Volume 1, Issue 1, November 2012

Transcription

International Journal of
Advanced Biotechnology
and Bioinformatics
Publisher
Delhi Technological University
Shahbad Daulatpur, Bawana Road
Delhi-110042, India
Website
www.ijabb.dce.edu
Chief Patron
Prof. P. B. Sharma
Editor-in-Chief
Prof. Samir K. Brahmachari
Executive Editor
Dr. Yasha Hasija
Aim and Scope
INTERNATIONAL JOURNAL OF ADVANCED BIOTECHNOLOGY & BIOINFORMATICS is an
online, freely available, peer reviewed journal that endeavors to rapidly publish
original, authentic and fundamental research papers, review articles, case studies and
short communications in all the spheres of biotechnology and bioinformatics. With
biotechnology transforming every sphere of our lives by its innovations, the journal
attempts to provide a platform to both academic and industrial laboratories to share
their research and provide useful insights. The emphasis is to capture the novel thoughts
and ideas from all across the globe and make science available to the best of minds.
The journal is an effort to enlighten its audience with the recent trends in the spheres
of biotechnology and bioinformatics.
Topics of interest cover different aspects of life sciences and biomedical research
including genomics, proteomics, metabolomics, bioinformatics, bioprocess technology,
drug designing and discovery, systems biology and others.
Inimitable attributes of the journal:
• The journal aims to bring together the best of research in advanced biotechnology
and bioinformatics, with greater emphasis on the usefulness and applicability of
the work.
• Each research theme is collected from both biotechnology and bioinformatics sectors
and aims to be a useful resource for both the scientific and academic community.
• Apart from contemporary research, the journal also emphasizes the latest
developments in biotechnology and bioinformatics.
• It also aims to become a benchmark of quality research at both the national and
international levels in the coming years.
The contents of this journal are available for free at www.ijabb.dce.edu
DISCLAIMER:
The Editorial Board is responsible for the relevance and
significance of the manuscripts with respect to the objective
of the journal. The photographs, diagrams or views expressed
by the authors are entirely of their own and the Board shall not
bear responsibility of any copyright violation issue. Limited
copies have been printed of the inaugural issue. These are
complimentary copies and not for sale.
Advanced Biotechnology and
Bioinformatics
Chief Patron:
Prof. P. B. Sharma
Vice Chancellor,
Delhi Technological University,
Shahbad Daulatpur, Delhi, India
Editor-in-Chief
Founder Director, CSIR-Institute of Genomics and Integrative Biology (IGIB)
Chief Mentor, CSIR-Open Source Drug Discovery (OSDD)
Director General, Council of Scientific and Industrial Research (CSIR)
New Delhi -110001, India
Executive Editor
Dr. Yasha Hasija
Assistant Professor & Associate Head,
Department of Biotechnology,
Delhi Technological University,
Publisher
Shahbad Daulatpur, Bawana Road, Delhi-110042, India
Copyright © 2012 by the International Journal of Advanced
Biotechnology and Bioinformatics
All rights reserved. Subject to statutory exception and the provisions of
relevant collective licensing agreements, no part of this publication may
be reproduced, stored in a retrieval system, or transmitted in any form,
without the prior written permission of the publisher.
International Journal of Advanced Biotechnology and Bioinformatics
is an online, freely available, peer reviewed journal that endeavors to
rapidly publish original, authentic and fundamental research papers,
review articles, case studies and short communications in all the spheres of
biotechnology and bioinformatics.
This journal is published annually. Online access to the publication is
available free of charge at www.ijabb.dce.edu. For further information:
Dr. Yasha Hasija
Department of Biotechnology
Delhi-110042, India
Email: [email protected]; [email protected]
Table of Contents
Editorial Board ...................................................................................................................................................................................... 4
Chief Patron's Message ...................................................................................................................................................................... 7
Editor-in-Chief's Message ................................................................................................................................................................ 8
Message from the Hod, Department of Biotechnology, DTU .................................................................................... 9
Executive Editor's Message ......................................................................................................................................................... 10
•
Review Articles
Role of ppars as chemotherapeutics and anticancer molecules
Renu Bhatt, Vinoy Thomas, Derrick Dean, Elijah Nyairo, Udai P. Singh, Manoj K. Mishra ................................................................. 11
Towards solution structure and dynamics of bio-medically
important membrane proteins
Maruthi Kashyap, Harshesh Bhatt, Nishant Pandey, Neel Sarovar Bhavesh ......................................................................................... 19
An overview of ubiquitin e3 ligase in neurodegenerative disorders
Pravir Kumar, Gaurav Rana, Rashmi Ambasta ...................................................................................................................................... 26
Waste to energy: microbial fuel cell a novel approach to generate bio-electricity
Ishwar Chandra ....................................................................................................................................................................................... 33
•
Research Articles
Cytotoxicity and cell adhesion properties of human mesenchymal stem cells
in electrospun nanofiber polymer scaffolds
Zaynah Welcome, Hongzhuan Wu, Elijah Nyairo, Christian Rogers, Derrick Dean,
Kennedy Wekesa, Karyn Gunn, Robert Villafane .................................................................................................................................... 41
Pgx_ipg: A database of pharmacogenomics of major infectious disorders
Ruchika Sahajpal, Aditi Qamra, Vinod Scaria, Yasha Hasija ................................................................................................................. 48
inos gene c150t polymorphism and biomarkers of endothelial dysfunction in
stable ischemic heart disease: a pilot study
Shilpa Bhardwaj, Richa Dixit, MK Bhatnagar, Sanjay Tyagi, Jayashree Bhattacharjee ........................................................................ 59
Hydrolysis of whey lactose using ctab permeabilzed thermotolerant yeast
cells for subsequent fermentation to bioethanol
Minakshi Dahiya, Shilpa Vij, Subrota Hati ............................................................................................................................................. 65
Computational analysis of halotolerance genes from halophilic
prokaryotes to infer their signature sequences
Tamanna Anwar, Rajinder S. Chauhan ................................................................................................................................................... 69
Identification of t-cell antigenic determinants in the
proteins of human papillomavirus
Dharmendra Kumar Chaudhary, Indra Mani, Vijai Singh ...................................................................................................................... 79
INSIGHTS TO SEQUENCE INFORMATION OF ALPHA AMYLASE ENZYME FROM DIFFERENT
SOURCE ORGANISMS
Vivek Dhar Dwivedi , Tanuj Sharma , Amit Pandey , Sarad Kumar Mishra .......................................................................................... 87
EDITORIAL BOARD
Chief Patron
Editor-in-Chief
Executive Editor
Prof. P. B. Sharma
Dr. Yasha Hasija
Vice Chancellor
Shahbad Daulatpur
Delhi, India
Founder Director
CSIR-Institute of Genomics and
Integrative Biology (IGIB)
Chief Mentor
CSIR-Open Source Drug Discovery (OSDD)
Director General
Council of Scientific and Industrial Research (CSIR)
Assistant Professor & Associate Head
Dr. Aida Al Aqeel
Prof. Avadhesha Surolia
Dr. Bassam R. Ali
Prof. Bansi D. Malhotra
Dr. Chas Bountra
Prof. Doron Lancet
Prof. Edison T. Liu
Dr. Fahd Al-Mulla
Dr. Ghazi Omar Tadmouri
Prof. Gursharn S. Randhawa
Prof. Henry Huanming Yang
Prof. Howard L. McLeod
Prof. J. K. Pal
Dr. Jong Bhak
Prof. Mark McCarthy
Prof. Nasir Al-Allawi
Riyadh Armed Forces Hospital, Saudi Arabia
United Arab Emirates University, Al Ain - United Arab
Emirates
University of Oxford, England
The Jackson Laboratory, USA
Centre for Arab Genomic Studies, Dubai
Beijing Genomics Insitute (BGI)-Shenzhen, China
University of Pune, India
University of Oxford, England
National Institute of Immunology, India
Delhi Technological University, India
Weizmann Institute of Science, Israel
Kuwait University, Kuwait
Indian Institute of Technology Roorkee, India
University of North Carolina, U.S.A.
Theragen BiO Institute (TBI), Korea
University of Duhok, Iraq
Dr. Pravir Kumar
Dr. Rade Drmanac
Dr. Rama S. Verma
Prof. Richard G. H. Cotton
Prof. Rinti Banerjee
Prof. Ruth Chadwick
Prof. S. N. Mukhopadhyay
Prof. S. Maji
Dr. S. Ramachandran
Prof. Saroj Mishra
Prof Stephen Scherer
Prof. Subhash Chand
Prof T. S. Chandra
Prof. U. C. Banerjee
Prof. Yogendra Singh
Prof. Avadhesha Surolia
Indian institute of Technology Madras, India
Indian Institute of Technology - Bombay, India
Indian Institute of Technology - Delhi, India
Institute of Genomics and Integrative Biology, India
University of Toronto, Canada
Indian Institute of Technology - Madras, India
Institute of Genomics and Integrative Biology, India
Complete Genomics, Inc., U.S.A.
University of Melbourne, Australia
Cardiff University, UK
National Institute of Pharmaceutical Education and Research,
India
National Institute of Immunology, India
From the Chief Patron
I
n today’s fast changing world, there is a perpetual requirement for new
technologies and innovations in every sphere of industry. The ideas that
feed the ever mounting demand for novel applications are attained from
the rigorous endeavours put in by scientists and researchers all over the
world who work ardently to yield results.
I feel honoured and privileged to launch a new research initiative in the
form of research journal titled as “International Journal of Advanced
Biotechnology and Bioinformatics” that will be formally known as
IJABB. It is an attempt to promote an intellectual culture- a culture that is established on standards of
research, exchanges and acceptance of ideas, infringing boundaries of biases, prejudices and suspicions.
Therefore, being the Patron- in-Chief of the IJABB, I foresee that the journal would go far beyond its regional
and national peripheries to uphold culture of free exchange of original research and ideas on one hand and
alter local mind set of stringency or obscurantism in to open mind set ready to accept notions, change with
the spirit of harmony and accommodation. I envision, IJABB will serve as a stage to promote research
through free debates and communications between the academia and industry, researchers and the students,
administrators and the organizations and so on.
I am also elated to note that the accepted papers shall be published online, after an efficient peer review
under the able leadership of Prof. Samir K. Brahmachari as the Editor-in-Chief and Dr. Yasha Hasija as the
Executive Editor in IJABB. This is designed to emerge as a world class research journal carrying original
research work, which would be available, free of cost on the journal website www.ijabb.dce.edu
I wholeheartedly appreciate all the sincere efforts of the entire team of IJABB and wish them a grand success.
Prof P. B. Sharma
Vice Chancellor,
From the Editor-in-Chief
I
am delighted that the inaugural issue of the International Journal of
Advanced Biotechnology and Bioinformatics; the free, online and peer-
reviewed journal is now available.
I am sure that it will prove to be a much-sought-after annual research
journal for publishing novel and experimentally validated research papers
of originality and merit.
IJABB’s advantage manifests in its Editorial Board that comprises of
large number of senior scientists around the globe whose close interest and science contributions and value
to the contents and scope of the journal. Thus, IJABB sets the bar high ensuring quality publications for the
benefit of the global scientific community.
While the scientific world strides into the “Omics” era, and new knowledge is being captured every day, I am
sure the IJABB will be successful in capturing and disseminating the best of advanced research in the field of
Biotechnology and Bioinformatics, with great emphasis on the applicability of the work.
As Editor-in-Chief, I would like to invite the attention of all serious research scholars to this new research
journal that is now available for the publication of research papers, methods, databases, and all other
publications that push forward the boundaries of Biotechnology and Bioinformatics.
I am sure IJABB will be a publication of significance and that it will earn popularity in the future.
Founder Director, CSIR-Institute of Genomics and Integrative Biology (IGIB)
Chief Mentor, CSIR-Open Source Drug Discovery (OSDD)
Director General, Council of Scientific and Industrial Research (CSIR)
Message
B
iotechnology and Bioinformatics is now the great hope of the world.
Just as the industrial revolution and information technology brought
about successive paradigm shifts in the way human beings live and interact
in the world, the world now looks to biotechnology and bioinformatics to
bring about the next sweeping wave of change.
The possibilities of biotechnology and bioinformatics are so vast as to be
unimaginable even to our best minds. The implications and consequences
are tremendous, and there is palpable excitement about what biotechnology
can achieve in all spheres, from the scientific community to world governments.
IJABB aims to foster a flourishing scientific culture that celebrates and nurtures the multifarious and
superlative achievements of researchers. The journal is a receptacle created to collect and collate the best
ideas, and to inspire countless sparks of inspiration. The ethos behind this journal is to invite and accept
papers from all quarters, sans any bias whatsoever, the only criteria for selection being merit. And this is why
we believe that the future of the journal augers well.
With the sense of great exultation I feel elated to present the first edition of International Journal of Advanced
Biotechnology and Bioinformatics.
Prof. S. Maji
Head of Department
From the Executive Editor
I
t is my heartiest gratification to proclaim the first issue of International
Journal of Biotechnology & Bioinformatics. This journal is an effort to
edify its audience with the topical trends in the spheres of Biotechnology
and Bioinformatics.
By means of the International Journal of Advanced Biotechnology and
Bioinformatics, we endeavor to seize the novel thoughts and ideas from
all across the globe and make recent advancements available to the best
of minds in the scientific, professional as well as academic community.
Diverse attributes embraced by the journal extend from Genomics, Proteomics, Metabolomics, Bioinformatics,
Bioprocess Technology, Drug Designing and Discovery, Systems Biology and others associated to Life
Sciences and Biomedical Research.
The journal welcomes research papers, review articles, case studies and short communications allied to the
scope of the journal. In order to be considered for publication, a manuscript must meet the general criteria
of authenticity, timeliness, purpose and importance. The manuscript must be prepared as per the submission
guidelines available at http://www.ijabb.dce.edu/guidelines.html. Upon receipt, the manuscripts undergo a
swift prior assessment by our highly proficient editorial board. The selected manuscripts are then reviewed
by our esteemed reviewers having an expertise in the respective fields.
This journal will be published annually and the first issue contains eleven articles, covering different aspects
in biotechnology and bioinformatics research. We assure the attainment of set aims and objectives in the
days to come and are open for suggestions, to upgrade the journal in any way necessitated, so as to cater
for the advancement of Biotechnology and Bioinformatics, and the necessity for solving varied biological
complications.
Dr. Yasha Hasija
Assistant Professor & Associate Head,
Department of Biotechnology,
INTERNATIONAL JOURNAL OF ADVANCED BIOTECHNOLOGY AND BIOINFORMATICS
VOL.1, ISSUE.1, November 2012
ROLE OF PPARs AS CHEMOTHERAPEUTICS AND ANTICANCER
MOLECULES
Renu Bhatt1*, Vinoy Thomas2, Derrick Dean3, Elijah Nyairo4,
Udai P. Singh5, and Manoj K. Mishra6*
Department of Biotechnology, Guru Ghasi Das University, Bilaspur, India,
Center for Nanoscale Materials and Biointegration (CNMB), Department of Physics and 3Department of Material
Science and Engineering, University of Alabama at Birmingham (UAB), 1530 3rd Avenue South, Birmingham,
Alabama 35294 USA, 5Pathology, Microbiology and Immunology, School of Medicine, University of South Carolina,
Columbia, SC 29208, USA
4
Department of Physical Sciences and 6Department of Mathematics and Science, Alabama State University, 915 S.
Jackson St. Montgomery, Alabama 36101 USA
1
2
ABSTRACT
The role of Peroxisome Proliferator-Activated Receptors (PPARs) in the development and progression of several chronic
diseases such as obesity, diabetes, and cancer has been well established. PPARs are ligand binding transcription factors
that play important roles in many physiological processes during cell growth, lipid metabolism, inflammation, and
apoptosis. Due to diverse role of PPARs and their ligand in the regulation of cancer, the PPARs have shown potential in
chemoprevention and therapy of several types of cancer either as single agent or in combination with other anti-tumor
agents. This review focuses on recent advances in anti-tumorigenic activities of PPARs in different types of cancer.
Key words: Proliferator-activated receptors (PPARs), Acute renal failure (ARF), Cisplatin, anti-tumor compounds
1. INTRODUCTION
Cancer is one of the lethal diseases in the world and
millions of people die every year. To treat different
types of cancer, there are extensive investments in basic
and clinical research has been done. These investments
resulted in the use of several chemotherapeutic agents [14]
. These chemotherapeutic agents (such as cisplatin) and
their derivatives have been used to treat cancers including
sarcoma, small cell lung cancer, germ cell tumors,
lymphoma, ovarian, prostate, and other types of cancer. At
molecular level, these compound forms a complex inside
the cell which binds to DNA and crosslinks DNA). The
crosslinking of DNA initiates the apoptotic process of
tumor cells. During apoptotic process, these compounds
also affects other healthy cells that results in side effects.
For instance, nephrotoxicity is a common side effect of
cisplatin which has been in use as a chemotherapeutic
agent.
Corresponding Author:
Manoj K Mishra,
Department of Mathematics and Science, Alabama State University, 915
S. Jackson St. Montgomery, Alabama 36101 USA,
Email: [email protected] or
Renu Bhatt, Department of Biotechnology, Guru Ghasidas University,
Bilaspur, India,
E-mail: [email protected]
*
Cisplatin exerts its toxic effects through different
mechanisms. Published reports suggest that the toxicity of
chemotherapeutic agents is caused primarily by decreasing
the expression and reducing the enzyme activity of several
PPARs target genes [5-10].
PPARs are nuclear protein highly expressed in liver, heart,
renal proximal tubular cells, skeletal muscle, intestinal
mucosa and brown adipose tissues and are considered
metabolically very active. To encounter the side effects
of chemotherapeutic agents, the administration of PPAR
ligands have been useful. The PPAR ligands activate the
PPARs that result in a pleiotropic response including the
decreased peroxisomes proliferation, upregulation of fatty
acid oxidation, reduced inflammation and suppressions of
apoptosis. Reports have demonstrated that PPAR ligands
prevent the development of proximal tubules cell death
during cisplatin treatment by preserving peroxisomal and
mitochondrial fatty acid oxidation. PPARγ ligands and
amino acid deprivation promote apoptosis of melanoma,
prostate, and breast cancer cells [11-15]. This review article
focuses on the recent advancement in the mechanism
of action of PPARs in the prevention of cancer and
inflammation.
11
Bhatt R. et. al. ROLE OF PPARs AS CHEMOTHERAPEUTICS AND ANTICANCER MOLECULES
2. Peroxisome
(PPARs)
Proliferator–Activated
Receptors
PPARs are the transcription factors that play important
roles in the regulation of many diseases. The PPARs are
mainly three types (PPARα, PPARβ, PPARγ), each one is
encoded by different genes and express differently in many
parts of the human body [16-19]. PPARα is expressed in
liver, kidney, heart, muscle, adipose tissue and others and
is the main target of fibrate, drugs a class of amphipathic
carboxylic acid. It is also used in cholesterol and high
triglycerides disorders [18, 20].
2.1. PPARα and Fatty acid oxidation
Recent work from different group suggest that peroxisome
proliferator–activated receptor-α (PPARα) plays a critical
role in regulating fatty acid β-oxidation in kidney tissue
that helps in the preservation of kidney structure and
function during acute kidney injury. Study in a transgenic
mice expressing PPARα in the proximal tubule under
the control of the promoter of KAP2 (kidney androgenregulated protein 2) suggested that segment-specific upregulation of PPARα expression by testosterone improved
kidney function during chemotherapeutic-induced
(cisplatin or ischemia–reperfusion-induced) acute kidney
injury [3, 4, 21]. Ischemia–reperfusion injury or treatment
with cisplatin in wild-type mice causes inhibition of
fatty-acid oxidation, reduction of mitochondrial genes of
oxidative phosphorylation, fatty-acid metabolism, and the
tricarboxylic acid cycle. Results suggest proximal tubule
PPARα activity serves as a metabolic sensor. Therefore,
the increased expression of PPARα without the use of
an exogenous PPARα ligand in the transgenic mice is
sufficient to protect kidney function and morphology, and
to prevent abnormalities in lipid breakdown associated with
acute kidney injury [3, 4]. Thus, these results demonstrated
the understanding of PPARs and their ligands and their
interaction with various components of signal transduction
in nephrotoxicity.
2.2.PPARα ligands and their anti-inflamatory effect in
Cisplatin-induced Acute Renal Failure (ARF)
Cisplatin is one of the antitumor agents and has been
used in the chemotherapy. Nephrotoxicity is the major
side effect of the cisplatin-based chemotherapy [22, 23].
Over years of intensive work toward the improvement of
cisplatin delivery has resulted in the used carboplatin and
of oxaliplatin that has been used only for a very narrow
spectrum of cancer [24]. Earlier work has demonstrated
the molecular mechanisms of platinum compounds and
12
PPARα ligand for anti-inflammatory effect, DNA damage,
DNA repair, and induction of apoptosis via activation or
modulation of signaling pathways as a basis of platinum
resistance [3, 4, 22]. The protective effects of a PPARα
ligand preventing the inflammatory response induced by
cisplatin have been observed in wild-type mice and not
in PPARα null mice [3, 4, 25]. PPAR α ligands has shown to
prevent cisplatin-induced activation of NF-kB, as well as
the increased production of known targets of NF-kB such
as VCAM-1 and ICAM-1 suggesting a protective role
for PPARα in reducing not only cisplatin-induced tissue
injury but also inflammation [4, 22, 25]. The first evidence
for a role of PPARα in the control of the inflammatory
response came from a study that the inflammatory
response induced by leukotriene B4 was prolonged in
PPARα deficient mice [26]. Several other studies have
confirmed the anti-inflammatory properties of PPARα [3, 4,
9, 17]
. In other studies, the fibrates administration decreased
plasma concentrations of cytokines such as IL-6, TNF-a
IFN-γ fibrinogen and C-reactive protein [27]. The PPARα
repression of fibrinogen is due to negative interference of
PPARα with the CAAT/enhancer binding protein (CEBP)
pathway [28, 29]. A study had shown that prophylactic
administration of statins, which also mediate their effects
via PPARα, resulted in less contrast nephropathy[30].
PPARα ligand reduced the cisplatin mediated increase in
NF-κB binding activity and the inflammatory response
mediated by cisplatin are consistent with previous studies
demonstrating that PPARα reduces inflammation via
its effects on the NF-κB signaling pathway [28]. PPARα
ligands like fibrates can induce both IkBa mRNA and
protein expression in human aortic smooth muscle cells
and hepatocytes as well as reduce NF-κB DNA biding
activity. The induction of IκBαcan lead to acceleration
of NF-κB nuclear deactivation and prevention of NF-κB
from binding to the promoter of target genes, which results
in suppression of NF-κB-mediated target gene activation,
including cytokines (TNF-a, IL-6), adhesion molecules
(ICAM-1, VCAM-1), and enzymes (inducible nitric oxide
synthase, cyclooxygenase-2, PLA2) [31, 32]. PPARα ligands
can also repress both c-Jun and p65-induced transcription
of IL-6 promoter activity [28]. In conclusion, results clearly
indicated the anti-inflammatory effects of PPARα ligand
in cisplatin-induced ARF. PPARα interferes with different
steps of the inflammatory response induced by cisplatin,
by modulating the expression of proinflammatory
cytokines TNF-a, IL-6, and IFN-l, chemokines RANTES,
MIP2, and MCP1, and chemokine receptors CCR1 and
CCR5. In addition, PPARα prevents neutrophil infiltration
and inhibited NF-κB activities, suggesting that this
could represent a likely mechanism for cytoprotection in
cisplatin-mediated nephrotoxicity.
2.3. PPARα ligand prevents cisplatin-induced proximal
tubule cell death
Fibric acid derivatives (fibrates) have been used in clinical
practice for more than two decades as a class of agents
known to decrease triglyceride levels while substantially
increasing high-density lipoprotein (HDL) cholesterol
levels, with a limited but significant additional lowering
effect on low-density lipoprotein (LDL) cholesterol
levels. Their hypolipidemic effects can be explained by
their specific binding to and activation of nuclear receptor
PPARα [4, 18]. It has established that the use of fibrates
protects renal function primarily by increasing renal fatty
acid oxidation as well as preventing proximal tubule cell
death in the animal models of ischemia/reperfusion (I/R)
and cisplatin-induced acute renal failure [4, 33, 34]. Recent
work also suggests that the administration of fibrates
ameliorates cisplatin-induced acute renal failure by
preventing proximal tubule cell apoptosis and necrosis.
Although the beneficial effect of fibrates on decreasing
extracellular lipid levels has been well established, the
intracellular mechanism(s) by which fibrates prevent
proximal tubule cell death in cisplatin mediated
nephrotoxicity have not been previously examined
in renal proximal tubular cells in culture. Published
report [35] examined the cellular mechanisms by which
Bezafibrate (PPARα ligand) treatment inhibit cisplatin
mediated tubular injury in LLCKP cells, by preventing
cisplatin induced translocation of pro-apoptotic marker
Bax from the cytosol to the mitochondria and also by
increasing the expression of mitochondrial Bcl-2. Ligand
also prevented cisplatin-induced cytochrome c release
from the mitochondrial to the cytosolic compartment and
significantly reduced cisplatin induced caspase3 activation
that lead to proximal tubule cell death. Cisplatin is an
effective chemotherapeutic agent used in the treatment of
a wide variety of cancer malignancies [36]. Proximal tubular
damage by cisplatin leads to acute renal failure and high
mortality [23, 37, 38]. Previous studies have examined the
cellular mechanisms by which cisplatin causes proximal
tubular cell death[39].Several studies suggest that Bax
translocation from the cytosol to the mitochondria and
subsequent release of cytochrome c represent an important
mechanism involved in cisplatin-induced apoptotic [40-42].
PPARβ is expressed ubiquitously and its function is
relatively unknown. Recent studies suggest that PPAR β
may be a target for non-steroidal anti-inflammatory drugs
induced tumors suppression in colorectal and other tumors.
Breast cancer cell proliferation promotes epidermal
growth factor and their receptors (EGFRs). FABP5
(fatty acid binding protein) correlates with a marked upregulation in cancer mammary tissue. FABP5 functions
to deliver ligands and to enhance the transcriptional
activity of the nuclear receptors peroxisome proliferator
–activated receptors beta/delta [43, 44]. The expression of
the intracellular lipid binding protein FABP5 is highly upregulated in mammary tumors that arise from amplification
of ErB2 in the mouse model of breast cancers MMTVneu(45) as well as in human pancreas, breast, bladder and
prostate cancer[46]. FABP5 functions in conjunction with
the nuclear receptors PPAR β, a receptors whose activation
protects cells against apoptosis and facilitates cell growth
and migration [45, 46].
PPARγ plays an important role in cell proliferation,
differentiation and apoptosis[47]. It plays a role in both
adipocyte differentiation and carcinogenesis. Its ligands
lead to the inhibition of nitric oxide, cytokine and adhesion
molecule expression, in part by antagonizing the activities
of transcriptional factors. PPAR g ligands have potent
tumor –modulatory effects on several types of tumors
[48]
. In thyroid cancer cell lines, it has been shown that
the expression of PPARγ correlates with the sensitivity of
troglitazone (an anti-diebetic and anti-inflammatory drug)
and 15d-PGJ2 (15-Deoxy-Delta-12,14-prostaglandin
J2, an endogenous PPARγ ligand) to cell death. Thyroid
cancer cells that did not express PPARγ showed no
growth inhibition after treatment with troglitazone and
15d-PGJ2 compared with thyroid cancer cells that did
express PPARγ and were sensitive to growth inhibition by
troglitazone and 15d-PGJ2, suggesting PPARγ-dependent
growth inhibition [49]. Another study in thyroid cancer cell
lines also implicates PPARγ as an important target. In this
study, ciglitazone was effective in reducing the growth
of thyroid cancer cells that expressed PPARγ, but had
no effect in reducing growth in a thyroid cancer cell line
that do not express PPARγ [50]. Another interesting study
by this group is the over expression of PPARγ in thyroid
cancer cells significantly increased apoptosis compared
with to cells transfected with empty vector or vector with
nonfunctional PPARγ cDNA.
The recent findings from a transgenic mouse study may
provide an explanation for why thyroid cancer is susceptible
to treatment with PPARγ agonists [51-53]. Mice harboring
a knock-in dominant negative mutant thyroid hormone
receptor β (TRβPV/PV mouse) spontaneously develop
follicular thyroid carcinoma similar to human thyroid
cancer. Using the offspring from the cross of TRβPV/+
and PPARγ+/− mice [53] investigators have reported that
thyroid carcinogenesis progressed significantly faster in
TRβPV/PV mice with PPARγ insufficiency from increased
cell proliferation and reduced apoptosis. Reduced
PPARγ protein activated the NF-κB signaling pathway,
resulting in the activation of cyclin D1 and repression
13
of critical genes involved in apoptosis. The treatment of
TRβPV/PV mice with a PPARγ agonist, rosiglitazone,
delayed the developmentof thyroid tumorigenesis by
increasingapoptosis[49]. In contrast, in colon cancer
cells, both troglitazone and 15d-PGJ2 have been shown
to downregulate c-Myc expression [54] increasing the
expressions growth arrest and DNA-damage [54-57].
suggesting that these might be directly regulated.
Reports from different worker suggest that oxidative stress
induced by PPAR γ loss of function results in lysosomal
autophagy which can contribute to malignant progression
[62]
. Thus, the modulation of PPAR γ signaling by glitazone
drug could be considered as an addition to anti-oxidant
diets to inhibit progression of HGPIN to prostate cancer.
In human lung cancer cells, troglitazone induced
apoptosis as well as PPARγ and ERK1/2 accumulation
in the nucleus. Both PPARγ siRNA and U0126, a specific
inhibitor of ERK1/2, blocked these effects of troglitazone,
suggesting that troglitazone-induced apoptosis is PPARγand ERK1/2-dependent. Moreover, inhibition of ERK1/2
by U0126 also significantly decreased the levels of
PPARγ, suggesting a positive crosstalk between PPARγ
and ERK1/2 or an autoregulatory feedback mechanism to
amplify the effect of ERK1/2 on cell growth arrest and
apoptosis [58].
2.4. PPAR γ and human multiple myeloma cells
A recent study in colon cancer cells showed that
troglitazone enhanced the binding of PPARγ to PPRE
in the POX promoter, activated the POX promoter, and
increased endogenous POX expression. Blocking of
PPARγ activation either by the antagonist GW9662 or
deletion of the PPAR-responsive element in the POX
promoter only partially decreased the POX promoter
activation in response to troglitazone, suggesting also
the involvement of PPARγ-independent mechanisms.
Thus, this study indicates that both PPARγ-dependent and
-independent mechanisms are involved in the troglitazoneinduced POX expression [59]. Recent studies have reported
the role of PPAR γ and prostate cancer. PPAR γ plays a
role in maintaining the peroxisomal, mitochondrial, and
lysosomal biogenesis and maturation during prostatic
epithelial cellular growth and differentiation. In PPAR
γ deficient prostrate epithelial cell, showed decreased
in Catalase and PMP70 proteins and degenerated
mitochondria. These changes are associated with mouse
PIN (prostatic intraepithelial neoplasia) formation
and progressions. Microarray revealed alterations to
peroxisomal and mitochondrial fatty acid transporter
synthesis and oxidative metabolism in PPAR γ deficient
mPrE cells as compared to the control cells. Disruption
of PPARγ-signaling results in altered in altered fatty
acid metabolism and induction of oxidative stress and
hypoxia, as supported by increased Hyou-1 and hairless
(Hr), and decreased hairy and enhancer of split1 (Hes1)
gene expression in addition COX-2, GSTs and uPAR
which show similar changes in expression patterns in
clinical samples of human PIN and in other mouse model.
A number of these altered genes contain a PPRE domain
14
[60, 61]
Multiple myeloma is a hematological cancer with poor
prognosis, with an average survival of only 3-5 years.
PPAR γ and its ligands are the new targets in the treatment
of B cell malignancies. PPAR γ overexpressions in
multiple myeloma cells reduce their proliferation and
induce apoptosis. Treatment with ciglitazone, a selective
PPAR γ agonist augments these beneficial effects. PPAR
γ activation status may be an important prognostic marker
for multiple myeloma [63, 64]. PPAR γ ligand may have
potential therapeutic benefits in the treatment of breast
cancer. Obesity plays an important role in Breast cancer.
Leptin, mostly produced by adipose tissue, reported to
play role in mammary carcinogenesis. The anti-diabetic
thiazolidinediones, inhibits leptin gene expressions
through ligand activation of the PPAR γ and exert antiproliferative and apoptotic effects on breast carcinoma.
PPAR γ prevented the development of leptin-induced
MCF-7 tumor xenografts and inhibited the increased
cell-cell aggregation and proliferation observed on leptin
exposure. PPAR γ ligands abrogated the leptin-induced
up regulation of leptin gene expressions and its receptors
in breast cancer and leptin signaling mediated by MAPK/
STAT3/AKT phosphorylation and counteracted leptin
stimulatory effect on estrogen signaling [65].
3. Co-treatment of PPARα and PPAR γ
The co-treatment of the dual PPARα/γ ligand bezafibrate
plus vorinostat resulted in strong additive anti-proliferative
actions in three prostate cancer cells, altered genome-wide
gene expression profiles selectively, and induced cell
cycle arrest and programmed cell death profiles. Refining
the uniquely regulated gene targets by vorinostatand
bezafibrate co-treatment, by comparison with tumorspecific mRNA expression patterns, revealed that 50%
of genes regulated by the voronistat and bezafibrate cotreatment were restored to comparable levels observed in
normal prostate epithelial cells. Network analyses of these
genes revealed enrichment for several targets interfacing
between cell cycle and lipid metabolism regulatory sub
networks [66].
4. Molecular
mechanisms
regulation of PPARs
of
transcriptional
All PPARs have a basic structure of functional domains
such as DNA binding domain (DBD) and ligand binding
domain (LBD). The DBD contains two Zinc finger patterns
which bind to the regulatory region of DNA when the
receptor is activated. The LBD has an extensive secondary
structure of several alpha helices and a beta sheet.
Natural and synthetic ligand, bind to the LBD, activating
the receptor. PPARs first dimerize with the retinoid X
receptors (RXR) and bind to specific regions on the DNA
of target genes. These DNA sequences are termed PPREs
(peroxisome proliferator response elements). The DNA
consensus sequence is AGGTCAXAGGTCA with X being
a random nucleotide. Generally, this sequence occurs in
the promoter region of a gene and when the PPAR bind
its ligand, transcription of targets genes are increased or
decreased, depending on the gene. The RXR also forms a
heterodimer with a number of other receptors like vitamin
D and thyroid receptors.
5. Role of nano-engineered cisplatin-polymer
nanoparticles as chemotherapeutics
With the advances in nanoscience and nanotechnology,
there is great interest in developing nanodelivery systems
for improving effectiveness of cancer therapeutic drugs that
are already on the market. Ideally, nanodelivery systems
allow for more specific targeting of the drug, thereby
improving efficacy and minimizing side effects. In fact,
utilizing nanotechnology principles in drug design and
delivery, researchers are trying to develop nanomedicine
systems to be able to deliver the drug to the targeted
tissue with controlled drug release kinetics and vanish
from the body through native degradation pathways.
Since the use of cisplatin, chemotherapy for most cancers
is limited due to nephrotoxicity and some other cancers
[22, 23]
as mentioned earlier and the roles of PPARs in
modulating different types of tumor; many attempts have
been made to engineer cisplatin-nanoparticles to in view
of limiting the toxicity impact of cisplatin. The selective
delivery (targeting) of cisplatin drug to tumor cells
would significantly reduce drug toxicity, and improve its
therapeutic index. There are mainly two approaches exist
in the literature for encapsulation of cisplatin viz. physical
entrapments and chemical conjugation. The cisplatin have
been encapsulated in polymeric nanoparticles prepared
by double emulsion methods. For example, Polylactideco-glycolide- methoxy (polyethylene glycol), mPEG
nanaoparticles (PLGA–mPEG) revealed prolonged drug
residence in blood upon intravenous administration [67]. At
the targeted site PLGA–mPEG nanoparticles encapsulated
with cisplatin exhibited rapid degradation and release.
Later, PLGA-mPEG based cisplatin nanoparticles with
an average size of 150-160 nm and approximately 2%
w/w cisplatin content were prepared by a modified
emulsification and solvent evaporation method [68]. The
cisplatin-loaded PLGA-mPEG nanoparticles appeared to
be effective in delaying tumor growth in HT 29 tumorbearing SCID mice. The group of mice treated with
cisplatin-loaded nanoparticles exhibited a higher survival
rate compared with the free cisplatin group. Very recently,
a report on the targeted delivery of a cisplatin prodrug using
PLGA-PEG nanoparticles (150±15 nm encapsulating
~5% wt/wt Pt(IV) pro-drug) for safer and more effective
prostate cancer therapy in vivo was documented[69].
