images were the pooled standard containing
equal amount of protein from each samples and therefore represented an average
of all the samples to be compared.
176
pH 5
Gel 1,
(chick # 1)
pH 8 pH 5
Cy3 treated
pH 8
Cy5 control
pH 5
pH 8
Cy2 pool standard
pH 5
Gel 2,
(chick # 2)
pH 8 pH 5
Cy3 treated
pH 8
Cy5 control
pH 5
pH 8
Cy2 pool standard
Figure 36. Typical fluorescent protein profiles of the pre-labelled retinal tissues
by different CyDyes (Cy3 for treated eyes; Cy5 for control eyes; Cy 2 for the
177
pooled standard). The labelled retinal samples of each animal were mixed prior
to 2-D PAGE. Each gel contained 50μg total protein separated by a pH 5-8 IPG
strip in the first dimension and 12% linear polyacrylamide gel in the second
dimension electrophoresis. Relevant images were captured by excitation with
different lasers using the Typhoon 9400 Variable Mode Imager.
The DIGE approach allowed co-running of different samples in the same gel
which have produced highly repeatable and consistent gel images of the six
analytes electrophoresed by 2-D PAGE. It could be observed from Figure 36 that
not only the protein spots but also the streaks or gel distortions due to the
experimental artefacts were almost identical amongst the three fluorescent
images of the same gel. In addition, the protein profiles of the reciprocal CyDye
labelling were also very similar to the above gel images (data not shown) which
suggested there was minimal preferential labelling of CyDyes
8.3.3
Image analysis by DeCyder DIA
The protein co-detection of the three different CyDye labelled images in
each gel was first analyzed by the DIA module. In order to perform reliable
quantification, a built-in normalization function to compensate for any
experimental variations, such as differences in laser power, fluorescence
labelling and sample loading, was performed. The normalized abundances of all
protein spots were obtained by comparing against the pooled standard (Cy3/Cy2
vs Cy5/Cy2). They were further compared between the treatment and the control
eyes and the results were shown as normal distribution histograms (log
10
of all
spot volume ratios) in Figure 37.
The retinal protein profiles of the two animals were very similar. Figure 37
showed all the protein spots that were present in both the treatment and control
178
eyes. Protein spots were plotted with the log volume ratio on the x-axis while the
left Y-axis showed the number of spots and the right Y-axis showed the spot
volume. As the histograms showed in the blue curves, it could be seen that the
normalized volume ratio (red curves) fitted very well to the data of both animals.
After the exclusion of experimental artefacts (e.g. dusts) by the internal software
filters, 1505 and 1456 spot pairs were detected in gel 1 and gel 2 respectively. To
identify the protein spots that were significantly different in their expressions, the
data (5%) that were having two standard deviations (2SD) away from the
distribution were recorded (the black vertical lines represents the 2SD). It was
found that 47 spots (31% for gel 1) and 61 spots (4.2% for gel 2) showed an
up-regulation whereas 58 spots (3.9% for gel 1) and 55 spots (3.8% for gel 2)
showed a down-regulation after the 7-day -10D lens wearing.
Gel 1, (chick #1)
decrease
Gel 2, (chick #2)
increase
decrease
increase
Figure 37. Histograms of the normalized spot volumes within a co-detected
image pairs using DIA module for two animals. The diagram showed the total
number of spots against log volume ratio simulated a normal distribution
(indicated by the red line). By applying the ± 2SD filter (the black vertical lines),
most of the spots (green spots) fell within the constraint (ratio = 1, or log
[volume ratio] = 0) while the blue spots indicated a volume increase and the red
spots indicated a volume decrease in the treatment eyes.
179
Due to ability of sample multiplexing in one single gel, the spot boundary
detection by the DIA of all images was found to be almost identical without
further need of gel warping or manual editing which was a difficult but necessary
task in the conventional 2-D PAGE. The perfect matching of the protein profiles
for fully automated spot matching and quantification ensured confident protein
comparison. Moreover, the normalized spot volume data allowed a rapid
overview of the differential protein expressions at customized criteria of
fold-differences in terms of spot area, spot intensity or spot volume. However,
the DIA analysis is applicable only to different proteins profiles within the same
gel.
8.3.4
Image analysis by DeCyder BVA
Using the BVA module, the differential protein expression of those
co-detected pairs between the treatment and control eyes across all four gel runs
(two biological replicas and two analytical replicas) could be quantified. Similar
approach has been recently described (Berendt et al. 2005). In order to identify
the “differentially expressed proteins”, relatively conservative selection criteria
were used. Each of them had to fulfil all of the following criteria: first of all,
there was at least 1.5 folds mean difference between the treatment and control
groups in terms of the spot volume. It has been demonstrated that 10% change in
spot volume could achieve higher than 95% statistical confidence using the
DIGE technique (Unlu et al. 1997). Secondly, the differentially expressed spot
had to be observed in all four gels. Thirdly, it had to achieve a statistically
significant fold change (P ≤ 0.05) by using the built-in T-test statistics software.
Finally, these spots were checked manually to confirm that they were true protein
spots instead of streaks or other artefacts.
180
More than a hundred of the protein pairs with were found by the DIA
modules in each gel, but only 22 spots met the present criteria. Amongst these
differentially expressed proteins, 15 spots showed an up-regulation and only 7
spots showed a down-regulation. Therefore, up-regulation of proteins seemed to
be the dominant features in the expression profiles. Their locations on the 2-D
gels were annotated and shown in Figure 37.
Figure 38. A typical retinal DIGE gel image showing the annotations and
locations of differential protein expressions in response to -10D lens wearing.
The treatment and control samples were labelled with different CyDyes and
mixed in 50:50 ratio and separated in 12% linear gels. Image analysis was
performed with the DeCyder BVA module to identify the changes in protein
amount. The up-regulated proteins were marked in blue colour while the
down-regulated proteins were marked in red colour.
181
8.3.5
Effect of CyDyesTM reciprocal stain
Since DIGE Cydyes labelling is a relatively new technique in comparative
proteomics, the chemical properties of Cydyes are still being optimized. There
was also concern for differential lysine labelling for particular proteins in using
different CyDyes (He and Chiu 2003). Actually, one study has reported
preferential lysine labeling for particular proteins and the result was await to be
further studied (Tonge et al. 2001). Since this technology has not been applied to
retinal samples, experiments were conducted to control these potential problems
by using a reciprocal labelling experimental design. Furthermore, although the
ImageMasterTM 5 gel analysis software was not originally designed for DIGE
application, after converting the 16-bit *.gel DIGE file format to 12-bit *.tif
image format using the Adobe Photoshop imaging software, preferential CyDyes
labelling could be studied by taking advantage of the built-in image stacking
(overlay) function. The differential expressed protein spots between the
defocused and control eyes were found to be very similar in the reciprocal stain
of Gel 1 and Gel 3. Taking the 22 differential expressed spots in Figure 39 as
examples, it showed that the up-regulation and down-regulation of protein in
response to the -10D lens treatment could still be observed in both gels even
using different CyDyes labels. Therefore, with the reciprocal stain, it was in
effect adding an extra internal control to eliminate any possible false positive
results caused by the labelling dyes themselves.
182
Up-regulation (blue)
Down-regulation (red)
Figure 39. examples of the Cy3 and Cy5 dyes reciprocal labelling effect for the
22 filtered differentially expressed protein spots (indicated by arrows) between
Gel 1 (treated sample was labelled by Cy3) and Gel 3 (treated sample was
reciprocally labelled by Cy5). All gel sections were captured by the
ImageMasterTM 5 image analysis software using the gel stacking function in
which up-regulated proteins were simulated as blue colour while down-regulated
proteins were simulated as red colour. Similar protein amount between the
defocused and control eyes were shown in dark colour. The differential
expressions were found to be consistent when using either CyDyes.
8.3.6
Decyder analysis after the second phase electrophoresis
To allow for a better study of the higher molecular weight proteins, the 2-D
gels were re-run after the first running was finished and the typhoon imager had
captured the first gel image. This continuing and further electrophoretic
separation of higher molecular weight proteins was not possible with
conventional electrophoresis after staining. Since the second dimension
separation was repeated on all gels in the same system for the same period of
183
time, the multiplexed gels image profiles after the re-run were still very similar.
By applying the same filtering criteria, most of the 22 differentially expressions
could be observed again with significant differences found by the Decyder BVA.
The locations of these spots were shown in Figure 40. However, three of the low
abundant proteins (#979, #1257 and #1260) were found to be too faint to be
detected again in all four gels due to the gel re-run. Therefore, they were not
included as they no longer fulfilled all of the pre-set criteria.
Interestingly, in addition to those previously identified spots, 4 new spots (1
up-regulation and 3 down-regulations) were found to show significant changes
after the re-run possibly due to better molecular weight in-gel separations. Their
annotations were also shown and circled in Figure 40. This result showed another
advantage of DIGE as compared to the conventional 2-D PAGE in particular for
scarce protein samples. Protein profiles can be captured after the designated
running time and then the gel, which is assembled in the low-fluorescence glass
plate, can be reinstalled for further electrophoresis. The pre-mixed proteins in the
same gel were still moving together which can ensure a perfect overlapping of
the image profiles for a reliable analysis after re-running the gel. In addition, as
the TyphoonTM scanner is a point scanner the photobleaching effects due to
constant gel illumination may be avoided. The photobleaching of CyDyes for
extended experiment was also found to be insignificant in the study although a
slight enhancement of excitation laser power was required in the second phase
image capture.
184
Figure 40. The DIGE gel image after a second phase electrophoresis to resolve
the higher molecular weight proteins. Proteins with molecular weight less than
about 25 kDa ran off the gel. Comparing to Figure 38, four additional spots (in
circles) were found which have significant differential protein expressions. The
up-regulated proteins were marked in blue colour while the down-regulated
proteins were marked in red colour.
The individual data was also analyzed with the Decyder BVA and the results
of each differentially expressed protein were shown in Figure 41. The figure
showed the actual protein changes of a particular spot in each of the four gels in
term of spot volume between the treatment and control eyes. In addition, the 3-D
simulations of the corresponding spots which represented the typical abundance
in term of protein volume in the same gel were also shown. It was particularly
185
useful for comparing high abundant spots (such as spot 1124 and 1245) where
the gray scale intensities were almost saturated in 2D view. These 3-D
representations also allowed objective comparisons of the actual spots intensities
and profiles as they were not affected by manual contrast and brightness
adjustments. The present results showed that the differential expressions (fold
change) in all of the selected spots were very similar and repeatable even across
different gels. The spot boundaries as detected by the Decyder software also
matched extremely well between the control and treated samples. The P values of
paired t-test for most of the spots were far less than 0.02 which indicated
consistent protein expressions and labelling efficiency in both up-regulated and
down-regulated proteins.
The use of a pooled internal standard as in the current DIGE experimental
design was not possible in the conventional 2-D PAGE. The Cy2 labelled
samples facilitated an accurate spot detection and quantification across different
gels. The internal standard was pooled from all protein samples and by
quantifying the ratios (log of the ratios) between the internal standard and
experimental samples, one may be able to normalize the spot signals so that
comparison across different gels was possible. The inter-gel comparison allowed
an unbiased and accurate statistical calculation. This design is powerful in the
studying of time courses or dose dependent changes of protein signals. The
inclusion of an internal pooled standard also helped in differentiating real
biological signals from experimental variations (Alban et al. 2003). The benefit
of such internal standard was also evident in the present study. For example, it
could be observed from the 3-D views that the protein amounts of spots #1123
and #1245 seemed to be up-regulated in the treatment eyes if the protein ratios to
186
the internal standard were not taken into consideration. A previous report has
addressed this issue and showed that 42 out of 52 (80%) statistical significant
real difference could be overlooked without the use of the internal standard
(Friedman et al. 2004).
Since the internal control has effectively minimized the gel running
variations, the DIGE experiment does not need to be repeated as many times as
the conventional silver stained 2-D PAGE. In addition, the use of fluorescent
labelled CyDyes in DIGE has greatly extend the detection limits and sensitivity
of current comparative proteomic studies (He and Chiu 2003; Kolkman et al.
2005). DeCyder image analysis software has provided ease in the data analysis
and has the capability of fully automated and parallel analysis of multiple gels.
Compared to other fluorescent dye such as Sypro Ruby, photobleaching was not
a major problem with CyDyes (Gharbi et al. 2002). Because the CyDyes were
relatively stable, it was possible to re-run the gel to better profile the high
molecular weight proteins.
187
(a) Up-regulated proteins
1.7 fold, p=0.029
Spot 154
control
treated
1.9 fold, p=0.01
Spot 171
control
treated
2.0 fold, p=0.002
Spot 384
control
treated
Spot 445
control
Spot 544
control
1.8 fold, p=0.002
treated
1.5 fold, p=0.006
treated
1.9 fold, p=0.019
Spot 155
control
treated
1.7 fold, p=0.03
Spot 176
control
treated
Spot 387
control
Spot 346
control
Spot 594
control
1.8 fold, p=0.0002
control
1.7 fold, p=0.002
treated
1.8 fold, p=0.042
treated
188
treated
1.6 fold, p=0.014
Spot 320
control
treated
1.5 fold, p=0.0001
Spot 444
control
treated
2.3 fold, p=0.005
Spot 162
treated
Spot 502
control
Spot 726
control
1.9 fold, p=7.8e-005
treated
1.6 fold, p=0.003
treated
(a) up-regulated proteins (cond.)
Additional protein found after second phase electrophoresis:
Spot 153
control
1.6 fold, p=0.009
treated
189
(b) down-regulated proteins
-1.6 fold, p=0.0003
Spot 567
control
treated
Spot 1124
control
Spot 1260
control
-1.6 fold, p=0.023
treated
Spot 979
control
treated
Spot 1245
control
-2.0 fold, p=0.003
-1.5 fold, p=0.016
treated
-1.5 fold, p=.002
Spot 1123
control
treated
-1.5 fold, p=0.024
Spot 1257
control
treated
-1.7 fold, p=0.019
treated
Additional proteins found after second phase electrophoresis:
Spot 713
control
-1.6 fold, p=0.032
treated
Spot 717
control
-1.5 fold, p=0.016
treated
-1.6 fold, p=0.043
Spot 1013
control
treated
Figure 41. The comparative individual data (with fold changes and paired t-test
values) for those filtered spots by Decyder software. Up-regulated proteins were
shown in panel (a) while down-regulated proteins were shown in panel (b).
Graphical views showed the standardized log abundance of spot volume (y-axis)
against the changes of proteins between the control and treatment groups (x-axis)
in all 4 gels. Typical 3-D views were also shown for each spot pair.
