MALDI-TOF MS - Nordwestschweiz

Identifikation von Mikroorganismen mittels
MALDI-TOF Massenspektrometrie Schnelle und günstige Charakterisierung von
Bakterien und Pilzen
5. November, 2011
Basel
Valentin Pflüger
Guido Vogel
Dominik Ziegler
André Strauss
Bernard Jenni
Identification of biological systems
morphology
immunological
Microscopy,
smell, color etc.
mono- or polyclonal
antibodies
ID
molecular
specific-PCR, 16S-Seq., RT-PCR
SNP, MLST, RFLP, VNTR, PFGE…
biochemical
metabolic capacities
1900
1950
2000
?
Modern approaches in taxonomy:
proteomics & genomics
protein
DNA
ID
genome
proteome
species
definition & determination
Vo y a g e r
0
3000
4 4 2 3 . 9 ,
2 1 1 7 ]
2117.3
9000
Mass (m/z)
10975.2
10493.9
10110.8
9611.5
8903.3
9075.2
12271.4
8054.3
8383.8
7000
8610.6
7424.9
7209.8
6629.0
6786.7
6984.6
6271.2
5897.8
5000
6137.3
4026.9
4535.6
30
4765.4 4738.6
40
6533.3
50
3132.3
3311.8
3491.4
% Intensity
60
10
=
8823.5
70
20
# 1 = > Ad v BC( 3 2 , 0 . 5 , 1 . 0 ) = > NF 0 . 7 [ BP
9476.2
4861.0
90
80
Sp e c
mass
fingerprint
4424.2
100
11000
13000
DNA
fingerprint
MALDI-TOF MS: history
Matrix Assisted Laser Desorption/Ionization Time-Of-Flight
Mass Spectrometry
developed in 1980‘s by Karas & Hillenkamp and Tanaka et al.
first commercial apparatus in 1991
MALDI-TOF MS
Matrix Assisted Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry
MALDI-TOF
Mass Spectrometry:
the MS
velocity of the ion
depends on the mass-to-charge (m/z) ratio
~ 200 cm
Time-Of-Flight: ions acceleration
(electric field) and time-of-flight to
the detector is recorded
Laser Desorption/Ionization:
matrix ionization (laser pulses) and
partial transfer of its (+) charge to the analytes
Matrix-Assisted:
sample embedded in a matrix,
Axima™ Confidence
avoid destruction
by the laser
facilitate vaporisation and ionization
Detector for linear
mode
IC-MALDI-TOF MS
24 mV[sum= 2382 mV] Profiles 1-100 Smooth Av 50
7154.3
%Int.
9490.6
mass ranges and applications
100
80
75
7274.3
4392.6
85
Intact Cell MALDI-TOF MS
Late 90`s
Direct application of whole cells
70
65
2000
3000
4000
5000
6000
7000
8000
9000
10000
11000
12000
13000
14000
15019.7
15371.3
14476.7
13610.6
14087.2
12218.7
0
12945.0
5
12425.0
11152.0
11784.6
10317.1
8940.5
9789.4
6487.1
6886.9
6109.2
5562.2
4131.3
4779.9
10
3574.5
15
2162.3
20
2607.6
25
3125.9
30
4743.5
35
9160.5
7252.3
40
8372.2
45
8107.4
50
7702.1
55
7236.7
6217.4
60
15000
16036.8
90
8267.7
5411.2
95
16000
17000
18000
19000
1[c].1K1
20000
DNA, fatty acids, sugars
metabolites
matrix
enzymes & enzyme complexes
structural proteins & polymers
0
m/z
reflector
100000
linear
IC-MALDI-TOF MS of bacteria
differences in peak patterns
Pantoea agglomerans
Acinetobacter lwoffi
04
z/m
08
Burkholderia cepacia
Raoultella ornithinolytica
Staphylococcus aureus
Escherichia coli
4000
m/z
8000
distinctly different peak patterns when analysing different taxa
Available commercial Systems
Workflow of AXIMA@SARAMIS™
Step 1 – Sample preparation: Smear-methode
FlexiMass-Target
with 48 positions
addition of 0.5 µl Matrix solution
colony selection and
transfer of cells
suitable for bacteria, yeasts and filamentous fungi
Workflow of AXIMA@SARAMIS™