Designed core–shell structure nanoparticles based on
block copolymer of methoxy poly (ethylene glycol)–
polycaprolactone (mPEG–PCL) for cisplatin incorporation
into the nanoparticles with high encapsulation efficiency
more than 75% [70]. Controlled release of cisplatin was
observed in a sustained manner that in vitro cytotoxicity
studies proved the efficacy of cisplatin-loaded
nanoparticles against BGC823 and H22 cells in a dose and
time-dependent manner. Furthermore, in vivo intratumoral
administration to improve the tumor-targeted delivery
exhibited superior antitumor effect with cisplatin-loaded
nanoparticles against free cisplatin control by delaying
tumor growth when delivered intratumorally, while no
significant improvement was observed when they were
administrated intraperitoneally.
Polymer−cisplatin conjugate nanoparticles with pHsensitive drug delivery characteristics were also
reported for controlled release of cisplatin. For example,
therapeutic nanoparticles (sub-100 nm size) consisting of
polymer−cisplatin conjugates based on copolymer of PEG
(hydrophilic) and PLA (hydrophobic) colvalently bonded
to cisplatin through a hydrazone bond to form micelles[71].
Being pH sensitive delivery vehicle, these micelles can
potentially minimize the drug loss during circulation in
the blood (neutral pH), and trigger rapid intracellular drug
release after the nanoparticles are endocytosed by the
target cells (acid pH).
Another group [72] has used a novel polymer, glucosaminefunctionalized polyisobutylene-maleic acid to form
complex with platinum (Pt) and the monomeric units
through a monocarboxylato and an O → Pt coordinate
bond. Again, this complex can self-assemble into a
nanoparticle, which releases cisplatin in a pH-dependent
manner. Further studies by the authors have shown that
these nanoparticles rapidly internalized into the endolysosomal compartment of cancer cells, and exhibit an
15
IC50 (4.25 ± 0.16 μM) comparable to that of free cisplatin
(3.87 ± 0.37 μM). This nanoformulation also exhibited
enhanced antitumor efficacy in terms of tumor growth
delay in breast and lung cancers and tumor regression in
a K-rasLSL/+/Ptenfl/fl ovarian cancer model and reduced
systemic and nephrotoxicity, validated by decreased
biodistribution of platinum to the kidney.
Investigators have also explored the feasibility of cisplatin
incorporation in dendrimers, a unique class of repeatedly
branched polymeric macromolecules with numerous arms
extending from a center, resulting in a nearly-perfect
three-dimensional geometric pattern. One example was
polyamindoamine dendrimer (PAMAM) generation
conjugated to cisplatin through the sodium carboxylate
surface giving a fairly water soluble nanoformulation of
dendrimer–platinate (20–25 wt% platinum) with the ability
to release cisplatin slowly in vitro[73]. When injected i.p. into
mice bearing B16F10 tumor cells, this formulation showed
superior activity over cisplatin and when administered i.v.
to treat a palpable s.c. B16F10 melanoma, the dendrimer-Pt
displayed additional antitumor activity whereas cisplatin
was inactive. In short, nanoengineering of biocompatible
and biodegradable polymer based cisplatin-conjugated/
encapsulated delivery systems enables the development of
nanoformulations with maximal tolerated-dose of cisplatin
can improve its antitumor efficacy by capitalizing on the
inherent properties of nanoscaled particles.
Therefore, the evidences discussed above demonstrate
that due to diverse role of PPARs and their ligand in
the regulation of cancer, the PPARs can be used in
chemoprevention and therapy of several types of cancer
either as single agent or in combination with other antitumor agents. But to understandthe mechanism and
to reduce the side effects of these chemotherapeutic
molecules, more experimental debate will be needed to
establish the anti-tumorigenic activities of PPARs in tumor
development, progression and clearance.
REFERENCES
1. Reddy, R.C., et al., Chemotherapeutic drugs induce PPARgamma expression and show sequence-specific synergy
with PPAR-gamma ligands in inhibition of non-small cell
lung cancer. Neoplasia, 10(6): 597-603, 2008.
2. Hamaguchi, N., et al., In vitro and in vivo therapeutic efficacy
of the PPAR-gamma agonist troglitazone in combination
with cisplatin against malignant pleural mesothelioma cell
growth. Cancer Sci. 101(9): 1955-64.2010.
3. Li, S., et al., PPAR-alpha ligand ameliorates acute renal
failure by reducing cisplatin-induced increased expression
of renal endonuclease G. Am J Physiol Renal Physiol,
287(5): F990-8, 2004.
16
4. Li, S., et al., PPAR alpha ligand protects during cisplatininduced acute renal failure by preventing inhibition of renal
FAO and PDC activity. Am J Physiol Renal Physiol, 286(3):
F572-80, 2004
5. Adam, M., et al., Evaluation of the toxicity of tirapazamine
plus cisplatin in a mouse tumor model. Strahlenther Onkol,
182(4): 231-9, 2006.
6. Aminsharifi, A., et al., Preventive role of exogenous
testosterone on cisplatin-induced gonadal toxicity: an
experimental placebo-controlled prospective trial. Fertil
Steril. 93(5): 1388-93.2010.
7. Atessahin, A., et al., Chemoprotective effect of melatonin
against cisplatin-induced testicular toxicity in rats. J Pineal
Res, 41(1): 21-7, 2006.
8. Curigliano, G., et al., Cisplatin, etoposide and continuous
infusion bleomycin in patients with testicular germ cell
tumors: efficacy and toxicity data from a retrospective
study. J Chemother, 21(6): 687-92, 2009.
9. Hellberg, V., et al., Cisplatin and oxaliplatin toxicity:
importance of cochlear kinetics as a determinant for
ototoxicity. J Natl Cancer Inst. 101(1): 37-47, 2009.
10. Zhang, L., et al., Cisplatin-induced toxicity is associated
with platinum deposition in mouse kidney mitochondria
in vivo and with selective inactivation of the alphaketoglutarate dehydrogenase complex in LLC-PK1 cells.
Biochemistry, 45(29): 8959-71. 2006.
11. Campbell, S.E., et al., Gamma tocopherol upregulates
the expression of 15-S-HETE and induces growth arrest
through a PPAR gamma-dependent mechanism in PC-3
human prostate cancer cells. Nutr Cancer, 61(5): 649-62.
2009.
12. Nunez, N.P., H. Liu, and G.G. Meadows, PPAR-gamma
ligands and amino acid deprivation promote apoptosis of
melanoma, prostate, and breast cancer cells. Cancer Lett,
236(1): 133-41. 2006.
13. Paltoo, D., et al., Pro12Ala polymorphism in the peroxisome
proliferator-activated receptor-gamma (PPAR-gamma)
gene and risk of prostate cancer among men in a large
cancer prevention study. Cancer Lett, 191(1): 67-74. 2003.
14. Radhakrishnan, S.K. and A.L. Gartel, The PPAR-gamma
agonist pioglitazone post-transcriptionally induces p21 in
PC3 prostate cancer but not in other cell lines. Cell Cycle,
4(4): 582-4. 2005.
15. Segawa, Y., et al., Expression of peroxisome proliferatoractivated receptor (PPAR) in human prostate cancer.
Prostate, 51(2): 108-16. 2002.
16. Auwerx, J., T.A. Cock, and C. Knouff, PPAR-gamma: a
thrifty transcription factor. Nucl Recept Signal, 1: e006.
2003.
17. Dai, X., et al., PPAR gamma is an important transcription
factor in 1 alpha,25-dihydroxyvitamin D3-induced
involucrin expression. J Dermatol Sci, 50(1): 53-60. 2008.
18. Djouadi, F., C.J. Weinheimer, and D.P. Kelly, The role of
PPAR alpha as a "lipostat" transcription factor. Adv Exp
Med Biol, 466: 211-20. 1999.
33. Portilla, D., et al., Etomoxir-induced PPARalpha-modulated
enzymes protect during acute renal failure. Am J Physiol
Renal Physiol, 278(4): F667-75. 2000.
19. Tontonoz, P., E. Hu, and B.M. Spiegelman, Stimulation
of adipogenesis in fibroblasts by PPAR gamma 2, a lipidactivated transcription factor. Cell, 79(7): 1147-56. 1994.
34. Portilla,
J.,
et
al.,
Progressive
multifocal
leukoencephalopathy treated with cidofovir in HIV-infected
patients receiving highly active anti-retroviral therapy.
J Infect, 41(2): 182-4. 2000.
20. Tontonoz, P., et al., Adipocyte-specific transcription factor
ARF6 is a heterodimeric complex of two nuclear hormone
receptors, PPAR gamma and RXR alpha. Nucleic Acids Res,
22(25): 5628-34. 1994.
35. Nagothu, K.K., et al., Fibrate prevents cisplatin-induced
proximal tubule cell death. Kidney Int, 68(6): 2680-93.
2005.
21. Braissant, O., et al., Differential expression of peroxisome
proliferator-activated receptors (PPARs): tissue distribution
of PPAR-alpha, -beta, and -gamma in the adult rat.
Endocrinology, 137(1): 354-66. 1996.
36. Lebwohl, D. and R. Canetta, Clinical development of
platinum complexes in cancer therapy: an historical
perspective and an update. Eur J Cancer, 34(10): 1522-34.
1998.
22. Arany, I., et al., Cisplatin-induced cell death is EGFR/src/
ERK signaling dependent in mouse proximal tubule cells.
Am J Physiol Renal Physiol, 287(3): F543-9. 2004.
37. Price, M., J. Megyesi, and R.L. Safirstein, Cell cycle
regulation: repair and regeneration in acute renal failure.
Semin Nephrol, 23(5): 449-59. 2003.
23. Arany, I. and R.L. Safirstein, Cisplatin nephrotoxicity.
Semin Nephrol, 23(5): 460-4. 2003.
38. Price, M., R.L. Safirstein, and J. Megyesi, Protection of
renal cells from cisplatin toxicity by cell cycle inhibitors.
Am J Physiol Renal Physiol, 286(2): F378-84. 2004.
24. Suzuki, R., et al., A phase II study of carboplatin and
paclitacel with meloxicam. Lung Cancer, 63(1): 72-6. 2009.
25. Li, S., et al., Anti-inflammatory effect of fibrate protects
from cisplatin-induced ARF. Am J Physiol Renal Physiol,
289(2): F469-80. 2005.
26. Martin-McNulty, B., et al., 17 Beta-estradiol attenuates
development of angiotensin II-induced aortic abdominal
aneurysm in apolipoprotein E-deficient mice. Arterioscler
Thromb Vasc Biol, 23(9): 1627-32. 2003.
27. Despres, J.P., et al., Gemfibrozil reduces plasma
C-reactive protein levels in abdominally obese men with
the atherogenic dyslipidemia of the metabolic syndrome.
Arterioscler Thromb Vasc Biol, 23(4): 702-3. 2003.
28. Delerive, P., et al., Peroxisome proliferator-activated receptor
alpha negatively regulates the vascular inflammatory gene
response by negative cross-talk with transcription factors
NF-kappaB and AP-1. J Biol Chem, 274(45): 32048-54.
1999.
29. Gervois, P., et al., Negative regulation of human fibrinogen
gene expression by peroxisome proliferator-activated
receptor alpha agonists via inhibition of CCAAT box/
enhancer-binding protein beta. J Biol Chem, 276(36):
33471-7. 2001.
30. Attallah, N., et al., The potential role of statins in contrast
nephropathy. Clin Nephrol, 62(4): 273-8. 2004.
31. Delerive, P., J.C. Fruchart, and B. Staels, Peroxisome
proliferator-activated receptors in inflammation control. J
Endocrinol. 169(3): 453-9. , 2001
32. Delerive, P., et al., Identification of liver receptor homolog-1
as a novel regulator of apolipoprotein AI gene transcription.
Mol Endocrinol, 18(10): 2378-87. 2004.
39. Okuda, M., et al., Role of apoptosis in cisplatin-induced
toxicity in the renal epithelial cell line LLC-PK1.
Implication of the functions of apical membranes, Biochem
Pharmacol, 59(2): 195-201. 2000.
40. Wei, Q., et al., The pathological role of Bax in cisplatin
nephrotoxicity. Kidney Int, 72(1): 53-62. 2007.
41. Neuwelt, A.J., et al., Using acetaminophen's toxicity
mechanism to enhance cisplatin efficacy in hepatocarcinoma
and hepatoblastoma cell lines. Neoplasia, 11(10): 1003-11.
2009.
42. Vandermeers, F., et al., Valproate, in combination with
pemetrexed and cisplatin, provides additional efficacy to
the treatment of malignant mesothelioma. Clin Cancer Res,
15(8): 2818-28. 2009.
43. Schug, Z.T., et al., Molecular characterization of the inositol
1,4,5-trisphosphate receptor pore-forming segment. J Biol
Chem, 283(5): 2939-48. 2008.
44. Schug, T.T., et al., Opposing effects of retinoic acid on cell
growth result from alternate activation of two different
nuclear receptors. Cell, 129(4): 723-33. 2007.
45. Morgan, L., R.I. Nicholson, and S. Hiscox, SRC as a
therapeutic target in breast cancer. Endocr Metab Immune
Disord Drug Targets, 8(4): 273-8. 2008.
46. Adamson, E., et al., Egr1 signaling in prostate cancer.
Cancer Biol Ther, 2(6): 617-22. 2003.
47. Sertznig, , et al., Present concepts and future outlook:
function of peroxisome proliferator-activated receptors
(PPARs) for pathogenesis, progression, and therapy of
cancer. J Cell Physiol, 212(1): 1-12. 2007.
48. Tsubouchi, Y., et al., Inhibition of human lung cancer cell
growth by the peroxisome proliferator-activated receptor-
17
gamma agonists through induction of apoptosis. Biochem
Biophys Res Commun, 270(2): 400-5. 2000.
49. Ohta, K., et al., Ligands for peroxisome proliferatoractivated receptor gamma inhibit growth and induce
apoptosis of human papillary thyroid carcinoma cells. J
Clin Endocrinol Metab, 86(5): 2170-7. 2001.
50. Martelli, M.L., et al., Inhibitory effects of peroxisome
poliferator-activated receptor gamma on thyroid carcinoma
cell growth. J Clin Endocrinol Metab, 87(10): 4728-35.
2002.
51. Murata, S., R. Katoh, and A. Hashi, Ectopic thyroid
hormone producing tumor. Nihon Rinsho, Suppl 3: 291-4.
2006.
52. Takabayashi, S., et al., A novel hypothyroid dwarfism due to
the missense mutation Arg479Cys of the thyroid peroxidase
gene in the mouse. Mol Endocrinol, 20(10): 2584-90.
2006.
53. Kato, Y., et al., PPARgamma insufficiency promotes
follicular thyroid carcinogenesis via activation of the
nuclear factor-kappaB signaling pathway. Oncogene,
25(19): 2736-47. 2006.
54. Shimada, T., et al., Characteristics of the peroxisome
proliferator activated receptor gamma (PPARgamma)
ligand induced apoptosis in colon cancer cells. Gut, 50(5):
658-64. 2002.
55. Satoh, H., et al., Japanese herbal medicine in patients with
advanced lung cancer: prolongation of survival. J Altern
Complement Med, 8(2): 107-8. 2002.
56. Satoh, H., et al., Lung cancer in patients with psychiatric
disorders. Lung Cancer, 35(1): 97. 2002.
57. Satoh, H., Y.T. Yamashita, and K. Sekizawa, Lung cancer
among medical professionals. Chest, 122(4):
1500-1.
2002.
58. Li, M., et al., Apoptosis induced by troglitazone is both
peroxisome proliferator-activated receptor-gamma- and
ERK-dependent in human non-small lung cancer cells. J
Cell Physiol, 209(2): 428-38. 2006.
59. Pandhare, J., S.K. Cooper, and J.M. Phang, Proline oxidase,
a proapoptotic gene, is induced by troglitazone: evidence
for both peroxisome proliferator-activated receptor gammadependent and -independent mechanisms. J Biol Chem,
281(4): 2044-52. 2006.
60. Keen, H.L., et al., Gene expression profiling of potential
PPARgamma target genes in mouse aorta. Physiol
Genomics, 18(1): 33-42. 2004.
61. Perera, R.J., et al., Identification of novel PPARgamma
target genes in primary human adipocytes. Gene, 369: 909. 2006.
62. Hippert, M.M., S. O'Toole, and A. Thorburn, Autophagy in
cancer: good, bad, or both? Cancer Res, 66(19): 9349-51.
2006.
18
63. Garcia-Bates, T.M., S.H. Bernstein, and R. Phipps,
Peroxisome proliferator-activated receptor gamma
overexpression suppresses growth and induces apoptosis in
human multiple myeloma cells. Clin Cancer Res, 14(20):
6414-25. 2008.
64. Garcia-Bates, T.M., et al., Role of peroxisome proliferatoractivated receptor gamma and its ligands in the treatment
of hematological malignancies. PPAR Res, 2008: 834612.
2008.
65. Catalano, S., et al., In vivo and in vitro evidence that
PPARgamma ligands are antagonists of leptin signaling in
breast cancer. Am J Pathol. 179(2): 1030-40.
66. Rhodes, D.R., et al., Probabilistic model of the human
protein-protein interaction network. Nat Biotechnol, 23(8):
951-9. 2005.
67. Avgoustakis, K., et al., PLGA-mPEG nanoparticles of
cisplatin: in vitro nanoparticle degradation, in vitro drug
release and in vivo drug residence in blood properties. J
Control Release, 79(1-3): 123-35. 2002.
68. Gryparis, E.C., et al., Effect of conditions of preparation
on the size and encapsulation properties of PLGA-mPEG
nanoparticles of cisplatin. Drug Deliv, 14(6): 371-80.
2007.
69. Dhar, S., et al., Targeted delivery of a cisplatin prodrug for
safer and more effective prostate cancer therapy in vivo.
Proc Natl Acad Sci U S A. 108(5): 1850-5.
70. Li, X., et al., Superior antitumor efficiency of cisplatinloaded nanoparticles by intratumoral delivery with
decreased tumor metabolism rate. Eur J Pharm Biopharm,
70(3): 726-34. 2008.
71. Aryal, S., C.M. Hu, and L. Zhang, Polymer--cisplatin
conjugate nanoparticles for acid-responsive drug delivery.
ACS Nano. 4(1): 251-8.
72. Paraskar, A.S., et al., Harnessing structure-activity
relationship to engineer a cisplatin nanoparticle for
enhanced antitumor efficacy. Proc Natl Acad Sci U S A.
107(28): 12435-40.
73. Malik, N., E.G. Evagorou, and R. Duncan, Dendrimerplatinate: a novel approach to cancer chemotherapy.
Anticancer Drugs, 10(8): 767-76. 1999.
TOWARDS SOLUTION STRUCTURE AND DYNAMICS OF BIOMEDICALLY IMPORTANT MEMBRANE PROTEINS
Maruthi Kashyap, Harshesh Bhatt, Nishant Pandey and Neel Sarovar Bhavesh*
International Centre for Genetic Engineering and Biotechnology,
Aruna Asaf Ali Marg, New Delhi 110067
ABSTRACT
Traditionally, membrane proteins have been attractive targets for therapeutics. Over 40% of all the currently available drugs
in the market target membrane proteins. Therefore, basic structure-function understanding of OMPs and their complexes
could provide valuable information to improving human health. Recent advances in over-expression strategies, in vitro
reconstitution and biophysical methods, and improved detergents and synthetic lipids have made possible exploration of
increased number of membrane protein targets. Still, structure-function studies on integral membrane proteins and their
complexes are scant (~341 unique structures to date) when compared to soluble protein studies (~82,000 structures as
of May 2012). In many of the membrane protein structures solved by X-ray crystallography, the flexible extracellular
loops are poorly defined and this limits interpretation. In many instances, these loops are important targets for inhibitor
design. NMR spectroscopy is likely to be more successful as it is unparalleled in providing atomic resolution structural
and dynamic information on flexible proteins and of loop regions.
1. INTRODUCTION
Genome sequencing projects have provided the fields of
structural biology and molecular biophysics with new
opportunities and challenges as they provide a basis
for the broad understanding of the molecular basis of
life. Computational analyses of various genomes have
predicted that typically 20–25% of a proteome consists
of membrane proteins, among which in gram negative
bacteria 2–3% are integral outer membrane proteins
(OMPs). The vital roles of membrane proteins in biological
systems include ion/molecule transport, virus reception,
energy regulation, signaling, etc, which makes them of
commercial interest as attractive targets for therapeutics.
Over 40% of all the currently available drugs in the market
target membrane proteins [1]. Therefore, basic structurefunction understanding of OMPs and their complexes
could provide valuable information to improving human
health.
Recent advances in over-expression strategies, in vitro
reconstitution and biophysical methods, and improved
detergents and synthetic lipids have made possible
exploration of increased number of membrane protein
targets [2-3]. Still, structure-function studies on integral
membrane proteins and their complexes are scant (~341
Neel Sarovar Bhavesh
International Centre for Genetic Engineering and Biotechnology,
Aruna Asaf Ali Marg, New Delhi 110067
E-mail : [email protected]
*
unique structures to date) when compared to soluble
protein studies (~82,000 structures as of May 2012) [4,5].
Out of these 82 membranes protein structures have been
solved by NMR spectroscopy [6]. In many of the membrane
protein structures solved by X-ray crystallography, the
flexible extracellular loops are poorly defined [4] and this
limits interpretation. In many instances, these loops are
important targets for inhibitor design. In addition to atomic
structure of proteins, understanding of intrinsic dynamics
and changes in it upon binding of natural ligands/inhibitor
is equally essential for design of new inhibitors [7]. NMR
spectroscopy is likely to be more successful as it is
unequaled in its ability to provide information on atomic
resolution structural and dynamic information on flexible
proteins and of loop regions [8-10].
In light of this, we have initiated a project using multidimensional solution-state NMR spectroscopy for
determination of de novo structures of bio-medically
important outer membrane proteins from Salmonella,
causative agent of Salmonellosis. Salmonellosis is a
worldwide scourge affecting ~1.3 billion worldwide. It is
part of the family of food borne diseases caused due to
ingestion of contaminated food items such as eggs, dairy
products, and meats, but almost any foodstuff can be
implicated. This disease is specifically costly in monetary
and human terms for populations residing in Asia and
Africa. The recent outbreak of human salmonellosis is of
serious concern to travelers and domestic populations in
developing countries and poorly nourished children are
19
Kashyap et. al. TOWARDS SOLUTION STRUCTURE AND DYNAMICS OF BIO-MEDICALLY IMPORTANT MEMBRANE PROTEINS
the major victims [11-12].
Salmonella belongs to a family of entero-pathogenic
Gram-negative bacteria. More than 2500 known types,
or serotypes, of Salmonella have been identified. Out of
these Salmonella typhimurium has recently re-emerged
as the most important serotype in human salmonellosis.
Salmonella infections can cause diseases ranging from
stomach pain, diarrhea, nausea, chills, systemic typhoid
fever and headache that normally appear within 1-2 days
after eating contaminated food. Infants, young children,
elderly, and immuno-compromised individuals (patients
on drug therapy, elderly, young) are affected more severely
and infection can be life-threatening [11-15]. Because
of the increasing prevalence of antibiotic resistant S.
typhimurium isolates, an understanding of the growth and
pathogenesis of this organism is important for developing
new therapeutics [16-18]. Three-dimensional structures
of proteins involved in different stages of Salmonella
infection and structure-function studies will shed light
on central parasite processes like invasion, adhesion and
development of drug resistance. Structural and functional
information on Salmonella proteins is scant: (a) of the
more than ~5000 Salmonella proteins only few have been
studied structurally, and (b) a large number of salmonella
proteins remain of unknown function.
Among many proteins required for virulence, OMPs of
Salmonella are involved in early interaction with host
during pathogenesis. The vital roles of these OMPs in
Salmonella include ion/molecule transport, virus reception,
energy regulation, signaling, adhesion etc, which makes
them of commercial interest as targets for new drug
developments. Computational analysis of its genome has
predicted that about a third of its proteome consists of
membrane proteins (Out these there are predicted to be
more than 100 OMPs in Salmonella typhimurium) [19].
In our approach, a set of five bio-medically important
proteins from pathogenic Salmonella species have
been selected and steps towards sample preparation are
undertaken. All the selected five OMPs are (a) functionally
characterized proteins; (b) have less than 300 residues; (c)
play important roles during infection and (d) reported to
be monomeric in nature.
2. MATERIAL AND METHODS
2.1 Cloning, over-expression and purification of
Salmonella OMPs
The production of pure, correctly folded and functional
OMPs in milligram amounts is a critical step for structural
and dynamic studies. Cloning and over-expression of
20
selected OMPs have been undertaken simultaneously. For
cloning the genes, chromosomal DNA from Salmonella
typhimurium was extracted according to standard
protocols. Primers were designed for all five genes in a
manner that genes are cloned without the periplasmic
transport signal sequence. This strategy promotes the
formation of inclusion bodies, which is good for large
expression required for structural studies. The selected
membrane proteins are cloned in both pET11a and
pET28a (with N-terminal His-tag) expression vectors.
Protein expressed in pET28a vector is easily purified
using Ni-NTA chromatography but has six histidine
residues at the N- or C-terminal while proteins expressed
in pET11a vector does not have any extra residues at the
terminals but requires multiple purification steps like
ion-exchange chromatography. Upon sequencing and
confirmation of wild type sequences expression are tested
in E. coli BL21(DE3) codon plus cells using Luria-Bertani
(LB) medium. The expression levels are maximized by
optimizing different parameters of growth and expression
like temperature, concentration of inducer, cell density
for induction and expression period. Once best conditions
have been achieved we purify the proteins in large amounts
using ion-exchange chromatography and gel filtration
chromatography
2.2 Preparation of [13C,15N,2H]-labeled proteins
Uniform isotope enrichment by 13C and 15N of protein
is essential for multi-dimensional NMR spectroscopy
and for this size of protein it is absolutely required
to additionally label with 2H nuclei. Because of the
significantly lower gyromagnetic ratio of 2H compared
to 1H (γ[2H]/γ[1H] = 0.15), replacement of protons with
deuterons removes contributions to proton linewidths
from proton-proton dipolar relaxation and 1H-1H scalar
couplings. At deuteration levels between 50–75%, the
expected decrease in sensitivity resulting from the limited
number of protons is offset to a large extent by a reduction
in peak line-widths. Therefore, replacement of 1H by 2H
nuclei reduces the relaxation of NMR signal, which are
significantly higher for proteins larger than 35 kDa [20-21].
Structure determination protocol by NMR spectroscopy
uses distances between different 1H-1H atoms (protons) in
proteins [22]. As [13C, 15N, 2H]-labeled proteins contain very
few 1H atoms (only exchangeable protons like backbone
HN-atoms are exchanged with bulk water to get 1H atoms)
very few inter-proton distance can be measured, which can
lead to low-resolution structures (see Fig 1). Therefore,
in order to obtain more inter-protein distance restraints
selectively labeled samples are prepared, where methyls
of isoleucine, valine and leucine are protonated in the
deuterated background. This allows us to obtain the sidechain 13C and methyl-proton assignments and inter-proton
distances for structure determination. These assignments
are obtained using TROSY based 13C-13C TOCSY (Total
Correlation Spectroscopy) experiments [23].
Fig 1: Effect of uniform H-labeling of proteins on NMR signal and on
extraction of 1H,1H-NOEs constraints for structure calculation. White
balls are 1H atoms and thin yellow lines are observed 1H,1H-NOEs.
2
For uniform [13C,15N,2H]-labeling recombinant protein
needs to be produced in minimal media containing
[13C, 2H]-labeled-carbon source and [15N, 2H]-labeled
nitrogen source with D2O replacing the usual solvent
H2O. Bacteria are acclimatized to grow and express in
such complex media for efficient protein production. The
acclimatized bacteria are grown in labeled D2O medium
and the recombinant protein is over-expressed as per the
optimized condition and purification of inclusion bodies is
performed. The protein thus generated is uniformly [13C,
15
N, 2H]-labeled. Since the growth is known to be very slow
in D2O and expression is low we supplement the media by
vitamin mix. Similarly over-expression is also performed
in cell free system where solvent for all reagents is D2O
and [13C, 15N, 2H]-labeled amino acids are used [24-25].
The purified inclusion bodies containing over-expressed
OMP are dissolved in 8 M urea and further purification
is performed using ion-exchange chromatography on an
Akta Explorer 10s.
We recover the spent medium and perform distillation
under vacuum in a very controlled and insulated manner to
recover back 95% of the total volume of D2O for reuse. The
purity of D2O prepared in this manner is always assessed
by 1D 1H NMR spectroscopy, which has normally more
than 98% 2H content. The recovered D2O is used with
same efficacy for optimization of growth and expression.
2.3 Reconstitution in detergent micelle
Detergent micelles mimic the hydrophobic membrane
environment of bacteria and their size is within the
range for solution NMR studies. These make them a
popular choice for reconstitution of membrane proteins in
functional state, which can be made amenable for solution
NMR studies [23-26]. This step is very crucial as there is
no single standard detergent or reconstitution procedure,
which has been successful for membrane proteins whose
structures have been determined. The whole process
needs to be tailor made for each protein in absence of a
general protocol [27-28]. New detergent molecules are also
designed and synthesized in different research groups for
the enhancing the efficiency and speed of reconstitution
[29-30]
. Recently use uniformly 2H-labeled detergents have
reported to be highly beneficial for structural studies of
OMPs by solution-state NMR spectroscopy [31-32].
The reconstitution can be difficult or even problematic for
a given protein. Therefore we take up the reconstitution
of purified urea unfolded [15N, 2H]-labeled proteins
in different detergent micelle simultaneously. If no
precipitation is observed after the refolding, the sample is
concentrated using centricons (MWCO 30 kDa) and the
buffer is exchanged with phosphate buffer.
Following detergents are used for initial screening and if
required more and new detergents will be also tried.
Lauryldimethylamine-oxide (LDAO)
1-Oleoyl-2-Hydroxy-sn-Glycero-3-[Phospho-rac-(1-glycerol)] (LOPG)
1-Palmitoyl-2-Hydroxy-sn-Glycero-3-[Phospho-rac-(1-glycerol)]
(LPPG)
1,2-Dihexanoyl-sn-Glycero-3-Phosphocholine (DHPC)
1,2-Diheptanoyl-sn-Glycero-3-Phosphocholine (DH7PC)
N-Dodecylphosphocholine (DPC)
N-Octyl--D-glucopyranoside (OG)
N-Dodecyl- -D-maltoside (DM)
The correctness of reconstitution is monitored using
Circular-Dichroism (CD) and 2D [15N, 1H]-TROSY
(Transverse Relaxation Optimized Spectroscopy [33]).
CD easily probes the presence of secondary structures
in proteins. Well-dispersed resonances in 2D [15N, 1H]TROSY spectra with uniform line-shape confirm folded
state. NMR spectra for quality assessment are measured
on a four-channel 500 MHz Bruker AVANCE III NMR
spectrometer equipped with highly sensitive 5mm TCI
cryo-probe and 1.7mm TXI micro-probe. Use of 1.7mm
TXI probe-head helps in screening with minimal sample
amount [29-30].
21
2.4 Preparation of NMR sample and activity assays
2.6 Structure calculation and refinement
One major concern lies in keeping the pure protein
in folded, functional and stable state at milli-molar
concentration for days to be amenable for structural
investigations. Suitable conditions like ionic-strength,
pH, and buffer will be identified to keep the protein in
correctly folded state. Efforts are undertaken to maximize
the concentration of proteins on one hand and minimize
the detergents concentration on the other. This results
in higher sensitivity and better line-shape, which is
beneficial for longer NMR experiments and generation
of good quality restraints for structure calculations. Once
the optimum solution conditions for NMR are identified,
activity assay is performed in the same conditions to assess
the functional state of the reconstituted OMPs.
Conventional 3D-15N and 13C-edited TROSY based
[1H,1H]-NOESYs (Nuclear Overhausser enhanced
spectroscopy) are measured on a 700 MHz NMR
spectrometer. Automated peak picking and NOESYs peak
assignment software UNIO [36-37] and structure calculation
software CYANA [38] will be used for structure calculations.
Use of residual dipolar coupling (RDCs) is also envisage
for obtaining correct alignment of all domains with respect
to each other and refinement of structure using energy
minimization software AMBER [39].
2.7 Dynamics
The longitudinal and transverse relaxation rates (R1 and
R2) of backbone 15N nuclei as well as the Steady-state
15
N-{1H}-nuclear Overhauser enhancements (NOEs)
are useful probes of protein backbone dynamics, overall
molecular tumbling motions (tc) and conformational
exchange on a picosecond to millisecond time scale [40-41].
We will measure the dynamics of the membrane proteins
using two different magnetic field spectrometers for
obtaining accurate information on exchange phenomena.
3. results
Fig 2: Preparation of [13C, 15N, 2H]-labeled recombinant outer
membrane proteins in bacterial culture and cell free system.
2.5 Sequence-specific backbone resonance assignment
Obtaining sequence-specific backbone resonance
assignments is a pre-requisite and starting point for any
investigation by NMR spectroscopy. A series of 3D
and 4D TROSY based triple-resonance NMR spectra
are measured on the 700 MHz Bruker Avance III NMR
spectrometer equipped with highly sensitive cryoprobe.
The spectra are processed using TOPSPIN 2 and PROSA
[34]
software package and analyzed with CARA [35].
Upon successful completion of the backbone resonance
assignment the chemical shift information of 13C, 13C,
13
CO, 1HN and 15NH is used for calculation of secondary
chemical shift that provide information on secondary
structure. Secondary chemical shifts are deviation of
chemical shifts from its random coil values.
22
We have successfully cloned and over-expressed
Salmonella typhymurium OmpH and OmpW proteins in
isotope enriched minimal media (Fig 3A). The proteins
expressed as inclusion bodies, which were dissolved in 8
M urea solution. Purification protocol for OmpW has been
established (Fig 3B). Efforts are currently in progress for
other three proteins.
Fig 3: (A) SDS-PAGE showing over-expression of OmpH and OmpW
(B) purification of OmpW
We have been successful in reconstituting OmpW in
DHPC micelle and stable samples have prepared. Initial
2D [15N, 1H]-TROSY spectrum shows a large number of
well-resolved downfield-shifted peaks, which are typical
for -sheet structures (Fig 4). We have performed the
activity assay to confirm the functional state using Single
channel conductance where Colicin S4 inserted readily
into the OmpW at a potential of approximately -100 mV.
The sample conditions like pH, ionic strength, detergent
kind and concentration have been optimized to improve
the spectral quality – which is already quite encouraging.
We monitored the final concentration in the NMR sample
using 1D 1H NMR spectra. The size of OmpW-DHPC
micelle is about 90 kDa, which has been determined by
dynamic light scattering (DLS) and TROSY based NMR
experiment. Sequence-specific backbone resonance
assignment is under progress and we have already obtained
some assignments. One such stretch from TROSYHNCACB is shown in Fig. 5
Fig. 5: Selected strips showing the resonance assignments for
the stretch Arg63−Gly72. Blue and green lines show Cα and Cβ
connectivities respectively.
REFERENCES
1.
Stroud RM Choe S, Holton J, Kaback HR, Kwiatkowski W,
Minor DL, Riek R, Sali A, Stahlberg H and Harries W., 2007
Annual progress report synopsis of the Center for Structures
of Membrane Proteins. J. Struct. Funct. Genomics. 10,193208. 2009.
2.
Engel A and Gaub HE. Structure and mechanics of
membrane proteins. Annu. Rev. Biochem. 77, 127-148.
2008.
3.
Lacapère JJ, Pebay-Peyroula E, Neumann JM and Etchebest
C. Determining membrane protein structures: still a
challenge! Trends Biochem Sci. 32, 259-270. 2007
4.
Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN,
Weissig H, Shindyalov IN, Bourne PE The Protein Data
Bank. Nucleic Acids Res. 28, 235-242. 2000.
5.
White S., Membrane Proteins of Known Structure.
http://blanco.biomol.uci.edu/Membrane_Proteins_xtal.html
6.
White S., Membrane Proteins of Known Structure by NMR.
http://www.drorlist.com/nmr/MPNMR.html
7.
Hornak V and Simmerling C. Targeting structural flexibility
in HIV-1 protease inhibitor binding. Drug Discov. Today 12,
Fig 4: A [15N, 1H] TROSY spectrum of OmpW at 30°C measured on
a 700 MHz Bruker AVANCE III spectrometer.
23
132-138. 2007.
8.
9.
Montelione GT, Arrowsmith C, Girvin ME, Kennedy
MA, Markley JL, Powers R, Prestegard JH and Szyperski
T. Unique opportunities for NMR methods in structural
genomics. J. Struct. Funct. Genomics. 10,101-106. 2009.
Bhavesh NS and Hosur RV. Exploring ‘unstructured’
proteins. Proc. Indian. Natn. Sci. Acad. 70A, 579-596. 2003.
10. Bruschweiler R.
New approaches to the dynamic
interpretation and prediction of NMR relaxation data from
proteins Curr. Opin. Struct. Biol. 13 175–183. 2003.
11. World Health Organization fact sheet. http://www.who.int/
mediacentre/factsheets/fs139/en/
12. McGhie EJ, Brawn LC, Hume PJ, Humphreys D, Koronakis
V. Salmonella takes control: effector-driven manipulation
of the host. Curr. Opin. Microbiol. 12, 117-124. 2009.