190
8.3.7
Protein identification by MALDI-TOF MS
Using the in-gel digestion and MALD-TOF MS approach, most of the
differentially expressed protein spots (76% of all the filtered spots) could be
identified. However, only weak peptide signals were detected in the rest due to
the low peptide amount recovered. Almost all identifications were matched to the
Gallus gallus database except one protein spot (#594) which has a significant
match in the homology databases. These 15 up-regulated and 4 down-regulated
identified protein spots were annotated and listed in Table 11. According to the
prediction
of
their
subcellular
locations
using
PSORT
II
(http://psort.hgc.jp/form2.html), most of them (about 84%) were assigned to the
cytoplasm whereas the rest were assigned to the nuclear (about 16%). They
corresponded to 11 different proteins plus their isoforms. A brief description of
the functional roles for each protein was surveyed below.
z
(#154 and #162) Dynamin-1
It is one of the three isoforms of dynamin found in synapses and it
plays a role in the mitochondrial fusion and fission machinery. The
phosphorylation of dynamin-1 is essential for synaptic vesicle endocytosis in
nerve terminals (Smillie and Cousin 2005) and it is believed to support axonal
outgrowth as upregulation after synapse formation in the chick retinotectal
system was found (Bergmann et al. 1999). Recently, Jagasia et al. also showed
that DRP-1/dynamin-related protein was required for inducing mitochondrial
fragmentation and programmed cell death during C. elegans development
(Jagasia et al. 2005).
z
(#155) Villin 1
Villin 1 is a major structural component of the brush border
191
cytoskeleton, and an actin-associated protein that is associated with the actin core
bundle of microvilli. It is also present in the Muller's glial cells (Muller baskets)
of the retina (Hofer and Drenckhahn 1993). It belongs to one of the gelsolin
superfamily proteins that control actin organization by severing filaments,
capping filament ends and nucleating actin assembly. It might also involve in
several cellular processes, including cell motility, control of apoptosis and
regulation of phagocytosis (Silacci et al. 2004).
z
(#171 and #176) Dead (Asp-Glu-Ala-Asp) box polypeptide 1
It is a relatively newly protein. DEAD box proteins (DDX) are putative
RNA unwinding proteins with specific developmental role. Northern and Western
blot analyses showed the highest expression of DDX1 was found at early stages
of embryonic development in chicken. Tissue maturation is generally
accompanied by a decrease in expression, although DDX1 levels remains
elevated in the retina and brain during late embryonic stage. In situ hybridization
of retinal tissue sections revealed a widespread distribution of DDX1 mRNA at
early developmental stages with preferential expression in the amacrine and
ganglion cells (Godbout et al. 2002).
z
(#594) Nuclear RNA helicase (DEAD family) homolog - rat
RNA helicase is a putative enzyme which enables the unwinding of
double-stranded RNA. MS PMF result of HLA-B associated transcript and Bat1,
are also members of the DEAD family which is a large superfamily of proteins
conserved from bacteria and viruses to human (Tanner and Linder 2001). On the
sequence level, RNA helicases are identified by the presence of seven to eight
conserved motifs which are involved in binding an NTP, generally ATP, and
using the energy of hydrolysis to unwind dsRNA (de la Cruz et al. 1999). RNA
192
helicases are therefore thought to act as "RNA chaperones" or "maturases" to
ensure that the correct interactions are formed or as energy-dependent
"facilitators" that catalyze conformational changes and drive multistep reactions
requiring sequential rearrangements of RNA interactions.
z
(#320)
Dihydropyrimidinase-related
protein
2,
DRP2
(or
Collapsin response mediator protein, CRMP-62)
CRMP-62 is well known of its involvement in the neuronal growth
cone collapse and it is localized exclusively in the developing chick nervous
system. Introduction of anti-CRMP-62 antibodies into dorsal root of ganglion
neurons can effectively block collapsin-induced growth cone collapse. It was
suggested that CRMP-62 may be involved as one of the intracellular components
of the related signaling cascade initiated by an unidentified transmembrane
collapsin-binding protein (Goshima et al. 1995). CRMP was also recently found
to play a key role in the neuronal polarization as overexpression of CRMP-2
induced the formation of multiple axons (Inagaki et al. 2001). CRMP may play a
crucial role in regulating axonal growth by interacting with soluble tubulin
transport or microtubule assembly (Fukata et al. 2002; Kimura et al. 2005). More
globally, difference in its protein level between neonatal and adult brain were
also recently characterized using the 2DE approach (Fountoulakis et al. 2000).
z
(#346) Seryl-tRNA synthetase
The current knowledge related to this protein is relatively limited. The
enzyme catalyses the attachment of an amino acid to its cognate transfer RNA
molecule in a highly specific two-step reaction (Eriani et al. 1990). Vincent et al.
first assembled 2 overlapping clones of SARS, called SERS, from human fetal
and infant brain cDNA libraries in 1997 (Vincent et al. 1997). However, there is
193
still no available information to suggest any functional role of this proteins in eye
growth.
z
(#384, #387, #444, #445, #544) Tubulin
Tubulin is one of the abundant proteins in chick retina according to the
previous result of proteome database. It is well known that the morphological
changes are closely related to the reorganization of cytoskeletal proteins such as
actin and tubulin. Microtubule, consist of alpha- and beta-tubulin, is one of the
constituents in many eukaryotic cell structures. They serve a number of cellular
functions including cell mobility, intracellular transport and cell division. Their
importance in ocular system has been proposed in previous studies. During the
optic nerve regeneration process of the bullfrog, a rapid and transient increase of
the messenger RNA of alpha-tubulin gene (Mizobuchi et al. 1988). Also, using
Northern blot analysis and in situ hybridization, it was found that the rat homolog
of alpha-tubulin was highly expressed during the extension of neuronal processes
(Miller et al. 1987). In addition, beta-tubulin was also found to express in the
differentiating retinal neuroblasts and it may have important role in the retinal
ganglion cell differentiation (Bozanic et al. 2006). A time course of the
expression of beta-tubulin during development has been characterized in the
mouse retina (Sharma et al. 2003).
z
(#502) Septin 6
Septins are GTPases for cytokinesis and other processes requiring
spatial organization of the cell cortex, but their exact molecular functions in these
processes are unknown (Finger 2002). Septin 6 was found to be abundantly
expressed in the adult mouse brain according to immunohistochemical study. It
was found to be associated with synaptic vesicles in various brain regions
194
(Kinoshita et al. 2000). Meanwhile, growing evidence suggests that mammalian
septins functionally or physically interact with a number of molecules such as
actin, actin-binding proteins and proteins of membrane fusion machinery
(Kinoshita and Noda 2001). Mammalian septins were recently showed to
regulate microtubule stability through interaction with the microtubule-binding
protein MAP4 (Kremer et al. 2005).
z
(#712) aldolase C
It belongs to the class I fructose-bisphosphate aldolase family in which
aldolase C is one of the members expressed in the brain tissue. It is a glycolytic
enzyme that catalyses the reversible aldol cleavage or condensation of
fructose-1,6-bisphosphate into dihydroxyacetone-phosphate and glyceraldehyde
3-phosphate and it is involved in the glycolysis as well (Marsh and Lebherz
1992). Aldolase C increases during the development of mammalian foetal brain,
and is expressed at high levels in adult brain (Makeh et al. 1994). Moreover,
Northern blot analysis of aldolase C mRNA showed protein amount decreased in
the chicken liver while progressive activation was found in the brain during the
growth process (Ono et al. 1990). Aldolase C was also reported to take part as a
nuclear factor in the stabilization od DNA synthesis and was involved in the
transcription of genes associated with cell growth and differentiation (Ronai
1993).
z
(#1123 and #1124) phosphoglycerate mutase 1 (brain)
This protein was also known as Phosphoglycerate mutase 1
(PGAM1_CHICK) in SwissProt protein database. It is a glycolytic enzyme that
catalyzes
the
interconversion
of
3-
and
2-phosphoglycerate
with
2,3-bisphosphoglycerate as the primer of the reaction. The protein shared the
195
same family to previous identified protein as phosphoglycerate mutase type B
subunit, PGM-B in retinal developmental growth in Chapter 6. Previous study
also showed its up-regulation in the development of trisomy 19 mice (Lorke
1994). A more recent developmental study in chick embryo also showed similar
up-regulation in the protein expression (Agudo Garcillan et al. 2005). DiMauro
et al. even suggested that both PGAM-A and PGAM-B are the same protein
(DiMauro et al. 1986). Furthermore, the PMF identification for #1124 also
confirmed the significant sequence similarity of these spots to PGAM-B.
z
(#1245) PREDICTED: similar to natural killer cell enhancing
factor isoform
This
Peroxiredoxins
protein
are
belongs
recently
to
the
reviewed
peroxiredoxin
as
(Prdx)
multifunctional
family.
antioxidant
thioredoxin-dependent peroxidises. The major functions of Prdxs include cellular
protection against oxidative stress, modulation of intracellular signaling cascades
and regulation of cell proliferation (Immenschuh and Baumgart-Vogt 2005; Rhee
et al. 2005). Prdx I is the most abundant and ubiquitously distributed in
mammalian tissues. According to the study by Neumann et al., Prdx1-deficient
fibroblasts showed decreased proliferation and increased sensitivity to oxidative
DNA damage, whereas mice lacked Prdx1 showed abnormalities in numbers,
phenotype, and function of natural killer cells. They suggested that Prdx1 was an
important defence against oxidants in aging mice (Neumann et al. 2003). Other
peroxiredoxin family members, peroxiredoxin 3 (also known as antioxidant
protein 1) and peroxiredoxin 5, were shown to reduce apoptosis and was thought
to be responsible for regulation of cellular proliferation, differentiation and
anti-oxidative function in different parts of the body (Tsuji et al. 1995; Shih et al.
196
2001; Wang et al. 2002). Furthermore, a recent study showed that peroxiredoxin
2 deficiency increased the production of peroxide, enhanced activation of PDGF
receptor and subsequently increased cell proliferation and migration in response
to PDGF (Choi et al. 2005).
By and large, the compensated myopic growth in terms of differential
protein expression was very similar between different animals. Nevertheless,
given that the inter-animal variations in protein expression is known to be higher,
the differential protein profiles between the defocus and control eyes of the same
animal were compared so as to further minimize variation. Moreover, binocular
visual system provides a unique platform for comparative proteomics study as
different manipulations of the two eyes of a single animal, with same genetic
make up, were possible.
Proteins that are differentially expressed in diseased conditions may be of
interest as potential diagnostic markers and consequently of clinical interest.
Most of the identified proteins in the present study have previously been found in
the nervous system and have been described in the literature. However, their
roles in myopia development are yet to be established.
Considering that lens-induced myopia was due to axial elongation, it was
not surprising to see the clear up-regulation of the cytosketetal proteins (Tubulin,
#384, #387, #444, #445, #544), actin-associated protein (Villin 1, #155) or those
responsible for the retinal axon growth (Dynamin-1, #154 and #162) in the
treatment eyes. Protein with multiple functions may involve in axonal growth,
actin organization or neuronal cone growth is also believed to play important
roles in the signaling cascade (CRMP-62, #320). In addition, two of these
197
proteins (PGAM1, #1123 and #1124) that could be linked directly to normal
ocular development were also identified in the previous study (Chapter 6.2).
However, whether the down-regulation of PGAM is a passive response to
growing process remains unknown. On the other hand, other upstream
modification is also likely to take place in the RNA level (DEAD family, #171
and #176, #594; Seryl-tRNA synthetase, #346) or transcription process (Aldolase
C, #712). Furthermore, since proteins such as heat shock protein (#134),
phosphoglycerate mutase 1 (#1123 and #1124), dihydropyrimidinase related
protein-2 (DRP-2) (#320) and peroxiredoxin 1 (#1245) are all susceptible to
oxidation or involved in the oxidation process; it is thus conceivable that
oxidative stress may play a potential role in the pathogenesis of myopia
development. The present findings, using proteomic approach and in the light of
current literatures of protein functions, may contribute to a global understanding
of the complex protein expressions and interplay during the compensated myopic
growth. Therefore, the present data may provide a new perspective to the current
myopia research direction.
On technical aspects, it has previously been shown that CyDye binding was
compatible to protein identification with mass spectrometry techniques using
minimal labelling approach (to less than 5%) (Tonge et al. 2001; Zhou et al. 2002;
Fujii et al. 2005). In the present study, protein identifications were performed on
preparative 2-D gels by using the conventional PAGE since it was found that the
MS compatible silver stain on the original gels was not satisfactory after the
DIGE electrophoresis was re-run. Usually, the highest pixel area excised
represented the highest abundance of a particular protein spot on gel with the MS
compatible stain approach. However, in the case of DIGE, spot intensity may
198
only represent the location of the lysine but not the protein itself. This
discrepancy complicated the locating of proteins in stained spots to be cut and
might hinder the success of recovering sufficient peptides during in-gel protein
digestion for later MS analysis. A clear benefit of using separate preparative gels
over the CyDye labelled gel for protein identification was that more protein can
be recovered from the preparative gel for later successful MS analysis.
When compared to the conventional 2-D PAGE, the DIGE approach was
able to filter and identify larger number of differentially expressed retinal
proteins in response to the -10D lens treatment. The present data showed for the
first time that these proteins were differentially expressed in the myopic eyes. It
should also be noted that the criteria on the differentially expressed proteins was
set stringently and conservatively so that only proteins with the most significant
differences were studied. In addition, it is anticipated that more candidate
proteins could be discovered by using IPGs of different pH ranges or zoom-gels.
Therefore, the regulatory mechanisms at the protein level in lens-induced myopia
are likely to be more complicated.
Although there are apparent merits in the DIGE technique, it is not without
limitations. The DIGE approach is not applicable to study proteins which have no
lysine group because of the lysine labelling property of the CyeDyes. Also, the
DIGE technique still shares some of the inherent limitations of the conventional
2-D PAGE technique. For example, it is ineffective in detecting membrane bound
proteins, proteins of extreme pH and low abundance proteins. The DIGE system
is technical inconvenient in searching for the On-Off protein differences (instead
of up- or down regulation) between the treatment and control groups due to the
missing of the counterpart proteins in either of the samples. In theory, the latter
199
two problems could be remedied by capturing multiple profiles with increasing
laser power in order to extend the dynamic detection range which is again not
possible in the conventional silver staining technique. A new DIGE development
has recently been reported which uses the “saturation labelling” method to label
the cysteine residues and this approach may further extend the application of
DIGE and overcome some of the current limitations of DIGE (Shaw et al. 2003).
200
Table 11. A list of differentially expressed chick retinal proteins after 7 days -10D lens treatment. The proteins were detected by DecyderTM
analysis software using DIGE approach and were identified by MALDI-TOF MS.
DIGE NCBI GI no. Mascot Protein Name
Spot a)
no.
154
118099274 PREDICTED: similar to dynamin 1 isoform 1
155
45382125
162
PIRSF ID
b)
MOWSE RMS
c)
error
score
d)
(ppm)
Number of sequence
matched
coverage
peaks /
unmatched
peaks
Mascot Mascot M.W. Organism g)
e)
f)
pI.
(da)
SwissProt /
TrEMBL
accession
h)
no.
SwissProt /
UniProt entry
i)
name
-
197
21
14 / 5
18.0%
6.98
97611
Gallus Gallus
-
-
PIRSF002347
152
25
14 / 6
19.7%
5.88
92821
Gallus Gallus
P02640
VILI_CHICK
118099274 PREDICTED: similar to dynamin 1 isoform 1
-
203
20
11 / 3
18.0%
6.98
97611
Gallus Gallus
-
-
171
45383053
DEAD (Asp-Glu-Ala-Asp) box polypeptide 1
-
128
35
11 / 3
18.1%
6.64
83458
Gallus Gallus
Q641Y8
DDX1_RAT
176
45383053
DEAD (Asp-Glu-Ala-Asp) box polypeptide 1
-
180
20
14 / 2
23.0%
6.64
83458
Gallus Gallus
Q641Y8
DDX1_RAT
320
3122036
Dihydropyrimidinase related protein-2 (DRP-2)
(Collapsin response mediator protein CRMP-62)
PIRSF001238
152
20
9/5
24.8%
5.96
62691
Gallus Gallus
33340025
Collapsin response mediator protein-2B
PIRSF001238
152
20
9/5
24.8%
6.05
62619
Gallus Gallus
Q90635
DPYL2_CHICK
45383177
Dihydropyrimidinase-like 2
-
146
20
9/5
21.0%
6.03
73908
Gallus Gallus
346
71897227
Seryl-tRNA synthetase
PIRSF001529
166
9
11 / 11
28.8%
6.11
58837
Gallus Gallus
-
-
384
71575
Tubulin alpha chain - chicken (fragment)
-
216
19
13 / 1
44.8%
5.00
46256
Gallus Gallus
223280
Tubulin alpha
-
216
19
13 / 1
44.8%
5.00
46256
Gallus Gallus
P02552
TBA1_CHICK
135393
Tubulin alpha-1 chain
PIRSF002306
216
19
13 / 1
44.8%
5.00
46256
Gallus Gallus
387
71575
Tubulin alpha chain - chicken (fragment)
-
225
9
16 / 5
50.0%
5.00
46256
Gallus Gallus
P02552
TBA1_CHICK
444
52138699
Tubulin, beta 2
PIRSF002306
200
20
14 / 4
37.1%
4.78
50377
Gallus Gallus
P32882
TBB2_CHICK
445
537407
Beta tubulin
PIRSF002306
343
25
23 / 3
54.0%
4.79
50172
Cricetulus
griseus
P09203
P32882
TBB1_CHICK
TBB2_CHICK
Villin 1
201
118099195 PREDICTED: hypothetical protein (beta tubulin)
502
544
71895629
Septin 6
343
25
23 / 3
54.0%
4.78
50285
Gallus Gallus
PIRSF006698
181
38
13 / 6
35.9%
6.67
48999
Gallus Gallus
P09206
TBB3_CHICK
Q14141
SEPT6_HUMAN
P09206
TBB3_CHICK
Q5ZHZD
UAP56_CHICK
-
234
22
17 / 8
49.0%
5.95
43514
Sycon sp.