Step 2 – Measurement
loading samples to
AXIMIA
FlexiMass target holder 4 X 48
8327
automated spectrum
acquisition ~20 sec
4161
5095
4363
5380
6254
4767
4183
3125 3635
3000
4000
7707
6315
5231
5000
5751
6410
6000
7157
7000
8351
9537
9555
7729
8000
m/z
8877
9452
9000
10466
10000
1[c].2B1
11000
12000
13000
Workflow of AXIMA@SARAMIS™
Step 3 – Identification with SuperSpectra
8327
4161
matching to SuperSpectra
5095
computing sum of peak weights
4363
5380
4767
4183
3125
3000
4000
6254
7707
6315
5231
5000
6410
6000
7157
7000
8351
9537
ranking
matching SuperSpectra
9555
7729
8000
m/z
10466
check
for
conflicting significant results
9452
8877
10000 result
11000 with
12000confidence
13000
delivering
value
9000
Workflow of AXIMA@SARAMIS™
Step 4 – Identification with SuperSpectra
10
49
6
7
81 975
61
85
88 77
1
91 3
09
96
34
73
71
68
20
6
61 13
65 9
55
35
44
04
32
56
36
85
relative intensity
51
45
Trichophyton_rubrum_1
Superspectrum
matching fingerprints of
two clinical isolates to
SuperSpectra
best match with
T. rubrum_1 SuperSpectrum
(containing 44 peaks):
# 539: 39 matches, Σ 1036 points
# 582: 37 matches, Σ 1011 points
539
582
3000
4600
6200
from Erhard et al. 2007, Exp. Dermatol.
m/z
7800
9400
11000
both isolates identified as
Trichophyton rubrum
with 99% confidence
Workflow of AXIMA@SARAMIS™
Step 5 Comparison tools
5263
7774
9638
8176
4086
3142
3000
3771
4000
4817
4469
6009
8792
6746
5709 6260 6788
5000
6000
7000
7545
8339 8962
7888
8000
m/z
comparison to mass spectral patterns
of reference spectra in the database
9000
9970
10219
10000
11000
12000
13000
cluster analysis of selected reference
and sample mass spectra
Evaluation of AXIMA@SARAMIS I
result summary
no spectrum: 1%
no identification: 3%
identification with
80-90% confidence: 6%
identification with
90-99% confidence: 90%
high hit rate in daily routine after a very short training phase
SARAMIS is readily applicable in routine analysis
Identification of different bacterial taxa
Cronobacter spp.
Identification of different bacterial taxa
Yersinia enterocolitica biotypes
MALDI-TOF MS: Plant pathogens
i
ic
t as
ma
nie
nsi
• rpsL gene: 30S S12 protein
ra
lo
tiv
o
E.
na
• Interventions with streptomycin
E.
m
al
rs
• Rosacea affected
pa
pa
ya
e
pe
E.
E.
• causative agent of fireblight
E. p
apay
ae
a
icol
phid
E. a
Erwinia amylovora
E. toletana
Erwinia ssp. identification
E
i
idi
s
.p
E . bi
s
e
llinga
E. piriflorinigrans
E. amylovora
e
rifolia
E. p y
0.08
MALDI-TOF MS: Erwinia amylovora
0.2 mV 0.3 mV
13635.0
%Int.
13607.0
rpsL allels for streptomycin resistance
100
95
90
100
85
95
80
70
13703.7
75
13354.2
85
S12, +28 Da,
Lysin→ Arginin
S12, wt
80
90
65
60
75
55
70
50
65
45
40
60
35
55
30
50
25
20
45
15
40
10
35
5
0
30
13200
13250
13300
13350
13400
13450
13500
13550
m/z
25
20
15
10
5
0
13600
13650
13700
13750
13800
13850
MALDI-TOF MS spectra database modules
Dermatophytes: clinical relevant species
Trichophyton ssp, Microsporum ssp.
24 species in module
based on ITS1 and 2 taxonomy
>85 % ID in clinical routine samples
M. fulvum
M. gypseum
M. persicolor
M. audouinii
M. canis
T. erinacei
M. praecox
T. terrestrae
M. racemosum
T. tonsurans
T. megnini
0.09
Microsporum ssp.