13. Chalker RB and Blaser MJ. A review of human
salmonellosis: III. Magnitude of Salmonella infection in the
United States. Rev. Infect. Dis. 10, 111-124 .1988.
14. Pang T, Bhutta ZA, Finlay BB, and Altwegg M. Typhoid
fever and other salmonellosis: a continuing challenge.
Trends Microbiol. 3, 253-255 .1995.
15. Gomez TM, Motarjemi Y, Miyagawa S, Kaferstein FK and
Stohr K. Foodborne salmonellosis. World Health Stat. Q.
50, 81-89 . 1997.
16. Glynn MK, Bopp C, Dewitt W, Dabney P, Mokhtar M, and
Angulo FJ. Emergence of multidrug-resistant Salmonella
enterica serotype typhimurium DT104 infections in the
United States. N Engl J Med 338, 1333-1338 . 1998.
17. Molbak K, Baggesen DL, Aarestrup FM, Ebbesen JM,
Engberg J, Frydendahl K, Gerner-Smidt P, Petersen AM,
and Wegener HC. An outbreak of multidrug-resistant,
quinolone-resistant
Salmonella
enterica
serotype
typhimurium DT104. N Engl J Med 341, 1420-1425 .1999.
18. Threlfall EJ, Frost JA, Ward LR, and Rowe B. Increasing
spectrum of resistance in multiresistant Salmonella
typhimurium. Lancet 347, 1053-1054 .1996
19. ExPASy: SIB Bioinformatics Resource Portal-Home
http://www.expasy.ch
20. Gardner KH and Kay LE. The use of 2H, 13C, 15N
multidimensional NMR to study the structure and dynamics
of proteins. Annu. Rev. Biophys. Biomol. Struct. 27, 357406. 1998.
21. Tugarinov V, Kanelis V and Kay LE. Isotope labeling
strategies for the study of high-molecular-weight proteins
by solution NMR spectroscopy. Nat. Protoc. 1, 749-754.
2006.
22. Billeter M, Wagner G and Wüthrich K. Solution NMR
structure determination of proteins revisited. J Biomol
NMR. 42,155-158. 2008.
24
23. Fernández C and Wüthrich K. NMR solution structure
determination of membrane proteins reconstituted in
detergent micelles. FEBS Lett. 555, 144-150. 2003.
24. Staunton D, Schlinkert R, Zanetti G, Colebrook
SA, Campbell ID. Cell-free expression and selective
isotope labelling in protein NMR Magn. Reson. Chem. 44
Spec No:S2-9. 2006.
25. Koglin A, Klammt C, Trbovic N, Schwarz D, Schneider
B, Schäfer B, Löhr F and Bernhard F, Combination of cellfree expression and NMR spectroscopy as a new approach
for structural investigation of membrane proteins. Magn.
Reson. Chem. 44 Spec No:S17-23.
26. Arora A and Tamm LK. Biophysical approaches to
membrane protein structure determination. Curr. Opin.
Struct. Biol. 11, 540-547. 2001.
27. Vinogradova O, Sönnichsen F and Sanders CR 2nd. On
choosing a detergent for solution NMR studies of membrane
proteins. J. Biomol. NMR. 11, 381-386. 1998.
28. Krueger-Koplin RD, Sorgen PL, Krueger-Koplin ST,
Rivera-Torres IO, Cahill SM, Hicks DB, Grinius L,
Krulwich TA and Girvin ME. An evaluation of detergents
for NMR structural studies of membrane proteins. J.
Biomol. NMR. 28, 43-57. 2004.
29. Zhang Q, Horst R, Geralt M, Ma X, Hong WX, Finn MG,
Stevens RC and Wüthrich K. Microscale NMR screening of
new detergents for membrane protein structural biology. J.
Am. Chem. Soc. 130, 7357-7363. 2008.
30. Stanczak P, Horst R, Serrano P, Wüthrich K. NMR
characterization of membrane protein-detergent micelle
solutions by use of microcoil equipment. J. Am. Chem. Soc.
131, 18450-18456. 2009.
31. Hiller S, Garces RG, Malia TJ, Orekhov VY, Colombini
M, Wagner G. Solution structure of the integral human
membrane protein VDAC-1 in detergent micelles. Science
321, 1206-1210. 2008.
32. Hiller S and Wagner G. The role of solution NMR in the
structure determinations of VDAC-1 and other membrane
proteins. Curr. Opin. Struct. Biol. 19, 396-401. 2009.
33. Fernández C and Wider G. TROSY in NMR studies of the
structure and function of large biological macromolecules.
Curr. Opin. Struct. Biol. 13, 570-580. 2003.
34. Güntert P, Dötsch V, Wider G and Wüthrich K. Processing
of multi-dimensional NMR data with the new software
PROSA. J. Biomol. NMR. 2, 619-629. 1992.
35. Keller R. The Computer Aided Resonance Assignment
Tutorial, first edition, ISBN 3-85600-112-3, CANTINA
Verlag. 2004.
36. Herrmann T, Güntert P, and Wüthrich K. Protein NMR
structure determination with automated NOE-identification
in the NOESY spectra using the new software ATNOS. J.
Biomol. NMR 24, 171–189. 2002.
37. Herrmann T, Güntert P, and Wüthrich K. Protein NMR
structure determination with automated NOE assignment
using the new software CANDID and the torsion angle
dynamics algorithm DYANA. J. Mol. Biol. 319, 209–227.
2002.
38. Güntert P. Automated NMR structure calculation with
CYANA. Methods Mol. Biol. 278, 353-378. 2004.
39. Case DA, Darden TA, Cheatham TE III, Simmerling CL,
Wang J, Duke RE, Luo R, Crowley M, Walker RC, Zhang
W, Merz KM, Wang B, Hayik S, Roitberg A, Seabra G,
Kolossváry I, Wong KF, Paesani F, Vanicek J, Wu X, Brozell
SR, Steinbrecher T, Gohlke H, Yang L, Tan C, Mongan J,
Hornak V, Cui G, Mathews DH, Seetin MG, Sagui C, Babin
V, and Kollman PA, AMBER 10, University of California,
San Francisco. 2008.
40. Mittermaier A and Kay LE. New tools provide new insights
in NMR studies of protein dynamics. Science 312, 224-228.
2006.
41. Kay LE. Protein dynamics from NMR Nat. Struct. Biol.
Supp. 5 513-517. 1998.
25
Kumar P. et. al. AN OVERVIEW OF UBIQUITIN E3 LIGASE IN NEURODEGENERATIVE DISORDERS
AN OVERVIEW OF UBIQUITIN E3 LIGASE IN
NEURODEGENERATIVE DISORDERS
Pravir Kumar1, 2, *, Gaurav Rana1, and Rashmi Ambasta1
Department of Biotechnology, Delhi Technological University, Delhi 110042
Department of Neurology, Adjunct faculty, Tufts University School of Medicine, Boston, MA (USA)
1
2
ABSTRACT
The Ubiquitin-Proteasome System (UPS) plays a crucial role in maintaining the protein homeostasis upon any alteration
in the cellular process such as signalling, cell cycle deregulation, apoptosis and transcription ailments that trigger the
UPS pathway to maintain the integrity of cell. Inside the cellular milieu, misfolded or aggregated proteins are repaired
by molecular chaperonic machinery but beyond a threshold of correction and refolding, cells eliminates these unwanted
proteins through UPS where E3 ligase is a decisive element to recognise these target proteins and subsequently covalent
attachment with a chain of Ubiquitin molecules (generally through ubiquitin Lys48) for destruction. Destruction of
protein molecules is highly orchestrated process which is energy dependent and transfer of ubiquitin molecule for
instance is mediated by a cascade of enzymatic reaction and substrate recognition by E3 ligase. During this process,
ubiquitin is eliminated and the target protein gets degraded into small peptides. There are two core classes of E3 ligase
have been discovered where a members of the E6-AP-related family of homologous to the E6-AP C terminus (HECT)
domain is responsible for the catalytic activity during ubiquitination process. The other E3s class: Really Interesting
New Gene (RING) finger domain which is potentially much larger and works as a facilitator of protein interaction and
subsequently ubiquitination. There are several evidences indicating an alteration, mutation, deficiency or malfunctioning
in Ubiquitin E3 ligase that lead to hereditary and other forms of neurodegeneration. In this review we have compiled
various Ubiquitin E3 ligases and their function in different neurodegenerative diseases.
1. INTRODUCTION
Monitoring and regulating the level of a functionally
active protein is a highly complex and securely regulated
process. An adequate balance between its rate of synthesis
and degradation, which may be dependent on posttranslational modification, must be upheld. This balance is
largely maintained by the activity of UPS. The implication
of UPS has been well studied in several neurodegenerative
disorders. One of the major discoveries was the
characterisation of the RING finger as a multi-protein
domain capable of E3 activity [1]. Several of these proteins
and those of the E3 family including an HECT domain have
been largely identified as proteins that are either directly
responsible for, or allied with specific neurodegenerative
disorders. In case of familial AD, 3 genetic loci have been
associated: APP on chromosome 21, PS1 on chromosome
Dr. Pravir Kumar, PhD
Associate Professor,
Delhi Technological University (Formerly Delhi College of Engineering),
FW4TF3, Mechanical Engineering Building, Shahbad Daulatpur,
New Bawana Road, Delhi 110042
E-mail: [email protected]; [email protected]
Phone: +91-9818898622; +91-9003386752
*
26
14 and presenilin 2 (PS2) on chromosome 1. All 3 mutant
genes can increase Aβ deposits and subsequent plaque
formation.
PS1 and PS2 are likely to be components of the multiprotei n γ-secretases required for proteolytic cleavage of
APP to form Aβ [2]. Presenilins are degraded via the UPS,
by an E3 complex containing the F-box protein FBXW7[3].
Co-expression of FBXW7 and APP causes increased
presenilin ubiquitylation and elevated Aβ production.
The consequences of UPS in PD have been extensively
studied. In the familial forms of PD, α-synuclein, Parkin,
UCH-L1 and DJ-1 are associated with the UPS, Parkin
and UCH-L1 as components of the system, modified and/
or mutant α-synuclein and DJ-1 as targets.
Recent immunohistochemical analysis revealed that the
RING-IBR-RING protein, Dorfin, localised within the
inclusions of ALS patients and interacted with mutant,
but not wild-type SOD1 gene associated with HD
occurrence [4]. Since huntingtin is ubiquitinated, and the
known huntingtin interactant HIP-2 can bind 4 separate
RING finger proteins, these latter molecules may promote
the ubiquitination and degradation of huntingtin [5].
2. Therapeutic strategies and Clinical
applications of Ubiquitin E3 ligases
in neurodegenerative disorders
Ubiquitin E3 ligases are the potential therapeutic targets
known because of their specificity towards substrates.
Due to allosteric modification of the E3s active site, the
substrate binding region reports specificity to E3s and
this contributes to the change in the affinity towards
specific substrates to control ubiquitinated substrate
accrual [6]. However there are several Ubiquitin E3
ligases have endorsed their active involvement in the
neurodegenerative diseases but out of a series of Ubiquitin
E3 ligases, CHIP and Parkin has been extensively studied
in neurodegeneration.
Parkin, as an E3 ubiquitin ligase, is a protective gene that
can be utilized as a therapeutic agent by ubiquitinating
or degrading misfolded proteins to offset multiple
pathologies in neurodegenerative diseases [7]. CHIP acts
as a triage to enhance the neuronal capacity in order to
maintain polyQ proteins in a soluble, non-aggregated state
and potential therapeutic target in the important class of
neurodegenerative diseases [8]. More revelation pertaining
the mechanisms of degradation of oligomeric α-Synuclein
by CHIP may contribute to the successful development
of drug therapies that target oligomeric α-synuclein by
mimicking or enhancing the powerful effects of CHIP[9].
Although, CHIP presents as a potential therapeutic target
for the neurodegenerative disorders, there is a probability
that it would diminish if there is a redundancy of
actions among several E3 ligases. Thus, while targeting
therapeutics each active ligase has to be in a multidrug
protocol. The prospect of redundancy in E3 ligase action
is recommended by reports that overexpression of either
CHIP or Parkin enhances ubiquitination of polyglutamineexpanded ataxin-3 and diminishes its cellular toxicity. In
the above mentioned cases, Hsp70 is responsible for the
action of E3 ligase and this chaperone, which is common
to both ubiquitination pathways, may ultimately be the
best therapeutic target [10, 11, 12]. An overview of ubiquitin
E3 ligase with known function is enlisted in Table 1 with
possible roles:
Table 1: A comprehensive overview of involvement of Ubiquitin E3 ligase in neurodegenerative disorders
Murine double minute
(Mdm2)
PD
Knockdown of DJ-1 and mdm2 (negative regulator of p53) leads to the dopaminergic
neuronal cell death even without toxin exposure. Another study demonstrated that
Mdm2 does not ubiquitinate p53 even when it is associated with it due to proteasome
dysfunction that interferes with normal UPS.
AD
Under stress conditions, the complex of Mdm2 with p53 gets disrupted and p53 is
stabilised. p53 then interacts with GSK-3b which leads to hyperphosphorylation of tau
and increased production of Ab.
HD
In response to cellular stress, p53 gets activated and the interaction of Mdm2 and p53
prevents p53 from enhancing DNA damage repair cascade.
ALS
Antagonists of p53- Mdm2 can be of real importance in gene therapy of
neurodegenerative disorders
PD, HD ALS
Anaphase- Promoting
Complex (APC)
RanBP2
No role has been reported
AD
Cdh1, an activator of (APC/C) regulates axonal growth, synaptic plasticity and survival.
APC/C-Cdh1 is highly essential to prevent cyclin B1accumulation which will cause
neuronal cell death. Cyclin B1accumulates in degenerating brain areas in Alzheimer’s
disease and stroke.
PD
RanBP2 acts as an E3 small ubiquitin-related modifier (SUMO) ligase
AD, HD
ALS
AD
AD
[13],[14];
[15]; [5];
[16]
[17]; [18];
[19]
Although, PPIL2 has been observed to positively regulate β-site amyloid precursor
protein cleaving enzyme(BACE) and β-secretase activity/Aβ production but it has been
reported that common genetic variation in the BACE1-interacting proteins, RTN3 and
PPIL2, does not influence platelet β-secretase activity or susceptibility to AD in this
population.
[20]; [21];
[22]; [23]
STUB can be used as a therapeutic target for anti- Alzheimer's Disease Chinese
Medicine. STUB1/CHIP acts as an E3 ligase and modulates the process of NAD(P)H:
Quinone
Oxidoreductase 1 (NQO1) Accumulation which is disrupted in Alzheimer's Disease.
27
PD
TOPORS
AD, HD
ALS
PD, HD,
ALS
SCF (Fbx2)
HRD1
AD
SCF (Fbx2) is an E3 Ligase, involved in binding and ubiquitination of BACE1 via
Trp 280 residue of F-box-associated domain. Overexpression of Fbx2 in neurons of
transgenic mice verified BACE1 degradation and decreased Aβ production.
PD
HRD1 is up-regulated in response to protection against Parkinson's Disease in 6-OHDA
treated mice.
AD
Provides protection against ER stress and may reduce Aβ production. The investigation
of toxicity of Aβ oligomers reported upregulation of HRD1 in the neurons of transgenic
mice.
HD, ALS
Parkin
TOPORS arrests the transcription activity of p53, which is then restored by DJ-1 in
Parkinson's Disease.
[24]
[25];
[26]; [27]
[28]; [29];
[30];[31]
PD
Parkin requires proteasome activity to arrest lewy body formation but when mutated,
results in the damage of dopaminergic neurons.
AD
Responsible for autophagic clearance of damaged mitochondria and ubiquitinated Aβ.
HD
Ubiquitinates the polyglutamine-expanded proteins and then eliminates it, to avert the
mutilation of the UPS
ALS
Plays an essential role in reducing TDP-43 burden via ubiquitination and degradation in
ALS
IBM
During the study of Inclusion Body Myositis (IBM), Parkin has been found to
ameliorate the human-induced Amyloid Precursor Protein (APP) defects in skeletal
muscles of transgenic flies.
[32]; [33];
[34]
PD
Gigaxonin
AD
HD
Maintains neuronal survival and cytoskeletal integrity and can act as a better therapeutic
approach towards the neurodegenerative disorders like AD, PD, HD and ALS with
Ubiquitin Proteasome System (UPS) defects.
[35]
ALS
PD
ITCH
AD
HD
Degrades p63 and contains WW domains that are associated with several signalling
complexes invoved in human diseases like Alzheimer's Disease, Huntington's Disease.
ALS
Nedd4-1 (neuralprecursor cell-expressed
developmentally
PD, HD,
ALS
downregulated gene
4-1)
AD
PD HD ALS
RNF182
TRAF6 (Tumor
Necrosis Factor
Receptor-associated
Factor 6 )
28
AD
PD, ALS
Highly upregulated during the stages of neuronal development but its finction changes
over time. It mediates ubiquitination of GluA1-containing AMPARs, which causes
endocytosis and lysosomal degradation of AMPARs. But this changes as the time passes
and this has been found to be implicated with Alzheimer's Disease
[36]
[37]; [38]
RNF182 is a RING finger E3 ligase that is responsible for E2-dependent
polyubiquitination in vitro. It has been found up regulated in AD brains and neuronal
cells exposed to injurious insults and targets ATP6V0C protein for degradation.
[39]
AD
TRAF6 has been observed to ubiquitinate tau but in TRAF6 knockout mice, tau
ubiquitination doesnot take place.
HD
TRAF6 in association with Huntingtin protein is responsible for ubiquitination and
enhance aggregate formation in Huntington's Disease.
[40]; [41]
Dactylidin
TRIM9
PD, HD,
ALS
A Novel cytosolic RING finger protein is highly up regulated in the tissues of AD
patients and is implicated in the progression of AD.
PD
TRIM9, in alliance with E2 ubiquitin conjugating enzyme UbcH5b acts as an E3
ubiquitin ligase and also regulates function of neurons. It has been observed that
immunoreactivity of TRIM9 is suppressed in the areas of brain affected due to
Parkinson's Disease and also involved in the pathogenesis of Lewy body Disease via
ligase activity.
PD
PARK2
AD, HD,
ALS
PD
AD, HD,
ALS
Siah-1 (Seven in
absentia homologue-1)
PD
AD, HD,
ALS
PD
Dorfin
ALS
AD
HD
PD
Nrdp1
AD, HD,
ALS
AD, PD,
HD
NEDL1
ALS
PD, PD, HD
Gp78
ALS
PD, AD, HD
Atrogin-1 and MuRF1
AD
AD, HD
ALS
XIAP (X- linked
Inhibitors of apoptosis)
ALS
[1]
[42]
PARK2 is a gene that performs E3 ligase activity, but when mutated results in neuronal
dysfunction. Mutations in PARK2 has been reported to be the common cause of earlyonset Parkinson's disease.
[43]
Plays a pivotal role in cell cycle regulation. It contains RING finger domain, responsible
for E3 ubiquitin ligase activity in the UPS. S-nitrosylation of XIAP compromises its
function as an anticaspase-3 and antiapoptotic protein, contributing the progression of
PD pathogenesis.
[44]
Siah-1 is a RING- type E3 ubiquitin ligase does not degrade α-synuclein via UPS, rather
facilitates α-synuclein accumulation and Lewy Body formation resulting in PD.
[45]
Dorfin acts as a RING-IBR type ubiquitin ligase (E3) which ubiquitylates mutant
superoxide dismutase in Amyotrophic Lateral Sclerosi (ALS). Valosin-containing
protein (VCP) directly interacts and regulates Dorfin, which leads to the formation of
Ubiquitylated inclusions (UBIs) and further advances neurodegeneration like ALS or
PD.
[4]
Overexpression of Nrdp1 negatively regulates Parkin level via proteasome-dependent
manner and enhances production of Reactive Oxygen Species (ROS). There was a
hypothesis that Nrdp1 may be associated with Parkinson's Disease but the recent
studies in Chinese population showed no association of Nrdp1 in the pathogenesis of
[46]; [47]
A homologue to E6AP carboxyl terminus- (HECT-) type ubiquitin protein E3 ligase
(NEDL1) promotes degradation of mutated SOD via UPS. Recent findings
recommended that human NEDL1 transgenic mice might develop ALS-like symptoms
like motor abnormalities and reduction in muscle strength.
[48]
Mammalian gp78 acts as an E3 ligase which promotes ER-associated degradation
(ERAD). It involves ubiquitination and degradation of ataxin-3 and SOD1, which are
responsible for ALS.
[49]
Regulated by an Akt/Forkhead (FKHR) signaling pathway. Present in increased amount
in human skeletal muscle atropy in ALS models. MuRF1 is another E3 ligase example
investigated for skeletal muscle atropy in ALS.
[50]
29
PD, AD, HD
HERC
Rhes
ALS
AD, PD,
ALS
HD
PD, HD,
ALS
Sel-10
NEDD8 (neural
precursor cell
expressed,
developmentally downregulated 8)
CHIP (C-terminus
HSP70 interacting
protein)
HERC gene contains a HECT domain that functions as a ubiquitin ligase and is
involved in cell signalling, trafficking etc. Missense mutation in HERC1 gene causes
degeneration of Purkinje cell in tambaleante mutant mice.
Rhes is a small G-protein that has the properties of SUMO E3 ligase and is involved in
mutant huntingtin cytotoxicity.
PD
NEDD8 is present in the Lewy Body of Parkinson's Disease.
AD
NEDD8, member of the cullin family is known for the formation of ubiquitinated
inclusions via UPS and is found to be in the neurofibrillary tangles in Alzheimer's
disease.
[3]
[53]
PD
Acts as a chaperone and facilitates Parkin-mediated PAEL-R ubiquitination in
AD
Acts as an E3 ubiquitin ligase and co-chaperone to reduce Aβ toxicity.
HD
Quality control ubiquitin ligase to moderate the toxicity of polyglutamine-expanded
proteins.
ALS
Plays a role in proteasomal degradation of mutant SOD1.
AD, HD,
ALS
[52]
Sel-10, a member of the SCF (Skp1-Cdc53/CUL1-F-box protein) E2-E3 ubiquitin
ligase family interacts with Presenilin (PS) which is responsible for ubiquitination and
alteration of Aβ production in Alzheimer's Disease.
HD, ALS
[51]
AD
PD
SKP1A
Component of the ubiquitin-proteasome/E3 ligase complex, Skp1, Cullin 1, F-box
protein. Known as a potential modifier in sporadic PD neurodegeneration.
[54];[8];
[55]
[56]; [57]
3. CONCLUDING REMARK AND FUTURE
PERSPECTIVE
Ubiquitin Proteasome Pathway (UPP) is emerging as a
major participant in neurodegenerative diseases and a full
understanding of this intricate system must be attained to
better comprehend the pathogenesis of these devastating
neurodegenerative disorders. The challenge in the future
will be to identify ways to harness the UPP for treatment
of neurodegenerative disorders. Inhibition of the UPP
might be anticipated to deteriorate most neurodegenerative
diseases (Fig. 1). Augmentation of the UPP poses
distinctive challenges, such as deliverance of UPP
components to the nervous system or detection of drugs
that supplement the degradation of damaged and toxic
proteins without compromising normal UPP functions.
Recent elucidation of RING motif-containing proteins, as
a major class of E3s has rapidly broadened our
understanding of many neurodegenerative disorders.
30
Fig..1: A hypothetical model indicating the role of Ubiquitin E3
ligase in association with molecular chaperones and co-chaperones.
Ubiquitin E3 ligase has a decisive role in the selective degradation of
non functional proteins to maintain the cellular homeostasis.
REFERENCES
1.
von Rotz RC, Kins S, Hipfel R, von der Kammer H, Nitsch RM.
The novel cytosolic RING finger protein dactylidin is up-regulated
in brains of patients with Alzheimer's disease. Eur J Neurosci.
21(5):1289-98. 2005.
16. Fleischer A, Ghadiri A, Dessauge F, Duhamel M, Rebollo MP,
Alvarez-Franco F, Rebollo A. Modulating apoptosis as a target for
effective therapy. Mol Immunol. 43(8):1065-79. 2006.
17. Almeida A, Bolaños JP, Moreno S. Cdh1/Hct1-APC is essential for
the survival of postmitotic neurons. J Neurosci. 25(36):8115-21.
2005.
2.
Glickman MH, Ciechanover A. The ubiquitin-proteasome
proteolytic pathway: destruction for the sake of construction.
Physiol Rev. 82(2):373-428. 2002.
18. Maestre C, Delgado-Esteban M, Gomez-Sanchez JC, Bolaños JP,
Almeida A. Cdk5 phosphorylates Cdh1 and modulates cyclin B1
stability in excitotoxicity. EMBO J. 27(20):2736-45. 2008.
3.
Li J, Pauley AM, Myers RL, Shuang R, Brashler JR, Yan R, Buhl
AE, Ruble C, Gurney ME. SEL-10 interacts with presenilin 1,
facilitates its ubiquitination,and alters A-beta peptide production. J
Neurochem. 82(6):1540-8. 2002.
19. Hegde AN. Ubiquitin-proteasome-mediated local protein
degradation and synaptic plasticity. Prog Neurobiol.73(5):311-57.
2004.
4.
Ishigaki S, Hishikawa N, Niwa J, Iemura S, Natsume T, Hori S,
Kakizuka A,Tanaka K, Sobue G. Physical and functional interaction
between Dorfin and Valosin-containing protein that are colocalized
in ubiquitylated inclusions in neurodegenerative disorders. J Biol
Chem. 279(49):51376-85. 2004.
5.
Illuzzi JL, Vickers CA, Kmiec EB. Modifications of p53 and the
DNA Damage Response in Cells Expressing Mutant Form of the
Protein Huntingtin. J Mol Neurosci. 2011.
6.
Upadhya SC, Ding L, Smith TK, Hegde AN. Differential regulation
of proteasome activity in the nucleus and the synaptic terminals.
Neurochem Int. 48(4):296-305. 2006.
7.
Khandelwal PJ, Moussa CE. The Relationship between Parkin
and Protein Aggregation in Neurodegenerative Diseases. Front
Psychiatry. 1:15. 2010.
8.
Miller VM, Nelson RF, Gouvion CM, Williams A, RodriguezLebron E, Harper SQ,Davidson BL, Rebagliati MR, Paulson HL.
CHIP suppresses polyglutamine aggregation and toxicity in vitro
and in vivo. J Neurosci. 25(40):9152-61. 2005.
9.
Ballinger CA, Connell P, Wu Y, Hu Z, Thompson LJ, Yin LY,
Patterson C. Identification of CHIP, a novel tetratricopeptide
repeat-containing protein that interacts with heat shock proteins
and negatively regulates chaperone functions. Mol Cell Biol.
(6):4535-45. 1999.
10. Tsai YC, Fishman PS, Thakor NV, Oyler GA. Parkin facilitates
the elimination of expanded polyglutamine proteins and leads to
preservation of proteasome function. J Biol Chem. 278(24):2204455. 2003.
11. Jana NR, Dikshit P, Goswami A, Kotliarova S, Murata S, Tanaka
K, Nukina N. Co-chaperone CHIP associates with expanded
polyglutamine protein and promotes their degradation by
proteasomes. J Biol Chem. 280(12):11635-40. 2005.
12. Morishima Y, Wang AM, Yu Z, Pratt WB, Osawa Y, Lieberman
AP. CHIP deletion reveals functional redundancy of E3 ligases in
promoting degradation of both signaling proteins and expanded
glutamine proteins. Hum Mol Genet. 17(24):3942-52. 2008.
13. Proctor CJ, Gray DA. GSK3 and p53 - is there a link in Alzheimer's
disease? Mol Neurodegener. 5:7. 2010.
14. Bretaud S, Allen C, Ingham PW, Bandmann O. p53-dependent
neuronal cell death in a DJ-1-deficient zebrafish model of
Parkinson's disease. J Neurochem. 100(6):1626-35. 2007.
15. Nair VD, McNaught KS, González-Maeso J, Sealfon SC, Olanow
CW. p53 mediates nontranscriptional cell death in dopaminergic
cells in response to proteasome inhibition. J Biol Chem.
281(51):39550-60. 2006.
20. Um JW, Min DS, Rhim H, Kim J, Paik SR, Chung KC. Parkin
ubiquitinates and promotes the degradation of RanBP2. J Biol
Chem. 281(6):3595-603. 2006.
21. Espeseth AS, Huang Q, Gates A, Xu M, Yu Y, Simon AJ, Shi XP,
Zhang X, Hodor P,Stone DJ, Burchard J, Cavet G, Bartz S, Linsley
P, Ray WJ, Hazuda D. A genome wide analysis of ubiquitin ligases
in APP processing identifies a novel regulator of BACE1 mRNA
levels. Mol Cell Neurosci. 33(3):227-35. 2006.
22. Tsvetkov P, Adamovich Y, Elliott E, Shaul Y. E3 ligase STUB1/
CHIP regulates NAD(P)H:quinone oxidoreductase 1 (NQO1)
accumulation in aged brain, a process impaired in certain Alzheimer
disease patients. J Biol Chem. 286(11):8839-45. 2011.
23. Zhang GR, Cheng XR, Zhou WX, Zhang YX. Age-related
expression of STUB1 in senescence-accelerated mice and its
response to anti-Alzheimer's disease traditional Chinese medicine.
Neurosci Lett. 438(3):371-5. 2008.
24. Shinbo Y, Taira T, Niki T, Iguchi-Ariga SM, Ariga H. DJ-1 restores
p53 transcription activity inhibited by Topors/p53BP3. Int J Oncol.
26(3):641-8. 2005.
25. Gong B, Chen F, Pan Y, Arrieta-Cruz I, Yoshida Y, Haroutunian
V, Pasinetti GM.SCFFbx2-E3-ligase-mediated degradation of
BACE1 attenuates Alzheimer's disease amyloidosis and improves
synaptic function. Aging Cell. 9(6):1018-31. 2010.
26. Deshaies RJ. SCF and Cullin/Ring H2-based ubiquitin ligases.
Annu Rev Cell Dev Biol.15:435-67. 1999.
27. Zheng N, Schulman BA, Song L, Miller JJ, Jeffrey PD, Wang P,
Chu C, Koepp DM, Elledge SJ, Pagano M, Conaway RC, Conaway
JW, Harper JW, Pavletich NP. Structure of the Cul1-Rbx1-Skp1-F
box Skp2 SCF ubiquitin ligase complex. Nature. 416(6882):703-9.
2002.
28. Saito R, Kaneko M, Okuma Y, Nomura Y. Correlation between
decrease in protein levels of ubiquitin ligase HRD1 and amyloidbeta production. J Pharmacol Sci. 113(3):285-8. 2010.
29. Kaneko M, Koike H, Saito R, Kitamura Y, Okuma Y, Nomura
Y. Loss of HRD1-mediated protein degradation causes amyloid
precursor protein accumulation and amyloid-beta generation. J
Neurosci. 30(11):3924-32. 2010.
30. Umeda T, Tomiyama T, Sakama N, Tanaka S, Lambert MP, Klein
WL, Mori H. Intraneuronal amyloid β oligomers cause cell death
via endoplasmic reticulum stress, endosomal/lysosomal leakage,
and mitochondrial dysfunction in vivo. J Neurosci Res. 89(7):103142. 2011.
31. Mei J, Niu C. Alterations of Hrd1 expression in various encephalic
regional neurons in 6-OHDA model of Parkinson's disease.
Neurosci Lett. 474(2):63-8. 2010.
31
32. Kim C, Srivastava S, Rice M, Godenschwege TA, Bentley B,
Ravi S, Shao S, Woodard CT, Schwartz LM. Expression of human
amyloid precursor protein in the skeletal muscles of Drosophila
results in age- and activity-dependent muscle weakness. BMC
Physiol. 11:7. 2011.
33. Khandelwal PJ, Herman AM, Hoe HS, Rebeck GW, Moussa
CE. Parkin mediates beclin-dependent autophagic clearance of
defective mitochondria and ubiquitinated Abeta in AD models.
Hum Mol Genet. 20(11):2091-102. 2011.
34. Park YY, Lee S, Karbowski M, Neutzner A, Youle RJ, Cho H. Loss
of MARCH5 mitochondrial E3 ubiquitin ligase induces cellular
senescence through dynamin-related protein 1 and mitofusin 1. J
Cell Sci. 123(Pt 4):619-26. 2010.
35. Ganay T, Boizot A, Burrer R, Chauvin JP, Bomont P. Sensorymotor deficits and neurofilament disorganization in gigaxonin-null
mice. Mol Neurodegener. 6:25. 2011.
47. Mo X, Liu D, Li W, Hu Z, Hu Y, Li J, Guo J, Tang B, Zhang Z, Bai
Y, Xia K. Genetic screening for mutations in the Nrdp1 gene in
Parkinson disease patients in a Chinese population. Parkinsonism
Relat Disord. 16(3):222-4. 2010.
48. Zhang L, Haraguchi S, Koda T, Hashimoto K, Nakagawara A.
Muscle atrophy and motor neuron degeneration in human NEDL1
transgenic mice. J Biomed Biotechnol. 831092. 2011.
49. Ying Z, Wang H, Fan H, Zhu X, Zhou J, Fei E, Wang G. Gp78, an
ER associated E3, promotes SOD1 and ataxin-3 degradation. Hum
Mol Genet. 18(22):4268-81. 2009.
50. Léger B, Vergani L, Sorarù G, Hespel P, Derave W, Gobelet C,
D'Ascenzio C, Angelini C, Russell AP. Human skeletal muscle
atrophy in amyotrophic lateral sclerosis reveals a reduction in Akt
and an increase in atrogin-1. FASEB J. 20(3):583-5. 2006.
36. Bellomaria A, Barbato G, Melino G, Paci M, Melino S. Recognition
of p63 by the E3 ligase ITCH: Effect of an ectodermal dysplasia
mutant. Cell Cycle. 9(18):3730-9. 2010.
51. Mashimo T, Hadjebi O, Amair-Pinedo F, Tsurumi T, Langa F,
Serikawa T, Sotelo C, Guénet JL, Rosa JL. Progressive Purkinje
cell degeneration in tambaleante mutant mice is a consequence of
a missense mutation in HERC1 E3 ubiquitin ligase. PLoS Genet.
5(12):e1000784. 2009.
37. Schwarz LA, Hall BJ, Patrick GN. Activity-dependent
ubiquitination of GluA1 mediates a distinct AMPA receptor
endocytosis and sorting pathway. J Neurosci. 30(49):16718-29.
2010.
52. Subramaniam S, Mealer RG, Sixt KM, Barrow RK, Usiello A,
Snyder SH. Rhes, a physiologic regulator of sumoylation, enhances
cross-sumoylation between the basic sumoylation enzymes E1 and
Ubc9. J Biol Chem. 285(27):20428-32. 2010.
38. Colledge M, Snyder EM, Crozier RA, Soderling JA, Jin Y,
Langeberg LK, Lu H, Bear MF, Scott JD. Ubiquitination regulates
PSD-95 degradation and AMPA receptor surface expression.
Neuron. 40(3):595-607. 2003.
53. Mori F, Nishie M, Piao YS, Kito K, Kamitani T, Takahashi H,
Wakabayashi K. Accumulation of NEDD8 in neuronal and glial
inclusions of neurodegenerative disorders. Neuropathol Appl
Neurobiol. 31(1):53-61. 2005.
39. Liu QY, Lei JX, Sikorska M, Liu R. A novel brain-enriched E3
ubiquitin ligase RNF182 is up regulated in the brains of Alzheimer's
patients and targets ATP6V0C for degradation. Mol Neurodegener.
3:4. 2008.
54. Kumar P, Ambasta RK, Veereshwarayya V, Rosen KM, Kosik KS,
Band H, Mestril R, Patterson C, Querfurth HW. CHIP and HSPs
interact with beta-APP in a proteasome-dependent manner and
influence Abeta metabolism. Hum Mol Genet. 16(7):848-64. 2007.
40. Babu JR, Geetha T, Wooten MW. Sequestosome 1/p62 shuttles
polyubiquitinated tau for proteasomal degradation. J Neurochem.
94(1):192-203. 2005.
55. Williams AJ, Knutson TM, Colomer Gould VF, Paulson HL. In
vivo suppression of polyglutamine neurotoxicity by C-terminus of
Hsp70-interacting protein (CHIP) supports an aggregation model
of pathogenesis. Neurobiol Dis.33(3):342-53. 2009.
41. Zucchelli S, Marcuzzi F, Codrich M, Agostoni E, Vilotti S, Biagioli
M, Pinto M, Carnemolla A, Santoro C, Gustincich S, Persichetti
F. Tumor Necrosis Factor Receptor-associated Factor 6 (TRAF6)
Associates with Huntingtin Protein and Promotes Its Atypical
Ubiquitination to Enhance Aggregate Formation. J Biol Chem.
286(28):25108-17. 2011.
42. Tanji K, Kamitani T, Mori F, Kakita A, Takahashi H, Wakabayashi
K. TRIM9, a novel brain-specific E3 ubiquitin ligase, is repressed
in the brain of Parkinson's disease and dementia with Lewy bodies.