AR-2003
-
214
22
16 / 9
40.0%
4.78
50285
Gallus Gallus
-
123
48
7/3
21.0%
6.65
46100
Rattus
norvegicus
114606329 PREDICTED: HLA-B associated transcript 1 isoform 9
-
123
48
7/3
19.0%
5.36
49223
Pan troglodytes
114606331 PREDICTED: HLA-B associated transcript 1 isoform 1
-
123
48
7/3
19.0%
5.50
49490
Pan troglodytes
114606315 PREDICTED: HLA-B associated transcript 1 isoform 7
-
123
48
7/3
19.0%
5.58
49738
Pan troglodytes
PIRSF003023
123
48
7/3
19.0%
5.51
49444
Homo sapiens
-
121
60
13 / 11
31.8%
5.79
39023
Gallus Gallus
-
-
32967422
Beta-tubulin
118099195 PREDICTED: hypothetical protein (beta tubulin)
594
-
539961
62897383
Nuclear RNA helicase (DEAD family) homolog - rat
HLA-B associated transcript 1 variant
712
226855
1123
71895985
phosphoglycerate mutase 1 (brain)
PIRSF001490
134
32
7/0
45.3%
7.03
29051
Gallus Gallus
Q5ZLN1
PGAM1_CHICK
1124
71895985
phosphoglycerate mutase 1 (brain)
PIRSF001490
191
42
9/2
52.0%
7.03
29051
Gallus Gallus
Q5ZLN2
PGAM1_CHICK
1245
50751518
PREDICTED: similar to natural killer cell enhancing
factor isoform 4
-
144
34
9/4
34.0%
8.24
22529
Gallus Gallus
118094468
PREDICTED: similar to natural killer cell enhancing
factor isoform 4
-
144
34
9/4
33.0%
8.24
23333
Gallus Gallus
a)
Aldolase C
A GI number (GenInfo Identifier) is assigned to each nucleotide and protein sequence accessible through the The National Center for
Biotechnology Information search systems (NCBI). b) The PIR (Protein Information Resource) is a non-redundant reference protein database at
Georgetown University Medical Centre. c) Score for the protein with significant match calculated by Mowse scoring algorithm in the Mascot
system.
d)
The mass differences (error) between the calculated and experimental mass values for the matched protein in ppm.
202
e & f)
Theoretical
values of the isoelectric point and molecular weight obtained in the database search using Mascot system. g) The species identified with significant
score for a particular protein. h) SwissProt is a protein knowledgebase maintained collaboratively by the Swiss Institute of Bioinformatics and the
The European Bioinformatics Institute; TrEMBL is a computer-annotated supplement of Swiss-Prot that contains all the translations of EMBL
nucleotide sequence entries not yet integrated in Swiss-Prot. i) The UniProt (Universal Protein Resource) is a comprehensive catalog of protein
information created by the consortium members PIR, European Bioinformatics Institute and Swiss Institute of Bioinformatics.
203
8.4 Conclusion
The research provideds an overview of the differential protein expressions
which may be involved in the lens-induced myopia by using a DIGE
experimental approach. A total of 26 retinal proteins were detected which showed
significant change in their protein amounts as compared to the control protein
profile. Amongst them, 19 were successfully identified by the MALDI-TOF MS.
Their possible roles in relation to myopic growth have also been discussed.
To tackle complex biological events such as myopia with proteomics, the
quest for accuracy is as important and powerful as aiming for high throughput.
This study demonstrated for the first time that the DIGE approach can effectively
identify retinal protein candidates which were differentially expressed in the
compensated myopic eye. The DIGE method can also effectively speed the
experimentation as compared to the conventional 2D PAGE. In addition, the
incorporation of an internal pooled standard has greatly improved the quality of
data so that signals due to real biological changes rather than system variations
can be discerned with confidence. It allowed for an unbiased detection of small
differential changes with statistical confidence which could not be easily
achieved by conventional 2-D PAGE. As a result, global protein differences
between populations or samples could be more accurately identified and
quantified.
Although a full picture of the protein interactions in the induced
emmetropization remains unclear, this study has attempted to enrich the overall
understanding of the mechanism of myopia and open up new directions in
myopia research. It is hypothesized that these differentially expressed retinal
proteins may play significant roles in the biological cascade of reactions that
204
underlie myopic eye growth. Elucidation of their exact roles in the
emmetropization process may hold vital keys for future treatment and
management of human myopia
205
Chapter 9: Summary and conclusions
The aim of the current study is to investigate the basic biological
mechanism of myopia from a protein perspective. The hypothesis is that the
retina acts not only as photoreceptors but also as an efferent centre that generates
signals to induce choroidal and scleral changes in myopia. In particular, the study
searched for differential retinal protein expression using a novel proteomic
approach for mass screening of proteins and their dynamic changes in 2D gels.
The research findings of the present study were summarized below:
1.
The refractive errors of the normal growing chicks in the first 20 days
after hatching were measured. Majority of the eyes (67.9%) was found
to have against-the-rule astigmatism. Compensated emmetropization in
chicks using optical lenses (-10D or +10D) or occluders have also
successfully been induced and quantified. The chicks can fully
compensate to both -10D and +10D lens treatment after about 7 days
lens wearing whereas greater variability was observed in the occluder
treatment. These observations were similar to previous published
studies.
2.
A workable proteomic protocol for studying chick retina have been
devised which includ sample homogenization, protein quantification,
2-D gel stainings (coomassie blue and silver stain), protein profile
analysis and protein identification by MALDI-TOF MS. These
procedures were optimized for chick retina through different control
experiments.
3.
The first chick retinal proteome database was established which
206
consists of 155 proteins from 2D proteomic map covering 3-10 pH
range. These identified proteins were further classified according to
their subcellular locations as well as their molecular functions using
online databases. Most of the proteins (about 71%) were found to be
present in the cytoplasm. Based on the gene ontology information, over
80% of the identified proteins falls into three major functional
categories of “catalytic activity” (39%), “binding” (33%) and
“transporter activity” (10%).
4.
A number of differential protein expressions in normal growth of chick
eyes at three time-points were found using the established working
protocol. After MALDI-TOF MS, five of them could be successfully
identified and their possible roles in the ocular growth were discussed.
5.
In treatment eyes, two candidate retinal proteins were found to be
differentially expressed in the 2D gels after wearing lenses or occluders
for different durations. In myopic eyes, Apolipoprotein AI (Apo-AI)
was found to be down-regulated while destrin; actin depolymerising
factor, ADF (Destrin) was found to be up-regulated in the defocused
eye. They may have significant functional roles in regulating eye
growth.
6.
A novel Two-Dimensional fluorescence difference gel electrophoresis
(2-D DIGE) technique in studying differential protein expressions in
lens-induced myopic chick retina has been tested. The data showed that
it has additional benefits and advantages over the traditional 2-D PAGE.
With this technique, 16 protein spots showed up-regulation and 11
spots showed down-regulation whereas 70% of the filtered protein
207
spots could be successfully identified.
The work in this dissertation laid a foundation for proteomic applications in
myopia research. The optimised working protocols for identifying differential
protein expressions in retinal tissues may help to advance similar study in
myopia research and other eye research.
With a better understanding of the key protein players involved in the
development of compensated myopia in terms of their genesis, functions and
locations, new clues may be provided for devising future treatments for human
myopia.
208
APPENDIX 1.
z
Raw data for normal emmetropization (Chapter 3.2.1 and 3.2.2)
1 day-old
Chick eye
241R
241L
242R
242L
244R
244L
245R
245L
246R
246L
247R
247L
216R
216L
217R
217L
218R
218L
219R
219L
220R
220L
221R
221L
222R
222L
336R
336L
337R
337L
338R
338L
339R
339L
400R
400L
401R
401L
402R
402L
403R
403L
404R
404L
405R
405L
406R
406L
407R
407L
Vertical
axis
2.00
3.00
1.50
1.50
1.00
1.50
2.00
4.00
1.50
2.00
3.00
3.50
2.00
3.00
2.00
2.00
3.00
1.00
2.00
2.50
2.00
2.00
3.50
3.50
2.00
3.00
2.00
3.00
2.00
1.50
3.00
3.00
3.00
3.00
3.00
2.00
2.00
2.00
1.50
1.50
2.00
3.00
2.00
3.00
2.00
3.00
2.00
2.00
1.50
1.50
Horizontal Sphere
axis
3.50
3.50
4.00
4.00
2.00
2.00
2.50
2.50
2.00
2.00
2.50
2.50
3.00
3.00
4.50
4.50
1.50
1.00
2.00
1.50
3.50
3.50
3.50
3.00
3.00
3.00
3.50
3.50
3.00
3.00
2.50
2.50
3.00
3.00
2.00
2.00
3.00
3.00
3.00
3.00
2.50
2.50
3.00
3.00
3.00
3.50
3.00
3.50
3.00
3.00
4.00
4.00
2.00
2.00
3.00
3.00
3.00
3.00
2.50
2.50
4.00
4.00
3.00
3.00
3.00
3.00
3.00
3.00
2.00
3.00
1.50
2.00
2.00
2.00
2.00
2.00
1.50
1.50
2.00
2.00
2.00
2.00
3.00
3.00
2.00
2.00
3.00
3.00
3.00
3.00
3.50
3.50
2.00
2.00
2.50
2.50
1.50
1.50
2.00
2.00
Cyl.
Axis
-1.50
-1.00
-0.50
-1.00
-1.00
-1.00
-1.00
-0.50
-0.50
-0.50
-0.50
-0.50
-1.00
-0.50
-1.00
-0.50
90
90
90
90
90
90
90
90
180
180
90
180
90
90
90
90
-1.00
-1.00
-0.50
-0.50
-1.00
-0.50
-0.50
-1.00
-1.00
90
90
90
90
90
180
180
90
90
-1.00
-1.00
-1.00
90
90
90
-1.00
-0.50
180
180
-0.50
90
-1.00
-0.50
90
90
-0.50
90
-0.50
90
209
Equiv.
sphere
2.75
3.50
1.75
2.00
1.50
2.00
2.50
4.25
1.25
1.75
3.25
3.25
2.50
3.25
2.50
2.25
3.00
1.50
2.50
2.75
2.25
2.50
3.25
3.25
2.50
3.50
2.00
3.00
2.50
2.00
3.50
3.00
3.00
3.00
2.50
1.75
2.00
2.00
1.50
1.75
2.00
3.00
2.00
3.00
2.50
3.25
2.00
2.25
1.50
1.75
Chick no.
241
242
244
245
246
247
216
217
218
219
220
221
222
336
337
338
339
400
401
402
403
404
405
406
407
Weight
(g)
43.5
43
43.5
40.5
43
45
45
40
43
45
40
40
40
35
35
40
35
35
40
40
35
40
35
35
35
3 day-old
Chick eye
255R
255L
256R
256L
257R
257L
258R
258L
259R
259L
270R
270L
271R
271L
272R
272L
273R
273L
274R
274L
214R
214L
216R
216L
306R
306L
307R
307L
308R
308L
309R
309L
310R
310L
Vertical
axis
2.00
2.00
1.00
1.00
1.00
0.00
1.00
1.50
2.00
2.00
1.50
1.50
3.00
2.00
1.50
1.50
2.00
2.50
1.50
2.00
2.00
1.50
2.50
2.50
0.50
0.50
1.00
2.00
2.00
1.50
1.50
2.00
2.00
2.00
Horizontal Sphere
axis
3.00
3.00
3.00
3.00
2.00
2.00
0.50
1.00
2.00
2.00
1.00
1.00
2.00
2.00
3.50
3.50
2.00
2.00
4.00
4.00
2.50
2.50
2.00
2.00
3.50
3.50
2.00
2.00
1.00
1.50
1.00
1.50
2.50
2.50
3.00
3.00
1.50
1.50
3.00
3.00
2.00
2.00
1.50
1.50
2.50
2.00
2.50
2.50
1.00
1.00
1.00
1.00
2.00
2.00
4.00
4.00
2.00
2.00
1.50
1.50
3.00
3.00
3.50
3.50
3.00
3.00
2.00
2.00
Cyl.
Axis
-1.00
-1.00
-1.00
-0.50
-1.00
-1.00
-1.00
-2.00
90
90
90
180
90
90
90
90
-2.00
-1.00
-0.50
-0.50
90
90
90
90
-0.50
-0.50
-0.50
-0.50
180
180
90
90
-1.00
90
-0.50
180
-0.50
-0.50
-1.00
-2.00
90
90
90
90
-1.50
-1.50
-1.00
90
90
90
210
Equiv.
sphere
2.50
2.50
1.50
0.75
1.50
0.50
1.50
2.50
2.00
3.00
2.00
1.75
3.25
2.00
1.25
1.25
2.25
2.75
1.50
2.50
2.00
1.50
2.25
2.50
0.75
0.75
1.50
3.00
2.00
1.50
2.25
2.75
2.50
2.00
Chick no.
255
256
257
258
259
270
271
272
273
274
214
216
306
307
308
309
310
Weight
(g)
35
40
40
40
40
35
33
35
35
30
40
40
50
50
50
55
50
7 day-old
Chick eye
097R
097L
098R
098L
099R
099L
100R
100L
101R
101L
102R
102L
106R
106L
107R
107L
108R
108L
109R
109L
110R
110L
111R
111L
112R
112L
113R
113L
148R
148L
174R
174L
175R
175L
176R
176L
Vertical
axis
0.50
0.00
1.00
0.50
0.50
0.50
1.00
0.50
0.00
1.00
0.00
0.50
1.50
1.50
0.50
1.50
1.50
0.50
1.00
0.00
1.00
2.00
1.00
3.00
0.00
0.50
1.50
1.50
0.50
1.00
2.00
3.00
2.00
3.00
3.50
3.00
Horizontal Sphere
axis
1.00
1.00
1.00
1.00
2.00
2.00
1.50
1.50
1.50
1.50
1.50
1.50
2.00
2.00
1.50
1.50
1.00
1.00
1.50
1.50
0.00
0.00
0.00
0.50
2.00
2.00
3.00
3.00
2.50
2.50
3.00
3.00
2.00
2.00
1.50
1.50
1.50
1.50
0.50
0.50
3.00
3.00
3.00
3.00
2.00
2.00
3.00
3.00
1.50
1.50
1.50
1.50
1.50
1.50
2.00
2.00
2.00
2.00
3.00
3.00
1.50
2.00
2.00
3.00
3.00
3.00
3.00
3.00
3.00
3.50
2.50
3.00
Cyl.
Axis
-0.50
-1.00
-1.00
-1.00
-1.00
-1.00
-1.00
-1.00
-1.00
-0.50
0.00
-0.50
-0.50
-1.50
-2.00
-1.50
-0.50
-1.00
-0.50
-0.50
-2.00
-1.00
-1.00
90
90
90
90
90
90
90
90
90
90
0
180
90
90
90
90
90
90
90
90
90
90
90
-1.50
-1.00
90
90
-0.50
-1.50
-2.00
-0.50
-1.00
-1.00
90
90
90
180
180
90
-0.50
-0.50
180
180
211
Equiv.
sphere
0.75
0.50
1.50
1.00
1.00
1.00
1.50
1.00
0.50
1.25
0.00
0.25
1.75
2.25
1.50
2.25
1.75
1.00
1.25
0.25
2.00
2.50
1.50
3.00
0.75
1.00
1.50
1.75
1.25
2.00
1.75
2.50
2.50
3.00
3.25
2.75
Chick no.
97
98
99
100
101
102
106
107
108
109
110
111
112
113
148
174
175
176
Weight
(g)
70
64
55.5
53
65.5
67.5
64
60.5
60
55
57.5
56
65.5
66.5
65.9
80
70
75
10 day-old
Chick eye
260R
260L
261R
261L
262R
262L
263R
263L
264R
264L
275R
275L
276R
276L
410R
410L
411R
411L
412R
412L
413R
413L
414R
414L
Vertical Horizontal Sphere
axis
axis
1.00
1.50
1.50
1.50
2.00
2.00
1.50
2.00
2.00
0.00
2.00
2.00
0.00
0.00
0.00
-0.50
-0.50
-0.50
0.50
1.00
1.00
1.50
2.00
2.00
0.00
2.00
2.00
1.00
2.50
2.50
1.50
2.00
2.00
1.50
2.50
2.50
2.00
2.00
2.00
1.50
2.00
2.00
1.00
1.00
1.00
1.00
1.50
1.50
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.50
1.50
1.50
2.00
2.00
0.50
1.00
1.00
1.50
1.50
1.50
1.50
2.00
2.00
1.00
1.00
1.00
Cyl.