T. interdigitiale
T. violaceum
T. verucosum
T. rubrum
0.1
Trichophyton ssp.
MALDI-TOF MS spectra database modules
Clinical yeasts : Candida ssp.
34 Candida species in database
>90% ID in clinical routine samples
identification from positive blood cultures possible
MALDI-TOF MS spectra database modules
Environmental fungi: Air- Surface, and Food-samples
high species diversity…
classification of references
ID on genus level
focus on „relevant“ species
60% ID in indoor air samples
Penicillium ssp.
Fusarium ssp.
Aspergilllus ssp.
MALDI-TOF MS: differentiation of fungal species
Verticillium spp.
Verticillium tricorpus
Gibellulopsis nigrescens
Verticillium longisporum
Acrostalagmus luteoalbus
Musicillium theobromae
Verticillium albo-atrum
Plectosphaerella cucumerina
Verticillium dahliae
0.09
IC MALDI-TOF MS of cell-lines
Differentiation of cell-lines
Homo sapiens
NK3.3
WIL2S
• Identification of specific marker proteins
on the species level
Raji
Hela
CMT93
RAW264
Mus musculus
Spodoptera frungiperda
• Independent of passage number
and medium supplements
SF21
• Differentiation of lineages within
the same species
SF9
Trichoplusia ni
H5
Drosophila melanogaster
CRL1963
MALDI-TOF MS for the characterization of insects
Ceratopogonidae, Culicoides spp.(biting midges)
Vector for Bluetongue virus
Current Taxonomy/Identification
• Morphological and
• molecular (RT-PCR)
• Distinguish between sibling species of the fruit fly
Drosophila melanogaster (Campbell, 2005)
• Distinguish three species from three genera of
plant-sucking aphids (Perera et al, 2005)
• Establish phylogenetic relationships among
13 species of Drosophila flies (Feltens et al, 2010)
MALDI-TOF MS for characterization of insects
Ceratopogonidae, Culicoides spp.(biting midges)
C. obsoletus
Identification and discrimination of
14 Culicoides spp. was possible
C. scoticus
• Fast and reliable sample preparation
C. dewulfii
• Head-Thorax for MALDI-TOF MS
• Abdomen for multiplex PCR and further analysis
C. imicola
1-3 mm C. pulicaris
C. punctatus
MALDI-TOF MS: plant differentiation
Zea mays strain differentiation using disected and extracted embryos
relativ identity
Amadeo
LG 32.222
LG 32.12
268 mV[sum= 53693 mV] Profiles 1-200 Smooth Av 50
7483.9
%Int.
• disection of seed
• extraction of embryo
• acquisition of peptide
mass fingerprint
100
LG 32.20
Ricardinio
95
90
85
80
75
70
65
popcorn
7369.2
60
55
sweetcorn
16742.9
15422.4
16083.1
13432.0
13743.2
14012.9
12045.0
12456.0
10461.8
9557.4
8606.6
9066.0
8144.8
7420.1
6715.0
3788.4
15
7709.7
8029.7
20
3084.9
25
4055.5
30
4465.4
35
7310.6
5127.2
40
5856.6
6160.9
45
5497.6
5399.0
50
10
5
0
3000
4000
5000
6000
7000
8000
9000
10000
11000
12000
m/z
13000
14000
15000
16000
17000
18000
19000
20000
Peptide mass fingerprinting using MALDI-TOF MS
Take home message
• Peptide mass fingerprinting using MALDI-TOF MS is a valuable tool for the fast and
cost effective identification and characterization of diverse biological systems.
• Mabritec is a service provider and R&D partner in the field of MALDI-TOF mass
spectrometry and has an outstanding experience in applying this technology to a
wide range of biological questions.
Collaborators
Agroscope Changins Wädenswil
B. Duffy, J. Poithier, F. Rezzonico
Institut für Parasitologie Zürich
A. Mathis, C. Kaufmann, I. Steinmann
Swiss TPH
C. Lengeler, P. Müller
Agroscope Reckenholz Tänikon ART
Franco Widmer, Mireille Dessimoz
ABC Labor Spiez
N. Schürch, M. Wittwer
Instituto cantonale di Microbiologia
O. Petrini, M. Tonolla, Xavier Perret
Thank you…