Neurobiol Dis. 38(2):210-8. 2010.
43. Veeriah S, Morris L, Solit D, Chan TA. The familial Parkinson
disease gene PARK2 is a multisite tumor suppressor on chromosome
6q25.2-27 that regulates cyclin E. Cell Cycle. 9(8):1451-2. 2010.
44. Tsang AH, Lee YI, Ko HS, Savitt JM, Pletnikova O, Troncoso JC,
Dawson VL, Dawson TM, Chung KK. S-nitrosylation of XIAP
compromises neuronal survival in Parkinson's disease. Proc Natl
Acad Sci U S A.106 (12):4900-5. 2009.
45. Lee JT, Wheeler TC, Li L, Chin LS. Ubiquitination of alphasynuclein by Siah-1 promotes alpha-synuclein aggregation and
.apoptotic cell death. Hum Mol Genet. 17(6):906-17. 2008.
46. Yu F, Zhou J. Parkin is ubiquitinated by Nrdp1 and abrogates
Nrdp1-induced oxidative stress. Neurosci Lett. 440(1):4-8. 2008.
32
56. Fishman-Jacob T, Reznichenko L, Youdim MB, Mandel SA. A
sporadic Parkinson disease model via silencing of the ubiquitinproteasome/E3 ligase component SKP1A. J Biol Chem.
284(47):32835-45. 2009.
57. Furukawa Y, Vigouroux S, Wong H, Guttman M, Rajput AH, Ang
L, Briand M, Kish SJ, Briand Y. Brain proteasomal function in
sporadic Parkinson's disease and related disorders. Ann Neurol.
51(6):779-82. 2002.
WASTE TO ENERGY: MICROBIAL FUEL CELL A NOVEL
APPROACH TO GENERATE Bio-ELECTRICITY
Ishwar Chandra*
Amity Institute of Biotechnology, Amity University, Noida sector-125, UP, India
ABSTRACT
This compiled work is a brief on Microbial fuel cell, a future technology to generate electricity, simultaneously cleaning
the water and solving many problems related to cleaner fuel production. The aim of this report is to familiarize people
about this technology, as it can solve multiple problems of fuel, water and electricity. This is focused because it is easy
to operate, economic, stable and effective in use. In a country like India where tons of waste is generated daily can be
used as such for this purpose without any modification or with little modification. The report comprises introduction to
MFC, its materials used for construction and different designs which can help you to build your own MFC.
Keywords: Microbial fuel cells, Waste water treatment, Microbes, Electricity, Fuels
1. INTRODUCTION
In India waste is generated in bulk, while its maintenance
and control is very limited. As the fossil fuels and energy
resources are on the verge of completion, all eyes are on
renewable energy sources and green energy. Scientists are
trying to find new technologies for electricity generation
from cheaper sources without polluting environment.
MFC, Microbial fuel cells are one of those renewable
source of energy for the production of electricity from
waste. Microbial fuel cells are batteries that generate
current using organic source as a raw material with the
aid of microbes. It is a catalytic reaction where the organic
matter is oxidised in anaerobic conditions and charges are
generated, which in turn produces current in a system.
Fig. 1 shows a schematic diagram of a typical microbial
fuel cell (MFC). As can be seen in figure, it consist
of anode chamber (where organic waste is oxidised),
cathode chamber (consisting of an electrolyte solution)
and a proton exchange membrane, all connected to a load
through an external circuit.
Fig. 1: Working of a typical microbial fuel cell (MFC)
Microbes here play a very vital role in oxidising the
organic waste. Microbes generate electrons and protons
by oxidizing organic waste at the anode in the absence
of oxygen. Electrons that are produced in this process are
transferred to cathode chamber through an external circuit
while the protons diffuse through the proton exchange
membrane to the cathode, where electrons combine with
protons and oxygen to form water. Thus in this way water
is produced at the cathode chamber. Oxidising the organic
substance is not the only important thing, but the transfer
of the electrons to the electrode is also an important aspect.
Here also microorganism comes into play. A general
reaction taking place is as follows:
Glucose as a substrate fuel
Ishwar Chandra
Amity Institute of Biotechnology, Amity University,
Noida sector-125, UP, India
*
Anode: C6H12O6 + 6H2O → 6CO2 + 24H+ + 24eCathode: 6O2 + 24H+ +24 e-→12H2O
Overall: C6H12O6 + 6O2 → 6CO2 + 6H2O + electricity
33
Ishwar Chandra: WASTE TO ENERGY: MICROBIAL FUEL CELL A NOVEL APPROACH TO GENERATE Bio-ELECTRICITY
Acetate (typical for wastewater) as a substrate fuel
Anode: CH3COOH + 2H2O →2CO2 + 8H+ + 8eCathode: 2O2 + 8H+ + 8e-→ 4H2O
Overall: CH3COOH + 2O2 →2CO2 + 2H2O + electricity
MFC are constructed in lab scale generating current in
different range. MFC are also gone to a large scale ex
Benthic microbial fuel cell (BMFC) The benthic microbial
fuel cell (BMFC) is a field-deployable and uniquely
configured microbial fuel cell that relies on the natural
redox processes in aqueous sediments[1].
Basicaly there are two types of MFC, Mediator microbial
fuel cell Most of the microbial cells are electrochemically
inactive. The electron transfer from microbial cells to
the electrode is facilitated by mediators such as thionine,
methyl viologen, methyl blue, humic acid, neutral red and
so on[2,3]. Most of the mediators available are expensive
and toxic.
The ideal mediator has the following properties: i) It
should display reversible redox reaction to function as an
electron shuttle; ii) It should have appreciable solubility
in an aqueous solution and stability; iii) It should freely
penetrate the cell membrane to capture electrons; and
iv) It should have low formal potential. The lower the
formal potential, the larger the cell voltage since it is the
difference between the cathode and anode potentials[4].
Mediator-free microbial fuel cell do not require a mediator
but uses electrochemically active bacteria to transfer
electrons to the electrode (electrons are carried directly
from the bacterial respiratory enzyme to the electrode).
Among the electrochemically active bacteria are
Shewanella putrefaciens[5].
compounds to carbon dioxide while transferring electrons
to electrodes with extraordinarily high efficiencies.
Electricigens make it possible to convert renewable
biomass and organic wastes directly into electricity
without combusting the fuel, which wastes substantial
amounts of energy as heat[7]. There are different types of
microbes which are used in MFC for electron transfer.
Each microbe has its own kind of mechanism for voltage
generation and voltage output. Thus current produced is
also dependent on the type of microbe. Table 1 summarises
some of the microbes used in different types of MFC to
generate current. One of the most successful microbes
used now days is Geobacter sulfurreducens which can
enhance the amount of current in an MFC. Geobacter
sulfurreducens produces current densities in MFC that
are among the highest known for pure cultures[8]. Most of
the MFC operate at normal temperature range but some
also operate at mesophilic temperatures with an increased
power density and coulombic efficiency, Firmicutes
Thermincolasp.strain JR was isolated from mesophilic
MFC. Firmicutes Thermincolasp.strain JR,not only
produced more current than known organisms it also did
demonstration of direct anode reduction by a member of
this phylum first time[9]. Systematic study of microbial fuel
cells comprised of thermophilic Bacillus licheniformis
and Bacillus thermoglucosidasius has been carried out
under various operating conditions. Substantial amount of
electricity was generated when a redox mediator was used.
Being affected by operation temperature, the maximum
efficiency was obtained at 50oC [10].
The power output of the MFC depends on various factors
like type of inoculum microbes, material used for anode
and cathode, proton exchange membrane. One more factor
affecting the power of the MFC is size of cathode area.
It has a large impact on the migration and conversion of
proton and electron on electrode, resulting the change
in the internal resistance of the MFC, and affecting the
MFC output power, and the type of waste product being
oxidised. Geometric position of the anode and cathode
also affect the fuel cell power performance[6].
2. ELECTRICIGENS: MICROBES
GENERATING ELECTRICITY
USED
IN
Electricity producing micro-organisms, are known as
electricigens. Electricigens are recently discovered
microorganisms with the ability to oxidize organic
34
Fig. 2: Geobacter fuel cells powering a calculator.
3. DIFFERENT
ANODE
MATERIALS FOR MFC
AND
CATHODE
Anode materials- Graphite anodes are the most abundantly
used one[11]and its cost is also low. They are porous metal,
therefore graphite anodes used for MFC are pre-treated
with oil or wax to prevent internal pores deterioration
by mechanical & chemical action on anode that cause
softening & swelling, oiling and waxing results in reduced
penetration of the electrolyte and increased mechanical
strength. Carbon paper and carbon clothes are also used,
mainly for the lab-scale study of current generations[12].
Cathode materials- Cathode are usually made up of
platinum[12], major concern is the optimization of MFC
design in order to maximize power output and reducing
installation and operation costs simultaneously[13]. The
cost of the Platinum catalyst used at the cathode is a major
limitation to MFC application and economic viability. For
this reason some researchers have recently started working
on the Concept of bio-cathodes that would use bacteria
instead of Platinum as a biocatalyst at the cathode[12, 14].
Sometime same anode and cathode materials are used
in the construction of MFC[15]. The electrodes are made
from carbon rods, inert metals can also be used, metals
such as copper, iron, zinc, aluminium etc should be
avoided as they may give rise to spurious generation of
current from electrochemical dissolution of the metal[16].
Solar energy can serve as an alternative energy source for
MFC operation[17] proposed the concept of a ‘living solar
cell’ in which the green alga Chlamydomonas reinhardtii
produces hydrogen photosynthetically which in turn is
oxidized in situ to produce current. Phototrophic MFCs
represent an approach to convert solar energy into electric
energy through photosynthetic microorganisms[18].
Table 1: Various microbes used in MFC
Microorganism
Waste source
Aim
Reference
Clostridium acetobutylicum
and Clostridium
thermohydrosulfuricum.
Cellulosic Waste
Bioelectricity
production
Abhilasha S and
Mathuriya et al, 2009
Yogurt bacteria and methylene
blue as mediator
Waste Carbohydrate
(manure sludge)
Bioelectricity
production
Keith Scott et al,2007
Pseudomonas putida,
Saccharomyces cerevisiae,
Lactobacillus bulgaricus,
Escherichia coli and
Aspergillus niger
Glucose
Low Voltage Power
Generation
M. Rahimnejad et al,
2009
Anaerobic mixed consortia
Waste Water
Bioelectricity
production
S. Venkata Mohan et
al, 2007; O. Lefebvre
et al, 2008
Mixed population
Decay Organics
Bioelectricity
production
Reimers et al., 2001
Shewanella putrefaciens
Starch WW
Bioelectricity
production and waste
water treatment
Gil et al, 2003
Geobacter sulpfurreducens
Acetate
Bioelectricity
water treatment
Bond & Lovley, 2003
Synechococcus sp.
Light as a fuel
Bioelectricity
production
Tsujimura et al., 2001
35
Activated sludge
Glucose
Bioelectricity
production
Park & Zeikus, 2003
Mixed population
Glucose
Bioelectricity
production
Rabaey et al., 2003
Mixed population
Sugar WW
Bioelectricity
water treatment
Habermann &
Pommer, 1991
Geobacteraceae
Organic matter in
marine sediments
Open lakeèlectricity
and bioremediation of
organic contaminants
in Subsurface
environments
Daniel R.Bond et al,
2002
Some studies have revealed gene expression of certain
microbes resulting in the high density current production,
a study demonstrate that G.sulfurreducens biofilms
producing relatively high levels of current have substantial
differences in their electron-transfer capabilities compared
with biofilms growing on the same graphite surface, but
with fumarate serving as the electron acceptor. These
differences are associated with changes in expression of a
small number of genes primarily encoding outer surface,
electron- transfer proteins[19]. The electrodes can be dipped
in suitable electrolytic solution dissolved in appropriate
buffer and pH. Proton exchange membrane also called
as Cation exchange membrane (CEM), such as Nafion
[20,21,22,23]
, Ultrex[24] or a normal salt bridge[23, 25] are used
now days. Fig. 3-12 shows various designs of MFC.
4. SOME OF THE EXAMPLES
DIFFERENT DESIGNS OF MFC
SHOWING
4.1 Large scale MFC design
Fig. 3: Fuel Cell, showing cathode carbon-brushes (1 arrow) and
graphite plate mounted to a PVC plate above the load housing and
battery. The anode is buried to the right so that only the PVC cap and
handle are visible. Fuel Cell1 is in the background (2 arrow) [26]
36
4.2 Lab scale MFC design
Fig. 4: Tellurite Ion Set up. Tellurium is being deposited in the second
tube so as shown by the dark color (from : Kehinde Adeyemo Howard
University, The Use of Rhodobacter sphaeroides in Microbial Fuel
Cells)
Fig. 5: Microbial fuel cells (MFC) for the treatment of waste water.
Photograph of the set-up of drawing.
5. DIFFERENT APPLICATIONS OF MFC
1. Waste water treatment and electricity generation:
Application of microbial fuel cell (MFC) for
wastewater treatment could be an attractive
alternative to reduce the cost of treatment and generate
electricity. BOD and COD of the waste water can be
minimized using this technique and hence resulting
in water purification. Thus this dual purpose design is
economically stable[11].
Fig. 6: Single chamber MFC, where cathode and anode are at opposite
end soft he reactor chamber.Copyright 2004 American Chemical
Society.
2. Hydrogen production: Hydrogen is also one of the most
important gaseous fuels used. Hydrogen production is
also reportedly done using suitable MFC of certain
microbes either immobilized on electrode or freely
dispensed as a mixed consortium in some medium.
Microbial fuel cell based on the hydrogen evolution
by immobilized cells of Clostridium butyricum was
reported[27].
3. Electricity generation from sediments in a lake and
pond: Several years ago, Leonard Tender of the
Naval Research Laboratories in Washington, D.C.,
and Clare Reimers of Oregon State University in
Corvallis developed systems in which electricigens
produce electricity from mud! When a slab of graphite
(the anode) is buried in an aerobic marine sediment
sand then connected to another piece of graphite (the
cathode) that is suspended in the overlying aerobic
water, electricity[7] was produced.
Fig. 7: MFC designed by S. Venkata Mohan et al 2007
Fig. 8: Biofuel cell designed by M.Rahimnejad et al, 2009
Fig. 9: Sediment fuelcell. Prior to deployment in salt marsh sediments
on Nantucket Island, Mass.
37
6. DISCUSSION
Microbial fuel cells (MFC) are future clean energy
technology. MFC’s are capable of solving multiple
problems of waste water treatment, electricity generation
and hydrogen production. Cost of investment is law and
it is easily operated. This technology is very useful for
remote areas where electricity cannot be supplied. MFC
can be scaled-up to produce more power, it can also be
categorized as a safe waste disposal technology where
multiple problems are solved simultaneously. It can also
be used as a biosensor (medical device) for detecting
certain biological molecule. While low current density
and long time of operation is its biggest drawbacks. Many
scientists are working on suitable MFC design to increase
the current density. It’s been believed that MFC will be
one of the main sources of electricity generation and waste
water treatment technology in future.
REFERENCES
Fig. 10: Deployed sediment fuel cells.
4. Robot EcoBot-II (Bristol, 2007)
Fig. 11: Robot EcoBot-II, It is designed to power itself solely by
converting unrefined insect biomass into useful energy using on-board
microbial fuel cells with oxygen cathodes ( Source: http://en.wikipedia.
org/wiki/EcoBot).
Fig. 12: Benthic Unattended Generator (BUG) Weather buoy, Potomac
River, The Naval Research Laboratory's Center for Bio/Molecular
Science and Engineering, Washington. (Source: http://www.nrl.navy.
mil/code6900/bug/).
38
1.
C. E. Reimers, P. Girguis, H. A. Stecher iii, L. M. Tender,
N. Ryckelynck And P. Whaling, Microbial fuel cell energy
from an ocean cold seep. Geobiology, 4, 123–136. 2006
2.
Lithgow, A.M., Romero, L., Sanchez, I.C., Souto, F.A.,and
Vega, C.A. Interception of electron-transport chain in
bacteria with hydrophilic redox mediators. J. Chem.
Research, (S), 178–179. 1986
3.
Kim, B.H., Kim, H.J., Hyun, M.S., Park, D.H., Direct
electrode reaction of Fe (III) reducing bacterium Shewanella
putrefacience. J Microbiol. Biotechnol. 9, 127–131. 1999
4.
Kim, N., Choi, Y., Jung, S. and Kim, S. . Development of
Microbial Fuel Cells using Proteus vulgaris. Bull. Korean
Chem. Soc, 21 (1), 44-48. 2000
5.
Cuong, A.P. , Jung, S.J., Phung, N.T., Lee, J., Chang, I.S.,
Kim, B.H., Yi, H. and Chun, J., A novel electrochemically
active and Fe(III)-reducing bacterium phylogenetically
related to Aeromonas hydrophila, isolated from a microbial
fuel cell. FEMS Microbiol. Lett., 223(1): 129-134. 2003
6.
Keith Scott, and Cassandro Murano, Microbial fuel cells
utilising carbohydrates. J Chem Technol Biotechnol, 82,
:92–100. 2007
7.
Derek R. Lovley, Microbial Energizers: Fuel Cells That
Keep on Going Microbes that produce electricity by
oxidizing organic compounds in Biomass may someday
power useful electronic devices. Microbes, 1(11), 323-329.
2006
8.
Hana Yi, Kelly P. Nevin, Byoung-Chan Kim, Ashely E.
Fraks, Anna Klimes, Leonard M. Tender, Derek R. Lovley,
Selection of a variant of geobecter sulfurreducens with
enhanced capacity for current production in microbial fuel
cells. Biosensors and Bioelectronics, 24, 3498-3503. 2009
9.
Kelly C Wrighton, Peter Agbo, Falk Warnecke, Karrie A
Weber, Eoin L Brodie, Todd Z DeSantis, Philip Hugenholtz,
Gary L Andersen and John D Coates, A novele cological
role of the Firmicutes identified in thermophilic microbial
Fuel cells. The ISME Journal, 2, 1146–1156. 2008
21. Park,D.H.; Zeikus,J.G. Utilization of electrically reduced
neutral Red by Actinobacillus succinogenes: physiologica
lfunction of Neutral red in membrane-driven fumarate
reduction and energy conservation. J.Bacteriol., 181, 24032410. 1999
10. Youngjin Choi, Eunkyoung Jung, Hyunjoo Park, Seung R.
Paik, Seunho Jung, and Sunghyun Kim, Construction of
Microbial Fuel Cells Using Thermophilic Microorganisms,
Bacillus licheniformis and Bacillus thermoglucosidasius.
Bull. Korean Chem. Soc., 25(6), 813-816. 2004
22. Logan,B.E.; Murano,C.; Scott,K.; Gray,N.D.; Head, I.M.,
Electricity generation from cysteine in a microbial fuel cell.
Water Res., 39, 942-952. 2005
11. M.M. Ghangrekar and V.B. Shinde, Wastewater Treatment
in Microbial Fuel Cell and Electricity Generation: A
Sustainable Approach , Paper presented in the 12th
international sustainable development research conference,
April 6-8, 2006.
12. O.Lefebvre, A.Al-Mamun and H.Y.Ng, A microbial fuel
cell equipped with a biocathode for Organic removal and
denitrification. Water Science & Technology, 58.4, 281-285.
2008
13. Lefebvre, O., Al-Mamun,A., Ooi,W.K., Ng,H.Y., Tang,Z.&
Chua,D.H.C. An insight into cathode options for microbial
fuel cells. Water Sci.Technol. 57, 2031–2037. 2008
14. He,Z. & Angenent,L.T. 2006 Application of bacterial
biocathodes in microbial fuel cells. Electroanalysis, 18(1920), 2009–2015.
15. Daniel R.Bond, Dawn E. Holmes, Leonard M.Tender,
Derek R.Lovley, Electrode-Reducing Microorganisms That
Harvest Energy from Marine Sediments, Science 295(1),
283-285. 2002.
23. Min,B.; Cheng,S.; Logan,B.E. Electricity generation using
membrane and salt bridge microbial fuel cells. Water Res.,
39, 1675-1686. 2005
24. Rabaey,K.; Lissens,G.; Siciliano,S.D.; Verstraete,W.,
A microbial Fuel cell capable of converting glucose to
electricity at high rate And efficiency. Biotechnol. Lett., 25,
.1531-1535. 2003
25. Bruce E .Logan, Bert Hamelers, Rene Rozendal, Uwe
Schroder, Jurg Keller, Stefano Freguia, Peter Aelterman,
Willy Verstraete, and Korneel Rabaey, Microbial Fuel Cells:
Methodology and Technology. Environ. Sci. & technol, 20,
11.5 A-11.5L. 2006
26. C. E. Reimers, p. Girguis, H. A. Stecher iii, L M.
Tender, N. Ryckelynck and P. Whaling, Microbial fuel cell
energy from an ocean cold seep. Geobiology, 4, 123–136.
2006.
27. I.Karube,T.Matsunaga,S.Tsuru,S.Suzuki, Biochemical fuel
cell utilizing immobilized cells of Clostridium butyricum.
Biotechnol.Bioeng., 19, 1727–1733. 1977
16. H.P.Bennetto, Electricity generation by microorganism.
Biotechnology education, 1(4), 163-168. 1990
28. Uwe Schroder, Juliane Nießen, and FritzScholz, A
Generation of Microbial Fuel Cells with Current Outputs
Boosted by More Than One Order of Magnitude. Angew.
Chem., 115, 2986–2989. 2003
17. Rosenbaum,M., Schröder,U., Scholz,F.,.Utilizing the green
alga Chlamydomonas reinhardtii formicrobial electricity
generation: a living solar cell. Appl.Microbiol.Biotechnol.,
32, 753–756. 2005
29. Abhilasha S Mathuriya, V N Sharma, Bioelectricity
production from paper industry waste using a microbial fuel
cell by Clostridium species. J Biochem Tech, 1(2), 49-52.
2009
18. He,Z., Kan,J., Mansfeld,F., Angenent,L.T., Nealson,K.H.,
Self-sustained Phototrophic microbial fuel cells based
on the synergistic cooperation between Photosynthetic
microorganisms and heterotrophic bacteria. Environ.Sci.
Technol. 43, 1648–1654. 2009.
30. Keith Scott, Cassandro Murano, Microbial fuel cells
utilising carbohydrates. J Chem Technol Biotechnol, 82,
92–100. 2007
19. Kelly P. Nevin1., Byoung-Chan Kim.,Richard H.Glaven ,
Jessica P.Johnson, TrevorL.Woodard, Barbara A. Methe ,
RaymondJ.DiDonato,Jr., SeanF.Covalla1, Ashley E.Franks,
Anna Liu, Derek R., Anode Biofilm Transcriptomics
Reveals Outer Surface Components Essential for High
Density Current Productionin Geobacter sulfurreducens
Fuel Cells. Plos ONE, 4(5) , e5628. 2009.
20. Bond, D. R.; Holmes,D. E.; Tender, L. M.; Lovley, D. R.
Electrode reducing microorganisms that harvest energy
from marine sediments. Science, 295,483-485. 2002
31. M.Rahimnejad, N.Mokhtarian, G.D. Najafpour, W.
Ramli Wan Daud and A.A. Ghoreyshi, Low Voltage Power
Generation in aBiofuel Cell Using Anaerobic Cultures.
World Appl. Sci. J., 6 (11) , 1585-1588. 2009
32. S. Venkata Mohan, S. Veer Raghavulu, S. Srikanth and P. N.
Sarma, Bioelectricity production by mediatorless microbial
fuel cell under acidophilic condition using wastewater
as substrate: Influence of substrate loading rate. Current
Science, 92(6) , 12- 25. 2007.
39
Suggested Reading
Bond, D.R., D.E. Holmes, L.M. Tender, and R.Lovley. Electrode
reducing microorganisms harvesting energy from marine
sediments. Science, 295, 483–485.2002
Chaudhuri, S.K., and D.R.Lovley.. Electricity from direct
oxidation of glucose inmediator-less microbial fuel cells. Nature
Biotechnol., 21, 1229–1232. 2003
Gregory, K.B., and D.R. Lovley.. Remediation and recovery
of uranium from contaminated subsurface environments with
electrodes. Environ.Sci.Technol. 39, 8943–8947. 2005
Logan,B.E., Simultaneous waste water treatment and biological
electricity generation. WaterSci.Technol., 52:31–37. 2005
Rabaey,K.,and W.Verstraete. Microbial fuel cells novel
biotechnology for energy generation. Trends.Biotechnol., 6,
291–298.2005
Reguera, G., K.D.McCarthy, T.Mehta, J.Nicoll, M.T.Tuominen,
and D.R. Lovley. Extracellular electron transfer Via microbial
nanowires. Nature 435, 1098–1101. 2005
Shukla,A.K., P.Suresh, S.Berchmans, and A.Rahjendran,.
Biological fuel cells and their applications. Curr.Sci., 87, 455–
468. 2004
Derek R. Lovley, Microbial Energizers: Fuel Cells That Keep
on Going Microbes that produce electricity by oxidizing organic
compounds in Biomass may someday power useful electronic
devices. Microbe, 1(11), 323-329. 2006
Biofuels Engineering Process Technology Caye M. Drapcho,
Nghiem Phu Nhuan, Terry H. Walker, in 2008 by The McGrawHill Companies.
40
CYTOTOXICITY AND CELL ADHESION PROPERTIES OF HUMAN
MESENCHYMAL STEM CELLS IN ELECTROSPUN NANOFIBER
POLYMER SCAFFOLDS
Zaynah Welcome1, Hongzhuan Wu1, Elijah Nyairo2*, Christian Rogers2, Derrick Dean3,
Kennedy Wekesa1, Karyn Gunn1, Robert Villafane1
Department of Biological Sciences, 2Center of Nanobiotechnology Research
Alabama State University, Montgomery, AL 36101, USA
3
Department of Materials Science and Engineering
University of Alabama at Birmingham, Birmingham, AL 35294, USA
1
ABSTRACT
Biodegradable polymer nanofiber scaffolds have high porosity; with interconnected pores and high surface area-tovolume ratio that makes them ideal for tissue regeneration and drug delivery applications. In this work, biodegradable
polymer nanofiber mats were produced by electrospinning polycaprolactone (PCL). The PCL, and PCL/ Hydroxyapatite
(HA) scaffolds were characterized using Scanning Electron Microscope (SEM), Differential Scanning Calorimeter
(DSC), and Fourier Transform Infrared Spectroscopy (FTIR). The cytotoxic properties of nanofiber scaffolds were
evaluated in vitro cell culture system with human embryonic palatal mesenchymal (HEPM) cells. Cellular injury
induced by nanofiber scaffolds were evaluated by measuring cell viability with 3-(4,5-dimethylthiazol-2-yl)-5-(3carboxymethoxy phenyl)-2-(4-sulfophenyl)-2H-tetrazolium compound (MTS). The overall data indicates PCL could be
used as a substitute material for bone tissue regeneration. Bone morphogenic protein (BMP)-2 added along with HA and
PCL showed enhanced cell adhesion around nano-scaffolds.
Keywords: tissue regeneration, scaffolds, tissue engineering, cytotoxicity, cell adhesion
1. INTRODUCTION
Bone is a highly vascularized tissue and is classified
into two categories[1-3], cortical or dense, compact bone
(low porosity: 10%, modulus: 12-18 GPa, ultimate
tensile strength: 50-150 MPa) and cancellous or spongy,
trabecular bone (high porosity: 75%, modulus: 10-500
MPa, ultimate tensile strength: 10-20 MPa). Bone is a
natural nanocomposite material and consists of two major
components: cells and the extra cellular matrix (ECM).
The ECM present in the bone skeleton is a highly porous
three-dimensional structure with nanoscale morphology.
It consists of various body proteins such as collagen and
serves as the mineral pool for hydoxyapatite (HA), which
is composed mainly of calcium and phosphate. Cells bind
to the components of the ECM[2]. Scaffolds are man-made
replicas of this natural ECM based on synthetic material.
Elijah Nyairo
Center of Nanobiotechnology Research
Alabama State University, Montgomery, AL 36101, USA
*
Tissue regeneration is a viable option that avoids
problems associated with transplantable grafts. Scaffolds
made from biodegradable polymers are engineered
and implanted to facilitate repair of damaged tissue.
The scaffolds are designed to provide an environment
conducive to cell growth which helps expedite the
regeneration process[4-5]. Furthermore, multifunctional
scaffolds can be engineered to repair injured tissues while
providing growth-aiding proteins or delivering drugs to
treat the injured site in a manner that reduces problems
associated with other types of drug delivery[6-8].
Research within the last few years shows substantial gains
in the use of an artificial extracellular matrix (scaffold) to
support bone tissue regeneration. In order to obtain new
tissue growth, the scaffold must exhibit biocompatibility,
large surface area, porosity, appropriate mechanical
properties and enhanced cell adhesion[9-13]. A scaffold for
tissue engineering can be looked at as a surrogate ECM[14].
The natural ECM not only contributes to mechanical
integrity, but also serves as a signaling and regulatory
41
Welcome Z. et. al. CYTOTOXICITY AND CELL ADHESION PROPERTIES OF HUMAN MESENCHYMAL STEM CELLS IN ELECTROSPUN
NANOFIBER POLYMER SCAFFOLDS
unit in the development, and maintenance of tissue
generation, with the aid of growth factors, hormones,
and gene expression[10, 14-16]. Both chemical and structural
biocompatibility is important in successful scaffold
design, and this is determined by material selection and
architecture, respectively. The chemical characteristics of
a material surface will mediate the adsorption of biologic
molecules that regulate cell activities, such as adhesion
and migration[17-18].
Scaffolds are currently made from a bioabsorbable
material, which degrade as the cells grow in, and repair the
tissue and therefore do not require a second surgery for
scaffold removal. In addition to the natural polymer
collagen, Polyglycolic acid (PGA), poly (D,L-lactide-coglycolide) (PLGA), and polycaprolactone (PCL) are
examples of synthetic biodegradable polymers which have
been successfully used to make scaffolds for tissue
regeneration[19]. The goal of this study is to mimic the
ECM by understanding the fundamental mechanisms
involved in the adsorption and release of therapeutics from
PCL nanofiber scaffolds. The scaffold must exhibit
biocompatibility, appropriate mechanical properties and
enhanced cell adhesion for new tissue growth. Our
research also takes particular interest in HA, since, by
depositing it onto the fibers, we can more closely mimic
the ECM of bone and can help control release rate of the
growth factor, BMP-2. BMP-2 and HA that can be
absorbed, and integrated into biodegradable scaffolds.
Hydroxyapatite is a major inorganic component of bone.
This component can be used as a signaling mechanism for
the cells because is it bioactive. HA is produced from
calcium carbonate in marine coral through a technique of
phosphoric acid processing and hydrothermal.
slower rate than for example, PGA and therefore has
been studied in controlled drug release systems and longterm implant devices. PCL has some unusual properties
including low glass transition temperature (-66°C)
and melting temperature (60°C), but a high thermal
stability. These properties are related to PCL’s chain of
carbons, since longer chains give rise to lower melting
temperatures (Tm) and glass transition temperatures
(Tg). Biodegradable bone scaffolds provide a promising
alternative for regenerating bone tissue with optimum
functional and mechanical properties.
2. MATERIALS AND METHODS
2.1 Materials
PCL with an inherent viscosity of 1.24 dL/g in
chloroform was received from Absorbable Polymers
LLC (Birmingham, AL). HA nanopowder with particles
of 100–150 nm diameters and 15 m2 g−1 surface area was
purchased from Nanocerox, Inc. (Ann Arbor, MI).
2.2 Preparation of Nanofibrous Scaffolds by
Electrospinning
PCL pellets were dissolved in a chloroform/methanol
mixture (3:1 v/v). The polymers were dissolved using a
magnetic stirrer to achieve approximately a ~13-wt%
solution, transferred to a 20 mL syringe with 251/2 guage
needle and electrospun at a high voltage (GAMMA High
Voltage Research, Ormondo Beach, FL) of 15kV to create
nanofibers (Fig. 1). A feeding rate of 3.6 ml/h was set in
an F100 Syringe Pump (Chemyx Inc, Houston TX) and a
grounded aluminum collector plate was placed 12-15 cm
from the tip of the needle.
Chemical Structure of Poly (ε-caprolactone) (PCL)
Poly (ε-caprolactone) (PCL) is a semicrystalline,
bioresorbable, aliphatic polyester and its degradation
products are metabolised via the tricarboxylic acid (TCA)
cycle. Extensive in vitro and in vivo biocompatibility and
efficacy studies of PCL have been performed resulting in
the US Food and Drug Administration (FDA) approval for
use in a number of biomedical devices[20-23]. PCL can be
electrospun into nanofiber scaffolds with high porosity,
interconnected pores and high surface area-to-volume
ratio that makes them ideal for bioengineering applications
and drug delivery applications. PCL degrades at a much
42
Fig.1 Schematic representation of electrospinning set-up consists of
a syringe pump, high voltage source, solution needle and grounded
aluminum collector
2.3. Electrophoretic Deposition of Hydroxyapatite onto
Fibers
To coat the individual nanofibers of the scaffold with
HA nanoparticles, the electrophoretic deposition method
was implemented. The HA nanoparticles dispersion was
prepared by mixing 7.5 gm HA powder in 250 ml isopropyl
alcohol to which 1 wt % polyvinyl butyrate (PVB) was
added as a surfactant. This was followed by sonication
of the mixture for 3 h at ambient temperature to break
all agglomerates and achieve a good dispersion of HA
nanoparticles in the solution. The PCL/HA solution was
electrospun and the process parameters such as electric
filed, feed rate and distance between the needle and the
collector were kept the same as for electrospinning of neat
PCL.
2.4 Characterization of PCL and PCL/HA
Nanocomposite Scaffolds
2.4.1 Scanning Electron Microscopy (SEM)
SEM (Philips SEM 510) was used for determining
and optimizing the fiber morphology of PCL and
PCL/HA scaffolds. Samples were sputter coated
with Gold. The coated samples were examined
at an accelerating voltage of 10 kV. SEM
micrographs were analyzed by an image-analyzer
(Image –proplus, Media Cybernetics Co., USA)
for the measurement of fiber diameters.
2.4.2 Differential Scanning Calorimetry (DSC)
DSC experiments were carried out to determine
the differences in crystallinity of PCL compared
to the electrically spun PCL fibers and due to
the presence of HA during electrospining. The
polymer samples (15 mg) were ramped at 10◦C/
min to 100◦C in a DSC instrument (DSC Q 2000,
TA Instruments, New Castle, DE).
2.4.3 Fourier-Transform Infrared (FTIR)
Spectroscopy
FTIR spectra of polymer nanofiber samples were
recorded in the attenuated total reflection (ATR)
mode using an IR spectrophotometer (Thermo
Fisher Co., USA). The spectra were obtained
with 32 scans per sample ranging from 4000 to
400 cm-1.
2.5 Absorption and Release of Therapeutics from
Scaffolds
The PCL, PCL/HA scaffolds of 6mm diameter were placed
in 2.0 mL low retention (Fisher Scientific) microtubes
followed by addition of 250 µL of recombinant human
BMP-2 (R&D Systems, Minneapolis, MN) at 0.25 µg/
mL in Phosphate Buffer Saline (PBS) solution without
Ca2+ and Mg2+ at pH 7.4. The sample was incubated for
24 h at 4oC without shaking and the remaining solution
was collected from tubes and saved for detecting unbound
BMP-2. The loosely attached proteins were removed
by washing the scaffold with 1 mL of PBS. The coated
scaffold was held at 37oC in 1mL of PBS with shaking
at 150 rpm (Fig. 2). To measure the concentration of the
therapeutics released, 200µL of solution from each tube
was transferred at different time intervals (day 0, 1, 2, 7,
14, and 21) and stored at 4oC in low retention microtubes
for detection of BMP-2 released from scaffolds by ELISA
(Enzyme-Linked Immuno Sorbent Assay). 100 µL of
fresh PBS was added to the original 1mL of BMP-2 + PBS
solution.
Fig. 2: Schematic representation of Release study process
2.6 Cell Culture
Human embryonic palatal mesenchymal cells (HEPM)
were purchased from ATCC (Manasas, VA). The HEPM
cells were grown in differentiation media that constitutes
Eagles Minimal Essential Medium (EMEM) containing
10% fetal bovine serum, 0.1% Penicillin-StreptomycinAmphotericin B solution, and cells from passages 5-9 were
used in this study. In this medium, the cells appeared to
have a homogenous, fibroblast-like appearance and upon
exposure to differentiation media, all of the cells acquired
an osteoblastic, cuboidal morphology; and formed a
mineralized matrix. This has also been confirmed by
others[24]. HEPM cells were seeded onto disks and allowed
to adhere to the scaffolds to evaluate early and late cell
spreading. Following this incubation, cells were fixed
with 3.7% formaldehyde, permeabilized with 0.2% Triton
X-100, and then exposed to antibody specific for paxillin,
a protein that is localized to focal adhesion structures[25].
2.7 Cytotoxicity
Cells were plated in 96-well culture plates at approximately
5000 cells/well and exposed to fibers without drug loadings.