Axis
-0.50
-0.50
-0.50
-2.00
90
90
90
90
-0.50
-0.50
-2.00
-1.50
-0.50
-1.00
90
90
90
90
90
90
-0.50
90
-0.50
90
-0.50
-0.50
-0.50
90
90
90
-0.50
90
212
Equiv.
sphere
1.25
1.75
1.75
1.00
0.00
-0.50
0.75
1.75
1.00
1.75
1.75
2.00
2.00
1.75
1.00
1.25
1.00
1.00
1.50
1.75
0.75
1.50
1.75
1.00
Chick no.
260
261
262
263
264
275
276
410
411
412
413
414
Weight
(g)
65
70
70
75
70
45
45
68
68
60
58
59.5
14 day-old
Chick eye
284R
284L
285R
285L
286R
286L
287R
287L
303R
303L
304R
304L
305R
305L
305eR
305eL
410R
410L
411R
411L
412R
412L
413R
413L
414R
414L
Vertical
axis
1.50
0.50
1.50
1.50
0.50
0.50
0.00
0.00
0.50
1.00
1.00
0.50
1.00
1.00
0.50
0.00
0.50
0.50
0.50
0.50
1.00
1.00
0.50
1.00
1.00
0.50
Horizontal Sphere
axis
2.00
2.00
2.00
2.00
2.00
2.00
2.00
2.00
1.00
1.00
1.50
1.50
1.00
1.00
0.50
0.50
1.00
1.00
2.00
2.00
1.00
1.00
1.00
1.00
1.50
1.50
1.50
1.50
0.50
0.50
0.00
0.00
1.00
1.00
1.50
1.50
1.50
1.50
1.00
1.00
1.50
1.50
2.00
2.00
1.50
1.50
1.50
1.50
1.50
1.50
1.00
1.00
Vertical
axis
1.00
0.50
0.00
0.50
0.00
0.50
1.50
1.50
0.00
0.50
0.50
0.50
0.50
0.00
0.50
0.50
0.00
0.50
1.00
0.50
Horizontal Sphere
axis
1.50
1.50
1.50
1.50
0.50
0.50
1.00
1.00
0.00
0.50
0.50
2.00
2.00
2.00
2.00
0.50
0.50
1.00
1.00
0.50
0.50
0.50
0.50
1.50
1.50
1.00
1.00
0.50
0.50
1.50
1.50
1.00
1.00
0.50
0.50
1.00
1.00
1.00
1.00
Cyl.
Axis
-0.50
-1.50
-0.50
-0.50
-0.50
-1.00
-1.00
-0.50
-0.50
-1.00
90
90
90
90
90
90
90
90
90
90
-0.50
-0.50
-0.50
90
90
90
-1.00
-1.00
-0.50
-0.50
-1.00
-1.00
-0.50
-0.50
-0.50
90
90
90
90
90
90
90
90
90
Cyl.
Axis
-0.50
-1.00
-0.50
-0.50
90
90
90
90
-0.50
-0.50
-0.50
-0.50
90
90
90
90
-1.00
-1.00
90
90
-1.00
-1.00
90
90
-0.50
90
Equiv.
sphere
1.75
1.25
1.75
1.75
0.75
1.00
0.50
0.25
0.75
1.50
1.00
0.75
1.25
1.25
0.50
0.00
1.00
1.00
1.00
0.75
1.25
1.50
1.00
1.25
1.25
0.75
Chick no.
Equiv.
sphere
1.25
1.00
0.25
0.75
0.00
0.50
1.75
1.75
0.25
0.75
0.50
0.50
1.00
0.50
0.50
1.00
0.50
0.50
1.00
0.75
Chick no.
284
285
286
287
303
304
305
305e
410
411
412
413
414
Weight
(g)
110
120
120
115
100
90
105
100
95
100
90
83.5
85
20 day-old
Chick eye
265R
265L
266R
266L
267R
267L
268R
268L
269R
269L
410R
410L
411R
411L
412R
412L
413R
413L
414R
414L
213
265
266
267
268
269
410
411
412
413
414
Weight
(g)
100
120
120
120
120
115
112
100
103
97
z
Raw data for compensated myopia (Chapter 3.2.3)
Group A: -10D lens wear from 1 day-old. (Grey = tretment eye)
1 day-old
Chick eye Vertical Horizonta
axis
l axis
318R
2.50
2.50
318L
2.50
2.50
319R
2.00
2.50
319L
1.50
2.00
320R
3.00
2.00
320L
3.00
3.00
321R
2.00
2.50
321L
1.50
2.50
236R
1.50
1.50
236L
2.00
2.00
237R
2.50
2.00
237L
2.50
2.50
238R
1.00
1.00
238L
1.00
1.50
240R
0.50
1.00
240L
2.00
2.00
Sphere
2.50
2.50
2.50
2.00
3.00
3.00
2.50
2.50
1.50
2.00
2.50
2.50
1.00
1.50
1.00
2.00
Cyl.
after 3 days wearing
Axis
-0.50
-0.50
-1.00
90
90
180
-0.50
-1.00
90
90
-0.50
180
-0.50
-0.50
90
90
Equiv.
sphere
2.50
2.50
2.25
1.75
2.50
3.00
2.25
2.00
1.50
2.00
2.25
2.50
1.00
1.25
0.75
2.00
Vertical Horizonta
axis
l axis
-7.00
-7.00
1.00
3.00
-7.00
-8.00
0.50
1.00
-6.00
-5.00
1.00
1.50
-5.00
-5.00
3.00
4.00
2.00
2.00
-8.00
-8.00
-6.00
-7.00
3.00
2.00
1.50
1.50
-7.50
-7.00
1.00
2.00
-8.00
-8.00
214
Sphere
-7.00
3.00
-7.00
1.00
-5.00
1.50
-5.00
4.00
2.00
-8.00
-6.00
3.00
1.50
-7.00
2.00
-8.00
Cyl.
Axis
-2.00
-1.00
-0.50
-1.00
-0.50
90
180
90
90
90
-1.00
90
-1.00
-1.00
180
180
-0.50
-1.00
90
90
Equiv.
sphere
-7.00
2.00
-7.50
0.75
-5.50
1.25
-5.00
3.50
2.00
-8.00
-6.50
2.50
1.50
-7.25
1.50
-8.00
Chick
318
319
320
321
236
237
238
240
Weight (g)
1 day after 3
old
days
40.0
58.0
40.0
45.0
40.0
50.0
35.0
50.0
42.5
80.0
47.0
82.0
46.0
70.0
49.0
90.0
1 day-old
after 5 days wearing
Chick eye Vertical Horizonta
axis
l axis
092R
-1.00
-1.50
092L
-1.00
-0.50
093R
1.50
-3.00
093L
1.00
1.50
094R
1.00
0.50
094L
0.50
-2.00
095R
1.00
0.50
095L
1.00
0.50
096R
1.00
-0.50
096L
1.00
0.50
216R
2.00
3.00
216L
3.00
3.50
217R
2.00
3.00
217L
2.00
2.50
218R
3.00
3.00
218L
1.00
2.00
219R
2.00
3.00
219L
2.50
3.00
Sphere
Cyl.
Axis
-1.00
-0.50
1.50
1.50
1.00
0.50
1.00
1.00
1.00
1.00
3.00
3.50
3.00
2.50
3.00
2.00
3.00
3.00
-0.50
-0.50
-4.50
-0.50
-0.50
-2.50
-0.50
-0.50
-1.50
-0.50
-1.00
-0.50
-1.00
-0.50
180
90
180
90
180
180
180
180
180
180
90
90
90
90
-1.00
-1.00
-0.50
90
90
90
Chick eye Vertical Horizonta
axis
l axis
248R
2.00
3.00
248L
2.00
3.00
249R
2.50
3.00
249L
3.00
3.00
250R
2.00
3.00
250L
3.00
3.00
251R
3.00
3.00
251L
4.00
4.00
220R
2.00
2.50
220L
2.00
3.00
221R
3.50
3.00
221L
3.50
3.00
222R
2.00
3.00
222L
3.00
4.00
223R
1.50
2.00
223L
2.00
2.50
Sphere
Cyl.
Axis
3.00
3.00
3.00
3.00
3.00
3.00
3.00
4.00
2.50
3.00
3.50
3.50
3.00
4.00
2.00
2.50
-1.00
90
-0.50
90
-1.00
90
-0.50
-1.00
-0.50
-0.50
-1.00
-1.00
-0.50
-0.50
90
90
180
180
90
90
90
90
Equiv.
sphere
-1.25
-0.75
-0.75
1.25
0.75
-0.75
0.75
0.75
0.25
0.75
2.50
3.25
2.50
2.25
3.00
1.50
2.50
2.75
Vertical Horizonta
axis
l axis
-9.50
-7.00
0.00
0.00
1.00
2.00
-8.00
-8.50
-8.50
-7.50
0.00
1.00
0.50
2.00
-8.50
-7.00
0.50
0.00
-9.00
-7.00
-6.00
-7.00
2.00
3.00
-7.00
-7.00
2.00
2.50
-5.50
-6.00
0.50
1.00
-7.00
-7.00
2.00
2.50
Equiv.
sphere
2.50
3.00
2.75
3.00
2.50
3.00
3.00
4.00
2.25
2.50
3.25
3.25
2.50
3.50
1.75
2.25
Vertical Horizonta
axis
l axis
1.50
2.00
-9.00
-10.00
-10.00
-10.00
0.00
1.00
-10.00
-11.00
1.50
3.00
-12.00
-11.00
1.00
1.50
2.50
2.50
-7.00
-9.00
2.00
2.00
-9.00
-10.00
-9.00
-10.00
0.50
0.50
2.50
2.00
-7.00
-7.50
1 day-old
Sphere
Cyl.
Axis
-7.00
0.00
2.00
-8.00
-7.50
1.00
2.00
-7.00
0.50
-7.00
-6.00
3.00
-7.00
2.50
-5.50
1.00
-7.00
2.50
-2.50
90
-1.00
-0.50
-1.00
-1.00
-1.50
-1.50
-0.50
-2.00
-1.00
-1.00
90
180
90
90
90
90
180
90
180
90
-0.50
-0.50
-0.50
90
180
180
-0.50
180
Equiv.
sphere
-8.25
0.00
1.50
-8.25
-8.00
0.50
1.25
-7.75
0.25
-8.00
-6.50
2.50
-7.00
2.25
-5.75
0.75
-7.00
2.25
Chick
Equiv.
sphere
1.75
-9.50
-10.00
0.50
-10.50
2.25
-11.50
1.25
2.50
-8.00
2.00
-9.50
-9.50
0.50
2.25
-7.25
Chick
092
093
094
095
096
216
217
218
219
after 7 days wearing
215
Sphere
Cyl.
Axis
2.00
-9.00
-10.00
1.00
-10.00
3.00
-11.00
1.50
2.50
-7.00
2.00
-9.00
-9.00
0.50
2.50
-7.00
-0.50
-1.00
90
180
-1.00
-1.00
-1.50
-1.00
-0.50
90
180
90
90
90
-2.00
180
-1.00
-1.00
180
180
-0.50
-0.50
180
180
248
249
250
251
220
221
222
223
Weight (g)
1 day after 5
old
days
36.0
53.0
40.0
63.0
45.0
60.5
36.0
52.5
39.0
63.0
45.0
48.0
40.0
50.0
43.0
50.0
45.0
50.0
Weight (g)
1 day after 7
old
days
42.5
80.0
47.0
82.0
46.0
70.0
49.5
90.0
40.0
55.0
40.0
54.0
40.0
54.0
40.0
60.0
1 day-old
Chick eye Vertical Horizonta
axis
l axis
336R
2.00
2.00
336L
3.00
3.00
337R
2.00
3.00
337L
1.50
2.50
338R
3.00
4.00
338L
3.00
3.00
339R
3.00
3.00
339L
3.00
3.00
Sphere
2.00
3.00
3.00
2.50
4.00
3.00
3.00
3.00
Cyl.
-1.00
-1.00
-1.00
after 9 days wearing
Axis
90
90
90
Equiv.
sphere
2.00
3.00
2.50
2.00
3.50
3.00
3.00
3.00
Vertical Horizonta
axis
l axis
-11.00
-9.00
0.00
0.50
-11.00
-12.00
0.50
1.00
-10.00
-11.00
-0.50
0.50
-9.00
-9.00
0.50
0.50
216
Sphere
Cyl.
Axis
-9.00
0.50
-11.00
1.00
-10.00
0.50
-9.00
0.50
-2.00
-0.50
-1.00
-0.50
-1.00
-1.00
90
180
180
90
180
90
Equiv.
sphere
-10.00
0.25
-11.50
0.75
-10.50
0.00
-9.00
0.50
Chick
336
337
338
339
Weight (g)
1 day after 9
old
days
35.0
90.0
35.0
80.0
40.0
80.0
35.0
80.0
Group B: -10D lens wear from 3 day-old. (Grey = tretment eye)
3 day-old
after 1 day wearing
Chick eye Vertical Horizonta
axis
l axis
212R
1.50
2.00
212L
1.00
2.00
213R
1.50
2.50
213L
2.50
2.00
214R
2.00
2.00
214L
1.50
1.50
215R
1.50
2.00
215L
3.00
3.00
Sphere
Cyl.
Axis
2.00
2.00
2.50
2.50
2.00
1.50
2.00
3.00
-0.50
-1.00
-1.00
-0.50
90
90
90
180
-0.50
90
Chick eye Vertical Horizonta
axis
l axis
224R
1.00
2.00
224L
1.50
2.50
225R
1.50
1.50
225L
1.00
1.50
226R
1.50
2.00
226L
2.50
2.50
227R
2.50
2.50
227L
2.50
2.50
Sphere
Cyl.
Axis
2.00
2.50
1.50
1.50
2.00
2.50
2.50
2.50
-1.00
-1.00
90
90
-0.50
-0.50
90
90
Equiv.
sphere
1.75
1.50
2.00
2.25
2.00
1.50
1.75
3.00
Vertical Horizonta
axis
l axis
2.00
1.50
0.50
-0.50
1.50
2.00
1.50
-0.50
0.00
0.00
2.00
2.00
2.00
2.00
-0.50
0.00
Equiv.
sphere
1.50
2.00
1.50
1.25
1.75
2.50
2.50
2.50
Vertical Horizonta
axis
l axis
-3.50
-3.00
2.50
2.00
2.00
2.00
-4.00
-2.50
1.00
1.50
-4.00
-4.00
-3.00
-4.00
2.00
2.00
3 day-old
Sphere
Cyl.
Axis
2.00
0.50
2.00
1.50
0.00
2.00
2.00
0.00
-0.50
-1.00
-0.50
-2.00
180
180
90
180
0.00
180
-0.50
180
Equiv.
sphere
1.75
0.00
1.75
0.50
0.00
2.00
2.00
-0.25
Chick
Equiv.
sphere
-3.25
2.25
2.00
-3.25
1.25
-4.00
-3.50
2.00
Chick
212
213
214
215
after 3 days wearing
217
Sphere
Cyl.
Axis
-3.00
2.50
2.00
-2.50
1.50
-4.00
-3.00
2.00
-0.50
-0.50
90
180
-1.50
-0.50
90
90
-1.00
180
224
225
226
227
Weight (g)
3 day after 1
old
day
35.0
40.0
35.0
35.0
40.0
40.0
45.0
45.0
Weight (g)
3 day after 3
old
days
53.5
64.5
54.0
68.5
52.0
63.0
52.0
65.0
3 day-old
Chick eye Vertical Horizonta
axis
l axis
228R
0.00
0.00
228L
0.50
0.50
229R
1.50
1.50
229L
1.50
2.00
230R
1.50
2.00
230L
2.00
1.50
230eR
1.50
2.50
230eL
2.00
2.50
Sphere
Chick eye Vertical Horizonta
axis
l axis
231R
1.50
1.50
231L
2.00
2.00
232R
3.00
3.00
232L
4.00
4.00
233R
2.50
2.50
233L
2.50
2.50
234R
3.00
4.00
234L
3.50
4.00
Sphere
0.00
0.50
1.50
2.00
2.00
2.00
2.50
2.50
Cyl.
-0.50
-0.50
-0.50
-1.00
-0.50
after 5 days wearing
Axis
90
90
180
90
90
Equiv.
sphere
0.00
0.50
1.50
1.75
1.75
1.75
2.00
2.25
Vertical Horizonta
axis
l axis
1.00
1.00
-8.00
-8.00
-6.00
-7.00
1.00
1.50
-6.00
-7.00
0.00
2.00
-7.00
-7.00
1.00
1.50
Equiv.
sphere
1.50
2.00
3.00
4.00
2.50
2.50
3.50
3.75
Vertical Horizonta
axis
l axis
1.00
1.00
-9.00
-10.00
-10.00
-10.00
1.50
2.00
1.00
1.00
-11.00
-11.00
-11.00
-12.00
0.50
1.50
3 day-old
1.50
2.00
3.00
4.00
2.50
2.50
4.00
4.00
Cyl.
-1.00
-0.50
Sphere
1.00
-8.00
-6.00
1.50
-6.00
2.00
-7.00
1.50
Cyl.
Axis
-1.00
-0.50
-1.00
-2.00
180
90
180
90
-0.50
-90
Equiv.
sphere
1.00
-8.00
-6.50
1.25
-6.50
1.00
-7.00
1.25
Chick
Equiv.
sphere
1.00
-9.50
-10.00
1.75
1.00
-11.00
-11.50
1.00
Chick
228
229
230
230e
after 7 days wearing
Axis
90
90
218
Sphere
1.00
-9.00
-10.00
2.00
1.00
-11.00
-11.00
1.50
Cyl.
Axis
-1.00
180
-0.50
90
-1.00
-1.00
90
180
231
232
233
234
Weight (g)
3 day after 5
old
days
49.0
63.5
49.5
62.0
51.5
58.0
50.0
60.0
Weight (g)
3 day after 7
old
days
42.5
80.0
47.0
82.5
46.0
70.5
49.5
90.0
Group C: -10D lens wear from 4 day-old. (Grey = tretment eye)
4 day-old
Chick eye Vertical Horizonta
axis
l axis
138R
1.00
2.00
138L
1.50
2.00
139R
1.50
1.50
139L
0.50
1.00
140R
-1.00
0.00
140L
1.00
2.00
141R
0.50
1.00
141L
1.50
1.50
after 1 day wearing
Sphere
Cyl.
Axis
2.00
2.00
1.50
1.00
0.00
2.00
1.00
1.50
-1.00
-0.50
0.00
-0.50
-1.00
-1.00
-0.50
90
90
90
90
90
90
90
Equiv.
sphere
1.50
1.75
1.50
0.75
-0.50
1.50
0.75
1.50
Vertical Horizonta
axis
l axis
-1.00
0.00
2.00
3.00
-2.50
-1.00
0.50
2.00
-3.00
-2.00
1.00
1.00
2.00
1.00
0.00
1.00
219
Sphere
Cyl.
Axis
0.00
3.00
-1.00
2.00
-2.00
1.00
2.00
1.00
-1.00
-1.00
-1.50
-1.50
-1.00
90
90
90
90
90
-1.00
-1.00
180
90
Equiv.
sphere
-0.50
2.50
-1.75
1.25
-2.50
1.00
1.50
0.50
Chick
138
139
140
141
Weight (g)
4 day after 1
old
day
46.0
55.0
44.0
51.0
46.0
52.0
46.0
56.0
4 day-old
Chick eye Vertical Horizonta
axis
l axis
150R
2.00
4.00
150L
2.00
3.00
151R
1.00
1.50
151L
1.00
2.00
152R
1.00
1.00
152L
0.50
2.00
169R
1.50
2.00
169L
1.50
2.00
170R
1.50
2.00
170L
2.00
2.50
171R
2.00
2.00
171L
1.50
1.50
172R
1.50
2.00
172L
4.00
3.00
173R
2.00
3.00
173L
2.00
2.00
197R
1.00
2.00
197L
1.50
3.00
198R
3.00
3.50
198L
2.00
2.00
199R
3.00
4.00
199L
0.00
0.50
200R
4.00
4.00
200L
4.00
4.50
201R
3.00
3.00
201L
2.50
3.50
202R
2.00
3.50
202L
3.50
2.50
after 3 days wearing
Sphere
Cyl.
Axis
4.00
3.00
1.50
2.00
1.00
2.00
2.00
2.00
2.00
2.50
2.00
1.50
2.00
4.00
3.00
2.00
2.00
3.00
3.50
2.00
4.00
0.50
4.00
4.50
3.00
3.50
3.50
3.50
-2.00
-1.00
-0.50
-1.00
90
90
90
90
-1.50
-0.50
-0.50
-0.50
-0.50
90
90
90
90
90
-0.50
-1.00
-1.00
90
180
90
-1.00
-1.50
-0.50
90
90
90
-1.00
-0.50
90
90
-0.50
90
-1.00
-1.50
-1.00
90
90
180
Equiv.
sphere
3.00
2.50
1.25
1.50
1.00
1.25
1.75
1.75
1.75
2.25
2.00
1.50
1.75
3.50
2.50
2.00
1.50
2.25
3.25
2.00
3.50
0.25
4.00
4.25
3.00
3.00
2.75
3.00
Vertical Horizonta
axis
l axis
-5.00
-5.00
2.00
2.00
1.50
1.50
-5.00
-4.00
-0.50
0.50
-5.00
-3.50
1.50
2.00
-6.50
-7.50
-6.50
-5.50
3.00
1.00
2.50
2.00
-3.00
-3.00
3.00
2.00
1.50
1.50
-2.50
-0.50
2.00
2.50
0.50
1.00
-7.50
-5.50
1.00
2.00
-5.00
-5.50
0.00
0.50
-5.50
-5.00
-7.00
-7.00
-1.00
-1.00
-6.00
-5.00
0.50
1.50
2.00
3.50
-5.50
-6.00
220
Sphere
-5.00
2.00
1.50
-4.00
0.50
-3.50
2.00
-6.50
-5.50
3.00
2.50
-3.00
3.00
1.50
-0.50
2.50
1.00
-5.50
2.00
-5.00
0.50
-5.00
-7.00
-1.00
-5.00
1.50
3.50
-5.50
Cyl.
Axis
-1.00
90
-1.50
-0.50
-1.00
-1.00
-2.00
-0.50
90
90
180
90
180
180
-1.00
180
-2.00
-0.50
-0.50
-2.00
-1.00
-0.50
-0.50
-0.50
90
90
90
90
90
180
90
90
-1.00
-1.00
-1.50
-0.50
90
90
90
180
Equiv.
sphere
-5.00
2.00
1.50
-4.50
0.50
-4.25
1.75
-7.00
-6.00
2.00
2.25
-3.00
2.50
1.50
-1.50
2.25
0.75
-6.50
1.50
-5.25
0.25
-5.25
-7.00
-1.00
-5.50
1.00
2.75
-5.75
Chick
150
151
152
169
170
171
172
173
197
198
199
200
201
202
Weight (g)
4 day after 3
old
days
45.0
63.5
44.0
60.0
46.0
64.0
60.0
80.0
60.0
75.0
55.0
75.0
60.0
70.0
55.0
70.0
50.0
75.0
45.0
70.0
50.0
75.0
50.0
75.0
50.0
70.0
50.0
70.0
4 day-old
after 5 days wearing
Chick eye Vertical Horizonta
axis
l axis
116R
0.00
0.00
116L
0.00
-0.50
117R
1.50
2.00
117L
1.50
1.00
118R
0.50
0.50
118L
0.50
0.50
119R
0.00
1.00
119L
1.00
2.00
120R
2.00
2.00
120L
1.50
1.00
121R
-0.50
0.00
121L
-0.50
0.50
122R
1.00
1.00
122L
3.00
1.50
178R
3.00
3.00
178L
3.00
3.00
179R
1.50
1.50
179L
2.00
3.00
180R
2.50
2.50
180L
2.50
2.50
Sphere
Chick eye Vertical Horizonta
axis
l axis
204R
2.00
3.00
204L
3.00
3.50
205R
2.00
3.00
205L
3.50
3.50
206R
3.00
3.00
206L
2.50
4.00
207R
3.00
4.00
207L
3.00
4.50
208R
1.50
2.50
208L
3.00
2.50
210R
2.00
2.00
210L
1.50
3.00
Sphere
Cyl.
Axis
3.00
3.50
3.00
3.50
3.00
4.00
4.00
4.50
2.50
3.00
2.00
3.00
-1.00
-0.50
-1.00
90
90
90
-1.50
-1.00
-1.50
-1.00
-0.50
90
90
90
90
180
-1.50
90
0.00
0.00
2.00
1.50
0.50
0.50
1.00
2.00
2.00
1.50
0.00
0.50
1.00
3.00
3.00
3.00
1.50
3.00
2.50
2.50
Cyl.
Axis
-0.50
-0.50
-0.50
180
90
180
-1.00
-1.00
90
90
-0.50
-0.50
-1.00
180
90
90
-1.50
180
-1.00
90
Equiv.
sphere
0.00
-0.25
1.75
1.25
0.50
0.50
0.50
1.50
2.00
1.25
-0.25
0.00
1.00
2.25
3.00
3.00
1.50
2.50
2.50
2.50
Vertical Horizonta
axis
l axis
-5.00
-4.00
3.00
2.50
-6.00
-6.00
3.50
3.50
-8.00
-5.00
2.50
2.50
-6.00
-8.50
5.00
4.00
-3.50
-2.50
3.50
3.00
-4.00
-2.50
4.50
3.50
-4.00
-7.50
3.50
3.00
2.00
2.00
-8.00
-8.00
-7.00
-7.00
1.50
2.50
-6.50
-6.00
0.50
1.00
Equiv.
sphere
2.50
3.25
2.50
3.50
3.00
3.25
3.50
3.75
2.00
2.75
2.00
2.25
Vertical Horizonta
axis
l axis
-11.00
-11.00
0.00
0.00
-1.00
1.50
-11.00
-10.00
-10.00
-10.00
1.00
1.00
1.00
1.50
-10.00
-9.50
-8.00
-6.00
-0.50
1.00
-2.00
0.00
-8.00
-5.50
4 day-old
Sphere
Cyl.
Axis
-4.00
3.00
-6.00
3.50
-5.00
2.50
-6.00
5.00
-2.50
3.50
-2.50
4.50
-4.00
3.50
2.00
-8.00
-7.00
2.50
-6.50
1.00
-1.00
-0.50
90
180
-3.00
90
-2.50
-1.00
-1.00
-0.50
-1.50
-1.00
-3.50
-0.50
180
180
90
180
90
180
180
180
0.50
180
Equiv.
sphere
-4.50
2.75
-6.00
3.50
-6.50
2.50
-7.25
4.50
-3.00
3.25
-3.25
4.00
-5.75
3.25
2.00
-8.00
-7.00
2.50
-6.25
1.00
Chick
Equiv.
sphere
-11.00
0.00
0.25
-10.50
-10.00
1.00
1.25
-9.75
-7.00
0.25
-1.00
-6.75
Chick
116
117
118
119
120
121
122
178
179
180
after 7 days wearing
221
Sphere
-11.00
0.00
1.50
-10.00
-10.00
1.00
1.50
-9.50
-6.00
1.00
0.00
-5.50
Cyl.
Axis
-2.50
-1.00
90
90
-0.50
-0.50
-2.00
-1.50
-2.00
-2.50
90
90
90
90
90
90
204
205
206
207
208
210
Weight (g)
4 day after 5
old
days
49.5
59.5
58.5
85.0
57.0
86.5
50.5
75.0
53.0
78.0
49.0
67.0
49.5
72.0
60.0
100.0
55.0
90.0
60.0
100.0
Weight (g)
4 day after 7
old
days
45.0
90.0
40.0
100.0
50.0
110.0
45.0
100.0
55.0
110.0
45.0
100.0
Group D: -10D lens wear from 14 day-old. (Grey = tretment eye)
14 day-old
after 3 days wearing
Chick eye Vertical Horizonta
axis
l axis
284R
1.50
2.00
284L
0.50
2.00
285R
1.50
2.00
285L
1.50
2.00
286R
0.50
1.00
286L
0.50
1.50
287R
0.00
1.00
287L
0.00
0.50
Sphere
Cyl.
Axis
2.00
2.00
2.00
2.00
1.00
1.50
1.00
0.50
-0.50
-1.50
-0.50
-0.50
-0.50
-1.00
-1.00
-0.50
90
90
90
90
90
90
90
90
Chick eye Vertical Horizonta
axis
l axis
303R
0.50
1.00
303L
1.00
2.00
304R
1.00
1.00
304L
0.50
1.00
305R
1.00
1.50
305L
1.00
1.50
305eR
0.50
0.50
305eL
0.00
0.00
Sphere
Cyl.
Axis
1.00
2.00
1.00
1.00
1.50
1.50
0.50
0.00
-0.50
-1.00
90
90
-0.50
-0.50
-0.50
90
90
90
Equiv.
sphere
1.75
1.25
1.75
1.75
0.75
1.00
0.50
0.25
Vertical Horizonta
axis
l axis
-5.50
-6.00
0.00
1.00
-6.50
-5.50
2.50
2.50
-6.00
-6.00
0.50
1.00
-6.50
-6.00
1.50
2.00
Equiv.
sphere
0.75
1.50
1.00
0.75
1.25
1.25
0.50
0.00
Vertical Horizonta
axis
l axis
-7.00
-5.50
1.00
2.00
-10.00
-10.00
0.00
1.00
-7.00
-7.00
1.00
1.50
-8.00
-7.00
0.50
0.50
14 day-old
Sphere
Cyl.
Axis
-5.50
1.00
-5.50
2.50
-6.00
1.00
-6.00
2.00
-0.50
-1.00
-1.00
180
90
90
-0.50
-0.50
-0.50
90
90
90
Equiv.
sphere
-5.75
0.50
-6.00
2.50
-6.00
0.75
-6.25
1.75
after 5 days wearing
222
Sphere
Cyl.
Axis
-5.50
2.00
-10.00
1.00
-7.00
1.50
-7.00
0.50
-1.50
-1.00
90
90
-1.00
90
-0.50
-1.00
90
90
Equiv.
sphere
-6.25
1.50
-10.00
0.50
-7.00
1.25
-7.50
0.50
Weight (g)
Chick 14 day after 3
old
days
284 110.0 125.0
285 120.0 130.0
286 120.0 135.0
287 115.0 150.0
Weight (g)
Chick 14 day after 5
old
days
303 100.0 150.0
304
90.0
150.0
305 105.0 160.0
305e 100.0 160.0
z
Raw data for compensated hyperopia (Chapter 3.2.4)
Group A: +10D lens wear from 3 day-old. (Grey = tretment eye)
3 day-old
after 3 day wearing
Chick eye Vertical Horizonta
axis
l axis
292R
0.50
2.50
292L
0.50
2.50
293R
1.50
1.50
293L
1.50
2.50
294R
2.50
3.50
294L
1.00
2.50
295R
-1.50
-0.50
295L
-1.50
-0.50
296R
2.50
2.50
296L
2.50
2.50
297R
1.50
2.50
297L
1.00
2.50
Sphere
Cyl.
Axis
2.50
2.50
1.50
2.50
3.50
2.50
-0.50
-0.50
2.50
2.50
2.50
2.50
-2.00
90
-1.00
-1.00
-1.50
-1.00
-1.00
90
90
90
90
90
-1.00
-1.50
90
90
Chick eye Vertical Horizonta
axis
l axis
298R
2.00
3.00
298L
2.50
2.50
299R
2.00
4.00
299L
3.00
4.00
300R
3.00
4.00
300L
3.00
3.00
301R
2.00
3.00
301L
1.50
2.00
302R
3.00
4.00
302L
3.00
4.00
306R
0.50
1.00
306L
0.50
1.00
307R
1.00
2.00
307L
2.00
4.00
308R
2.00
2.00
308L
1.50
1.50
309R
1.50
3.00
309L
2.00
3.50
310R
2.00
3.00
310L
2.00
2.00
Sphere
Cyl.