The treated cells were then assayed for viability using a
MTS (3-(4,5-dimethylthiazol-2-yl)-5-(3-arboxymethoxy
phenyl)-2-(4-sulfophenyl)-2H-tetrazolium)
solution (2 mg MTS/2 mL PBS) after 48h. MTS is
reduced by metabolically active cells resulting in purple
formazan which can be quantified spectrophotometrically.
Cells were treated with MTS for 30 min. Basal medium
was added to each well and the optical density, which is
43
proportional to living cells, was analyzed on a microplate
reader (Tecan Sunrise™, San Jose, CA).
2.8 Cell Adhesion Assays
CONTROL
PCL
PCL/HA
One hour incubation was selected because it was previously
determined that this time interval was sufficient to allow
tight attachment and initiation of cell spreading, whereas
the potential secretion of pro-adhesive matrix components
by the cells was minimized.
3.0 RESULTS AND DISCUSSION
Fig. 4: SEM image of PCL scaffolds (x 3.7 k)
Fig. 3: Images of Cell Adhesion taken with Nikon fluorescent
microscope at 20x, at time intervals 1, 2, 4, and 6 hours for control,
PCL, and PCL/HA. As time elapsed, all samples’ attachment increased.
At hour 6, PCL scaffold’s attachment matched that of the control (85%
attachment).
Disks of a uniform size (6mm) were punched from sheets
of electrospun fibers. Side-by-side adhesion assays were
performed with the fibers, plus and minus HA crystals.
Blends composed primarily of synthetic polymers with the
biomimetic RGD peptides were coated with the goal of
enhancing cell/materials associations.
The RGD
biomimetic peptide is known to facilitate cell adhesion by
engaging cell surface integrin receptors[26]. To evaluate
cell adhesion, HEPM cells were pre-labelled with a Cell
Tracker Green fluorescent dye (Molecular Probes) and
ProLong® Gold antifade reagent with 4',6-diamidino-2phenylindole (DAPI) (Fig. 3), a fluorescent stain
(Invitrogen, Grand Island, NY), and then seeded onto the
disks at 2.0 x 104 in a 96-well plate. Cells were allowed to
adhere for 1, 2, 4, and 6 hours. Attachment was also
quantified by a method widely described[27] where the
media along with two washes in PBS were collected, and
at each time interval cells were counted in supernatant.
The formula was used to calculate attachment[27].
SEM images of electrospun fibers collected using a static
collection target are shown (Fig. 4 and 5). Nanofibrous
PCL scaffolds show a randomly woven pattern because
they were collected on a stationary collecting plate. They
comprise more or less uniform fiber morphology with
interconnected pore structure. As the concentration of the
HA in the fibers increases, the fibers become rougher as
seen in fig. 5 compared to the neat PCL in fig. 4.
Fig. 5 SEM image of PCL + 10%HA (x5.5 k) composite scaffolds
A majority of the pure PCL and PCL+10%HA composite
fibers have diameters of 450±100 nm. This result is
consistent with observation reported in a recent study
44
involving electrospun protein fibers as matrices for tissue
engineering, where the average diameter of collagen
fibers is reported as 200-500 nm[28]. Therefore, the present
scaffolds have a majority of the fibers in the upper range
of nanoscale features of the natural ECM.
Mechanical (tensile) property measurements of electrospun
composites revealed that as the HA content increased, the
ultimate strength increased from 1.68 MPa for pure PCL to
2.65 MPa for PCL/HA composites with the addition of 10
wt% nanoHA. Similarly the tensile modulus also increased
gradually from 6.12 MPa to 8.0 MPa with increase of
nanoHA content in the PCL/nanoHA fibers revealing
increased stiffness of the fibers due to the presence of HA.
band around 1080 cm-1 and (P-O) of PO43- bending bands
in the 570-610 cm-1 range due to the presence of nanoHA
are present in composite fibers.
Table 1: Chart of optical density measurements via
Tecan Sunrise Microplate reader at (a) designated
concentrations and (b) of samples removed from the
microcentrifuge tube on designated days.
The result in Table 1 links optical density measurements
with concentration of BMP-2. BMP-2 is a potent bone
growth factor since it induces differentiation of
mesenchymal stem cells into bone-depositing osteoblasts.
The data shows the release of BMP-2 from the PCL and
PCL/HA at different time points. The measured optical
density of PCL and PCL/HA scaffolds fall in the same
range of less than 500 pg/mL (Fig. 7). Thus, this
observation provides important evidence that the BMP-2
on PCL and PCL/HA scaffolds maintains its biological
activity.
Fig. 6: DSC image of PCL and e-spun PCL
When pure PCL is compared to the electrically spun
PCL fiber (Fig. 6) the Tm decreases due to the decline
in crystallinity, which is caused by rapid structural
changes. This principle characteristic is attributed to rapid
structural changes after the electrospinning process. The
dotted line represents the commercial PCL bead, and the
solid line shows the electrospun PCL fibers. DSC scans
of composite PCL scaffolds revealed a slight increase in
melting point with the addition of the HA due to good
dispersion and interface bonding between PCL and HA
particles.The presence of HA in the fibers was confirmed
by FTIR. The FTIR spectra of the electrospun polymer
(PCL) composite fiber matrix showed characteristic
peaks for the polymer and hydroxyapatite. The ester
carbonyl (O-C=O) stretching peak was observed around
1727 cm-1 in both PCL and PCL/nanoHA composites. A
small but reproducible shift to lower wave number of the
ester carbonyl peak is ascribed to a weak interaction of
the polar C=O group with Ca2+ ions. The PO43- stretching
Fig. 7: Measured standard concentration of BMP-2. The measured
optical densities of the PCL and PCL/HA scaffolds all fall in the small
range of less than 500 pg/mL as specified in Table 1.
Cell viability of HEPM cells on PCL scaffold, PCL/HA,
and scaffolds that have absorbed BMP-2 are shown in Fig.
8. Cells on PCL alone have a viability of 97.9% and BMP2 soaked PCL have an increased viability of 99.5%. Cells
on PCL/HA alone have a viability percentage of 84.3%,
which is an acceptable viability, but in the presence of
BMP-2 viability increases to 99.2%. Thus, these results
suggest that PCL or PCL/HA were not cytotoxic to cells.
45
a number of observations in this study that includes the
cells ability to adhere to scaffolds and remain viable on
the scaffolds. The adhesion results demonstrate positive
potential of cells adhering to the scaffolds. High adherence
percentages show great potential for incorporation of cells
into the scaffolds. The presence of BMP-2 increased the
viability and proliferation of the HEPM cells on the PCL
and PCL/HA scaffolds.
ACKNOWLEDGEMENTS
Fig. 8: Cell viability is proven to be good with either scaffold (PCL or
PCL/HA), and viability has not been compromised even in the presence
of the protein, BMP-2.
Cell adhesion molecules help cells stick to each other and
to their surrounding environment.
Cell Adhesion
Molecules are proteins located on the surface of the cells
and helps in the binding with other cells or ECM. To verify
if the PCL or PCL/HA scaffolds were providing the cell
attachment appropriately; we conducted the cell adhesion
assay. In this study, the cell attachment was monitored at
hours 1, 2, 4, and 6 h of treatment. The results show great
potential of cells adhering to the scaffolds (Fig. 9).
This project was supported in part by National Science
Foundation grant (HRD-0734232).
REFERENCES
1. Yang S, Leong K, Du Z, Chua C. The Design of Scaffolds
for Use in Tissue Engineering. Part I. Traditional Factors.
Tissue Engineering 7, 6: 679-689. 2001
2.Murugan R, Ramakrishna S. Development of
nanocomposites for bone grafting. Composites Science and
Technology 65, 15-16: 2385-2406. 2005
3. Liebschner M A K, Wettergreen. Optimization of Bone
Scaffold Engineering for Load Bearing Applications. Topics
in Tissue Engineering 1: 1-39. 2003
4. Jose M V, Thomas V, Xu Y, Bellis S, Nyairo E, Dean
D. Aligned Bioactive Multi-Component Nanofibrous
Nanocomposite Scaffolds for Bone Tissue Engineering.
Macromolecular Bioscience 10: 433-444. 2010
5. Croce M A, Silvestri C, Guerra D, Carnevali E, Boraldi
F, Tiozzo R, Parma B. Adhesion and Proliferation of
Human Dermal Fibroblasts on Collagen Matrix. Journal of
Biomaterials Applications 18, 3: 209-222. 2004
6. Rai B, Teoh S H, Hutmacher D W, Cao T, Ho K H . Novel
PCL-based honeycomb scaffolds as drug delivery systems
for rhBMP-2. Biomaterials 26, 17: 3739-3748. 2005
Fig. 9: Cell Adhesion studies. Maximum cell adhesion was observed
at 6h of culture.
PCL seems to show greatest potential for adherence with
85% at 6 h. Therefore, our observation suggests that PCL
or PCL/HA provide great environment for cell attachment.
Maximum cell attachment was observed at 6 h of culture. At
4h and 6h time intervals, the PCL attachment percentages
come close to (82% at 4h) and meet the control attachment
percentage (85% at 6h). PCL/HA is not far behind at 6h
(79%).
Hence, our results demonstrates that the PCL and PCL/HA
scaffolds are ideal material for bone tissue regeneration
process and bone healing because they do not induce a
strong immune response[29]. This notion is supported by
46
7. Furth M, Atala A, Van Dyke M E."Smart biomaterials
design for tissue engineering and regenerative medicine.
Biomaterials 28, 34: 5068-5073. 2007
8. Yoshimoto H, Shin Y M, Terai H, Vacanti, J P. A
biodegradable nanofiber scaffold by electrospinning and its
potential for bone tissue engineering. Biomaterials 24, 12:
2077-2082 .2003
9. Reeves, Benjamin T., Joel D. Bumgardner, Judith A. Cole,
Yunzhi Yang, and Warren O. Haggard. "Lyophilization to
Improve Drug Delivery for Chitosan-calcium Phosphate
Bone Scaffold Construct: A Preliminary Investigation."
Journal of Biomedical Materials Research Part B: Applied
Biomaterials 90B.1 2009: 1-10
10. Furth ME, Atala A, and Van Dyke ME. "Smart Biomaterials
Design for Tissue Engineering and Regenerative Medicine
2606." Biomaterials 28.34 2007 : 5068-073
11. Lee, C.H., et al., “Nanofiber alignment and direction of
mechanical strain affect the ECM production of human
ACL fibroblast”. Biomaterials, 26.11 2005 : 1261-1270
mouse bone marrow-derived mesenchymal stem cellsGene
modification by ODNs in MSCs. Gene Therapy 15: 10351048. 2008
12. Khang, D., Sato, M., and Webster, T.J., “Directed osteoblast
functions on micro-aligned patterns of carbon nanofibers
on a polymer matrix.” Reviews on Advanced Materials
Science, 10.3 : 205-8 .2005
25. Schaller M D. Paxillin: a focal adhesion-associated adaptor
protein. Oncogene 20, 44: 6459 – 6472 . 2001
13. Liu, Z., et al., “Circulation and long-term fate of
functionalized, biocompatible single-walled carbon
nanotubes in mice probed by Raman spectroscopy.”
National Academy of Science Proceedings, USA. 105:
1410-1415. 2008
14. Jones PL, Schmidhauser C, Bissell MJ. ―Regulation of
gene expression and cell function by extracellular matrix.‖
Crit Rev Eukaryot Gene Expr 3.2 :137–54. 1993
15. Juliano RL, Haskill S. ―Signal transduction from the
extracellular matrix.‖ J Cell Biol 120.3 : 577–85 . 1993
16. Reid L, Morrow B, Jubinsky P, Schwartz E, Gatmaitan Z. ―
Regulation of growth and differentiation of epithelial cells
by hormones, growth factors, and substrates of extracellular
matrix‖. Ann NY Acad Sci : 372:354–70. 1981
26. Bellis S L.Advantages of RGD peptides for directing cell
association with biomaterials. Biomaterials 32, 18: 42054210. 2011
27. Appleford M R, Oh S, Cole J A, Carnes, D L, Lee M,
Bumgardner J D, Haggard W O, and Ong J L.Effects
of Trabecular Calcium Phosphate Scaffolds on Stress
Signaling in Osteoblast Precursor Cells. Biomaterials 28,
17: 2747-2753. 2007
28. Li M, Mondrinos M J, Gandhi M R, Ko F K, Weiss A
S, Lelkes P I. Electrospun Protein Fibers as Matrices for
Tissue Engineering. Biomaterials 20: 5999-6008. 2005
29. Chiara, G.; Letizia, F.; Lorenzo, F.; Edoardo, S.; Diego,
S.; Stefano, S.; Eriberto, B.; Barbara, Z.Nanostructured
Biomaterials for Tissue Engineered Bone Tissue
Reconstruction”. Int. J. Mol. Sci. 13, 1: 737-757. 2012
17. Rai, B., S. Teoh, D. Hutmacher, T. Cao, and K. Ho. "Novel
PCL-based Honeycomb Scaffolds as Drug Delivery
Systems for RhBMP-2." Biomaterials 26.17 : 3739-748.
2005
18. Eitan, A., et al., ―Surface modification of multiwalled
carbon nanotubes: To-ward the tailoring of the interface in
polymer composites.‖ Chemistry of Materials, 15.16 : 31983201. 2003
19.Huang Z-M, Zhang Y-Z, Kotaki M, Ramakrishna.A
review on polymer nanofibers by electrospinning and their
applications in nanocomposites. Composites Science and
Technology 63, 15: 2223-2253. 2003
20. R. S. Bezwada, D. D. Jamiolkowski, I. Lee, A. Vishvaroop,
J. Persivale, S. Treka-Benthin, M. Erneta, J. Suryadevara,
A. Yang and S. Liu. Monocryl suture, a new ultrpliable
absorbable monofilament suture. Biomaterials 16, 11411148. 1995.
21. Darney PD, Monroe SE, Klaisle CM and Alvarado A.
Polymers in Nanomedice. Am J. Obstet. Gynecol. 160,
1292 .1989
22. Woodward, S. C., Brewer, P. S., Moatamed, F., Schindler
A. and Pitt, C. G. The intracellular degradation of Poly
(e-caprolactone), J. Biomed. Mater. Res. 44, 437-444 .1985
23. Kweon H, Yoo MK, Park IK, Kim TH, Lee HC, Lee
HS, Oh JS, Akaike T and Cho CS. A novel degradable
polycaprolactone networks for tissue engineering.
Biomaterials 24, 801 .2003.
24. Flagler K, Alexeev V, Pierce EA and Igoucheva O. Sitespecific gene modification by oligodeoxynucleotides in
47
Sahajpal et. al. PGx_IPG: A DATABASE OF PHARMACOGENOMICS OF MAJOR INFECTIOUS DISORDERS
PGx_IPG:
A DATABASE OF PHARMACOGENOMICS OF MAJOR
INFECTIOUS DISORDERS
Ruchika Sahajpal1, Aditi Qamra1, Vinod Scaria2, Yasha Hasija1*
1
Department of Biotechnology, Delhi Technological University, Shahbad Daulatpur, Main Bawana Road,
Delhi- 110042;
2
Institute of Genomics and Integrative Biology (CSIR), Mall Road, Delhi, India
ABSTRACT
Research has made clear that individual variation in the efficacy and toxicity of drugs is largely determined by
genetic factors. Infectious diseases have multifactorial etiology leading to a complex interaction of drug-biomolecule
interactions subject to underlying genetic variation. We thus developed a comprehensive Locus specific database of
Single Nucleotide Polymorphisms (SNPs) present within genes that code for drug targets and/or influence drug response
for five infectious diseases- Malaria, Hepatitis C, Tuberculosis, Measles and HIV. This database ‘PGx_IPG’ is presented
to the scientific community via a freely accessible web interface open to contribution from the remote user. Currently
the database houses 30 drugs against 43 unique genes in 5 infectious diseases, containing 128 distinctive genetic single
nucleotide polymorphisms. We hope that this would serve as a handy reference for the scientific and medical community
working towards predictive and personalized medicine. The database is available at URL http://genome.igib.res.in/PGx/
home.php
Keywords: Pharmacogenomics, Infectious Diseases, drug, Single Nucleotide Polymorphisms, LOVD
1. INTRODUCTION
Infectious diseases have multifactorial etiology leading
to a complex interaction of drug-biomolecule interactions
subject to underlying genetic variation. It has been widely
recognized that different patients show different clinical
response against the same drug for a disease. [1] This
variability is an important factor in clinical practice and
can lead to adverse drug reactions and treatment failure.
Pharmacogenetics pursues to recognize and characterize
such individual genetic differences (single nucleotide
polymorphisms) in host genome that can affect the activity
of a particular drug, a promising advancement towards
personalized medicines. [2]
The completion of the Human Genome Project, with its
wide research [3,4] investigating genotype and phenotype
interactions including genetic databases, [5,6,7] brought to
Dr. Yasha Hasija, Assistant Professor and Associate Head, Department
of Biotechnology,
Delhi Technological University, Shahbad Daulatpur, Main Bawana
Road, Delhi- 110042, India. ([email protected])
*
48
light the extensive application of pharmacogenomics.
Genome wide association studies (GWAS), familial
associations, and gene analysis studies implicated a
strong relation between genotype and functional/clinical
outcomes of diseases. It is as a natural consequence at
the molecular level, that underlying genetic variability
contributes to not only varying disease affliction but also
differing drug responses. The interaction between drug
and its target and thereby its effectual response is subject
to the structural and physiochemical properties, adjoining
neighbors and external environment all making up a
jigsaw puzzle unique to every individual. Hope only lies
in deriving patterns of similarity to fill in missing gaps.
Many such successful attempts have been made in the
past and serve as comprehensive resources [8,9,10,11,12]
for applying pharmacogenomics to drug discovery and
development; many are too broad in scope and tend to
miss out on specific diseases and/or genetic associations or
focus only on specific population sets.[13] Where the earlier
attempts were based on evaluating individual risk based on
presence of genetic markers,[14] linking a pharmacogenetics
database housing clinical response data would lead to
rapid advances in personalized or tailor made medicine. It
is the need to further understand and accelerate the process
of effective treatment and management of fatal infectious
diseases, that a more holistic approach was considered.
We aim to contribute to the field of predictive medicine
to help combat the growing mortality rate due to existing
and continuously growing new infectious diseases. Our
objective is, thus, to build a drug-polymorphism database
that would link genetic variants to underlying functional
consequences leading to varying drug responses used in
treatment of five major infectious diseases. We created
an open source database associating genetic variations
to drug related effects in infectious diseases highlighting
and aiding the need of prognostic therapy. ‘PGx_IPG’
database harbors human drug-gene single nucleotide
polymorphisms associated in five important infectious
diseases- Malaria, Tuberculosis, Hepatitis C, Measles and
HIV. The database includes all genetic polymorphism data
available from published literature and existing public
databases across a wide range of populations and ethnic
races.
2. DATA COLLECTION AND SUBMISSION
Our work focuses on showcasing the pharmacogenetics
data of the candidate genes and associated polymorphisms
for five major polygenic infectious diseases- Hepatitis C,
Malaria, Tuberculosis, Measles and HIV. Drug related
data was sourced by querying diseases included in the
former database on two main public archives, namely
The Pharmacogenetics Knowledge Base[8] (PharmGKB
database) and The DrugBank[15]. Handpicking data from
referenced literature allowed a comprehensive database to
be built including statistical data related to variants and
patient specific data. Extensive literature survey was also
conducted to obtain up-to-date information and recent
findings. Literature database, Entrez PubMed at NCBI
(http://www.ncbi.nlm.nih.gov/sites/entrez) was queried
with the terms – “Disease name AND pharmacogenomics”,
“Disease name AND drug AND SNP” and “Disease name
AND varying drug response”. From the selected literature,
information was complied, including details of the
polymorphism, patient and disease. All data was manually
annotated and curated to ensure accuracy and remove any
redundant records.
The genes were referenced by the Human Gene
Nomenclature Committee (HGNC) [16] names and all
variants were reported according to the guidelines laid
down by the Human Genome Variation Society (HGVS)[17]
guidelines to ensure uniformity and allow the data to be
easily integrated with other resources. Mutalyzer 2.0 β-8
[18]
(HGVS nomenclature version 2.0) (https://mutalyzer.
nl/) was used to check the entries made along with the use
of dbSNP for scrutiny of the rsid and variant data.
3. DATABASE DEVELOPMENT
The Leiden Open Variation Database (LOVD) platform
- LOVD v.2.0 [14] was adopted to provide a user friendly
interface for web listing making it possible to query/search
the database through a number of parameters – drug
name, disease name, variant dbSNP rsid, variant location,
HGVS values (DNA change, predicted protein change),
statistical details such as p-value & odds ratio, population
study, PubMed ID of the associated referenced literature
etc. to name a few. LOVD v.2.0 is a freely available
Locus Specific Variation Database (LSDB)[19] that uses
PHP and MySQL open source softwares and follows
the recommendations of the Human Genome Variation
Society. It offers tools and resources as an out-of-box
utility and has a flexible and highly configurable back-end
while providing a very user-friendly curation interface. In
addition we have integrated with other online data analysis
resources and datasets like Mutalyzer 2.0.β-8[18], HGNC[16],
Ensembl Genome Browser[20], dbSNP (available at NCBI
http://www.ncbi.nlm.nih.gov/snp/)[21]. The LOVD link for
our database: ’PGx_IPG’ is available at the URL: http://
genome.igib.res.in/PGx/home.php.
4. ANALYSIS & DISCUSSION
The range and burden of infectious diseases is enormous.
Before Robert Koch's work in the late nineteenth century,
diseases such as tuberculosis and leprosy were widely
believed to be inherited disorders. [1,22,23] Heritability of
susceptibility to several infectious diseases has been
confirmed by studies in the twentieth century.[1,2]
Monitoring, controlling and treating continuous outbreaks
are under the control of an effective surveillance system
both nationally and globally, driven by the constant that
genetic variations regulate the manifestation and
therapeutics.
Fig. 1: Homepage of the PGx_IPG LOVD database available at http://
genome.igib.res.in/PGx/home.php
49
Fig.2: Classification of the 128 unique Single Nucleotide
Polymorphisms in five diseases according to genomic location
Needless to say, genetic factors are one of the primary
factors of susceptibility to infectious diseases. In a
relatively short evolutionary period, remarkably diverse
series of gene families have undergone modification in
response to the selective drive of infectious disorders.
Phenotype consequences have not confirmed to the
red cell but involve the immune system, cytokines,
histocompatibility complex and many other systems.
Table 1: PGx_IPG Database Statistics
Disease
Genes
Drugs
Variants (SNP)
5
43
30
256 ( 128 unique)
Our work reports drug response associated gene variants
in 5 infectious manifestations - Hepatitis C, Malaria,
Tuberculosis, Measles and HIV; across a spectrum of
43 unique genes. Compilation of associated drugs from
various reported experimental data, 30 unique drugs
were regulated by polymorphism in the individual
gene or genetic loci. The drugs were associated either
individually or in combination with gene variants in this
study. Rifampicin, efavirenz, Isoniazid, Amodiaquine,
Proguanil, mefloquine, Halofantrine, Measles Vaccines,
MMR, pegylated interferon alpha (PEG-IFN-alpha)ribavirin, Ritonavir, nelfinavir, nevirapine, indinavir,
abacavir and so on are a few drugs included in this study.
A total of 260 variations (including both individual single
nucleotide polymorphisms and in the form of interacting
variants or haplotypes) having valid rsid and related
reference literature were found to be associated to 5
diseases. Out of these 256, only 128 variants were found
to be unique. Human genes including ABCB1, ABCC2,
ADAR, APOC3, APOE, BCL2, CD209, CD46, CYP2B6,
CYP2C9, CYP2C19, CYP2C8, CYP2E1, CYP3A4,
CYP3A5, DDX58, G6PD, HCP5, IFIT1, IkK, IL2, IL10,
IL28B, IL7R, ITPA, LTB, TNF, LST1, LY96, SOD2,
MyD88, NAT2, NFkB, OAS1, OASL, RARB, EXRX,
SLAMF1, SLCO1B1, TLR2, TLR3, TLR4, TLR5, TLR6
and TRAF6 have been found to have pharmacogenetically
associated with atleast one of the five diseases.
For each 128 variant, specific genomic location was
found from the associated literature and databases such
as dbSNP and Ensembl. As an expected result, majority
of the SNPs (57) reported were found to be exonic i.e.
directly affecting the gene and its resulting phenotype. 47
variants were found to be in the intronic region. Remaining
16% variants were present in 5’UTR (6 variants), 5’Gene
flanking region (9 variants), 3’UTR/ 3’Gene flanking
region (3 variants). (Fig. 2)
Table 2: Complete list of all the genes and their variants associated with drugs analysis in five diseases. PubMed
IDs of all the references is provided with each variant.
DISEASE
DRUG
GENE
VARIANT
REFERENCE PubMed ID
Amodiaquine
CYP2C8
rs11572080, rs10509681
18855526
CYP3A4
rs12721634
21740570
G6PD
rs1050829, rs1050828,
rs137852328, rs76723693
19690618
Chlorproguanil, dapsone, artesunate
G6PD
rs1050828
19112496, 15183620,
Chlorproguanil, dapsone, artesunate,
artemether, lumefantrine
G6PD
rs1050829, rs1050828,
rs137852328, rs76723693
19690618
Halofantrine
CYP3A5
rs55817950
8096956
Mefloquine
CYP3A5
rs55817950
8096956
Proguanil
CYP2C19
rs4244285, rs4986893
10471063
Sulfadoxine, pyrimethamine, artesunate,
primaquine
G6PD
rs1050828
15183620, 20194698
Artemether, lumefantrine
Malaria
50
Rifampicin
Rifampicin, efavirenz
Isoniazid
Tuberculosis
Isoniazid,rifampicin
Isoniazid, rifampicin, pyrazinamide
Isoniazid, rifampicin, ethambutol, pyrazinamide
SLCO1B1
rs11045819, rs4149056
20660695
ABCB1
rs1045642
22162992
CYP2B6
rs3745274
22162992
NAT2
rs1801280, rs1799930,
rs1799931
22162992
CYP2E1
CYP2E1 *1A/*1A
16770646
NAT2
rs1799930, rs1799931,
rs1041983
18544910, 17950035
GSTM1
GSTM*0 ⁄ *0
18544910
NAT2
rs1799929, rs1799930,
rs1799931
10751073
GSTM1
GSTM*0 ⁄ *0
20853551, 17400324, 18397238,
GSTT1
GSTT1*0 ⁄ *0
20853551, 18397238
SOD2
mutant C allele (T/C or
C/C genotype)
17400324
CYP2C9
rs9332096, rs4918758
20941486
CYP2C19
rs4986893, rs3814637
20941486
NAT2
rs1801280, rs1799931,
rs1799930
20392357
SLCO1B1
rs4149032
21709081
BCL2
rs1800477
21159314
IFIT1
rs304478
21993426
OSAL
rs12819210
21993426
IL28B
rs12979860, rs8105790,
rs11881222, rs8103142,
rs28416813, rs4803219,
rs8099917, rs7248668,
rs4803219, rs12980275,
19684573, 19749757, 21374656,
21993426, 21745312, 22591106,
21907615, 20060832, 20389235,
21112657, 20621700, 21145807,
21505315, 21466653, 21257738,
20804372, 19749758, 22649509,
21911885, 20176026
ITPA
rs1127354, rs7270101
21628662, 20977565, 21503919,
22052220, 20637204, 21274861,
22430973
IL28B
rs8099917, rs12979860
21628662, 21726252
IL28B
rs12979860
21254158, 21951981
Pegylated interferon alpha(PEG-IFNalpha) plus ribavirin (RBV)
Hepatitis C
Pegylated interferon, ribavirin, and telaprevir triple therapy
Interferon-γ-inducible protein-10 (IP-10)+
PEG-IFN alfa-2 & ribavirin
51
Measles
52
Measles vaccines, MMR
ADAR
rs2229857
21939710
CD46
rs2724384, rs11118580
22086389, 17560639
CD209
-139C/T, -336C/T ,
-871C/T
21645571
DDX58
rs3205166
21939710
IkK
rs3747811, rs5029748
18325643
IL12B
rs3212227
21875636
IL2
rs2069762, rs2069763
21875636, 17152005
IL10
rs1800890, rs1800872,
rs1800871
21875636, 17152005
IL7R
rs6897932
21875636
LY96
rs11466004
18325643
MyD88
rs6853
18325643
NFkB
rs1585213, rs1801,
rs230494, rs230544,
rs230547
18325643
OAS1
rs10774671
21939710
RARB
rs6800566, rs6550976,
rs9834818, rs6550978,
rs6777544
22082653
RXRA
rs11102986, rs11103473,
rs11103482, rs10776909,
rs12004589, rs35780541,
rs2266677, rs875444
rs6537944, rs3118571
22082653
SLAMF1
rs3796504, rs164288
17560639
TLR2
rs3804100
18325643
TLR3
rs1879026, rs3775291,
rs3775296, rs5743305,
rs3775291
18325643, 22504413
TLR4
rs4986790, rs4986791,
rs7864330
18325643
TLR5
rs1291584, rs1773726,
rs1773729, rs1773727,
rs5744159, rs5744174,
rs851138, rs851139,
rs851186
18325643
TLR6
rs5743818
18325643
TRAF6
rs5030419
18325643
Abacavir
Efavirenz
HCP5
rs2395029
11888582, 15247625, 16998491,
17641165, 18256392, 18536095
ABCB1
rs2032582, rs1045642
20860463, 16267764, 16912957,
12545140
CYP2B6
rs3211371, rs34097093,
rs35303484, rs3745274,
rs28399499
16495778, 18281305, 20860463,
19779319, 19371316, 20723261,
15864119, 17235330, 15622315,
15864119
rs2740574
15622315, 16267764
CYP3A5
rs776746
20860463, 16267764, 15622315
ABCB1
rs2032582, rs1045642
14600574
APOC3
rs2854117, rs5128,
rs2854116
16417409, 15809899, 17700364
APOE
rs7412, rs429358
17700364, 15809899
ABCB1
rs2032582, rs1045642
16267764, 21824325, 22111602
CYP3A5
rs776746
16267764
rs2740574
16267764
CYP2C19
rs4244285
16267764
ABCC2
rs8187710, rs717620,
rs7080681, rs3740066,
rs2273697, rs17222723
19400747, 17083032
ABCB1
rs1045642
19400747, 17083032
ABCB1
rs1045642
14711599
ABCC2
rs8187710
19842932
ABCB1
rs2032582, rs1045642
19228205, 20017669, 16912956,
22354160, 21824325
CYP3A5
rs776746
20017669, 22111602, 21824325,
19228205
rs2740574
22111602, 19228205
CYP2B6
rs12721646, rs12721655,
rs58425034, rs28399499,
rs3745274, rs2279343,
rs3211371, rs35979566
20017669, 15864119, 18281305,
22111602, 21393201, 21441248,
21860339, 21824325, 19228205,
22354160, 15194512, 17559344,
17638512, 18171905
CYP2C19
rs12768009
21860339
CYP2C19
rs4244285
20147896
CYP2C9
rs1057910
20147896
rs2740574
19440701
CYP3A4
Ritonavir
Nelfinavir
CYP3A4
Tenofovir
HIV
Lopinavir
Nevirapine
Tipranavir
Indinavir
CYP3A4
CYP3A4
Efavirenz rifampin
CYP2B6
rs3745274
22162992
Efavirenz; nelfinavir
ABCB1
rs1045642
11809184
ABCB1
rs1045642
16912956
CYP2B6
rs3211371
18281305
CYP2B6
rs3745274
20723261
Efavirenz; nevirapine
Efavirenz lamivudine stavudine
53
Table 2 shows the complete list of all the genes and their
variants associated with drugs analysis in five diseases.
PubMed IDs of all the references is provided with each
variant. All drug-polymorphism associations have been
supported with statistical parameters – p value and odds
ratio to ensure a robust significance in the database.
It can be observed that HIV is the most widely studied
infectious disease amongst all five; having the largest
number of drugs and associated variants. Maximum
polymorphism was observed in PEG-IFN-alpha-ribavirin
therapy for Hepatitis C[24] and Efavirenz & Nevirapine
for HIV infection. Also drugs like Nelfinavir, Indianavir,
Tipranavir, Ritonavir, Tenofavir and lopinavir were found
to have an important role HIV related polymorphisms [25].
The cytochrome P-450 family of enzymes are involves
in influencing drug reactions, in corroboration with
vast research accounting it as one of the most important
enzymes that catalyse phase 1 drug metabolism.[26] Genes
of various cytochrome P-450 enzymes are observed to
play an important role in HIV, Tuberculosis and Malaria.
CYP2B6 and CYP2C19 represented the most important
factors of pharmacogenetic variation in drug metabolism
along with other members of the cytochrome family [27-29].
Measles is an important infectious disease.
Most of the pharmacogenetics studies for this disease
are done via measles vaccine/ MMR (Measles-MumpsRubella vaccine) treatment. TLR genes (TLR 2, 3,4,5,6)
and Interleukin genes (IL2, IL12B, IL10, IL7R) are found
to play an important role in Measles drug-gene interaction
studies.[30-33]
STRING v.9.0 [34], a Search Tool for the Retrieval
of Interacting Gene/ Proteins was used to assess the
functional interaction between 45 genes of 5 diseases.
(Fig. 3) presence of very close gene-gene interaction
was observed as a result. Separate STRING v.9.0
was performed to the genes specific for each disease.
(Fig. 4)
Fig.3: The combined functional network of interaction between genes harbouring variations associated with pharmacogenomics of Malaria,
tuberculosis, Measles, Hepatitis C and HIV. The data was generated from STRING online tool.
54
1
2
3
4
5
Fig.4: The individual functional network of interaction between genes harbouring variations associated with pharmacogenomics of (1) Hepatitis
C, (2) Measles, (3) Malaria, (4) Tuberculosis and (5) HIV respectively. The data was generated from STRING online tool.
55
The genetic susceptibility database revealed hotspot
geographical regions prone to an infectious disease in
interaction with their environment and lifestyle. It was
clear that prevalence of mutations indicated underlying
evolutionary pressures, the same of which can be said for
pharmacogenomics trends.
Most drugs are metabolized by several different
enzymes, can be transported by other types of proteins,
and ultimately interact with one or more targets giving
rise to recurring themes in pharmacogenetics i.e. the
presence of a few relatively common variant alleles of
genes encoding proteins important in drug response,
a larger number of much less frequent variant alleles,
and striking differences in the types and frequencies of
alleles among different populations and ethnic groups. To
observe this effect, functional annotation performed by
DAVID Bioinformatics Resource v.6.7 (http://david.abcc.
ncifcrf.gov/)[35,36]. The genes which harbored variations
were analyzed for interactions between them. Analysis
revealed that many of the genes formed close gene-gene
interactions as revealed from interactions based on direct
or physical interactions or interactions deduced using textmining, gene context and high-throughput experiments
including correlations in expression. [Table 3]
Table3: Pathway enrichment (KEGG Pathways) of 45 genes
Term
Genes
Count
%
P-Value
Bonferroni
FDR
Metabolism of xenobiotics by
cytochrome P450
GSTM1, CYP3A4, CYP3A5, CYP2C19, CYP2C9, CYP2B6, CYP2C8,
GSTT1, CYP2E1
9
20.0
5.4E-9
2.9E-7
5.3E-6
Drug metabolism
GSTM1, CYP3A4, CYP3A5, CYP2C19, CYP2C9, CYP2B6, CYP2C8,
GSTT1, CYP2E1
9
20.0
7.1E-9
3.8E-7
7.0E-6
Toll-like receptor signaling
pathway
TNF, MYD88, LY96, TLR2, TLR3,
TLR4, TLR5, TRAF6, TLR6
9
20.0
3.5E-7
1.9E-5
3.4E-4
Linoleic acid metabolism
CYP3A4, CYP3A5, CYP2C19, CYP2C9, CYP2C8, CYP2E1
6
13.3
1.2E-6
6.3E-5
1.1E-3
Retinol metabolism
CYP3A4, CYP3A5, CYP2C19, CYP2C9, CYP2B6, CYP2C8
6
13.3
3.3E-5
1.8E-3
3.2E-2
Arachidonic acid metabolism
CYP2C19, CYP2C9, CYP2B6, CYP2C8, CYP2E1
5
11.1
6.0E-4
3.2E-2
5.8E-1
Drug metabolism
CYP3A4, CYP3A5, ITPA, NAT2
4
8.9
3.3E-3
1.6E-1
3.2E0
Small cell lung cancer
BCL2, RXRA, RARB, TRAF6
4
8.9
2.1E-2
6.8E-1
1.9E1
Allograft rejection
TNF, IL10, IL2
3
6.7
2.6E-2
7.6E-1
2.3E1
Cytokine-cytokine receptor
interaction
TNF, IL7R, IL28B, LTB, IL10, IL2
6
13.3
3.6E-2
8.6E-1
3.0E1
Glutathione metabolism
GSTM1, G6PD, GSTT1
3
6.7
4.8E-2
9.3E-1
3.8E1
Pathogenic Escherichia coli
infection
LY96, TLR4, TLR5
3
6.7
6.1E-2
9.7E-1
4.6E1
RIG-I-like receptor signaling
pathway
DDX58, TNF, TRAF6
3
6.7
8.9E-2
9.9E-1
6.0E1
Jak-STAT signaling pathway
IL7R, IL28B, IL10, IL2
4
8.9
9.6E-2
1.0E0
6.3E1
The medical community is increasingly relying on variant
based data for the process of drug discovery and design.