Axis
3.00
2.50
4.00
4.00
4.00
3.00
3.00
2.00
4.00
4.00
1.00
1.00
2.00
4.00
2.00
1.50
3.00
3.50
3.00
2.00
-1.00
90
-2.00
-1.00
-1.00
90
90
90
-1.00
-0.50
-1.00
-1.00
-0.50
-0.50
-1.00
-2.00
90
90
90
90
90
90
90
90
-1.50
-1.50
-1.00
90
90
90
Equiv.
sphere
1.50
2.50
1.50
2.00
3.00
1.75
-1.00
-1.00
2.50
2.50
2.00
1.75
Vertical Horizonta
axis
l axis
6.50
7.50
0.50
1.00
6.50
7.50
1.50
2.50
6.50
7.50
0.00
1.00
7.50
8.50
0.50
1.00
7.50
7.50
0.50
1.50
7.50
7.50
0.50
1.00
Equiv.
sphere
2.50
2.50
3.00
3.50
3.50
3.00
2.50
1.75
3.50
3.50
0.75
0.75
1.50
3.00
2.00
1.50
2.25
2.75
2.50
2.00
Vertical Horizonta
axis
l axis
7.50
8.00
1.00
1.50
8.00
8.00
0.50
1.50
8.00
9.00
1.50
0.00
6.50
7.50
-0.50
-0.50
6.50
6.50
1.00
1.00
6.00
5.00
0.50
0.50
8.00
8.00
0.00
0.50
7.00
9.00
1.00
1.00
8.00
9.00
1.00
1.00
8.00
10.00
2.50
2.50
3 day-old
Sphere
Cyl.
Axis
7.50
1.00
7.50
2.50
7.50
1.00
8.50
1.00
7.50
1.50
7.50
1.00
-1.00
-0.50
-1.00
-1.00
-1.00
-1.00
-1.00
-0.50
90
90
90
90
90
90
90
90
-1.00
90
-0.50
90
Equiv.
sphere
7.00
0.75
7.00
2.00
7.00
0.50
8.00
0.75
7.50
1.00
7.50
0.75
Chick
Equiv.
sphere
7.75
1.25
8.00
1.00
8.50
0.75
7.00
-0.50
6.50
1.00
5.50
0.50
8.00
0.25
8.00
1.00
8.50
1.00
9.00
2.50
Chick
292
293
294
295
296
297
after 4 day wearing
223
Sphere
Cyl.
Axis
8.00
1.50
8.00
1.50
9.00
1.50
7.50
-0.50
6.50
1.00
6.00
0.50
8.00
0.50
9.00
1.00
9.00
1.00
10.00
2.50
-0.50
-0.50
90
90
-1.00
-1.00
-1.50
-1.00
90
90
180
90
-1.00
180
-0.50
-2.00
90
90
-1.00
90
-2.00
90
298
299
300
301
302
306
307
308
309
310
Weight (g)
3 day after 3
old
day
45.0
65.0
49.0
61.0
44.0
60.0
49.0
62.0
50.0
66.0
50.0
70.0
Weight (g)
3 day after 4
old
day
49.0
60.0
48.0
60.0
49.0
65.0
48.0
60.0
48.0
60.0
50.0
65.0
50.0
65.0
50.0
70.0
55.0
70.0
50.0
60.0
Group B: +10D lens wear from 4 day-old. (Grey = tretment eye)
4 day-old
after 4 day wearing
Chick eye Vertical Horizonta
axis
l axis
288R
0.00
0.50
288L
0.00
0.00
289R
0.50
1.00
289L
0.00
0.50
290R
1.50
2.00
290L
1.00
1.50
342R
1.50
2.00
342L
2.00
2.00
343R
2.50
2.50
343L
2.50
2.50
Sphere
Cyl.
Axis
0.50
0.00
1.00
0.50
2.00
1.50
2.00
2.00
2.50
2.50
-0.50
90
-0.50
-0.50
-0.50
-0.50
-0.50
90
90
90
90
90
Chick eye Vertical Horizonta
axis
l axis
083R
1.50
1.50
083L
1.50
1.50
084R
0.50
0.50
084L
-1.00
0.50
085R
-0.50
0.00
085L
1.00
1.00
086R
1.00
1.50
086L
1.00
0.50
Sphere
Equiv.
sphere
0.25
0.00
0.75
0.25
1.75
1.25
1.75
2.00
2.50
2.50
Vertical Horizonta
axis
l axis
10.00
9.00
-0.50
0.00
8.50
10.50
0.50
1.00
10.00
10.00
0.50
0.50
8.00
10.00
0.00
0.50
10.00
10.00
2.00
2.00
Equiv.
sphere
1.50
1.50
0.50
-0.25
-0.25
1.00
1.25
0.75
Vertical Horizonta
axis
l axis
12.00
11.00
-2.00
0.00
13.00
4.00
1.00
0.50
1.00
0.00
14.00
7.00
1.50
1.50
12.00
10.00
4 day-old
1.50
1.50
0.50
0.50
0.00
1.00
1.50
1.00
Cyl.
Sphere
Cyl.
Axis
10.00
0.00
10.50
1.00
10.00
0.50
10.00
0.50
10.00
2.00
-1.00
-0.50
-2.00
-0.50
180
90
90
90
-2.00
90
Equiv.
sphere
9.50
-0.25
9.50
0.75
10.00
0.50
9.00
0.50
10.00
2.00
Chick
Equiv.
sphere
11.50
-1.00
8.50
0.75
0.50
10.50
1.50
11.00
Chick
288
289
290
342
343
after 5 day wearing
Axis
-1.50
-0.50
90
90
-0.50
-0.50
90
180
224
Sphere
Cyl.
Axis
12.00
0.00
13.00
1.00
1.00
14.00
1.50
12.00
-1.00
-2.00
-9.00
-0.50
-1.00
-7.00
180
90
180
180
180
180
-2.00
180
083
084
085
086
Weight (g)
4 day after 4
old
day
50.0
65.0
55.0
70.0
50.0
65.0
50.0
65.0
50.0
60.0
Weight (g)
4 day after 5
old
day
44.0
82.0
47.0
78.0
46.0
73.0
46.0
78.0
z
Raw data for Form deprivation myopia (Chapter 3.2.5)
Black goggles wear from 1 day-old. (Grey = tretment eye)
1 day-old
after 3 day wearing
Chick eye Vertical Horizonta
axis
l axis
B1 R
3.00
4.00
B1 L
3.00
4.00
B2 R
2.00
2.00
B2 L
2.00
3.00
B3 R
3.00
4.00
B3 L
2.00
3.00
B4 R
5.00
5.00
B4 L
4.00
5.00
Sphere
Cyl.
Axis
4.00
4.00
2.00
3.00
4.00
3.00
5.00
5.00
-1.00
-1.00
90
90
-1.00
-1.00
-1.00
90
90
90
-1.00
90
Chick eye Vertical Horizonta
axis
l axis
244R
1.00
2.50
244L
2.00
2.50
245R
2.00
3.00
245L
4.00
4.50
246R
1.50
1.00
246L
2.00
1.50
247R
3.00
3.50
247L
3.50
3.00
Sphere
Cyl.
Axis
2.50
2.50
3.00
4.50
1.50
2.00
3.50
3.50
-1.50
-0.50
-1.00
-0.50
-0.50
-0.50
-0.50
-0.50
90
90
90
90
180
180
90
180
Equiv.
sphere
3.50
3.50
2.00
2.50
3.50
2.50
5.00
4.50
Vertical Horizonta
axis
l axis
-9.00
-9.00
2.00
2.00
-11.00
-10.00
2.00
3.00
2.00
3.00
-13.00
-13.00
1.00
1.00
-10.00
-12.00
Equiv.
sphere
1.75
2.25
2.50
4.25
1.25
1.75
3.25
3.25
Vertical Horizonta
axis
l axis
1.50
1.50
-6.00
-11.00
3.00
3.00
-11.00
-11.00
-8.00
-8.00
1.00
1.00
-17.00
-19.00
2.50
3.50
1 day-old
Sphere
-9.00
2.00
-10.00
3.00
3.00
-13.00
1.00
-10.00
Cyl.
Axis
-1.00
-1.00
-1.00
90
90
90
-2.00
180
Equiv.
sphere
-9.00
2.00
-10.00
3.00
3.00
-13.00
1.00
-11.00
Chick
Equiv.
sphere
1.50
-8.50
3.00
-11.00
-8.00
1.00
-18.00
3.00
Chick
B1
B2
B3
B4
after 5 day wearing
225
Sphere
1.50
-6.00
3.00
-11.00
-8.00
1.00
-17.00
3.50
Cyl.
Axis
-5.00
180
-2.00
-1.00
180
90
244
245
246
247
Weight (g)
1 day after 3
old
day
43.5
57.0
42.5
54.0
43.5
57.0
43.0
57.5
Weight (g)
1 day after 5
old
day
43.5
68.0
41.0
65.5
43.0
61.5
45.0
74.0
1 day-old
Chick eye Vertical Horizonta
axis
l axis
400R
3.00
2.00
400L
2.00
1.50
401R
2.00
2.00
401L
2.00
2.00
402R
1.50
1.50
402L
1.50
2.00
403R
2.00
2.00
403L
3.00
3.00
404R
2.00
2.00
404L
3.00
3.00
405R
2.00
3.00
405L
3.00
3.50
406R
2.00
2.00
406L
2.00
2.50
407R
1.50
1.50
407L
1.50
2.00
after 7 day wearing
Sphere
Cyl.
Axis
3.00
2.00
2.00
2.00
1.50
2.00
2.00
3.00
2.00
3.00
3.00
3.50
2.00
2.50
1.50
2.00
-1.00
-0.50
180
180
-0.50
90
-1.00
-0.50
90
90
-0.50
90
-0.50
90
Equiv.
sphere
2.50
1.75
2.00
2.00
1.50
1.75
2.00
3.00
2.00
3.00
2.50
3.25
2.00
2.25
1.50
1.75
Vertical Horizonta
axis
l axis
-23.00
-17.00
2.00
1.50
-29.00
-29.00
1.50
1.50
-17.00
-16.00
0.50
1.00
-30.00
-28.00
1.00
2.50
-28.00
-27.00
0.00
0.50
-17.00
-18.00
0.50
1.50
-15.00
-17.00
0.50
1.00
-28.00
-31.00
0.00
1.00
226
Sphere
Cyl.
Axis
-17.00
2.00
-29.00
1.50
-16.00
1.00
-28.00
2.50
-27.00
0.50
-17.00
1.50
-15.00
1.00
-28.00
1.00
-6.00
-0.50
90
180
-1.00
90
-2.00
-1.50
-1.00
-0.50
-1.00
-1.00
-2.00
-0.50
-3.00
-1.00
90
90
90
180
180
90
180
90
180
90
Equiv.
sphere
-20.00
1.75
-29.00
1.50
-16.50
1.00
-29.00
1.75
-27.50
0.25
-17.50
1.00
-16.00
0.75
-29.50
0.50
Chick
400
401
402
403
404
405
406
407
Weight (g)
1 day after 7
old
day
35.0
60.0
40.0
50.0
40.0
50.0
35.0
55.0
40.0
65.0
35.0
50.0
35.0
55.0
35.0
55.0
APPENDIX 2.
A list of chick retinal proteins identified by MALDI-TOF MS with their annotations (Chapter 5.3.1)
Spot NCBI GI
no.
no.
Mascot Protein Name
a)
NREF
Entry
Mascot Mascot Organism f)
c) coverage coverage
d)
M.W.
score
pI.
MOWSE intensity seq.
b)
(da)
e)
SwissProt / SwissProt /
TrEMBL
UniProt entry
accession
name
no.
1
3822553
2
g)
NF00047248
122
64.1%
15.9%
4.68
84697
Gallus Gallus
Q9YHD2
Q9YHD2
45383562 tumor rejection antigen (gp96) 1
NF00047483
118
50.2%
22.6%
4.81
91446
Gallus Gallus
P08110
ENPL_CHICK
3
63516
NF00046697
203
93.1%
21.2%
5.01
84466
Gallus Gallus
P11501
HS9A_CHICK
4
45382769
NF00047880
237
87.7%
37.9%
5.12
72088
Gallus Gallus
Q90593
GR78_CHICK
5
44969651 calreticulin
NF01896949
121
86.5%
17.1%
4.41
47079
Gallus Gallus
Q6EE32
Q6EE32
6
3023865
-
106
85.9%
26.3%
5.18
41211
O15975
GBQ_PATYE
7
63739
prolyl-4-hydroxylase (AA 5 - 494)
NF00047886
106
77.7%
21.8%
4.66
55174
Gallus Gallus
-
-
2144546
protein disulfide-isomerase (EC 5.3.4.1) precursor
-
105
77.7%
20.8%
4.69
57773
Gallus Gallus
P09102
PDI_CHICK
NF01028482
104
77.7%
20.3%
4.75
58896
Gallus Gallus
-
-
NF00050017
160
62.3%
34.8%
4.78
50377
Gallus Gallus
P32882
TBB2_CHICK
-
169
64.1%
43.3%
5.00
46256
Gallus Gallus
-
-
21703694
nuclear calmodulin-binding protein
h)
heat shock protein 90
heat shock 70kDa protein 5 (glucose-regulated
protein, 78kDa)
Guanine nucleotide-binding protein G(q), alpha
subunit
cognin/prolyl-4-hydroxylase/protein disulfide
isomerase
8
52138699 tubulin, beta 2
9
71575
tubulin alpha chain - chicken (fragment)
227
Mizuhopecten
yessoensis
63070
unnamed protein product
NF00047000
169
64.1%
43.2%
4.96
46385
Gallus Gallus
P02552
TBA1_CHICK
NF01957260
80
72.1%
18.2%
5.55
48372
Gallus Gallus
-
-
10
50755475 PREDICTED: similar to unc-84 homolog A
11
45382339 chromatin assembly factor 1 p48 subunit
NF00050581
100
58.2%
23.1%
4.74
47862
Gallus Gallus
Q9W7I5
Q9W7I5
12
50732409 PREDICTED: similar to vimentin - chicken
NF01955811
83
86.0%
22.2%
5.24
53178
Gallus Gallus
-
-
-
82
86.0%
22.2%
5.09
53167
Gallus Gallus
P09654
VIME_CHICK
NF01959240
150
73.6%
34.4%
5.16
50476
Gallus Gallus
Q9PTY0
ATPB_CYPCA
138533
Vimentin
PREDICTED: similar to ATP synthase beta chain,
13
50804057
14
50732728 similar to Secernin 1
NF01954659
136
87.3%
21.0%
4.86
69846
Gallus Gallus
-
-
15
45382393 gamma-subunit of enolase
NF00048684
232
93.2%
59.2%
4.84
47621
Gallus Gallus
O57391
ENOG_CHICK
16
45382393 gamma-subunit of enolase
NF00048684
232
83.9%
58.3%
4.84
47621
Gallus Gallus
O57391
ENOG_CHICK
17
53130278 hypothetical protein
NF02010384
148
83.2%
35.5%
5.59
56650
Gallus Gallus
Q5ZLC5
Q5ZLC5
NF01959240
137
72.1%
36.6%
5.16
50476
Gallus Gallus
-
-
NF01955811
234
79.3%
52.1%
5.24
53178
Gallus Gallus
-
-
-
218
82.7%
50.7%
5.09
53167
Gallus Gallus
P09654
VIME_CHICK
NF00046560
117
94.2%
33.8%
4.8
33115
Gallus Gallus
P50890
RSSA_CHICK
-
126
85.0%
39.0%
5.08
40352
Gallus Gallus
P53478
ACT5_CHICK
NF00050094
92
82.6%
19.7%
4.66
32840
Gallus Gallus
P16039
NPM_CHICK
NF01954408
136
51.2%
30.4%
5.15
38942
Gallus Gallus
P08239
GB01_BOVIN
NF00047962
94
80.2%
34.2%
6.41
12924
Gallus Gallus
Q9I895
Q9I895
NF00048773
86
80.2%
25.7%
6.18
17072
Gallus Gallus
P31395
STN1_CHICK
50804057
18
mitochondrial precursor, partial
PREDICTED: similar to ATP synthase beta chain,
mitochondrial precursor, partial
50732409 PREDICTED: similar to vimentin - chicken
138533
Vimentin
37kD Laminin receptor precursor /p40 ribosomal
19
1149509
20
86169
21
45383996 nucleophosmin; nucleolar phosphoprotein B23
22
50753611
23
7960152
associated protein
actin type 5, cytosolic
PREDICTED: similar to guanine nucleotide binding
protein alpha oB
leukemia-associated phosphoprotein p18
50053682 stathmin
228
PREDICTED: similar to Werner helicasae
24
50734127 interacting protein 1; Werner syndrome homolog
NF01956527
82
67.0%
16.2%
7.88
62108
Gallus Gallus
-
-
NF01961108
128
20.4%
31.9%
4.6
23164
Gallus Gallus
P08082
CLCB_RAT
NF01957009
97
69.7%
35.3%
4.67
29322
Gallus Gallus
P62258
143E_HUMAN
NF01957009
143
72.7%
49.0%
4.67
29322
Gallus Gallus
P62258
143E_HUMAN
NF02011439
123
67.5%
47.8%
4.68
28050
Gallus Gallus
Q5ZKC9
Q5ZKC9
NF00511802
125
67.5%
47.8%
4.69
28046 Mus musculus
P68254
143T_MOUSE
NF01949829
90
54.6%
9.3%
5.29
101356 Gallus Gallus
P61981
143G_HUMAN
-
172
83.6%
47.2%
4.75
28272
Bos taurus
P61981
143G_HUMAN
NF01947409
112
74.3%
26.7%
4.93
28691
Gallus Gallus
Q5ZLI2
Q5ZLI2
(human) interacting protein
PREDICTED: similar to clathrin, light polypeptide
25
50754937
26
50758188
27
50758188
28
53131390 hypothetical protein
isoform a; clathrin light chain LCB
PREDICTED: similar to epsilon isoform of 14-3-3
protein
PREDICTED: similar to epsilon isoform of 14-3-4
protein
tyrosine 3-monooxygenase/tryptophan
6756039
5-monooxygenase activation protein, theta
polypeptide
PREDICTED: similar to
3-monooxgenase/tryptophan 5-monooxygenase
29
50758472
activation protein, gamma polypeptide; tyrosine
3-monooxygenase/tryptophan 5-monooxygenase
activation protein, gamma polypeptide; 14-3-3
protein gamma
108451
14-3-3 protein - bovine
hypothetical protein: PREDICTED: similar to
30
53129746
Proteasome subunit alpha type 3 (Proteasome
component C8) (Macropain subunit C8)
(Multicatalytic endopeptidase complex subunit C8)
31
45384332 Calretinin
NF00048535
158
85.2%
55.0%
5.10
31171
Gallus Gallus
P07090
CLB2_CHICK
32
46048866 peptide elongation factor 1-beta
NF00050035
95
80.8%
24.2%
4.54
24860
Gallus Gallus
Q9YGQ1
Q9YGQ1
229
PREDICTED: similar to 14-3-3 protein beta/alpha
33
50758681 (Protein kinase C inhibitor protein-1) (KCIP-1)
NF01961224
190
100.0%
39.2%
4.82
32369
Gallus Gallus
P68251
143B_SHEEP
-
107
89.9%
36.1%
4.91
26443
Gallus Gallus
-
-
45382251 ubiquitin carboxyl-terminal hydrolase-6
NF00048819
83
71.1%
27.4%
4.91
26469
Gallus Gallus
Q9PW67
Q9PW67
35
53126513 hypothetical protein
NF02011138
86
81.4%
34.8%
5.22
23317
Gallus Gallus
Q5ZMT1
Q5ZMT1
36
481203
-
118
77.0%
42.6%
5.29
28835
Gallus Gallus
P60878
SN25_CHICK
37
45382893 CaBP-28
NF00050040
168
90.3%
47.7%
4.72
30376
Gallus Gallus
P04354
CABV_CHICK
38
50807165
NF01963032
102
63.5%
33.8%
4.75
23632
Gallus Gallus
P28066
PSA5_HUMAN
NF01956387
88
47.5%
49.5%
4.16
11817
Gallus Gallus
P63103
143Z_BOVIN
NF00112272
131
83.2%
33.2%
4.8
25198 Homo sapiens
P63012
RB3A_RAT
NF01951706
88
76.4%
14.3%
5.46
44753
Gallus Gallus
-
-
-
156
92.2%
31.7%
5.45
28790
Gallus Gallus
P08250
APA1_CHICK
NF00048630
102
78.4%
36.6%
4.9
19689
Gallus Gallus
P43347
TCTP_CHICK
-
127
96.5%
53.6%
5.01
22611
Gallus Gallus
-
-
45382903 calcium binding protein
NF00050222
127
96.5%
53.6%
5.01
22621
Gallus Gallus
P22728
VISI_CHICK
44
45382773 beta-synuclein
NF00047770
192
99.0%
54.1%
4.38
14054
Gallus Gallus
Q9I9G9
Q9I9G9
45
6440479
NF00126893
70
78.5%
27.2%
5.23
22293 Homo sapiens
-
-
(Protein 1054)
34
7522621
ubiquitin carboxy-terminal hydrolase-6 (EC 3.1.-.-)
SNAP-25 protein
PREDICTED: similar to zeta proteasome chain;
PSMA5, partial
PREDICTED: similar to tyrosine
39
50809985 3-monooxygenase/tryptophan 5-monooxygenase
activation protein, zeta polypeptide, partial
40
7689363
50751596
41
227016
42
45382329
43
86482
GTP-binding protein RAB3A
PREDICTED: similar to RAB3C, member RAS
oncogene family
apolipoprotein AI
growth-related translationally controlled tumor
protein
visinin - chicken
hippocalcin-like protein 3
230
46
45384366 calmodulin
NF00049513
93
54.3%
45.6%
4.1
16842
Gallus Gallus
O93410
O93410
47
50797888 PREDICTED: similar to valosin precursor, partial
NF01959101
181
91.2%
29.8%
4.93
56857
Gallus Gallus
P55072
TERA_HUMAN
48
50746361
NF01963408
89
71.2%
9.1%
7.80
127677 Gallus Gallus
-
-
49
50750447
NF01956159
75
84.5%
15.6%
5.11
68758
Gallus Gallus
Q13409
DYI2_HUMAN
50
50747380
NF01953040
98
89.8%
15.0%
5.53
81689
Gallus Gallus
-
-
51
45384386 homogenin
NF00048747
90
76.5%
14.8%
5.93
86120
Gallus Gallus
O93510
GELS_CHICK
50748790 PREDICTED: similar to heat shock protein 70
NF01301536
74
72.8%
12.9%
5.66
70098
Gallus Gallus
Q7SX63
Q7SX63
52
45383179 collapsin response mediator protein-1B
NF01548233
77
81.2%
18.7%
6.58
62766
Gallus Gallus
Q71SG3
Q71SG3
53
24234686 heat shock 70kDa protein 8 isoform 2
NF00123249
99
85.7%
23.1%
5.62
53598 Homo sapiens
-
-
45384370 heat shock cognate 70
NF00048173
74
71.1%
15.8%
5.47
71011
Gallus Gallus
O73885
O73885
NF01962763
73
84.7%
12.8%
6.18
78755
Gallus Gallus
-
-
NF01962981
89
100.0%
7.9%
7.14
142786 Gallus Gallus
P41250
SYG_HUMAN
NF01962060
176
100.0%
14.7%
9.11
126242 Gallus Gallus
P18708
NSF_CRIGR
NF00048173
88
46.2%
20.1%
5.47
70783
O73885
O73885
PREDICTED: similar to Osmotic stress protein 94
(Heat shock 70-related protein APG-1)
PREDICTED: similar to cytoplasmic dynein
intermediate chain 2C
PREDICTED: similar to Mitochondrial inner
membrane protein (Mitofilin) (p87/89)
PREDICTED: similar to NADH dehydrogenase
(ubiquinone) Fe-S protein 1, 75kDa precursor;
54
50750318
NADH dehydrogenase (ubiquinone), Fe-S
protein-1(75kD); NADH-coenzyme Q reductase;
complex I, mitochondrial respiratory chain, 75-kD
subunit; NADH dehydrogenase (ubiquinone...
55
50732627
56
50760643
57
2996407
PREDICTED: similar to Glycyl-tRNA synthetase
(Glycine--tRNA ligase) (GlyRS)
PREDICTED: similar to N-ethylmaleimide sensitive
fusion protein
heat shock cognate 70
231
Gallus Gallus
similar to Stress-70 protein, mitochondrial
58
57524986
precursor (75 kDa glucose regulated protein) (GRP
-
170
92.0%
28.3%
6.09
73432
Gallus Gallus
-
-
53127632 hypothetical protein
NF02011052
170
92.0%
28.3%
6.09
73432
Gallus Gallus
Q5ZM98
Q5ZM98
882147
NF00049381
164
100.0%
25.2%
5.96
62619
Gallus Gallus
Q90635
DPY2_CHICK
33340025 collapsin response mediator protein-2B
NF01548244
164
100.0%
25.2%
6.05
62691
Gallus Gallus
Q71SG1
Q71SG1
60
37590083 heat shock protein Hsp70
NF01301536
105
76.4%
17.7%
5.66
70098
Gallus Gallus
Q7SX63
Q7SX63
61
882147
NF00049381
84
100.0%
18.4%
5.96
62691
Gallus Gallus
Q90635
DPY2_CHICK
NF01548244
84
100.0%
18.4%
6.05
62619
Gallus Gallus
Q71SG1
Q71SG1
NF01962816
87
90.1%
16.1%
5.83
68334
Gallus Gallus
-
-
NF01950044
139
85.1%
39.2%
5.53
60190
Gallus Gallus
-
-
75) (Peptide-binding protein 74) (PBP74) (Mortalin)
(MOT)
59
CRMP-62
CRMP-62
33340025 collapsin response mediator protein-2B
PREDICTED: similar to Lysyl-tRNA synthetase
62
50754075
63
50734929
64
50741749 PREDICTED: similar to t-complex polypeptide 1
NF01947807
126
82.1%
28.9%
5.50
61057
Gallus Gallus
-
-
65
882147
NF00708442
137
93.9%
24.3%
5.96
62691
Gallus Gallus
Q53837
Q53837
33340025 collapsin response mediator protein-2B
NF01548244
137
93.9%
24.3%
6.05
62619
Gallus Gallus
Q71SG1
Q71SG1
882147
NF00049381
298
94.9%
62.2%
5.96
62691
Gallus Gallus
Q90635
DPY2_CHICK
NF01548244
298
94.9%
62.2%
6.05
62619
Gallus Gallus
Q71SG1
Q71SG1
NF01958869
126
69.6%
24.5%
6.36
58008
Gallus Gallus
Q5ZJ54
Q5ZJ54
NF01096103
138
90.5%
25.5%
5.76
56546
Gallus Gallus
Q8JG64
Q8JG64
66
(Lysine--tRNA ligase) (LysRS)
PREDICTED: similar to Hypothetical protein
MGC76252
CRMP-62
CRMP-62
33340025 collapsin response mediator protein-2B
PREDICTED: similar to chaperonin containing
67
50758158 TCP1, subunit 6A (zeta 1); chaperonin containing
T-complex subunit 6
58kDa glucose regulated protein precursor;
68
45383890 1,25D3-MARRS protein;
1,25D3-membrane-associated, rapid-response
232
steroid-binding protein; glucose regulated thiol
oxidoreductase protein
69
37695552 annexin 2
70
882147
CRMP-62
NF01442401
136
63.0%
39.2%
6.92
38915 Canis familiaris
Q6TEQ7
Q6TEQ7
NF00049381
78
88.1%
13.1%
5.96
62691
Gallus Gallus
Q90635
DPY2_CHICK
33340025 collapsin response mediator protein-2B
NF01548244
78
88.1%
13.1%
6.05
62619
Gallus Gallus
Q71SG1
Q71SG1
71
45383538 malic enzyme 1, NADP(+)-dependent, cytosolic
NF00775272
100
72.4%
35.0%
6.45
62531
Gallus Gallus
Q90XC0
Q90XC0
72
53130384 hypothetical protein
NF02010491
140
89.9%
33.9%
5.72
61105
Gallus Gallus
Q5ZL72
Q5ZL72
NF01952005
92
51.2%
28.0%
5.06
48043
Gallus Gallus
-
-
PREDICTED: similar to 60 kDa heat shock protein,
mitochondrial precursor (Hsp60) (60 kDa
50750210 chaperonin) (CPN60) (Heat shock protein 60)
(HSP-60) (Mitochondrial matrix protein P1) (P60
lymphocyte protein) (HuCHA60)
73
33340023 collapsin response mediator protein-2A
NF01548252
210
76.3%
39.2%
6.03
73395
Gallus Gallus
Q71SG2
Q71SG2
74
45383890 58kDa glucose regulated protein precursor
NF01096103
209
92.8%
43.2%
5.76
56146
Gallus Gallus
Q8JG64
Q8JG64
75
50747490 subunit (TCP-1-eta) (CCT-eta) (HIV-1 Nef
NF01955500
129
77.3%
32.8%
5.58
53908
Gallus Gallus
Q99832
TCPH_HUMAN
NF00047224
227
91.6%
52.9%
5.23
51107
Gallus Gallus
O93382
O93382
NF01955352
259
88.0%
51.0%
5.34
55045
Gallus Gallus
-
-
NF00050299
255
96.0%
48.8%
5.50
55357
Gallus Gallus
Q9I8A2
Q9I8A2
NF01955352
277
94.8%
60.7%
5.34
54703
Gallus Gallus
-
-
NF00050299
273
94.8%
60.5%
5.50
55015
Gallus Gallus
Q9I8A2
Q9I8A2
PREDICTED: similar to T-complex protein 1, eta
interacting protein)
76
77
45384364 Rab-GDP dissociation inhibitor
50806920
8163560
78
50806920
8163560
PREDICTED: similar to adenosinetriphosphatase
(EC 3.6.1.3) B chain - chicken
vacuolar H-ATPase B subunit osteoclast isozyme
PREDICTED: similar to adenosinetriphosphatase
(EC 3.6.1.3) B chain - chicken
vacuolar H-ATPase B subunit osteoclast isozyme
233
1085256
adenosinetriphosphatase (EC 3.6.1.3) B chain
-
273
94.8%
59.6%
5.50
55600
Gallus Gallus
-
-
NF01954798
116
26.2%
37.7%
5.64
47467
Gallus Gallus
P61979
ROK_MOUSE
NF01028477
76
100.0%
11.9%
9.5
51103
Gallus Gallus
Q8JIF5
Q8JIF5
NF01951848
117
58.4%
22.1%
6.01
57794 Homo sapiens
P78371
TCPB_HUMAN
NF01954798
127
47.8%
35.6%
5.64
47467
Gallus Gallus
P61979
ROK_MOUSE
NF01957184
111
44.4%
35.6%
5.64
42666
Gallus Gallus
P61980
ROK_MOUSE
NF02010807
130
84.8%
31.1%
6.02
50563
Gallus Gallus
Q5ZIC4
Q5ZIC4
-
151
83.9%
20.4%
4.78
50333
Gallus Gallus
P09203
TBB1_CHICK
NF00050017
"
83.9%
20.4%
4.78
50377
Gallus Gallus
P32882
TBB2_CHICK
-
128
64.9%
33.3%
6.17
47617
Gallus Gallus
P51913
ENOA_CHICK
NF00050013
72
62.8%
17.1%
6.17
47617
Gallus Gallus
P51913
ENOA_CHICK
-
115
75.0%
40.8%
6.17
47617
Gallus Gallus
P51913
ENOA_CHICK
-
124
71.4%
36.9%
6.17
47617
Gallus Gallus
P51913
ENOA_CHICK
PREDICTED: similar to heterogeneous nuclear
79
50762370 ribonucleoprotein K isoform a; dC-stretch binding
protein; transformation upregulated nuclear protein
80
22093559 E. coli Ras-like protein homologue
PREDICTED: similar to chaperonin containing
81
50728322 TCP1, subunit 2 (beta); chaperonin containing
t-complex polypeptide 1, beta subunit
PREDICTED: similar to heterogeneous nuclear
82
50762370 ribonucleoprotein K isoform a; dC-stretch binding
protein; transformation upregulated nuclear protein
PREDICTED: similar to heterogeneous nuclear
50800999 ribonucleoprotein K isoform a; dC-stretch binding
protein; transformation upregulated nuclear protein
83
53136380 hypothetical protein
84
2119277
beta-1 tubulin - chicken
52138699 tubulin, beta 2
Alpha enolase (2-phospho-D-glycerate
85
1706653
86
46048768 enolase
87
1706653
88
1706653
hydro-lyase) (Phosphopyruvate hydratase)
Alpha enolase (EC 4.2.1.11)
Alpha enolase (2-phospho-D-glycerate
hydro-lyase) (Phosphopyruvate hydratase)
234
89
1706653
90
Alpha enolase (2-phospho-D-glycerate
193
75.3%
47.9%
6.17
47617
Gallus Gallus
P51913
ENOA_CHICK
50746016 PREDICTED: similar to septin 6 isoform D; septin 2 NF01952054
105
92.8%
25.5%
6.53
49274
Gallus Gallus
-
-
91
8922712
septin 11
NF00131357
112
53.3%
33.3%
6.36
49367 Homo sapiens
Q9NVA2
SE11_HUMAN
92
211235
B-creatine kinase
NF00046968
130
87.9%
33.8%
5.78
42525
Gallus Gallus
P05122
KCRB_CHICK
93
211235
B-creatine kinase
NF00046968
135
56.7%
34.8%
5.78
42525
Gallus Gallus
-
-
-
134
56.7%
34.5%
5.93
42998
Gallus Gallus
-
-
NF00047182
133
56.7%
34.4%
5.93
43129
Gallus Gallus
P05122
KCRB_CHICK
-
87
55.7%
20.5%
5.93
42998
Gallus Gallus
-
-
NF00047182
87