Disease specific databases such as ours significantly cut
down on time and effort in understanding and extrapolating
findings to customized medicine. Such efforts would
help minimize trial and error leading to harmful or even
fatal side effects and avoid common pitfalls in disease
treatment.
A catalogue of genetic determinants of drug reactions
would lead to increased knowledge of drug mechanisms at
56
the molecular and cellular level along with development
of new therapeutic and diagnostic measures. Both drug
and dosage administration would be a controlled and
sartorial process exclusive to the patient in question. We
hope that this database would be a step forward in the field
of personalized and predictive medicine to ensure better
disease treatment and management.
REFERENCES
1.
Weinshilboum R. Inheritance and drug response. New Engl
J Med 348: 529−537. 2003.
2.
Wilkinson GR. Pharmacokinetics: the dynamics of drug
absorption, distribution, and elimination. In: Hardman JG,
Limbird LE, Gilman AG, eds. Goodman & Gilman's the
pharmacological basis of therapeutics. 10th ed. New York:
McGraw-Hill, 3-29. 2001.
3.
Kleyn, P.W. and Vesell, E.S., PHARMACOGENOMICS:
genetic variation as a guide to drug development, Science,
281:1820–1821, 1998.
4.
Lindpaintner K., Pharmacogenetics and the future of
medical practice. J. Mol. Med. 81:141–153. 2003.
5.
Locus-specific database domain and data content analysis:
evolution and content maturation towards clinical use.
Hum. Mutat. 31:1109-1116. 2010.
6.
Online Mendelian Inheritance in Man (OMIM), a
knowledgebase of human genes and genetic disorders.
Nucleic Acids Res. 33:D514-D517. 2005.
7.
Krawczak M et al, 2000. Human gene mutation database-a
biomedical information and research resource. Hum Mutat.
2000;15(1):45-51. 2000.
8.
Klein T.E., Chang J.T., Cho M.K., Easton K.L.,
Fergerson R.,et al. Integrating genotype and phenotype
information: an overview of the PharmGKB project.
Pharmacogenetics Research Network and Knowledge
Base. Pharmacogenomics J. 2001;1:167–170. 2000
(http://www.pharmgkb.org/)
9.
Iida A., Saito S., Sekine A., Takahashi A., Kamatani N.,
Nakamura Y. Japanese single nucleotide polymorphism
database for 267 possible drug-related genes. Cancer Sci.
97:16–24. 2006.
10. C. J. Zheng, L. Y. Han, B. Xie, C. Y. Liew, S. Ong, et al.
PharmGED: Pharmacogenetic Effect Database. Clinical
pharmacology and therapeutics, Vol.81, No.1. doi:10.1038/
sj.clpt.6100008. 2007.
11. Owen A, Pirmohamed M, Khoo SH, Back DJ.
Pharmacogenetics of HIV therapy. Pharmacogenet
Genomics. 16(10):693-703. 2006.
12. Ju-Youn Lee, InSong Koh. Drug to SNP: A
Pharmacogenomics Database for Linking Drug Response
to SNPs. Genome Informatics 12: 482–483 2001.
13. Matimba A., Oluka M., Ebeshi B., Sayi J., Bolaj O., et al.
Establishment of a biobank and pharmacogenetics database
of African populations. European Journal of Human
Genetics:16, 780–783; doi:10.1038/ejhg.49. 2008.
14. Fokkema, et al., 2005. LOVD: Easy creation of a locusspecific sequence variation database using an “LSDB-in-abox” approach. Hum Mutat. DOI: 0.1002/humu.2020. 2005
15. Wishart DS, Knox C, Guo AC, Cheng D, Shrivastava S et
al. DrugBank: a knowledgebase for drugs, drug actions and
drug targets. Nucleic Acids Res. 36(Database issue):D901-6.
2008 (http://drugbank.ca/)
16. Seal RL, Gordon SM, Lush MJ, Wright MW, Bruford
EA. genenames.org: the HGNC resources in 2011.
Nucleic Acids Res. 39 (Database issue): D514-9. 2011
(http://www.genenames.org/)
17. Den Dunnen and Antonarakis, 2000. Mutation nomenclature
extensions and suggestions to describe complex mutations:
a discussion. Hum Mutat. 15(1):7-12. 2000 (http://www.
hgvs.org/mutnomen/)
18. Wildeman M, van Ophuizen E, den Dunnen JT, Taschner
PE. Improving sequence variant descriptions in mutation
databases and literature using the Mutalyzer sequence
variation nomenclature checker. Hum Mutat. 29(1):6-13.
2008
19. Cotton RG, Auerbach AD, Beckmann JS, Blumenfeld OO,
Brookes AJ, Brown AF, Carrera P, Cox DW, Gottlieb B,
Greenblatt MS, Hilbert P, Lehvaslaiho H, Liang P, Marsh
S, Nebert DW, Povey S, Rossetti S, Scriver CR, Summar
M, Tolan DR, Verma IC, Vihinen M, den Dunnen JT.
Recommendations for locus-specific databases and their
curation. Hum Mutat.; 29(1):2-5. 2008.
20. Ensembl Genome Browser. http://www.ensembl.org
21. Sherry ST, Ward MH, Kholodov M, et al. dbSNP: the NCBI
database of genetic variation. Nucleic Acids Res. 29:308–
311. 2001.
22. Warren RM, Streicher EM, Gey van Pittius NC, Marais
BJ, van der Spuy GD, Victor TC, Sirgel F, Donald PR,
van Helden PD. The clinical relevance of Mycobacterial
pharmacogenetics. Tuberculosis (Edinb). 89(3):199-202.
2009.
23. Beiguelman B. Leprosy therapy and pharmacogenetics
(author's transl). Rev Med Chil. 103(5):344-9. 1975.
24. Tanaka Y et al. Genome-wide association of IL28B with
response to pegylated interferon-alpha and ribavirin therapy
for chronic hepatitis C. Nat Genet. 41(10):1105-9. 2009.
25. Shankarkumar U, Shankarkumar A, Ghosh K.
Human immunodeficiency virus therapeutics and
pharmacogenomics. Indian J Hum Genet. 17 Suppl 1:S226. 2011.
26. Ingelman-Sundberg M. Human drug metabolising
cytochrome P450 enzymes: properties and polymorphisms.
Naunyn Schmiedebergs Arch Pharmacol; 369: 89−104.
2004.
27. Dumond JB, Vourvahis M, Rezk NL, Patterson KB, Tien
HC, White N, Jennings SH, Choi SO, Li J, Wagner MJ,
La-Beck NM, Drulak M, Sabo JP, Castles MA, Macgregor
TR, Kashuba AD. A phenotype-genotype approach to
predicting CYP450 and P-glycoprotein drug interactions
57
with the mixed inhibitor/inducer tipranavir/ritonavir. Clin
Pharmacol Ther; 87(6):735-42. 2010.
28. Kim SH, Kim SH, Yoon HJ, Shin DH, Park SS, Kim
YS, Park JS, Jee YK. NAT2, CYP2C9, CYP2C19,
and CYP2E1 genetic polymorphisms in anti-TB druginduced maculopapular eruption. Eur J Clin Pharmacol.
Feb;67(2):121-7. 2011.
29. Haas DW, Smeaton LM, Shafer RW, Robbins GK, Morse
GD, Labbe L, Wilkinson GR, Clifford DB, D'Aquila RT,
De Gruttola V, Pollard RB, Merigan TC, Hirsch MS,
George AL Jr, Donahue JP, Kim RB. Pharmacogenetics of
long-term responses to antiretroviral regimens containing
Efavirenz and/or Nelfinavir: an Adult Aids Clinical Trials
Group Study. J Infect Dis; 192(11):1931-42. 2005.
30. Dhiman N, Ovsyannikova IG, Vierkant RA, Ryan JE,
Pankratz VS, Jacobson RM, Poland GA. Associations
between SNPs in toll-like receptors and related intracellular
signaling molecules and immune responses to measles
vaccine: preliminary results. Vaccine;26(14):1731-6. 2008.
31. Ovsyannikova IG, Haralambieva IH, Vierkant RA, O'Byrne
MM, Jacobson RM, Poland GA. Effects of vitamin
A and D receptor gene polymorphisms/haplotypes on
immune responses to measles vaccine. Pharmacogenet
Genomics;22(1):20-31. 2012.
32. Clifford HD, Yerkovich ST, Khoo SK, Zhang G, Upham
J, Le Souëf PN, Richmond P, Hayden CM. TLR3 and
RIG-I gene variants: Associations with functional effects
on receptor expression and responses to measles virus and
vaccine in vaccinated infants. Hum Immunol;73(6):677-85.
2012.
33. Dhiman N, Ovsyannikova IG, Cunningham JM, Vierkant
RA, Kennedy RB, Pankratz VS, Poland GA, Jacobson
RM. Associations between measles vaccine immunity and
single-nucleotide polymorphisms in cytokine and cytokine
receptor genes. J Infect Dis.;195(1):21-9. 2007.
34. Szklarczyk D, Franceschini A, Kuhn M, Simonovic M,
Roth A, Minguez P, Doerks T, Stark M, Muller J, Bork
P, Jensen LJ, von Mering C. The STRING database in
2011: functional interaction networks of proteins, globally
integrated and scored. Nucleic Acids Res.;39(Database
issue):D561-8. 2011.
35. Huang DW, Sherman BT, Lempicki RA. Systematic
and integrative analysis of large gene lists using DAVID
Bioinformatics Resources. Nature Protoc.4(1):44-57. 2009.
36. Huang DW, Sherman BT, Lempicki RA. Bioinformatics
enrichment tools: paths toward the comprehensive
functional analysis of large gene lists. Nucleic Acids Res;
37(1):1-13. 2009.
58
iNOS GENE C150T POLYMORPHISM AND BIOMARKERS OF
ENDOTHELIAL DYSFUNCTION IN STABLE ISCHEMIC HEART
DISEASE: A PILOT STUDY
Shilpa Bhardwaj1*, Richa Dixit1, MK Bhatnagar1, Sanjay Tyagi2, Jayashree Bhattacharjee1
Lady Hardinge Medical College & associated hospitals, Delhi, India-110001
2
G B Pant Hospital, New Delhi, India
1
ABSTRACT
AIM: To study the effect of a novel iNOS gene C150T, single nucleotide polymorphism, & biomarkers like nitric oxide
(NO) and endothelin (ET-1) in stable ischemic heart disease (IHD).
METHODS & RESULTS: 60 angiographically confirmed stable IHD patients, (age≥35years) and 60 age & sex
matched healthy volunteers with no known risk factors for IHD were enrolled in a case-control study. Plasma NO levels
were measured by modified Griess reaction. ET-1 levels were measured in plasma by ELISA kit. PCR-RFLP was done to
identify the iNOS gene C150T polymorphism and its effect on NO levels was also studied. Statistical analysis was done
using SPSS version 18. The levels of NO, a potent vasodilator, (p<0.05) were significantly lower in cases as compared
to controls whereas ET-1 levels were significantly high in cases. The frequency of T allele (19.5% vs 12%) was higher
in cases. The production of NO was higher in cases expressing T allele.
CONCLUSION: iNOS C150T polymorphism may affect endothelial functional status by changing NO levels and may
be a potential genetic marker for IHD.
Keywords: Stable Ischemic Heart Disease; iNOS gene; PCR-RFLP; Endothelin
1. INTRODUCTION
The Global Burden of Disease study projects 4.8 million
deaths due to ischemic heart disease (IHD) by the year 2020
AD [1]. The extent of burden it imposes on Indian health
care system can be estimated from the data which predicts
approximately 30 million patients with IHD in India [2].
It is prudent to search for new markers of endothelial
dysfunction along with the role of genetic component in
Ischemic heart disease to halt its progression.
IHD is the end result of atherosclerosis of coronary
arteries. These atherosclerotic vessels exhibit increased
vasoconstrictor tone. Endothelium-derived nitric oxide
(NO) is a potent vasodilator that plays a critical role in
regulating vascular tone. Reduction in basal NO release
may predispose individuals to hypertension, thrombosis,
vasospasm, and atherosclerosis. However, overproduction
Dr Shilpa Bhardwaj* (M.D Biochemistry),
Lady Hardinge Medical College & associated hospitals, Delhi,
India-110001
Email id: [email protected]
*
can also cause damage to cells and tissues due to formation
of reactive species like superoxide and peroxynitrite,
making NO a double-edged sword [3].
NO is synthesized from L-arginine by a family of three
distinct nitric oxide synthase (NOS). Inducible NOS
(iNOS), is a calcium independent isoform expressed
in response to cytokines during inflammation [4]. iNOS
expression is regulated at transcriptional level [5]. Not
much study has been done to reveal the role of iNOS gene
in IHD. A few studies suggest the role whereas studies
declining a role are also available. [6, 7] But this is the first
study to comment on functional relevance of coding region
(exon 16) of iNOS gene in stable IHD patients.
NOS are dimeric proteins and each monomer has an
oxygenase and a reductase domain with an interlinking
CaM binding region. Out of the several polymorphisms
studied in iNOS gene, C150T in exon 16 (E16) was found
to be the most frequent. Studies have indicated that even
single amino acid change may have dramatic effects on
enzymatic activity [8]. The C to T substitution in E16 of
iNOS gene possibly leads to higher production of NO [9].
59
Bhardwaj S et. al. iNOS iNOS GENE C150T POLYMORPHISM AND BIOMARKERS OF ENDOTHELIAL DYSFUNCTION IN STABLE
ISCHEMIC HEART DISEASE: A PILOT STUDY
E16 codes for the reductase domain of the protein where an
FMN binding site has a crucial role in controlling binding
of calmodulin (CaM) [10]. Regulation of NO synthase
activity by CaM has been shown to occur through the
control of electron transfer from FMN to heme across the
domain-domain interface [11].
Endothelin (ET-1), a 21 amino acid peptide was identified
in 1988. In addition to its powerful vasoconstrictor and
hypertensive actions, it stimulates cellular proliferation,
synthesis of matrix proteins, and chemotactic effects on
monocytes [12]. Elevated plasma levels of ET-1 have been
associated with IHD [13].
Therefore, we conducted this case-control study to explore
the effect of C150T polymorphism on the levels of nitric
oxide and affecting the pathogenesis of IHD. To the best
of our knowledge, this is the first study revealing the
role of iNOS C150T polymorphism in stable IHD and its
association with NO and ET-1.
2. METHODS
2.1 Study participants
The Case-control study was conducted in the Smt.
Sucheta Kriplani Hospital and G.B.Pant Hospital, New
Delhi, India. The participants (n=120) were enrolled after
written & informed consent and the study conforms to
the Declaration of Helsinki. The study protocol was in
agreement with the guidelines of the institutional ethics
committee.
The study population (n=120, males= 60%, females=
40%) consisted of 60 angiographically proven stable
cases of IHD (males= 64%, females=34%, mean age=
54.36±1.62 years) and 60 age and sex matched apparently
healthy volunteers (males= 62%, females= 38%, mean
age= 51±1.51 years) without clinical or ECG evidence of
IHD and without any family history of IHD formed the
control group. The stable diagnosed cases of IHD did not
show the occurrence of any acute episode in past 8 weeks,
progressive clinical or ECG changes. None of the subjects
had signs of acute or chronic inflammation and did not
undergo any recent surgery.
Cases were recruited from cardiac clinic of Smt. Sucheta
kriplani hospital (Delhi, India) and G.B.Pant hospital
(Delhi, India). Subjects with BMI≥25kg/m2 were
considered obese [14].
60
After a written informed consent, detailed clinical and
anthropometric characteristics were recorded in a proforma
for all the participants. Ten ml of fasting venous sample
was collected under sterile conditions and processed
immediately for separation of plasma and serum. For NO
and ET-1 estimation, the samples were drawn into plastic
tubes containing EDTA and centrifuged, aliquot and stored
at - 40ºC. The remaining cell aggregate (Buffy-coat) was
stored at - 70ºC till analyzed for PCR-RFLP. Repeated
freeze-thaw cycles were avoided. Samples were processed
without knowledge of their case-control status.
2.2 Analytical Procedures
Serum lipid profile was done on automated clinical
chemistry analyzer (Beckman systems; CX series).
ESR and TLC were measured to rule out any ongoing
inflammation (Coulter systems).
NO in plasma was determined indirectly by the
measurement of its stable decomposition product nitrite
(NO2-), employing the Griess reaction by modified
method of Mathew et al. (1996) [15]
ET-1 in plasma was determined using the commercially
available, human ET-1 Enzyme Immuno Assay kit by
DRG International Inc., (USA).
The DNA was extracted from buffy-coat fraction by
a detergent-mediated precipitation method using a
commercially available Genomic DNA Purification
Kit (cat#k0512) from Fermentas. Genomic DNA was
suspended in 1X TE buffer.
A polymerase chain reaction (PCR) was carried out to
identify the genotype of iNOS and single nucleotide
polymorphism (SNP) using the following primer pairs;
(Sense):5’-TGTAAACCAACTTCCGTGGTG-3’[16] and
(Anti-Sense):5’GTCTCTGCGGGTCTGAGAG-3’
(Operon, Genetix).
Amplification consisted of initial denaturation at 95℃
for 10 minutes, followed by 40 cycles of 30 seconds at
95℃, 30 seconds at 60℃ and 30 seconds at 72℃, then a
final extension at 72℃ for 5 minute. Amplified products
(288bp) were run on 2% agarose check gel. The Cytosine
(C) to Thymine (T) transversion had created a restriction
enzyme recognition site for Tsp509I so the resulting 288bp amplification product was digested with 1U of fast
digest Tsp509I restriction enzyme/10μl of PCR product for
10 minutes at 65ºC. The products were then run on a 3%
agarose gel. Restriction Fragment Length Polymorphism
(RFLP) was identified with ethidium bromide staining.
Homozygous wild-type individuals (CC) showed 113 bp
and 175 bp fragments, heterozygous individuals (CT)
showed three bands: 113 bp, 142 bp and 175 bp. (Fig. 2)
2.3 Statistical analysis
For comparison, Mann–Whitney U-test was used for
variables with a skewed distribution to analyze clinical
and laboratory data. Frequencies of genotypes were
compared with chi-square tests and Fischer’s exact test.
The association was expressed as an odds ratio (OR) with
95% confidence interval (95% CI). Multiple regression
analysis with adjusted OR for age, sex and BMI was also
done. A p≤0.05 was considered statistically significant.
Hardy-Weinberg equilibrium was tested for iNOS C150T
polymorphism. All analyses were performed with SPSS v
18.0 software program.
3. RESULTS:
The characteristics of participants are described in (table
1). ESR and TLC levels were within the normal range in
both cases and controls. (Fig. 1) depicts the comparison
between NO and ET-1 levels among cases and controls. An
inverse relation was observed between NO and ET-1 levels
in both the groups. The NO levels were significantly lower
in cases (p<0.05) whereas, ET-1 levels were significantly
higher in cases compared to controls.
Table 2: Genotype distribution in study population
CASE (N=50)
GENOTYPE
CONTROL
ODDS
RATIO
N
Frequency
%
N
Frequency
%
CC
35
70
38
76
0.74
(0.30-1.80)
CT
15
30
12
24
1.36
(0.56-3.3)
TT
0
-
0
-
p value=
0.653
C
0.805
80.5
0.88
88
df = 1
T
0.195
19.5
0.12
12
Χ2 = 0.457
Alleles
Fig. 1: Comparison of plasma NO & Endothelin levels in cases &
controls
Table 1: Study characteristics of population
AGE (years)
SEX :
Males
Females
Haemogram
ESR (mm Hg in
1st hr)
TLC (cells/cu.mm)
Endothelin(pg/ml)
Nitric oxide(µM)
Cases
Controls
p value
54.36±1.62
51±1.51
0.45
64%
34%
62%
38%
0.83
32.9 ± 2.5
6564 ± 272.2
18.9 ±1.6
5766
±174.6
0.001*
0.02*
22.3±1.5
18.08±1.30
0.04*
13.12±1.75
18.23±1.90
0.001*
*p value≤0.05 is considered statistically significant,
** values are expressed as Mean±S.E.M (Standard error of mean)
BMI : Body Mass Index
ESR: Erythrocyte sedimentation rate
HDL: High density lipoprotein
*p value≤0.05 is considered statistically significant,
** Values are expressed as Mean ± S.E.M (Standard error of mean)
df: degree of freedom
The iNOS Tsp509I genotypic distribution as seen on
ethidium-bromide stained agarose gel is shown in
(Fig 2). The CC genotype (wild type) was more frequent
in controls (76% vs 70%) whereas the CT genotype
(heterozygous mutant) was observed more in cases
(12% vs 30%) as shown in (Table 2). No TT was found
in any group. The distribution was in Hardy-Weinberg
equilibrium for the control group. The difference of
genotypes between the two groups was not statistically
significant but the mutant allele (T) occurred with higher
frequency (20% vs 12%) in cases. Even though, none of
the genotypes showed statistically significant association
with IHD, CT genotypes showed higher OR (1.36) and
95%CI (0.56-3.3) as compared to CC genotypes for IHD.
61
heart disease in Indian population to the best of my
knowledge.
Fig. 2: Ethidium-Bromide stained gel showing iNOS C150T single
nucleotide polymorphism, Tsp509I digested pcr products. M=
molecular marker (ladder)
The distribution of NO levels among different genotypes
is shown in (Table 3). The plasma NO levels were
significantly lower in cases as compared to controls
(p<0.05). CT genotypes (mutants) had higher NO levels
as compared to CC genotypes in patients of IHD though it
did not reach statistically significant proportions.
Table 3: NO distribution in genotypes of study
population
We also calculated the ratio of ET-1/NO in both cases and
controls and found a higher vasoconstrictor tone in cases
compared to controls (1.69 vs 0.99) which clearly suggests
the significance of NO supplementation in IHD patients.
LEVEL OF NO (µM)
GENOTYPE
CASES (N=50)
CONTROLS (N=50)
N
MEAN
S.E.M
N
MEAN
S.E.M
p VALUE
CC+CT
50
14.47
1.75
50
18.77
1.90
0.09
CC
35
13.00
2.04
38
19.28
2.36
0.05
CT
15
15.95
3.44
12
18.26
2.52
0.61
*p value≤0.05 is considered statistically significant.
NO: nitric oxide
S.E.M: Standard error of mean
4. DISCUSSION
Ischemic heart disease has a multifactorial etiology. The
study was conducted to evaluate the role of iNOS gene
polymorphism in its etiopathogenesis by altering NO
levels. It is the first study showing the effect of iNOS
C150T single nucleotide polymorphism in stable Ischemic
62
In this study, the mean plasma nitric oxide (NO) levels
were significantly (p<0.05) lower in cases as compared to
controls (14.47±1.75 μM vs 18.77±1.9 μM). The levels of
NO in blood are tightly regulated by controlled expression
of eNOS and iNOS. The decrease in NO levels in IHD
have been correlated with reduced eNOS expression [17]
and increased in vivo oxidative stress in long standing
cases of IHD.[18] Since NO alone has been considered to
be an important anti-atherogenic factor with antioxidant,
anti-inflammatory, antiproliferative, and vasodilatory
effects on vasculature, the lower NO levels in ischemic
heart disease patients may be considered to be one of
the contributing factors to atherosclerotic process. ET-1,
the most potent vasoconstrictor known, was found to be
significantly elevated in patients of IHD as compared to
controls suggestive of enhanced vascular tone in cases.
The results were similar to the observations of other
investigators[19]. Studies have demonstrated that the
vasoconstrictor tone mediated by endogenous ET-1 is
augmented in patients with atherosclerosis[20]. Moreover,
it has been demonstrated that circulating and tissue
endothelin immunoreactivity correlates with the severity
of human atherosclerotic disease [21]. Taken together, these
findings strongly suggest a role for ET-1 in the evolution
and progression of coronary atherosclerosis in humans.
Nitric oxide synthase (NOS) is the enzyme catalyzing
the synthesis of NO. iNOS (inducible-NOS) expression
is induced by cytokines during inflammation. Studies
have demonstrated increase in iNOS expression in human
atherosclerotic tissue [22,23]. PCR-RFLP was done to study
the genotypes of iNOS C150T polymorphism. In this
study, CC genotype was found more in controls whereas
CT genotype was more frequent in cases. No TT was
found in any group. The difference between the genotypes
was not found to be significant (p=0.65). The genotypic
distribution was in Hardy Weinberg equilibrium. Our
control iNOS genotype frequency is coincident with the
results presented by Shen et al, [16] which represents the
genotype frequency in Asia.
The Odds ratio (95% CI) did not show significant
association of the genotypes with IHD. This suggests that
the mutation alone is not sufficient to cause the disease
but may interact with other environmental and lifestyle
risk factors to affect the outcome of disease. This finding
again supports the view that the etiology of IHD is multifactorial and several factors interact to produce the disease.
The frequency of T allele (mutant allele) was higher in
cases than in controls (19.5% versus 12%), showing that T
allele might be the susceptibility allele for IHD in Indian
population. The results of this study may be supported by
findings in other diseases like diabetes and gastric cancer
[8,16]
In this study, we did not find any mutant homozygote (TT)
which could be one of the reasons for lack of significant
association of C150T polymorphism with IHD. However,
more studies with larger sample size are needed to confirm
genotypic risk associated with T allele.
We observed that in controls, NO levels were (significantly)
higher in the subjects expressing CC genotype than
CT genotype. But in cases, NO levels were found to be
comparable in CT genotypes and CC genotypes. This is
supported by the findings in other studies which show
that T allele leads to higher production of NO [16]. So, CT
genotypes in cases are expected to produce more NO by
interacting with several risk factors found in IHD patients.
In other words, the T allele expression is influenced by the
presence of risk factors or the inflammatory state which
exists in IHD patients.
Similar to the findings of Shen et al [16], the present study
also indicates that the cases with T allele have increased
level of NO, signifying the functional importance of the
polymorphism. But the presence of risk factors seems to
be an important factor affecting the expression of T allele.
However, since no TT genotypes were found, the impact
of homozygous mutation could not be assessed on NO
levels which would have probably altered the levels of NO
more significantly.
Studies have suggested that the rise of NO associated
with T allele may be due to an endogenously bound
CaM (calmodulin) which is essential in folding and
stabilizing this mutant and retained citrulline formation
[11]
. Not much work has been done on iNOS gene in
India. G Kumaramanickavel et al., [24] studied iNOS gene
in association with retinopathy in the Asian Indians.
Bhatnagar et al., [25] studied this mutation for pre-eclampsia
in India although it could not find any linkage.
In our cases, NO levels were already low in cases as
compared to controls and the rise in NO levels due to
polymorphsim may have a beneficial role. But to confirm
whether this rise is atheroprotective or atherogenic, more
studies should be done. Follow up studies will help in
establishing the long term effect of this mutation on the
severity of the disease.
To our knowledge, this study was the first one to examine
the significance of C150T iNOS gene polymorphism
in stable IHD in north Indians. Large-scale followup studies will be needed to establish the role of iNOS
C150T polymorphism, leading to amino acid substitution
Ser608Leu in the etiopathogenesis of stable cases of IHD.
5. CONCLUSION
Thus, endothelial dysfunction characterized by a fall in
vasodilators like NO and rises in vasoconstrictors like ET-1
reflects a vascular feature prone to atherosclerosis and may
therefore serve as a marker of the inherent atherosclerotic
risk in an individual. iNOS C150T polymorphism is
associated with increased NO formation in cases with T
allele which suggests the potential effect of this mutation
in etiopathogenesis of IHD. Many challenging issues still
remain unsolved, but disease identification at an early
stage in at risk population may enhance the aggressiveness
with which lifestyle modification and other interventions
can be initiated. Therefore, more studies focussing on the
molecular and cellular aspects of endothelium should be
initiated for both research and clinical interests.
CONFLICT OF INTEREST: None declared
ACKNOWLEDGMENT: We would like to thank the
participants & technical staff especially Ms Manisha who
cooperated with us during the study.
REFERENCES
1. M. Ezzati, M., Lopez, A.D., Rodgers, A., Vander,
S. H., Murray, C.J. Comparative Risk Assessment
Collaborating Group. Selected major risk factors and
global and regional burden of disease. Lancet; 360:
1347–60, 2002.
2. Gupta, R., Joshi, P., Mohan, V., Reddy, S.K., and
Yusuf. S. Global burden of cardiovascular disease.
Epidemiology and causation of coronary heart disease
and stroke in India. Heart; 94: 16–26, 2008.
3. Pal, P., Joseph, B.S. and Lucas, L. Nitric Oxide and
Peroxynitrite in Health and Disease. Physiol Rev; 87:
315-424, 2007.
4. Knowles, R.G., Monihda, S. Nitric oxide synthases
in mammals. Biochem J; 298: 249-58, 1994.
63
5. Xu, W., Charles, I., Monihda, S., Emson. P. Molecular
cloning and structural organization of inducible nitric
oxide synthase gene (NOS2). Biochem biophys res
commun; 219: 784-88, 1996.
6. Kunnas, A.T., Mikkelsson, J., Ilveskoski, E., Tanner,
M.M., Laippala, P., Penttila. A. A functional variant
of the iNOS gene flanking region is associated with
LAD coronary artery disease: an autopsy study. Eur J
Clin Invest; 33: 1032-37, 2003.
7. Muntwyler, J., M-Jaun, J., Luscher, T.F., Hanseler,
E., Hersberger. M. No evidence for involvement of
the human inducible nitric oxide synthase gene in
susceptibility to coronary artery disease. Clin chem.
Lab med; 43: 253-55, 2005.
8. Johannesen, J., Pie, A., Pociot, F., Kristiansen, O.P.,
Karlsen, A.E., Nerup, J. Linkage of the Human
Inducible Nitric Oxide Synthase Gene to Type 1
Diabetes. J Clin Endocrinol Metab; 86: s2792-96,
2001.
9. Shen, J., Wang, R.T., Wand, L.W., Wang, Z.X., Xing,
H.X., et.al. Ser/Leu polymorphism of iNOS gene was
found and identified in Chinese by denaturing high
performance liquid chromatography. Peking Daxue
Xuebao; 33: 486-92, 2001.
10. Eissa, N.T., Strauss, A.J., Haggerty, C.M., Choo,
E.K., Chu S.C., et.al. Alternative splicing of human
inducible nitric-oxide synthase mRNA. Tissue specific
regulation and induction by cytokines. The Journal of
biological chemistry; 271: 27184-87, 1996.
11. Chen, P.F., and Wu, K.K. Characterization of the Roles
of the 594–645 Region in Human Endothelial Nitricoxide Synthase in Regulating Calmodulin Binding
and Electron Transfer. The Journal of biological
chemistry; 275: 13155–63, 2000.
12. Rizvi, M.A., Katwa, L., Spadone, D.P., Myers,
P.R. The effects of endothelin-1 on collagen type I
and type III synthesis in cultured porcine coronary
artery vascular smooth muscle cells. J Mol Cell
Cardiol;28(2):243–52, 1996.
13. Gurmukh, S. S., Vibhuti, G. M., Mehra, A. P. Role of
Endothelin-1 in Genesis of Coronary Artery Disease.
Indian Heart J; 57: 121–27, 2005.
14. Redefining obesity and its treatment – the Asia-Pacific
perspective 2000: International Diabetes Institute in
Australia and WHO, Assessed www.diabetes.com.au/
pdf/obesity_report.pdf on feb, 2000.
15. Mathew, F., Glenda, J., Jack, L. Quantification of nitric
and nitrate in extracellular fluids. Metho Enzymol;
268: 237-46, 1996.
16. Shen, J., Wang, R.T., Wang, L.W., Xu, Y.C., Wang,
X.R. A novel genetic polymorphism of inducible
64
nitric oxide synthase is associated with an increased
risk of gastric cancer. World J Gastroenterol; 10:
3278-83, 2004.
17. Oemar, B.S., Tschudi, M.R., Godoy, N., Brovkovich,
V., Malinski, T. Reduced endothelial nitric oxide
synthase expression and production in human
atherosclerosis. Circulation; 97: 2494–98, 1998.
18. Fichtlscherer, S., Breuer, S., Schachinger, V.,
Dimmeler, S., Andreas, M.Z. C-reactive protein
levels determine systemic nitric oxide bioavailability
in patients with coronary artery disease. European
Heart Journal; 25: 1412–18, 2004.
19. Babaei, S., Picard, P., Ravandi, A., Monge, J.C., Lee,
T.C.,et.al. Blockade of endothelin receptors markedly
reduces atherosclerosis in LDL receptor deficient
mice: role of endothelin in macrophage foam cell
formation. Cardiovascular Research; 48: 158–67,
2000.
20. Bohm, F., Ahlborg, G., Johansson, B.L., Hansson,
L.O., Pernow, J.,et.al. Combined endothelin receptor
blockade evokes enhanced vasodilatation in patients
with atherosclerosis. Arterioscler Thromb Vasc Biol;
22: 674–79, 2002.
21. Gossl, M., Lerman, A. Endothelin Beyond a
Vasoconstrictor. Circulation; 113:1156-58, 2006.
22. Esaki, T., Hayashi, T., Muto, E., Kano, H., Kumar,
T.N.,et.al. Expression of inducible nitric oxide
synthase and Fas/Fas ligand correlates with the
incidence of apoptotic cell death in atheromatous
plaques of human coronary arteries. Nitric Oxide; 4:
561–71, 2000.
23. Pennathur, S., Bergt, C., Shao, B., Byun, J., Kassim,
S.Y.,et.al. Human atherosclerotic intima and blood
of patients with established coronary artery disease
contain high density lipoprotein damaged by reactive
nitrogen species. J Biol Chem; 279: 42977–83, 2004.
24. Kumaramanickavel, G., Sripriya, S., Vellanki, R.N.,
Upadyay, N.K., Badrinath, S.S., et.al. Inducible nitric
oxide synthase gene and diabetic retinopathy in Asian
Indian patients. Clinical Genetics; 61: 344-48, 2002.
25. Bhatnagar, S., Bhattacharjee, J., Vaid, M., Madan,
T., Trivedi, S.S., et.al. Role of nitric oxide and nitric
oxide synthase gene polymorphism in pregnancy
induced hypertension. Australian and New Zealand
Journal of Obstetrics and Gynaecology; 47: 477-82,
2007.
HYDROLYSIS OF WHEY LACTOSE USING CTAB PERMEABILZED
THERMOTOLERANT YEAST CELLS FOR SUBSEQUENT
FERMENTATION TO BIOETHANOL
Minakshi Dahiya*, Shilpa Vij and Subrota Hati
Whey Fermentation Lab, Dairy Microbiology Division, National Dairy Research Institute,
Karnal-132001, Haryana, India.
ABSTRACT
One of the most attractive options to check the proliferation of whey pollution is its bioconversion to ethanol employing
yeast, especially Kluyveromyces species. The presence of lactose as the only fermentable carbohydrate in whey confines
its use to selective fermentations involving microorganisms which are capable of breaking down lactose with the enzyme,
β-galactosidase. However, the industrial applications of β-galactosidase have been hampered by the costs involved in
downstream processing. To overcome the permeability barrier and prepare whole cell biocatalysts with high activities,
permeabilization of thermotolerant lactose fermenting yeast isolates W16, W23 and standard culture of NCDC 39 in
relation to β-galactosidase activity was optimized using cetyltrimethylammonium bromide (CTAB) as permeabilizing
agent. CTAB concentration and biomass load was optimized to enhance the lactose hydrolysis. Maximum lactose
hydrolysis (80%) was observed with 150 mg dw of thermotolerant yeast isolate W16 permeabilized cells for a period
of 6 h incubation. Permeabilized cells of thermotolerant yeast isolates W16, W23 and standard culture of NCDC 39
were tested as the source of lactase in the ethanol fermentation of whey by using thermotolerant non lactose fermenting
D54, D44 and SJ16 yeast isolates. Rapid lactose hydrolysis by small amounts of permeabilized yeast cells following
the fermentation of released glucose and galactose by non lactose fermenting yeast isolates enhances the overall ethanol
production compared to the fermentation in which the lactose was directly fermented.
Key Words: Bioethanol, Biological oxygen demand, Biomass, β-galactosidase, Cetyltrimethyl ammonium bromide,
Chemical oxygen demand, Fermentation, Hydrolysis, Lactose, Lactase, Kluyveromyces marxianus, Permeabilization,
Thermotolerant, Whey, Yeast
1. INTRODUCTION
The search for a satisfactory solution for disposal of the
unutilized whey produced in the manufacture of cheese
remains an area of intense concern for the dairy industry.
Although adequate technology is available to recover
selectively and concentrate the nutritious protein portion
of cheese whey [1], no widely accepted method has been
developed to utilize the lactose portion. Since conventional
waste treatment systems are costly, the ideal solution would
entail converting the lactose to a marketable product to
defray the operating costs and possibly recover the initial
capital outlay. One alternative often proposed is to ferment
the lactose into ethanol for use as a fuel or chemical
feedstock [2]. This process normally uses lactose-fermenting
Minakshi Dahiya,
Research Associate
Dairy Microbiology Division, National Dairy Research Institute,
Karnal-132001, Haryana, India; Tel: +91 184 225 9180;
Fax: +91 184 2250042;
E-mail: [email protected], [email protected]
*
yeasts such as Kluyveromyces fragilis or Candida
pseudotropicalis coupled with traditional fermentation
technology, but these yeasts are notoriously weak
fermenters in comparison with the standard industrial- type
strains of Saccharomyces cerevisiae, and although process
improvements through engineering are possible, a need
for strain improvement exists.
Earlier focus was on the enzymic hydrolysis by
β-galactosidase from various microorganisms either in
the free or immobilized form. However, in recent years
the use of whole or permeabilized cells particularly of
food grade yeast Kluyverornyces fragilis has received
more attention [3]. The use of permeabilization technology,
however, can overcome this problem and be helpful in
the development of a low-cost technology for lactose
hydrolysis. The present work was therefore carried out to
apply permeabilization technology for the production of
lactose-hydrolyzed whey using yeast cells and to find out
the optimal conditions for the maximal lactose hydrolysis
in whey and hence maximum ethanol production [4].
65
Dahiya M. et. al. HYDROLYSIS OF WHEY LACTOSE USING CTAB PERMEABILZED THERMOTOLERANT YEAST CELLS
FOR SUBSEQUENT FERMENTATION TO BIOETHANOL
2.5 Effect of Biomass load on lactose hydrolysis
2.1 Microorganism
The effect of permeabilized cell concentration on the
lactose hydrolysis was investigated by adding the different
levels of cell concentrations (50, 100, 150, 200, 250
and 300 mg dry wt/50ml) to the whey. The flasks were
incubated at 40°C under shaking conditions at 100 rpm for
6 h. the samples were taken out at specific intervals and
analysed for lactose content.
Kluyveromyces marxianus NCDC 39 was procured from
the National Collection for Dairy Cultures (NCDC),
Karnal (India). The thermotolerant lactose fermenting
yeast isolates (W16 & W23) and thermotolerant non
lactose fermenting yeast isolates (D44, D54 and SJ16)
were isolated in the lab.
2.2 Maintenance and Cultivation of the culture
2.6
Ethanol production from
permeabilized yeast cells
whey
by
CTAB-
The yeast cultures were revived on maintenance medium
YPD (Yeast extract-10g/l, Peptone-20g/l, Dextrose20g/l). The cultures were incubated at 40°C for 48 h and
maintained for fortnightly intervals on agar slants at 4°C.
The cultures were cultivated for the production of enzyme
on the fermentation media composed of lactose (5%),
peptone (0.5%), yeast extract (0.3%), ammonium sulphate
(0.2%) and potassium di-hydrogen orthophosphate (0.1%).
The 50 ml of fermentation media, in a 250 ml flask, were
inoculated with active yeast inoculum and incubated at
40°C for 36 h at 100 rpm in shaker incubator.
Whey (4.9% lactose) (pH 5.0) was fortified with 0.3%
(NH4)3SO4 and 0.3% yeast extract. The lactose in whey
was hydrolyzed by permeabilized cells of W16, W23 and
NCDC 39 strain (cell biomass 150 mg/ dry wt of each yeast
strains) at 40°C, under agitation for six hours. The selected
non lactose fermenting thermotolerant yeast strains (D54,
D44 and SJ16) were inoculated in the whey medium at
the rate of 1% and incubated at 40°C. The fermentation
was carried out for 90 h. Samples were collected at an
interval of 24 h, centrifuged and analyzed for ethanol
concentration.
2.3 Permeabilization of yeast cells
2.7 Lactose estimation
Permeabilization of W16 and W23 thermotolerant yeast
isolates and K. marxianus (NCDC 39) was carried out
following the method by Kaur [5] with slight modifications.
The cells were harvested from 50 ml of broth by
centrifugation at 5,000 rpm for 5 min at 4°C and washed
twice with phosphate buffer (0.1 M, pH 7.0). CTAB (0.03–
0.15%, w/v) was added to the yeast biomass of W16, W23
and K. marxianus (NCDC 39) and the final volume was
made 5 ml using the same buffer. The contents were mixed
on a vortex mixture and incubated for 10 min under shaking
conditions. After this, the cells were re-centrifuged and
washed twice with the same buffer and used for lactose
hydrolysis of whey.
2.4 Hydrolysis of whey lactose using CTAB permeabilized
yeast cells
The permeabilized yeast cells were used for lactose
hydrolysis in whey. In 50 ml of whey in 250 ml capacity
conical flasks permeabilized yeast cells were inoculated.
The flasks were incubated at 40°C under shaking
conditions at 100 rpm for 6 h (5). The samples were taken
at specific time intervals (0-6 h) and analyzed for lactose
content.
66
Residual lactose was estimated according to the method of
Nickerson et al. [6].
2.8 Ethanol estimation
Ethanol was estimated by the dichromate colorimetric
method, which is based on the complete oxidation of
ethanol by dichromate in the presence of sulphuric acid to
form acetic acid [7].
3. RESULTS AND DISCUSSION
3.1 Permeabilization of yeast cells
To find out the effectiveness of CTAB as a permeabilizing
agent, thermotolerant isolates W16, W23 and NCDC 39
cells were treated with different concentrations (0.030.15% w/v) of cetyltrimethyl ammonium bromide
(CTAB). The results (Fig. 1) showed a progressive increase
in the lactose hydrolysis up to a concentration of 0.06%
(v/v) of CTAB. Further increase in the concentration,
decreased the lactose hydrolysis. CTAB concentration of
0.06% (v/v) displayed maximum lactose hydrolysis for all
the three cultures i.e. for W16 (70±0.13%), W23
(62.66±0.11%) and NCDC39 (60±0.20%). The decrease
in enzyme activity at higher concentration of CTAB may
be attributed to the leakage of the enzyme from the cells or
cell lysis. Less lactose hydrolysis at low concentrations of
CTAB may be due to the insufficient amount of the agent
for effective permeabilization. The use of permeabilized
cells for studying enzymatic activities of micro-organisms
offers many advantages and this technique has been
applied to the different yeast cultures for β-galactosidase
activity using various permeabilization agents. Different
organic solvents for permeabilization of K. bulgaricus
IRC 101 cells for β-galactosidase activity have been
reported [8]. The maximum efficacy has been reported with
30% isopropanol, 40% tert-butanol and 70% ethanol. The
cetyl trimethyl ammonium bromide has been used for
permeabilization of yeast K. fragilis NRRL Y-1196 and
enzyme activity of 220.90 U/g (wet wt) has been reported
while using 0.1% CTAB [4]. Maximum lactose hydrolysis
(90%) of whey was obtained with 0.06% v/v of CTAB
concentration [5]. However, in the present study only 70%
lactose hydrolysis was obtained. Kluyveromyces cells are
known to possess a lactose carrier protein (lactose
permease) on their cell membrane that mediates the
transport of lactose across the cell membrane [9]. Yet,
availability of substrate seems to be the limiting factor in
expressing the full enzymatic activity of whole cells. In
permeabilization, the cell envelope is altered to allow
small molecules, such as substrates, products, or
coenzymes, to cross freely. The permeabilizing agent may
disrupt the membrane structures to allow the passive
passage of low molecular weight solutes in and out of
cells, including lactose and its products of hydrolysis.
These agents act on the cell membranes by decreasing the
phopholipid content [10]. Keeping in view the foregoing
points, a 0.06 % (v/v) concentration of CTAB was selected
for the permeabilization of yeast cells.
3.2 Effect of biomass on lactose hydrolysis by CTAB
permeabilized yeast cells
The effect of permeabilized cell concentration on the
lactose hydrolysis was investigated by adding the different
levels of cell concentrations (50, 100, 150, 200, 250 and
300 mg dry wt/ 50 ml) to the whey. It was seen that lactose
hydrolysis increased with increase in biomass concentration
of permeabilized cells up to 150 mg dw for W16, 250 mg
dw for W23 and 250 mg dw. Thereafter, no increase in
hydrolysis with further increase in biomass concentration
was observed (Fig. 2). Maximum lactose hydrolysis (80%)
was observed with 150 mg dw yeast biomass in all the
three thermotolerant lactose fermenting yeast isolates. The
increase in the lactose hydrolysis with the higher biomass
concentration may be due to the increased availability of
enzyme from yeast biomass. The lack of further increase
in lactose hydrolysis beyond biomass concentration of
level may be attributed to the substrate limitations or
product inhibition [5].
Fig. 2: Effect of cell biomass of CTAB permeabilized yeast cells on
lactose hydrolysis. Bars indicate the standard deviation from triplicate
determinations
3.3 Ethanol production by CTAB permeabilized yeast
(W16) cells
Fig. 3 gives the time course of ethanol fermentation by
thermotolerant yeast isolates W16, W23 and NCDC 39
in the whey medium. After 72 h of fermentation ethanol
production from 4.9 g/l of lactose-whey medium was 0.93%
v/v (W16), 0.87% v/v (W23) and 0.81% (NCDC 39) which
is very less (Fig. 3). Therefore, we used the permeabilized
cells of W16 as whole cell lactase to hydrolyze the lactose
of whey and the released monosaccharides were further
fermented by the D44, D54 and SJ16 isolates.
Fig. 1: Effect of CTAB concentration on the lactose hydrolysis in whey
67
Dahiya M. et. al. HYDROLYSIS OF WHEY LACTOSE USING CTAB PERMEABILZED THERMOTOLERANT YEAST CELLS
FOR SUBSEQUENT FERMENTATION TO BIOETHANOL
Fig. 3: Ethanol Production by lactose fermenting thermotolerant W16,
W23 yeast isolates and Standard culture of NCDC 39 in whey medium
Fig. 4: Ethanol Production by non lactose fermenting thermotolerant
D44, D54 and SJ16 yeast isolates with CTAB-permeabilized yeast
(W16) treated whey
Whey lactose was hydrolysed with 150 mg biomass
of W16 permeabilized cells for a period of 6 h [5]. The
production of ethanol from lactose hydrolyzed whey
medium (5% lactose) is depicted in Fig. 4. Data presented
in the Fig. 4 clearly shows that among all the non lactose
fermenting thermotolerant yeasts used D54 produced
1.54% v/v of ethanol, whereas D44 (1.23% v/v) and SJ16
yielded 1.09% v/v of ethanol from whey medium and it
more than ethanol production in the whey medium without
permeabilization (Fig. 3). Rosenberg et al [13] reported that
rapid lactose hydrolysis by small amounts of permeabilized
cells of Kluyveromyces marxianus CCYeSY2 following
the fermentation of released glucose and galactose by S.
cerevisiae resulted in a twofold enhancement of the overall
volumetric productivity (1.03 g/l x h), compared to the
fermentation in which the lactose was directly fermented
by K. marxianus.
4. CONCLUSIONS
The use of permeabilized cells technology can help to
overcome the problems/costs associated with enzyme
extraction and purification from yeast cells and development
68
of a low-cost technology for lactose hydrolysis. The present
work has focused on the optimization of permeabilized
cells technology for maximum hydrolysis of whey lactose
and its subsequent fermentation to produce bioethanol. Out
of two thermotolerant lactose fermenting yeast isolates i.e.
W16, W23 and one standard culture of NCDC 39, W16
act as a good source of lactase and showed maximum
lactose hydrolysis (80%) in 6 hour of incubation.
Subsequent fermentation of lactose hydrolysed whey by
non lactose fermenting thermotolerant yeast isolates leads
to enhancement in ethanol production.
REFERENCES
1.
Bailey, R. B., Benitez, T. and Woodward, A. Saccharomyces
cerevisiae Mutants Resistant to Catabolite Repression: Use
in Cheese Whey Hydrolysate Fermentation. Applied and
Environmental Microbiology: 44 (3). 1982
2.
Gawel, J. and Kosikowski, F. V. Improving alcohol
fermentation in concentrated ultrafiltration permeates of
cottage cheese whey. Journal of Food Science: 43. 1978.
3.
Bachhawat, N., Gowda, L. R. and Bhat, S. G. Single
step method of preparation of detergent- permeabilized
Kluyveromyces fragilis for lactose hydrolysis. Process
Biochemistry: 31(1). 1996.
4.
Logsdon, J. E. Ethanol, in: R. E. Kirk, D. F. Othmer (Eds.)
Encyclopedia of Chemical Technology. John Wiley & Sons,
Inc., New York. 2006.
5.
Joshi, M. S., Gowda, L. R. and Bhat, S. G. Permeabilization
of yeast cells (Kluyveromyces fragilis) to lactose by CTAB.
Biotechnology Letters: 9. 1987.
6.
Kaur, G., Panesar, P. S., Bera, M. B. and Kumar, H.
Hydrolysis of Whey Lactose Using CTAB-permeabilized
Yeast Cells. Bioprocess and Biosystem Engineering: 32.
2009.
7.
Nickerson, T. A., Vujicic, I. F. and Lin, A. Y. Colorimetric
estimation of lactose and its hydrolytic products. Journal of
Dairy Science : 59. 1976.
8.
Caputi, A. J., Ueda, M. and Brown, T. Spectrophotometric
Determination of Ethanol of Wine. American Journal of
Enology and Viticulture: 19. 1968.
9.
Decleire, M. De-Cat, W. and Van-Huynh, N. Comparison of
various permeabilization treatments on Kluyveromyces by
determining in situ beta galactosiadse activity. Enzyme and
Microbial Technology: 9. 1987.
10. Dickson, R. C and Markin, J. S. Physiological studies
of beta-galactosidase induction in K. lactis. Journal of
Bacteriology: 142. 1980.
COMPUTATIONAL ANALYSIS OF HALOTOLERANCE GENES
FROM HALOPHILIC PROKARYOTES TO INFER THEIR
SIGNATURE SEQUENCES
Tamanna Anwar1 and Rajinder S. Chauhan1*
Department of Biotechnology and Bioinformatics, Jaypee University of Information Technology,
Solan-173215, H.P. India
1
Abstract
Halophiles represent organisms which live, grow, and multiply in highly saline environments. The study of these organisms
has considerable biotechnological potential due to the identification of novel compounds of industrial importance. It has
been found that many proteins and enzymes do not withstand industrial reaction conditions. Thus, the characterization of
gene structures from the microorganisms that are able to thrive in hypresaline environments can be valuable information
to infer what makes halotolerant protein to work under halophilic environments. At present, only a minor fraction of the
halophilic microorganisms have been exploited. Driven by increasing industrial demands for biocatalysts that can cope
with halophilic industrial process conditions, a comparative genomics approach was used to identify genes involved
in halotolerance of halophiles. Comparative gene structure and protein properties were studied in extreme halophiles
(EH), moderate halophiles (MH), slight halophiles (SH) and non-halophiles (NH). Computational analysis of organisms
able to thrive in hypersaline environments resulted in identification of forty two halotolerance genes. Comparative gene
structure and protein properties were studied in halophiles. Forty-two genes involved in halotolerance were identified in
19 completely sequenced archaea and bacteria. The most predominant family of halotolerance proteins among halophiles
was of regulators of ion transporters (29.0 %) followed by transporters (24.0%). The halotolerance proteins of extreme
halophile (EH) are more acidic. There was an enormous increase of non-polar amino acids at the surface of EH. The
occurrence of non-polar amino acid at the surface of EH was one of the distinctive observations. The current study has
implications not in only understanding the structure of halotolerance proteins but the identification of specific domains/
motifs and signature that can help in the development of prediction tools for computational identification and analysis
of halotolerance proteins.
Keywords: Comparative analysis, Transporters, Halophiles, Halotolerant, Hypersaline
1. Introduction
Halophilic microorganisms are found in all three domains
of life: Archaea, Bacteria and Eucarya [1]. These halophilic
and halotolerant microbes live in the highly ionic
environments [2], one of the most important questions
asked about these microbes is the nature of adaptations
that these organisms have undergone to survive in highly
saline environments.
Microbes that inhabit hypersaline environments experience
intense osmotic pressure, thus these microorganisms use
“compatible solute strategy” or the “salt-in strategy” [3,4].
Prof. Rajinder S. Chauhan, Professor and Head, Department of
Biotechnology & Bioinformatics, Jaypee University of Information
Technology, Waknaghat, Dist. Solan, Himachal Pradesh-173234, India.
Tel No: +91-1792-239231, Fax: +91-1792-245362 (rajinder.chauhan@
rediffmail.com)
*
The halophiles produce biocatalysts that are functional
under extreme conditions, which have resulted in several
novel applications of enzymes in industrial processes
such as Nuclease H from Micrococcus varians subsp.
halophillls is used for the industrial production of the
flavouring agents 5’-guanylic acid and 5’-inosinic acid.
Amylase produced by a Bacillus sp. is stable at 60°C and
5M NaCl and could be used in the treatment of effluents
containing starchy or cellulosic residues [5]. The industrial
applications of enzymes that can withstand harsh saline
conditions have greatly increased over the past decade.
A major impetus driving research on halophiles is
the biotechnological potential associated with these
microorganisms and their cellular products.
From the early 1980’s, halophilic microorganisms
have been considered as a group of extremophiles with
a biotechnological potential similar to that of other
69
Anwar et al. COMPUTATIONAL ANALYSIS OF HALOTOLERANCE GENES FROM HALOPHILIC PROKARYOTES TO INFER THEIR SIGNATURE SEQUENCES
extremophilic microorganisms. The few halobacterial
exo-enzymes that have been reported include the amylases
from Halobacterium halobium and Halobacterium
sodomense, proteases from Halobacterium salinarium
and Halobacterium halobium; restrictases, from
Halobacterium ctitirubrum, Halobacterium halobium,
Halobacterium salinarium and Halococcus agglomeratus,
have been isolated and are available commercially [6,7,8].
Recent advances in the study of extremozymes point
to the acceleration of this trend. These extremophilic
microorganisms are already used for some biotechnological
processes, for example halobacteria are used for the
production of bacteriorhodopsin, and the alga Dunaliella
is used in the commercial production of β-carotene.
Several other potential applications of halophiles such as
the production of polymers (polyhydroxyalcanoates and
polysaccharides), enzymes, and compatible solutes, and
the use of these extremophiles in enhanced oil recovery,
cancer detection, drug screening and the biodegradation of
residues and toxic compounds are also reported [9,10].
Enzymes from halophiles of Soda Lake are used in the
cleaning industry [10]. An extracellular protease from
Halobacterium halobium has been exploited for efficient
peptide synthesis in water/N’-N’-dimethylformamide [11].
A p-nitrophenylphosphate phosphatase (p-NPPase) from
Halobacterium salinarum was used in an organic medium
at very low salt concentrations after entrapping the enzyme
in reversed micelles [12]. As a result, the characterization of
microorganisms that are able to thrive in extreme saline
environments has received a great deal of attention: such
halophiles are a valuable source of novel enzymes.
The current study presents an extensive and systematic
comparative analysis of archaeal and bacterial halophiles
with a view to computationally analyze the genes that are
involved in halophilic adaptation. We have examined the
preferences, if any, of a particular class of proteins that is
instrumental for halophilic adaptation. This study examines
in detail the properties of proteins involved in halotolerance
from extreme halophiles (EH), moderate halophiles (MH),
slight halophiles (SH) and non-halophiles (NH), to infer
specific protein signatures involved in halotolerance.
2.
Methods
2.1 Sequence Retrieval
Completely sequenced archaeal and bacterial halophiles/
non-halophiles (19 halophiles/non-halophiles) were
70
selected (Table 1) and the proteomes of the selected
halophiles were downloaded from GenBank [13]. Proteins
involved in halotolerance of different eukaryotic and
prokaryotic organisms were searched from literature
and GenBank database. Forty-two proteins involved in
halotolerance were searched (Table 2) and nucleotide and
amino acid sequences of these proteins were retrieved
from GenBank [13]. All the completely sequenced archaeal
and bacterial halophiles were searched at NCBI for the
presence of halotolerance genes.
2.2 Homology Search
A database containing proteomes of 19 archaeal and
bacterial halophiles/non-halophiles was created using
the tool FormatDB available at NCBI. Proteins for
halotolerance were searched for the homologues across
the created database of nineteen selected archaeal and
bacterial halophiles using BlastP. The proteins having
significant similarity (evalue 10-10) to the halotolerance
proteins were retrieved from halophilic archaeal and
bacterial species.
2.3 Characterization of proteins into classes and families
and identification of domains
The classification of halotolerance proteins from archaeal
and bacterial halophiles into a particular class and
presence of specific domains was carried out by using
bioinformatics tools available at Clusters of Orthologous
Groups of Proteins [14,15].
2.4 Comparative analysis of protein properties
Comparative analysis of different properties of
halotolerance proteins that were showing homologs with
70% identity and 60% coverage in different classes of
microorganisms such as EH, MH, SH and NH was done to
see the variation in acidic/basic behaviour, pI (Isoelectric
point), amino acid composition, etc. For this analysis,
twenty-one halotolerance proteins out of forty-two were
chosen because for rest of the proteins homologs in different
classes of halophiles were not found. The contributions
of each residue of the amino acid compositions in EH,
MH, SH and NH were estimated, based on the average
compositions of the twenty amino acid residues. Amino
Acid composition and isoelectric point (pI) of the proteins
are studied using Protein Calculator v 3.3 [16]. To see the
solvent accessibility of the protein molecules online tool
RVP-NET was used [17].
3. Results
3.1 Sequence and Homology Search
Total forty-two genes involved in halotolerance were identified through literature survey in different organisms. The
genes that are proved to be involved in halotolerance either through knock-out studies or through overexpression studies
were selected. These included 26.19% genes from plants, 38.10% genes from fungi, 33.33% genes from bacteria and
2.38% genes from archaea.
Table 1. Halophilic/non-halophilic archaea and bacteria selected for retrieving halotolerance genes/proteins
Category
Extreme halophile
Archaea
Halobacterium sp. NRC-1
Bacteria
Salinibacter ruber
Haloquadratum walsbyi
Haloarcula marismortui
Hyperthermus butylicus
Halorhodospira halophila
Alkalilimnicola ehrlichei
Alkaliphilus metalliredigens
Methanocaldococcus jannaschii
Methanococcoides burtonii
Methanopyrus kandleri
Natronomonas pharaonis
Pseudoalteromonas haloplankits
Chromohalobacter salexigens
Marinobacter aquaeolei
Oceanobacillus iheyensis
(15.0-30.0% Salt)
Moderate-halophiles
(5.0-15% Salt)
Slight-halophiles
(2.0-5.0% Salt)
Aeropyrum pernix
Methanocaldococcus vulcanius
Non-halophile
Bacillus amyloliquefaciens
(<2% Salt)
Table 2. Halotolerance genes reported in different organisms
Organism
Category
Source Organism
Gene
Archaea
Halobacterium salinarum
bop
Bacteria
Halomonas elongata
Organism
Source
Gene
Saccharomyces cerevisiae
hal4
ectA
hal5
Halomonas elongata
ectB
hal11
Halomonas elongata
ectC
ena1
Lactococcus lactis
dnaK
Debaryomyces hansenii
ena2
Tetragenococcus halophila
groEL
ppz1p
Lactococcus lactis
groES
ppz2p
Listeria monocytogenes
cysK
nhx1
Sinorhizobium meliloti
rtsE
ura5
ccpA
Arabidopsis thaliana
malic enzyme
Fungi
71
Fungi
gap
Beta vulgaris
ura4
gbuA
Sesuvium portulacastrum
stp
Halomonas elongata
nhaD
gsk1
Sinorhizobium meliloti
relA
Lophopyrum elongatum
esi47
Halobacterium salinarum
ndk
Beta vulgaris
stp4
Debaryomyces hansenii
gpd1
rcy1
tol1
Capsicum annuum
czf1
trk1
Beta vulgaris
eif-1A
Candida albicans
cnh1
Chlamydomonas sp. W80
bbc1
Lodderomyces elongisporus
hal2
aca4
Plants
3.2 Classification of Proteins Into Different Classes
3.3 Comparative Analysis of Protein Properties
The halotolerance proteins belong to five different
categories: Ion transporters, regulators of ion transporters,
chaperones, salt toxicity targets and genes involved
in osmotic tolerance. Ion transporters are involved in
ion transport and carry out essential functions in salt
tolerance. Regulators of ion transporters are the proteins
which regulate the activity of the Na+ efflux ATPase and of
the K+ uptake system. Salt toxicity targets are the proteins
which are identified in the system at the time of salt
toxicity (genes for the protein synthesis initiation factor,
uracil biosynthesis enzyme, etc. Osmotic tolerance genes
are those involved in maintaining osmotic balance through
the production of osmotic solutes. Chaperones help in
maintaining the structural stability of the halotolerance
proteins.
3.3.1 pI (Isoelectric Point)
Cataloging of halotolerance proteins from published
literature and their classification showed that majority of
the proteins belonged to regulators of ion transporters
(29.0%), followed by transporters 24.0%), salt toxicity
targets (21.0%), osmotic tolerance proteins (14.0%) and
chaperones (7.0%) (Fig. 1).
The increase in solubility and retention of function of
halophiles at highly saline environments is thought to
be due to the presence of high surface negative charge
in halophilic proteins [14]. It is reported that halophilic
bacteria have the shift of pI distribution toward acidity,
which is probably related to their adaptation to high salt
environments. Keeping this in consideration comparison
of pI in homologs of haotolerance proteins in EH, MH, SH
and NH was carried out. It was observed that the proteins
from EH’s have lowest pI with an average of 5.3 followed
by MH (6.3). There were slight differences in the average
pI of MH (6.2), SH (6.8) and NH (6.4) (Fig. 2). The
transporters, regulators of ion transporters and molecular
chaperones are more acidic in comparison to the proteins
for salt toxicity targets and osmotic tolerance proteins (e.g.
proteins involved in production of compatible solutes).
The protein encoded by gpd1, was less acidic (pI value
6.3) in EH than other proteins of EH (having pI values of
4.3-5.3). Similarly genes ura4, ura5, relA belonging to salt
toxicity targets and osmotic tolerance are also less acidic
than other proteins from EH. The proteins encoded by hal2,
hal3 and hal11 that are involved in transport mechanism
are more acidic (pI of 5.0-5.3) in EH in comparison to their
homologs in MH, SH and NH’s (pI of 9.0-9.5) (Fig. 2).
3.3.2 Amino Acid Composition of Halotolerance Proteins
Fig. 1: Functional classification of halotolerance proteins.
Classification of halotolerance proteins on the basis of their function
72
In order to survey the trend of amino acid composition
of halophilic proteins, the homologs from four groups
of halophiles (EH, MH, SH and NH) were examined.
Two sorts of amino acid compositions, first composition
of the entire protein molecule, and second amino acid
composition at the surface of the protein was considered.
An increase in frequency of acidic amino acid in EH was
observed and the trend was EH >MH >NH>SH (Fig. 3).
SH were showing lesser acidic amino acid frequency than
that of NH. The frequency of basic amino acid decreased
in the order EH < MH < NH < SH, here again in case of
MH basic amino acids were greater than NH. It is reported
that halophilic proteins are acidic in nature and the
increase in acidic amino acids is compensated by decrease
in basic amino acids. This trend was very well followed
in our results, except for proteins from SH that were not
consistent with this trend.
The frequency of Pro and Gly was higher in case of
extreme halophiles (Fig. 4a and 4b). These amino acids
often act as compatible solutes and osmoprotectants
under conditions of stress. There was an increase in the
frequency of Pro in EH, while in case of MH and SH the
frequency of Pro was even less than the NH.
Significant increase in the frequency of Pro among EH
was observed in the genes belonging to regulators of ion
transporters (aca4, esi47, hal3, hal5), transporters (ena1,
gbuA), osmotic tolerance proteins (gpd1, relA) and salt
toxicity target (hal2). The increase in the Pro frequency
was higher in the genes esi47 and hal5, both of which
belong to regulators of ion transporters (Fig. 4a).
Similarly, there was an increase in the frequency of Gly in
EH, while in case of MH the frequency of Gly was almost
equivalent to that of NH’s, except for the genes encoding
regulators of ion transporters (hal3, hal5) and salt toxicity
target (ura4), where Gly frequency was slightly higher
than NH. In SH the frequency of Gly was even less than
that of NH.
Fig. 2: Plot of average isoelectric point to compare acidic nature of proteins. Plot of average isoelectric point in proteins of EH, MH, SH and NH
to compare acidic nature of proteins in the four groups
Significant increase in the frequency of Gly among EH
was observed in the genes belonging to regulators of ion
transporters (esi47, hal3, hal5), transporters (ena1, ena2,
gbuA, hal11), osmotic tolerance proteins (cysK, gpd1,
relA) and chaperones (dnaK, groEL) (Fig. 4b).
3.3.3 Amino Acid Composition at the Surface of Proteins
Comparison of amino acid composition at the surface of
proteins showed that EH have abundance of acidic amino
acids at the surface in comparison to MH, SH and NH.
There was a marked reduction of basic amino acid at the
surface in EH, while the frequency of basic amino acid
was almost comparable in case of MH, SH and NH. One
of the strange observations was the enormous increase of
non-polar amino acid at the surface of EH (Fig. 5).
3.3.4 Comparison of Acidic and Basic Amino Acids among
Different Classes of Organisms
Comparison of acidic amino acids Asp and Glu in all the
four groups is presented in Fig. 6a and 6b. In our results
we observed that the frequency of Asp was higher in EH’s.
Whereas, in case of MH and SH, the frequency of Asp was
less than that of NH. The frequency of Glu was found to be
greater in MH’s in comparison to EH, MH and NH. No
73
significant pattern was observed for Asn and Gln in all the four groups. The frequency of basic amino acid lysine in EH
was much lower than the other three groups. While, there was not much difference in lysine composition in MH, HS and
NH (Fig. 6c).
Fig. 3: Comparison of acidic, basic, polar, and non-polar residues among halotolerance protein. Proportion of acidic, basic, polar, and non-polar
residues for each of the groups of EH, MH, SH and NH. Basic - Arg and Lys; acidic - Asp and Glu; polar - Asn, Gln, Ser, and Thr; nonpolar - Ile,
Leu, Met, Phe, Trp, Tyr, and Val; others - Ala, Cys, Gly, His, and Pro.
Fig. (4a): Average frequency of residue proline in halotolerance proteins. Average frequency of residue proline in halotolerance proteins from EH,
MH, SH and NH classes of organisms.
74
Fig. (4b): Average frequency of residue glycine in halotolerance proteins. Average frequency of residue glycine in halotolerance proteins from EH,
MH, SH and NH classes of organisms.
Fig. 5: Comparison of acidic, basic, polar, and non-polar residues at the surface of halotolerance proteins. Proportion of acidic, basic, polar, and
non-polar residues at the surface of halotolerance proteins for each of the groups of EH, MH, SH and NH. Basic - Arg and Lys; acidic - Asp and
Glu; polar - Asn, Gln, Ser, and Thr; nonpolar - Ile, Leu, Met, Phe, Trp, Tyr, and Val; others - Ala, Cys, Gly, His, and Pro.
75
4. Discussion
Computational analysis of proteins involved in
halotolerance in organisms with varying levels of
halotolerance such as extreme, moderate, slight and
non-halophiles with a view to understand variation
in sequence signatures in halotolerance proteins from
different categories was carried out. This study examined
in detail the comparison of properties of proteins involved
in halotolerance among different categories of halophiles.
To distinguish molecular adaptation of halophiles at
extreme halophilic conditions, a comparative analysis of
halotolerance proteins for properties like pI (Isoelectric
Point) and amino acid composition for homologs of
halotolerance proteins from different microorganisms
with varying levels of salt tolerance (EH, MH, SH and
NH) was carried out.
The halotolerance proteins obtained from literature showed
variation in numbers of proteins from different organisms,
in particular lower numbers in sequenced genomes of
halophilic bacteria and archaea may be due to the fact
that few halotolernace genes have been identified and
characterized in those through wet lab experimentation.
The most predominant family of proteins involved in
halotolerance among halophiles was of regulators of ion
transporters followed by transporters. It is reported that Na+
enters plant cells through transporters [19]. The membranes
of halophilic prokaryotes possess high Na+/H+ antiporter
activity, which use the proton electrochemical gradient as
the driving force for the extrusion of Na+ from the cell [18].
The comparison of pI in homologs of haotolerance genes
in EH, MH, SH and NH; revealed that EH have lowest
pI followed by MH. There were slight difference in the
average pI of MH (6.2), SH (6.8) and NH (6.4). Halophilic
bacteria have the shift of pI distribution toward acidity,
which is probably related to their adaptation to high salt
environments [20]. Earlier studies have also reported that
function of halophiles at highly saline environments is
thought to be due to the presence of high surface negative
charge in halophilic proteins [19]. It was also observed that
the proteins for transporters, regulators of ion transporters
and molecular chaperones are more acidic in comparison
to the proteins for salt toxicity targets and osmotic
tolerance proteins (e.g. proteins involved in production of
compatible solutes). Moreover, the proteins encoded by
genes, hal2, hal3 and hal11 that are involved in transport
mechanism are much more acidic in EH in comparison
to their homologs in MH, SH and NH. An increase in
frequency of acidic amino acid’s was observed in the order
EH>MH>NH>SH. The frequency of basic amino acid’s
was shown to decrease in the order EH<MH<NH<SH.
Halophilic proteins are acidic in nature and the increase
76
in acidic amino acid is compensated by decrease in
basic amino acid [20]. This trend was very well followed
in our results, except for proteins from SH that were
not consistent with this trend. The increase in solubility
and retention of function of halophiles at highly saline
environments is thought to be due to the presence of high
surface negative charge in halophilic proteins [19]. The
frequency of proline and glycine was also higher in case of
extreme halophiles. Amino acid’s often act as compatible
solutes and osmoprotectants under conditions of stress. It
is seen that Pro accumulates in Pisum sativum under salt
stress [20]. Enormous increase of non-polar amino acids
was observed at the surface of EH (Fig. 5). It is reported
that anti-freeze proteins have abundance of non-polar
groups at the surface [11]. Thus, the non-polar amino acids
at the surface of EH may be helping in adaptation of
psychrophilic conditions.
Fig. (6a): Comparison of residues Asp in halotolerance proteins.
Average frequency of residues Asp in EH, MH, SH and NH
Fig. (6b): Comparison of residues Glu in halotolerance proteins.
Average frequency of residues Glu in EH, MH, SH and NH
of basic amino acid at the surface of proteins from EH, in
comparison to MH, SH and NH. There was an enormous
increase of non-polar amino acid at the surface of EH in
comparison to other three groups. The current study has
implications in not only understanding the structure of
halotolerance proteins but the identification of specific
domains/motifs and signature amino acid residues can help
in the development of prediction tools for computational
identification and analysis of halotolerance proteins in
already sequenced or to be sequenced genomes.
6. Acknowledgements
Fig. (6c): Comparison of residues Lys in halotolerance proteins.
Average frequency of residues Lys in EH, MH, SH and NH
We are thankful to the Jaypee University of Information
Technology for providing financial assistance to carry out
the project.
The frequency of Proline and Glycine was also higher
in case of extreme halophiles. Amino acids often act as
compatible solutes and osmoprotectants under conditions
of stress. It is reported that Pro accumulated in Pisum
sativum under salt stress [20]. Proline appears to be the most
widely distributed compatible solute in organisms from
bacteria to plants. There is a positive correlation between
Pro accumulation and adaptation to salt and drought stress.
7. Author’s Contribution
Comparison of amino acids composition at the surface
of proteins showed that the halotolerance proteins in EH
have abundance of acidic amino acids at the surface in
comparison to MH, SH and NH (Fig. 5). The amino acid
residues located at the protein surface have been proposed
to bind to a network of hydrated salt ions that cooperatively
contribute to the stabilization [20].
RSC initiated the idea and supervised the work also, given
final approval of the version to be published. All authors
read and approve the final manuscript.
5. Conclusions
Computational analysis of the halotolerance proteins
resulted in identification of forty two proteins involved
in halotolerance. Functional classification of the proteins
revealed that the most predominant class of proteins
involved in halotolerance among halophiles was of
regulators of ion transporters followed by transporters.
The proteins of EH show more acidic nature in comparison
to proteins of MH, SH and NH. The frequency of acidic
amino acid Asp was higher in EH, whereas, in case of MH
and SH the frequency of Asp was even lesser than that
of NH. The frequency of Glu was found to be greater in
MH in comparison to EH, MH and NH. The frequency of
basic amino acid lysine in EH’s was much lower than the
other three groups. There was an increase in frequency of
Pro and Gly in case of EH. At the protein surface EH have
abundance of acidic amino acid in comparison to MH, SH
and NH. There was a marked reduction in the frequency
TA have made substantial contributions to conception
and design, and performed identification studies of
microorganisms and genes, also carried out analysis and
interpretation of data; have been involved in drafting
the manuscript or revising it critically for important
intellectual content.
REFERENCES
1.