55.7%
20.5%
5.93
43129
Gallus Gallus
P05122
KCRB_CHICK
-
207
86%
46.8%
5.93
42998
Gallus Gallus
-
-
NF00047182
205
85.8%
46.7%
5.93
43129
Gallus Gallus
P05122
KCRB_CHICK
NF01958761
92
88.6%
15.6%
8.80
77766
Gallus Gallus
-
-
6573492
hydro-lyase) (Phosphopyruvate hydratase)
Chain D, Crystal Structure Of Chicken Brain-Type
Creatine Kinase At 1.41 Angstrom Resolution
45384340 B-creatine kinase
94
6573492
Chain D, Crystal Structure Of Chicken Brain-Type
Creatine Kinase At 1.41 Angstrom Resolution
45384340 B-creatine kinase
95
6573492
Chain D, Crystal Structure Of Chicken Brain-Type
Creatine Kinase At 1.41 Angstrom Resolution
45384340 B-creatine kinase
PREDICTED: similar to adenine homocysteine
-
96
50758593
97
226855
aldolase C
-
105
64.4%
26.3%
5.79
39023
Gallus Gallus
-
-
98
226855
aldolase C
-
84
47.2%
36.6%
5.78
39023
Gallus Gallus
P53449
ALFC_CHICK
99
226855
aldolase C
-
124
57.4%
29.3%
5.79
39023
Gallus Gallus
P53449
ALFC_CHICK
100 226855
aldolase C
-
139
58.9%
51.1%
5.79
39023
Gallus Gallus
P53449
ALFC_CHICK
NF00050473
137
60.7%
26.0%
6.38
42747
Gallus Gallus
P16580
GLNA_CHICK
hydrolase
101 45382781 Glutamine synthetase
235
102 45383392 dimethylarginine dimethylaminohydrolase 1
NF01301538
115
51.0%
33.1%
5.44
31674
Gallus Gallus
Q7ZTS9
Q7ZTS9
103 164543
NF00149009
85
76.0%
27.7%
6.15
31978
Sus scrofa
-
-
NF02011213
96
85.1%
17.3%
7.60
40727
Gallus Gallus
Q5ZI29
Q5ZI29
NF01953996
94
85.1%
17.6%
7.50
51868
Gallus Gallus
-
-
NF00046938
112
100.0%
31.3%
5.74
33978
Gallus Gallus
Q9IAY5
Q9IAY5
NF01955415
110
55.2%
41.6%
5.41
33649
Gallus Gallus
Q9H115
SNAB_HUMAN
NF01950687
161
86.4%
49.7%
6.6
36690
Gallus Gallus
-
-
NF01951415
117
62.4%
35.9%
5.60
38121
Gallus Gallus
P79959
GBB1_XENLA
-
111
75.5%
25.7%
5.69
30820
Gallus Gallus
-
-
malate dehydrogenase (EC 1.1.1.37)
104 53136570 hypothetical protein
50752793
PREDICTED: similar to isocitrate dehydrogenase 3
(NAD+) alpha
105 45382147 syndesmos
PREDICTED: similar to N-ethylmaleimide sensitive
106 50738541
fusion protein attachment protein beta; brain
protein I47; brain protein 14; beta-soluble NSF
attachment protein
107 50749280
108 50759201
109 1079456
PREDICTED: similar to heterogeneous nuclear
ribonucleoprotein H3 isoform a
PREDICTED: similar to beta 1 subunit of
heterotrimeric GTP-binding protein
actin-capping protein beta chain, splice form 2
NF00048709
110
75.5%
25.3%
5.36
31573
Gallus Gallus
P14315
CAPB_CHICK
110 50730066 PREDICTED: similar to pyridoxal kinase, partial
45382141 actin-capping protein Z (cap-Z) beta subunit
NF01952121
77
100.0%
25.1%
5.68
31611
Gallus Gallus
-
-
111 50730861 PREDICTED: similar to esterase D
NF01959074
76
84.6%
23.7%
6.13
28345
Gallus Gallus
-
-
NF01950883
108
84.8%
16.4%
9.96
67972
Gallus Gallus
-
-
NF01951415
213
94.2%
51.9%
5.23
36682
Gallus Gallus
-
-
NF01955415
195
96.3%
56.8%
5.41
33647
Gallus Gallus
Q9H115
SNAB_HUMAN
112 50738978
PREDICTED: similar to Malate dehydrogenase,
cytoplasmic
113 50753091 PREDICTED: similar to Rlbp1-prov protein
PREDICTED: similar to N-ethylmaleimide sensitive
114 50738541
fusion protein attachment protein beta; brain
protein I47; brain protein 14; beta-soluble NSF
attachment protein
236
115 50755699 PREDICTED: similar to RIKEN cDNA 1700012G19 NF01957150
97
54.6%
37.9%
4.43
22956
Gallus Gallus
-
-
116 1079456
-
72
50.0%
25.7%
5.69
30820
Gallus Gallus
-
-
NF00048709
71
50.0%
25.3%
5.36
31573
Gallus Gallus
P14315
CAPB_CHICK
NF00290512
78
77.8%
20.5%
6.35
53839
O16672
O16672
NF01962011
131
97.2%
16.2%
10.03
101893 Gallus Gallus
P21796
POR1_HUMAN
NF01951594
127
49.3%
30.6%
6.00
30640
Gallus Gallus
-
-
NF00048214
81
100.0%
21.9%
6.08
29192
Gallus Gallus
O42265
PSA1_CHICK
NF01951985
78
92.4%
39.4%
5.79
26904
Gallus Gallus
-
-
NF01957940
102
37.8%
62.8%
8.94
23552
Gallus Gallus
P18669
PMG1_HUMAN
NF00049577
111
93.3%
36.9%
6.65
28361
Gallus Gallus
-
-
NF00046508
"
93.3%
36.3%
6.51
28823
Gallus Gallus
-
-
NF00048355
"
93.3%
35.8%
6.56
29388
Gallus Gallus
P07630
CAH2_CHICK
NF00046508
146
89.6%
57.8%
6.51
28823
Gallus Gallus
-
-
NF00048355
145
89.6%
56.9%
6.56
28989
Gallus Gallus
P07630
CAH2_CHICK
NF00046508
161
88.6%
67.2%
6.51
28823
Gallus Gallus
-
-
actin-capping protein beta chain, splice form 2
45382141 actin-capping protein Z (cap-Z) beta subunit
117 17560844 cytochrome p450 2N1 family member (5C726)
Caenorhabditis
elegans
PREDICTED: similar to Voltage-dependent
118 50755168
anion-selective channel protein 1 (VDAC-1)
(hVDAC1) (Outer mitochondrial membrane protein
porin 1) (Plasmalemmal porin)
119 50750103
PREDICTED: similar to methyltransferase 24 (37.8
kD) (3D495)
120 45384316 20S proteasome subunit C2
121 50760138
122 50749899
123 1334630
833606
PREDICTED: similar to Platelet-activating factor
acetylhydrolase, isoform 1b, alpha2 subunit
PREDICTED: similar to phosphoglycerate mutase
(EC 5.4.2.1) B chain - rat
unnamed protein product
carbonic anhydrase II (256 AA) (1 is 2nd base in
codon)
46048696 Carbonic anhydrase II
124 833606
carbonic anhydrase II (256 AA) (1 is 2nd base in
codon)
46048696 carbonic anhydrase II
125 833606
carbonic anhydrase II (256 AA) (1 is 2nd base in
codon)
237
46048696 carbonic anhydrase II
NF00048355
161
88.6%
66.2%
6.56
28989
Gallus Gallus
P07630
CAH2_CHICK
NF02011821
94
100.0%
20.8%
5.56
26311
Gallus Gallus
Q5ZJY1
Q5ZJY1
NF01961051
114
73.9%
38.2%
8.29
29251
Gallus Gallus
-
-
128 45382455 CLE7 protein
NF00048369
169
88.3%
53.6%
6.01
27486
Gallus Gallus
Q90706
Q90706
129 53133620 hypothetical protein
NF02011536
141
49.6%
45.1%
5.72
25075
Gallus Gallus
Q5ZJF4
Q5ZJF4
NF01961736
114
75.6%
37.0%
6.13
27852
Gallus Gallus
-
-
NF02011849
165
88.0%
48.8%
7.03
29051
Gallus Gallus
Q5ZLN1
Q5ZLN1
NF01957940
95
41.5%
38.6%
8.94
23552
Gallus Gallus
-
-
NF01564848
74
75.4%
21.3%
7.07
28828 Homo sapiens
Q6P6D7
Q6P6D7
NF01838762
"
75.4%
21.3%
6.67
28814 Homo sapiens
Q6FHK8
Q6FHK8
NF00048136
74
100.0%
20.6%
6.47
39145
Gallus Gallus
O02869
O02869
134 50732619 PREDICTED: similar to Guk1 protein
NF01960322
105
23.3%
22.2%
6.39
45731
Gallus Gallus
-
-
135 45382061 Triosephosphate isomerase
NF00049179
131
72.3%
39.1%
6.71
26832
Gallus Gallus
P00940
TPIS_CHICK
136 45382061 Triosephosphate isomerase
NF00049179
175
84.4%
49.6%
6.71
26832
Gallus Gallus
P00940
TPIS_CHICK
NF01958258
76
76.8%
33.8%
6.17
24486
Gallus Gallus
-
-
NF00047871
83
79.9%
31.1%
4.72
19525
Gallus Gallus
P02604
MLE1_CHICK
NF00050313
74
94.1%
14.6%
5.98
23678
Gallus Gallus
Q90965
Q90965
126 53133098 hypothetical protein
127 50751030
PREDICTED: similar to non-selenium glutathione
phospholipid hydroperoxide peroxidase
PREDICTED: similar to Proteasome subunit alpha
130 50748430
type 6 (Proteasome iota chain) (Macropain iota
chain) (Multicatalytic endopeptidase complex iota
chain)
131 53129115 hypothetical protein
50749899
PREDICTED: similar to phosphoglycerate mutase
(EC 5.4.2.1) B chain - rat
132 38566176 Phosphoglycerate mutase 1
49456447 PGAM1
133 1945745
137 50730713
138 212347
chLAMP, g11-isoform
PREDICTED: similar to DNA segment, Chr 10,
Johns Hopkins University 81 expressed
myosin a1 light chain (partial)
139 45382561 GTP-binding protein
238
140 50740506 PREDICTED: similar to glyoxylase 1; glyoxalase 1
NF01959509
113
70.8%
31.1%
6.1
20654
Gallus Gallus
-
-
141 50740506 PREDICTED: similar to glyoxylase 1; glyoxalase 1
NF01959509
147
79.4%
52.8%
6.1
20654
Gallus Gallus
-
-
142 20380955 Pitpnc1 protein
NF01009299
87
68.3%
60.6%
8.82
11315 Mus musculus
Q8K165
Q8K165
NF01951144
77
83.5%
19.4%
9.18
35325
Gallus Gallus
-
-
NF01959509
111
92.4%
42.2%
6.10
20654
Gallus Gallus
-
-
NF01959340
145
100.0%
41.8%
5.55
17440
Gallus Gallus
-
-
-
98
79.2%
57.9%
5.63
18846
Bos taurus
P84077
ARF1_HUMAN
NF02011224
94
79.2%
52.5%
6.84
20850
Gallus Gallus
Q5ZMA0
Q5ZMA0
-
89
75.4%
45.1%
5.63
18846
Bos taurus
P84077
ARF1_HUMAN
NF02011224
85
75.4%
45.1%
6.84
20850
Gallus Gallus
Q5ZMA0
Q5ZMA0
NF00050525
105
52.8%
43.6%
7.52
18920
Gallus Gallus
P18359
DEST_CHICK
-
85
78.8%
35.3%
6.12
15834
Gallus Gallus
-
-
150 56961659 eye-globin
NF02189843
111
60.6%
39.7%
5.48
17353
Gallus Gallus
-
Q5QRU6
151 45384320 cl. 453 fatty acid or lipid binding protein
NF00049646
139
93.7%
72.0%
5.62
14900
Gallus Gallus
Q05423
FABB_CHICK
152 45382717 protein kinase C inhibitor
NF00047299
99
67.8%
56.3%
6.28
13864
Gallus Gallus
-
Q9I882
PREDICTED: similar to Proteasome subunit beta
143 50759776
type 2 (Proteasome component C7-I) (Macropain
subunit C7-I) (Multicatalytic endopeptidase
complex subunit C7-I)
144 50740506 PREDICTED: similar to glyoxylase 1; glyoxalase 1
145 50745407
PREDICTED: similar to nucleoside diphosphate
kinase
Chain A, Arf1[delta1-17]-Gdp In Complex With A
146 42543522 Sec7 Domain Carrying The Mutation Of The
Catalytic Glutamate To Lysine.
53127520 hypothetical protein
Chain A, Arf1[delta1-17]-Gdp In Complex With A
147 42543522 Sec7 Domain Carrying The Mutation Of The
Catalytic Glutamate To Lysine.
53127520 hypothetical protein
148 45382979 destrin; actin depolymerizing factor
149 2134412
superoxide dismutase (EC 1.15.1.1) (Cu-Zn) chicken
239
153 45383752 creatine kinase, mitochondrial 1
NF00048372
158
88.7%
33.3%
8.74
47473
Gallus Gallus
P70079
KCRU_CHICK
NF00047022
146
85.8%
39.2%
6.77
40774
Gallus Gallus
-
-
154 45384486 PGK protein
NF00048094
105
90.7%
20.6%
8.31
45087
Gallus Gallus
P51903
PGK_CHICK
155 45384208 lactate dehydrogenase A
NF00046645
203
95.7%
41.0%
7.75
36776
Gallus Gallus
P00340
LDHA_CHICK
1545942
a)
mitochondrial creatine kinase
The GI number (GenInfo Identifier) is assigned to each nucleotide and protein sequence accessible through the The National Center
for Biotechnology Information search systems.
b)
The PIR (Protein Information Resource) is a non-redundant reference protein
database located at Georgetown University Medical Centre. c) Score for the protein with significant match calculated by Mowse scoring
algorithm in the Mascot system. d & e) Theoretical values of the isoelectric point and molecular weight obtained in the database search
using Mascot system. f) The species identified with significant score for a particular protein. g) SwissProt is a protein knowledgebase
maintained collaboratively by the Swiss Institute of Bioinformatics and the The European Bioinformatics Institute; TrEMBL is a
computer-annotated supplement of Swiss-Prot that contains all the translations of EMBL nucleotide sequence entries not yet integrated
in Swiss-Prot. h) The UniProt (Universal Protein Resource) is a comprehensive catalog of protein information created by the consortium
members PIR, European Bioinformatics Institute and Swiss Institute of Bioinformatics.
240
APPENDIX 3.
z Peptide Mass Fingerprinting results (PMF) of the differentially expressed
proteins involving in the normal chick eye growth (Chapter 6.2.3)
(#D1) Apolipoprotein AI (Apo-AI)
241
242
243
(#D3) Fatty acid-binding protein, retina. R-FABP
244
245
246
(#U2a & b) Phosphoglycerate mutase type B subunit. PGM-type B
247
248
249
(#U1)
Glyoxalase I
250
251
(#U3)
Destrin
252
253
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