Oren, A. Bioenergetic aspects of halophilism. Microbiology
and Molecular Biology Reviews 63(2), 334-348, 1999.
2.
Lanyi, JK. Salt-dependent properties of proteins from
extremely halophilic bacteria. Bacteriology Reviews 38(3),
272-290, 1974.
3.
Litchfield, CD. Survival Strategies for Microorganisms:
Hypersaline Environments and Their Relevance to Life on
Early Mars. Meteoritics and Planetary Science 33(4), 813819, 1998.
4.
Rus, A, Yokoi, S, Sharkhuu, A, Reddy, M, Lee, BH, et al.
AtHKT1 is a salt tolerance determinant that controls Na (+)
entry into plant roots. Proceedings of the National Academy
of Sciences 98(24), 14150–14155, 2001.
5.
Good, VA and Hartman, PA. Properties of the arnylase from
Halobacterium halobium. Journal of Bacteriology 104(1)
601-603, 1970.
6.
Oren, A. A thermophilic amyloglucosidase from
Halobacterium sodomense, a halophilic bacterium
from the Dead Sea. Current Microbiology 8,
225-230, 1983.
77
7.
Norberg, P and Hofsten, BV. Proteolytic enzymes
from extremely halophilic bacteria. Journal of General
Microbiology 55(2), 251-256., 1969.
8.
Izotova, LS, Strongin AY, Chekulaeva LN, Sterkin, VE,
Ostoslavskaya VI, et al. Purification and properties of
serine protease from Halobacterium halobium. Journal of
Bacteriology 155(2), 826-830, 1983.
9.
Rozzell, JD. Commercial scale biocatalysis: myths and
realities. Bioorganic & Medicinal Chemistry 7(10), 22532261, 1999.
10. Smith, MD and Danson, M. The life of brine: halophiles in
2001. Genome Biology 2, 4033.1–4033.3, 2001.
11. Kim, J and Dordick, JS. Unusual salt and solvent dependence
of a protease from an extreme halophile. Biotechnology and
Bioengineering 55(3), 471-479, 1997.
12. Marhuenda-Egea, FC, Piere-Velazquez, S, Cadenas, C and
Cadenas E. An extreme halophilic enzyme active at low salt
in reversed micelles. Journal of Biotechnology 93(2), 159164, 2002.
13. Benson, DA, Karsch-Mizrachi, I, Lipman, DJ, Ostell,
J and Sayers, EW. GenBank. Nucleic Acids Research,
39(Database issue), D32-37, 2011. www.ncbi.nlm.nih.gov/
Genbank/
14. Tatusov, RL, Natale, DA, Garkavtsev IV, Tatusova,
TA, Shankavaram, UT, et al. The COG database: new
developments in phylogenetic classification of proteins
from complete genomes. Nucleic Acids Research 29(1), 2228, 2001. www.ncbi.nlm.nih.gov/COG/
15. Servant, F, Bru, C, Carrere, S, Courcelle, E, Gouzy, J, et
al. ProDom: Automated clustering of homologous domains.
Briefings in Bioinformatics 3(3), 246-251, 2002. http://
prodom.prabi.fr/prodom/current/html/form.php
16. Putnam, C. The Scripps Research Institute. Protein
Calculator v 3.3, 2006. www.scripps.edu/~cdputnam/
protcalc.html
17. Ahmad, S, Gromiha, MM and Sarai, A. RVP-net: online
prediction of real valued accessible surface area of proteins
from single sequences. Bioinformatics, 19(14), 1849-1851,
2003.
http://gibk26.bse.kyutech.ac.jp/jouhou/shandar/
netasa/rvp-net/
18. Lanyi, JK and MacDonald, RE. Existence of electrogenic
hydrogen ion/sodium ion antiport in Halobacterium
halobium cell envelope vesicles. Biochemistry 15(21),
4608-4614, 1976.
19. Epstein, E. How calcium enhances plant salt tolerance.
Science 280(5371), 1906–1907, 1998.
20. Oren, A, and Mana, L. Amino acid composition of bulk
protein and salt relationships of selected enzymes of
Salinibacter ruber, an extremely halophilic bacterium.
Extremophiles 6(3), 217-223, 2002.
78
IDENTIFICATION OF T-CELL ANTIGENIC DETERMINANTS IN
THE PROTEINS OF HUMAN PAPILLOMAVIRUS
Dharmendra Kumar Chaudhary1,2, Indra Mani1,3, Vijai Singh1,4 *
National Bureau of Fish Genetic Resources, Canal Ring Road, PO- Dilkusha, Lucknow, 226002, India
2.
Department of Biotechnology, H.N.B. Garhwal University, Srinagar Garhwal, India
3.
Department of Biochemistry, Faculty of Science, Banaras Hindu University, Varanasi, 221005, India
4.
Molecular Diagnostics & Biotechnology Laboratory, Division of Crop Protection
Central Institute for Subtropical Horticulture, Lucknow -227107, India
1.
ABSTRACT
BACKGROUND: Human papillomavirus (HPV) infection is one of the most common sexually transmitted viral
infections which cause the cervical cancer in women globally. Identification of HPV T-cell epitopes would be an
important not only for our understanding of the protective immune response but also in the development of vaccines for
immunotherapy. Thus, there is an urgent need for HPV T-cell specific antigen for appropriate diagnostic and vaccination.
METHODOLOGY: We have used several bioinformatics tools for analysis of HPVs genome. Propred and Propred1
have been used for identification of T-cell epitopes in all protein sequences of HPVs.
RESULTS: Total 48 promiscuous T-cell epitopes in HPV 16 and 60 promiscuous T-cell epitopes in HPV 18 were
identified against major histocompatibility complex (MHC) Class I molecule. Whereas, total 41 T-cell epitopes in HPV
16 and 45 epitopes in HPV 18 were also identified for MHC class II molecule. These epitopes showed highest binding
score at optimal threshold and also verified using the existing data.
CONCLUSION: The characterization of novel T-cell epitopes and long lasting epitope specific memory T-cells may be
useful for development of a potential epitope based vaccine against HPV. These finding provide new insight for accelerating
immunology and immunotechnology for development of vaccines and monoclonal antibody for immunotherapy.
Keywords: Human Papillomavirus; T-cell; epitope; immunotherapy; major histocompatibility complex; vaccine
1. INTRODUCTION
Human papillomaviruses (HPVs) are causative agents of
tumor (papilloma) and also causes cervical cancer in
women. It is major concern of public health globally.
Cancer of the uterine cervix is second most common
malignant tumor in world (CANCER Mondial [http://
www-dep.iarc.fr/], 2005). Approximately, 100,0001,40,000 women are suffering from cervical cancer every
year constituting about 16% of the world’s annual
incidence.[1] However, cervical carcinomas are unfortunate
Molecular Diagnostics & Biotechnology Laboratory
Division of Crop Protection
Central Institute for Subtropical Horticulture
Rehmankhera, Lucknow -227107 (U.P.), India
Tel: +91 522 2841022
Fax: +91 522 2841025
E-mail: [email protected]
*
complications of long standing infections with high risk in
women.[2] In a meta-analysis of cervical squamous cell
carcinomas compared to high grade squamous
intraepithelial lesions HPV16, HPV18 and HPV45
appeared to display an elevated prevalence in cervical
cancer.[3] A second meta-analysis revealed that HPV16 and
HPV18 are more prevalent in Squamous Cell
Carcinoma (SCC) than in low-grade Squamous
Intraepithelial Leison (SIL).[3] There is an increasing the
demand for diagnostic for the detection of HPV and also
requires the suitable and potent vaccines for control of
infection. There are two vaccines such as Gardasil and
Cervarix against both highly pathogenic HPV types 16
and 18 which give protection for 70% of cervical cancers,
80% of anal cancers, 60% of vaginal cancers, and 40%
of vulvar cancers.[4] Therefore, we require more protection
against HPV and now bioinformatics tools have been
developed that can help for designing of more vaccines.
79
Chaudhary D. K. et. al. IDENTIFICATION OF T-CELL ANTIGENIC DETERMINANTS IN THE PROTEINS OF HUMAN PAPILLOMAVIRUS
Recently, development of several immunoinformatics and
computational biology tools are useful for identification of
antigenic regions (epitopes) in the protein sequences which
can accelerate the wet laboratory practices. These tools
have been developed on the basis of existing and validated
data with specific algorithms.[5] An epitopes are also
known as antigenic determinant in the protein sequences
which is recognized by the major histocompatibility
complex (MHC) molecules. These epitopes are short
peptides between 8 and 11 amino acids in lengths. The
advances immunoinformatics tools enable the systematic
identification of potential antigen from pathogenic
microorganisms that is possible to develop a safe and
effective vaccine against any infectious disease.[6,7] These
tools assist the designing of subunit vaccines that can start
from prediction of antigenic epitope in protein sequences.
[8]
Identification of T-cell epitopes in proteins of human
papilomavirus using Propred and Propred1 are the newer
strategies for the identification of antigenic peptide that can
use in diagnostic and further vaccines development.[9,10]
Therefore, one of major risk for working with pathogenic
microorganism can not be easily culture thus; it requires
high level biosafety containment facility. The culture of
HPV also requires the cell line for growing and all these
steps are time consuming, laborious and cost effective.
[11]
Therefore, antigen preparation of HPV is not an easy
process thus; immunoinformatics tools were helpful for
identification of antigenic site from complete protein
sequences which are available in databank. The aim of
present study was to identify and map the T-cell epitopes
in the complete genome encoding putative proteins
sequences of Human papilomavirus type 16 and 18.
There are an increasing the availability of genes and
genomes sequencing data of microbes that can help to
accelerate our wet laboratory experiments. We have used
Bioinformatics and Immunoinformatics tools for analysis
of whole of genome of Human papillomavirus. The
complete genome sequence of HPV type 16 and 18 were
retrieved from NCBI-GenBank (http://www.ncbi.nlm.
nih.gov/genbank/). The open reading frames (ORF) were
identified and verified from the whole genome sequences
using Gene Runner, ORF finder, APE and DNAstar
softwares. ApE, plasmid editor software was used to design
the genome of HPV. The expected molecular weight and
isoelectric point (pI) value of proteins were also verified
using Gene Runner and ExPasy (http://www.expasy.
org/). We have used Propred (http://www.imtech.res.in/
raghava/propred/) and Propred1 (http://www.imtech.res.
in/raghava/propred1/) immunoinformatics tools which
80
are available for identification of epitopes in the protein
sequences. There are significant efforts have been made
in last decade by several groups devoted their research
toward the development of procedures and algorithms
that allow more effective and accurate prediction of MHC
binding affinity. These tools cover maximum number of
human leukocyte antigen (HLA) comparison to other
immunoinformatics tools. Thus, we have considered the
parameters during epitopes prediction such as 4% threshold
with maximum binding score to HLA molecules.[9,10] The
predicted T-cell epitopes were also used for verification
and homology matching with other amino acids by NCBI
protein blast.
3. RESULTS
3.1 Physicochemical analysis of HPVs
Fig. 1: Position of putative genes sequences represented in genome of
Human Papillomavirus. (a): HPV type 16 and (b): HPV type 18.
The complete genome size of HPV 16 was 7904 bp but
the proteins encoding region was started from 83 for E6
to 7154 for L1 protein. While in HPV 18 was 7857 bp and
proteins encoding region was started from 105 for E6 to
7132 bp for L1 protein. The map of genome for HPV type
16 and 18 were shown (Fig. 1a and 1b) which indicates
the some part of protein coding region is fused with other
part of genes. No significant similarity was observed.
Table 1: Physicochemical properties of different
putative proteins of HPV type 16.
Protein
designation
Accession
number
Molecular
weight (kDa)
pI
E6
ACG75887.1
19.17
8.87
E7
ACG75888.1
11.02
4.04
E1
ACG75889.1
74.94
5.69
E2
ACG75890.1
41.81
7.30
E4
ACG75891.1
10.59
9.02
L2
ACG75892.1
50.71
6.14
L1
ACG75893.1
59.43
8.23
In the present study, seven proteins of HPV type16 and eight
proteins of HPV type 18 were used for physicochemical
analysis such as molecular weight, isoelectric point (pI
value) and antigenic nature. E1 protein showed the highest
molecular weight 74.94 kDa while the lowest molecular
weight was 10.59 kDa of E4 protein. Isoelectric point
of these proteins was ranged between 4.04 to 9.02. The
physicochemical properties of all 7 proteins of HPV type
16 were given (Table 1).
Table 2: Physicochemical properties of different
putative proteins of HPV type 18.
Protein
designation
Accession
number
Molecular
weight (kDa)
pI
E6
NP_040310
18.87
8.62
E7
NP_040311
11.99
4.62
E1
NP_040312
73.74
5.21
E2
NP_040313
41.38
7.39
E4
NP_040314
98.58
10.31
E5
NP_040315
08.30
7.09
L2
NP_040316
49.60
6.03
L1
NP_040317
63.63
8.15
The E4 protein of HPV type 18 having the highest
molecular weight 98.58 kDa and the lowest molecular
weight was 8.30 kDa of E5 protein. Isoelectric point of
these proteins was ranged between 4.62 to 10.31. The
physicochemical properties of all 8 proteins of HPV-18
were given (Table 2).
3.2 Identification and analysis of T-cells epitopes
In the present study, we have used all these protein which
is encoded by genome of HPV for identification and
mapping of T-cell epitopes. The identification of epitopes
in E6, E7, E1, E2, E4, L2, and L1 proteins of HPV 16
were investigated by PROPRED and PROPRED1 tools.
Total 48 epitopes were predicted for class I MHC and 41
epitopes for class II MHC molecules in these proteins. The
predicted epitopes having the MHC alleles for putative
proteins from HPV-16 were performed (Table 3). The other
most important type 18 of HPV was used for prediction of
epitopes in E6, E7, E1, E2, E4, E5, L2, and L1 proteins.
Total 60 epitopes were predicted for class I MHC and 45
epitopes for class II MHC molecules in these proteins. The
predicted epitopes having the MHC molecules for proteins
from HPV-18 were investigated (Table 4). Here, we have
preferred these tools due to it cover the maximum human
leukocyte antigen (HLA) alleles as compare to other
existing tools.
4. DISCUSSION
We have used the complete genome for identification of
T-cell epitopes of all proteins in HPV type 16 and 18. Here,
we have shown the minimal/optimal amino acid sequences
and the HLA restricting molecules of these dominant CD4
and CD8 T-cell epitopes in both HPVs. Major dominant
CD4 T-cell epitopes in HPV-16 were recognized in E7
86-94(LGIVCPICS; restricted by the HLA-DRB1_1104
molecule), E6 105-113 (LLIRCINCQ; restricted by
HLA-DRB1_0813), E1 466-474 (LRYQGVEFM;
restricted by HLA-DRB1_0301 molecule), E2 210218 (IRQHLANHS; restricted by HLA-DRB1_1327
molecule), E4 1-9 (YVLHLCLAA; restricted by HLADRB1_1502 molecule), L2 451-459 (YYMLRKRRK;
restricted by HLA-DRB1_0101 molecule) and in L1
4-12 (FIYILVITC; restricted by HLA-DRB1_1128
molecule) were identified with highest affinity. In HPV18 dominant CD4 T-cell epitopes were recognized in E7
82-90 (LRAFQQLFL; restricted by the HLA-DRB1_1501
molecule), E6 100-108 (LLIRCLRCQ; restricted by HLADRB1_0806), E1 418-426 (YRRAQKRQM; restricted by
HLA-DRB1_1120 molecule), E2 301-309 (LRYRLRKHS;
restricted by HLA-DRB1_0804 molecule), E4 58-66
(IVDLSTHFS; restricted by HLA-DRB1_0410 molecule),
E5 36-44 (FVYIVVITS; restricted by HLA-DRB1_1305
molecule), L2 371-389 (FKYSPTISS; restricted by HLADRB1_0421 molecule) and in L1 49-57 (LRNVNVFPI;
restricted by HLA-DRB1_0703 molecule) were also
identified with highest affinity
The homologous peptides IHSMNSTIL and IHSMNSSIL
derived from L1 HPV type 16 and 18 proteins respectively,
and with high specificity for particular allele, according
with an algorithm prediction program that induced T-cell
stimulation in patients with advanced cervical cancer
positive for HPV-16 or 18 infections. T-cell derived
from a patient with HPV type 18 infection which is
stimulated with peptide IHSMNSTIL have capable to kill
a cervical cancer cell line.[12] In another recent report, the
identification of T-cell epitopes from secretory and cell
surface proteins of M. tuberculosis H37Rv strain. Total 69
promiscuous nanomer T-cell epitopes have been identified
for MHC Class II and 47 promiscuous epitope has been
identified for MHC class I molecules.[13]
The prediction of T-cell epitopes in highly virulence
surface proteins such as hemagglutinin and neuraminidase
from Influenza A virus H5N1 has been earlier reported.
[10]
Recently, the T-cell epitopes have been identified
81
in thermostable hemolysin protein of Aeromonas
hydrophila that can use in immunodiagnostic reagent.[14]
In our study, we have identified the major dominant CD8
T-cell epitopes of HPV-16 in E7 20-28 (TDLYCYEQL;
restricted by the HLA-A2 molecule), E6 95-103
(LEQQYNKPL; restricted by HLA-B*2705), E1 507-515
(FGMSLMKFL; restricted by HLA-B*5102molecule),
E2 207-215 (SPEIIRQHL; restricted by HLA-CW*0401
molecule), E4 11-19 (TKYPLLKLL; restricted by
HLA-DRB1_1502 molecule), L2 78-86 (RPPTATDTL;
restricted by HLA-B*2705 molecule) and in L1 488-496
(FPLGRKFLL; restricted by HLA-MHC-kd molecule).
In HPV-18 major dominant CD8 T-cell epitopes were
identified in E7 23-31 (VDLLCHEQL; restricted by the
HLA-MHC-kd molecule), E6 110-118 (KPLNPAEKL;
restricted by HLA-B*2705), E1 456-464 (QQIEFITFL;
restricted by HLA- MHC-kd molecule), E2 75-83
(KAIELQMAL; restricted by HLA-B*2705 molecule),
E4 38-46 (RPTARRRLL; restricted by HLA- B*2705
molecule), E5 56-64 (CFLLPMLL; restricted by
HLA- MHC-kd molecule), L2 327-335 (APSPEYIEL;
restricted by HLA-B*2705 molecule) and in L1 66-74
(RPSDNTVYL; restricted by HLA-A20 molecule).
The evaluation of synthetic peptides as vaccine candidate
for flavivirus has been investigated. The prediction of
epitopes using computational tools and synthetic peptides
from E glycoprotein of Murray Valley encephalitis (MVE)
and DEN 2 viruses have been earlier reported and their
immunogenicity has been evaluated in mice.[15] The T-cell
epitopes of E6 protein have been identified from HPV
type 16 infected woman.[16] Recently, T-cell epitopes of
hepatitis B virus of seven proteins such as polymerase,
large-S- protein, middle –S- protein, S- protein, X- protein,
precore/core protein, core and E- antigen proteins have
been earlier reported.[17]
Table 3: The predicted epitopes in the different putative proteins of HPV type 16 with reference to MHC molecules.
Protein
E6
E7
T -cell epitopes
Amino acid
position
No. of MHC Class II
binding alleles
T -cell epitopes
Amino acid
position
No. of MHC Class
I binding alleles
VYRDGNPYA
59-67
4
LEQQYNKPL
95-103
19
SRTRRETQL
150-158
12
TDLYCYEQL
22-28
8
LIRREVYDF
43-61
11
LLIRCINCQ
105-113
20
IRGRWTGRC
134-142
7
LKFYSKISE
73-81
7
MHQKRTAMF
1-9
3
YRHYCYSVY
82-90
3
LGIVCPICS
86-94
24
YMLDLQPED
10-80
3
VTFCCQCDS
54-62
4
LRLCVQHTS
64-72
3
IRTLEDLIM
75-83
4
MHGDTPTLH
1-9
5
LRYQGVEFM
466-474
15
YIDDNLRNA
552-560
4
YRCDRVDDG
448-456
4
LADAKIGML
534-542
5
AMLAKFKEL
227-235
7
VOVLKRKYL
83-91
4
E1
IVKDCATMC
82
421-429
7
FLTALKRFL
477-485
5
CMMIEPPKL
325-333
4
FGMSLMKFL
507-515
10
CQTPLTNIL
208-216
4
AAFGLTPSI
260-268
5
LHRDSVDSA
256-264
8
L1
207-215
9
VILCPTSVF
191-199
5
ATHTKAVAL
221-229
5
210-218
22
QDVSLEVYL
95-103
6
VKIPKTTTV
349-357
6
QYSNEKWTL
86-94
3
DSVDSAPIL
260-268
5
LAVSKNKAL
62-70
6
VHAGGQVIL
186-194
5
SNTTPIVHL
283-291
4
KHKSAIVTL
327-335
3
RQHLANHSA
212-220
4
TKYPLLKLL
11-19
10
GLTVIVTLH
86-94
5
VCQDKILTH
L2
SPEIIRQHL
IRQHLANHS
E2
E4
9-17
5
YVLHLCLAA
1-9
30
LKLLGSTWP
15-23
3
WTVLQSSLH
69-77
3
LTVDPVGPS
92-100
8
IPKVEGKTI
33-41
11
IRYSRIGNK
300-308
6
SMGVFFGGL
50-58
8
IVALHRPAL
285-293
7
RPPTATDTL
78-86
15
FFSDVSLAA
464-472
5
PTFTDPSVL
161-169
3
FVTTPTKLI
241-249
6
NITDQAPSL
419-427
7
YYMLRKRRK
451-459
23
NIAPDPDFL
276-284
3
FTLSSSTIS
180-188
3
SRIGNKQTL
304-312
6
VEGKTLADQ
35-43
3
IDPAEEIEL
333-341
6
YGSMGVFFG
47-55
3
VPSVPSTSL
382-390
11
LGLYSRTTQ
224-232
4
VHYYYDFST
323-331
3
YRFVTSQAI
443-451
10
VEVGRGQPL
131-139
8
ISMDYKQTQ
172-180
8
FPLGRKFLL
488-496
17
FIYILVITC
4-12
15
LPSEATVYL
31-39
13
MTYIHSMNS
413-421
10
QYRVFRIHL
95-103
5
LFFYLRREQ
271-279
14
FGHPLLNKL
144-152
6
FVRHLFNRA
281-289
5
YHAGTHRLL
61-69
5
LELINTVIQ
213-221
7
YHIFFQMSL
20-28
8
YIKGSGSTA
302-310
4
LVPKVSGLQ
86-94
5
VNLKEKFSA
474-482
15
LKAKPKFTL
499-507
4
LQFIFQLCK
397-404
5
YRVFRIHLP
95-103
5
83
Table 4: The predicted epitopes in the different putative proteins of HPV type 18 with references to MHC molecules.
Protein
designation
E6
E7
E1
E2
E4
84
T -cell epitopes
Amino acid
position
No. of MHC Class II
binding alleles
T -cell epitopes
Amino acid
position
No. of MHC
Class I binding
alleles
LNPAEKLRH
111-119
10
LTEVFEFAF
41-49
07
VVYRDSIPH
53-61
13
KLPDLCTEL
13-21
14
LLIRCLRCQ
100-108
16
KPLNPAEKL
110-118
17
VYCKTVLEL
32-40
09
LCTELNTSL
17-21
10
DPTRRPYKL
6-14
12
CKCEARIEL
66-74
06
LRAFQQLFL
83-91
08
VDLLCHEQL
23-31
11
PIELVVESS
71-79
07
LRAFQQLFL
82-90
09
VMGDTPEWI
338-346
06
VQWAFDNEL
368-376
06
LVRNFKSDK
228-236
07
QQIEFITFL
456-464
08
YRRAQKRQM
418-426
20
CMLIQPPKL
311-319
06
VNPQCTLAQ
191-199
07
KSNCQAKYL
401-409
03
IRFRCSKID
432-440
05
FKDTYGLSF
218-226
04
VISFVNSTS
504-512
07
SRLTVAKGL
293-301
05
FGVNPTLAE
247-255
03
NPQCTLAQL
193-201
07
LQRLTIIQH
346-354
06
AELETAQAL
61-69
04
MLIQPPKLR
311-319
07
SPRLQEISL
110-119
07
VLILALLRY
279-288
10
ITFLGALKS
460-468
06
IVQFLRYQQ
448-456
12
EPLTDTKVA
518-526
05
FILYAHIQC
264-272
06
LKRKFAGGS
84-92
03
VQILVGYMT
355-363
04
KAIELQMAL
75-83
17
VAWDSVYYM
135-143
03
RYKTEDWTL
90-98
09
LRYRLRKHS
301-309
29
WTGAGNEKT
322-330
04
YNISKSKAH
65-73
04
IRWENAIFF
40-48
08
YRDISSTWH
312-320
03
SETQRTKFL
339-347
07
WTLQDTCEE
95-103
03
GTVNPLLGA
261-269
07
LHDLDTVDS
45-53
03
VQLHLQATT
68-76
09
SRRSSIVDL
54-62
11
LHLQATTKD
69-77
03
RPTARRRLL
38-46
12
YPLLSLLNS
11-19
08
NSVVVTLRL
80-88
05
E5
L2
L1
FVYIVVITS
36-44
38
YVFCFLLPM
52-60
21
LHIHAILS
63-71
15
VRRVAGPRL
217-225
VRFSRLGQR
CFLLPMLLL
56-64
14
HIHAILSLQ
65-73
09
06
SLGIFLGGL
49-57
08
293-301
05
VSVANPEFL
234-242
16
LTFDPRSDV
262-270
07
APSPEYIEL
327-335
17
FKYSPTISS
371-389
20
KRKRVPYFF
447-455
04
FYHDISPIA
318-326
03
AGTTTPAVL
133-141
08
FVGTPTSGT
180-188
04
IGIHGTHYY
427-435
13
IIQWSSLGI
43-51
06
IRLHRPALT
279-287
12
LQTFASSGT
196-204
03
VPKVEGTTL
32-40
11
YIELQPLVS
331-339
05
YYFIPKKRK
440-448
05
MVSHRAARR
1-9
03
YRFVQSVAI
479-487
10
SGHPFYNKL
179-187
09
LRNVNVFPI
49-57
23
VEIGRGQPL
166-174
09
WNVDLKEKF
508-516
07
RPSDNTVYL
66-74
20
LVYMVHIII
32-40
15
CGHYIILFL
42-50
06
IVTSDSQLF
359-367
04
MGDTVDQSL
328-336
05
VSVDYKQTQ
207-215
06
LPDPNKFGL
138-146
14
WRPSDNTVY
64-72
04
VDTTPSTNL
395-403
06
LRRKPTIGP
535-543
08
LTICASTQS
402-410
03
MSYIHSMNS
449-457
04
VTVVDTTPS
391-399
03
WNRAGTMGD
321-329
03
YHAGSSRLL
96-104
03
YRVFRVQLP
130-138
05
MFFCLRREQ
306-314
06
ILHYHLLPL
8-16
03
5. CONCLUSION
Disease diagnosis is one of the major challenges for HPV
by conventional techniques that can not be able to detect
the viruses at early stages. Immunoassays are good choice
for earlier diagnostic but it requires purified antigens. Thus;
these finding provide a better choice for synthesis of epitopes
that can help for diagnosis without in vitro grow and purify
HPV to minimize the time, labor and cost of diagnosis. The
further study will be needed to test our identified T-cell
epitopes for immunodiagnostic and development of peptide
based vaccines against cervical cancer.
85
AUTHORS' CONTRIBUTIONS: DKC, IM and VS
designed the research work and performed experiments.
All authors analyzed the data, wrote the paper and
approved the final manuscript.
11. Somvanshi P, Singh V, Seth PK. Prediction of epitopes in
hemagglutinin and neuraminidase proteins of Influenza
A virus H5N1 strain: A clue for diagnostic and vaccine
development. OMICS: Journal of Integrative Biology, 12:
61-69, 2008.
CONFLICT OF INTERESTS: There is no conflict of
interest.
12. Monroy-García A, Weiss-Steider B, Hernández-Montes J,
Ortiz-Navarrete VF et al. Identification of two homologous
antigenic peptides derived from L1 HPV-16 and 18 proteins
specific for the HLA-B*3901allele. Archives of Virology,
147: 1933-42, 2002.
ACKNOWLEDGMENTS
The authors are thankful to A.K. Singh, Pritee Singh and
Reena for providing the suggestions, fruitful discussion
and encouragement during experiment and preparation of
the manuscript.
REFERENCES
1. Luthra UK, Prabhakar AK, Seth P, Aggarwal SS, Murthy NS,
Bhatnagar P, Sharma BK. Natural history of precancerous
and early cancerous lesions of the uterine cervix. Acta
Cytologica, 31: 226-6, 1987.
2. Walboomers JM, Jacobs MV, Manos MM, Bosch FX et
al. Human papillomavirus is a necessary cause of invasive
cervical cancer worldwide. Journal of Pathology, 189: 129, 1999.
3. Clifford GM, Rana RK, Franceschi S, Smith JS, Gough G,
Pimenta JM. Human papillomavirus genotype distribution
in low-grade cervical lesions: comparison by geographic
region and with cervical cancer. Cancer Epidemiology,
Biomarkers & Prevention, 14: 1157-4, 2005.
4. De Vuyst H, Clifford GM, Nascimento MC, Madeleine MM,
Franceschi S. Prevalence and type distribution of human
papillomavirus in carcinoma and intraepithelial neoplasia of
the vulva, vagina and anus: A meta-analysis. International
Journal of Cancer, 124: 1626–1636, 2009.
5. Petrovsky N, Silva D, Brusic V. The future for
computational modelling and prediction systems in clinical
immunology. Novartis Foundation symposium, 254: 23-2,
2003.
6. Pizza M, Scarlato V, Masignani V, Giuliani MM et al.
Identification of vaccine candidates against serogroup B
Meningococcus whole genome sequencing. Science, 287:
1816-20, 2000.
7. Rappuoli R. Reverse vaccinology, a genome-based approach
to vaccine development. Vaccine, 19: 2688-91, 2001.
8. de Groot AS, Rappuoli R. Genome-derived vaccines. Expert
Review of Vaccines, 3: 59-6, 2004.
9. Singh H, Raghava GPS. ProPred: prediction of HLA-DR
binding sites. Bioinformatics, 17: 1236-7, 2001.
10. Singh H, Raghava GPS. ProPred1: prediction of
promiscuous MHC class-I binding sites. Bioinformatics,
19: 1009-4, 2003.
86
13. Somvanshi P, Singh V, Seth PK. In silico prediction
of epitopes in virulence proteins of Mycobacterium
tuberculosis H37Rv for diagnostic and subunit vaccine
design. Journal of Proteomics and Bioinformatics, 1: 14353, 2008.
14. Singh V, Mani I, Chaudhary DK, Somvanshi P. Molecular
detection and cloning of thermostable hemolysin gene from
Aeromonas hydrophila. Molecular Biology, 45: 551-60,
2011.
15. Gao XM, Liew XY, Tite JP. A dominant the epitope in
influenza nucleoprotein, analysis of the fine specificity and
functional repertoire of T-cells. Journal of Immunology,
144: 2730-7, 1990.
16. Nakagawa M, Kim KH, Moscicki AB. Patterns of CD8
T-cell epitopes within the human papillomavirus type 16
(HPV 16) E6 protein among young women whose HPV 16
Infection has become undetectable. Clinical and Diagnostic
Laboratory Immunology, 12: 1003-5, 2005.
17. Singh V, Mani I, Chaudhary DK, Somvanshi P. HLA
Class I and II binding promiscuity of the T-cell epitopes in
putative proteins of Hepatitis B virus. Journal of Computer
Science & Systems Biology, 2: 69-3, 2009.
INSIGHTS TO SEQUENCE INFORMATION OF ALPHA AMYLASE
ENZYME FROM DIFFERENT SOURCE ORGANISMS
Dwivedi Vivek Dhar¹, Sharma Tanuj¹, Pandey Amit² and Mishra Sarad Kumar³
¹Department of Bioinformatics, UCST, Dehradun, India
²Forest Pathology Division, F.R.I., Dehradun, India
³Department of Biotechnology, DDU Gorakhpur University, Gorakhpur, India
Abstract
Alpha amylase (AAM) is widely distributed among bacteria, fungi and plants. This enzyme hydrolyses alpha-bonds
of large alpha-linked polysaccharides, such as starch and glycogen, yielding glucose and maltose. In the present study,
thirty full- length amino acid sequences of α-amylase from bacteria, fungi, and plants were collected and subjected
to multiple sequence alignment (MSA), motif identification, domain identification, discovering individual amino acid
composition and phylogenetic tree construction. MSA revealed that three aspartic acid, two glycine, one phenylalanine,
one proline, one tyrosine, one arginine and one glutamic acid residues were identically conserved in all analyzed species.
Two major sequence clusters were obtained after phylogenetic tree construction. One cluster contains ten species of
plants, nine species of bacteria and four species of fungi, whereas the other one contains six species of fungi and one
species bacteria. The amino acid composition result revealed that the average frequency of amino acid glycine is 9.42
percent which is very high in comparison to other amino acids and an average frequency of cysteine is 1.22 which is very
low in all analyzed species. In addition, nine motifs which were unique for their groups were also identified.
Keyword: α-amylase, Phylogenetic analysis, Conserved regions, Motifs, Domains, Amino acid composition.
1. Introduction
Alpha amylase is an enzyme that acts as a catalyst for
the hydrolysis of alpha-linked polysaccharides into
α-anomeric products [1]. AAM is regulated through a
number of inhibitors. These inhibitors are classified into
six categories, based on their tertiary structures. Inhibitors
of α-amylase block the active site of the enzyme. Plants
use these inhibitors as a defense mechanism to inhibit the
use of α-amylase in insects, thus protecting themselves
from herbivory [2]. AAMs contain a number of distinct
protein domains. The catalytic domain has a structure
consisting of an eight-stranded alpha/beta barrel that
contains the active site, interrupted by a ~70-amino acid
calcium-binding domain protruding between beta strand
3 and alpha helix 3, and a carboxyl-terminal Greek key
beta-barrel domain [3]. Several alpha-amylases contain a
beta-sheet domain, usually at the C terminus. This domain
is organized as a five-stranded antiparallel beta-sheet [4,
5]
. Several alpha-amylases contain an all-beta domain,
usually at the C terminus [6]. Considering the above facts,
a study of amino acid sequences of alpha amylases from
different sources of organisms is quite challenging. In the
Dwivedi Vivek Dhar
Department of Bioinformatics, UCST, Dehradun, INDIA
*
present study, we performed the individual in silico studies
of amino acid sequences obtained from bacteria, fungi and
plants, and correlated them on the basis of some common
features.
2. Materials and Methods
The full-length amino acid sequences of alpha amylase
from bacteria, fungi, and plants were searched and
retrieved from Genpept protein database available at
NCBI. The sequences were arranged in bacterial, fungal
and plant profile respectively. The multiple sequence
alignment of the individual profiles was performed using
MUSCLE at the European Bioinformatics Institute.
Motifs were discovered in profiles using the expectation
maximization approach implemented in Multiple EM for
Motif Elicitation server [7]. Further, the discovered motifs
were used to search their protein family using Pfam [8] at
the Sanger Institute. The UPGMA approach implemented
in the Mega program [9] was employed for constructing
phylogenetic relationships among sequences. The
statistical reliability of the phylogenetic tree was tested
by bootstrap analysis [10] with 500 replications. Mega
program is also used for discovering individual amino acid
composition.
87
Dhar D. V. et. al. INSIGHTS TO SEQUENCE INFORMATION OF ALPHA AMYLASE ENZYME FROM DIFFERENT SOURCE ORGANISMS
3. RESULTS AND DISCUSSION
The accession number of retrieved sequences along with
the species name and origin is listed in Table 1. For MSA [11]
four profiles were created. One is from plant and bacterial
origin, second is from plant and fungal origin, third is from
bacterial and fungal origin, and fourth is from all plants,
fungal and bacterial origin. MSA showed the presence of
some conserved regions in all the sequences from different
profiles, while others were restricted only to their groups.
Three aspartic acid, two glycine, one phenylalanine, one
proline, one tyrosine, one arginine, and one glutamic
acid residues were identically conserved in all analyzed
species, three glycine, three aspartic acid, two proline, two
histidine, one tyrosine, one valine, one arginine residues
were also identically found in all the plant and bacterial
sources, three aspartic acid, two glycine, one proline,
one tyrosine, one arginine, one glutamic acid and one
asparagine residues were identically found in all plant and
fungal sources while three glycine, three aspartic acid,
one phenylalanine, one proline, one arginine, and one
glutamic acid residues were identically found in bacterial
and fungal α-amylases.
Table1: Retrieved sequences from Genpept protein database and their accession numbers.
Serial No.
88
Source
Species
Accession no.
1.
Bacteria
Geobacillus stearothermophilus
AAA22227.1
2.
Bacteria
Streptomyces venezuelae
AAB36561.1
3.
Bacteria
Streptomyces limosus
AAA88554.1
4.
Bacteria
Bacillus sp.
AAB18785.1
5.
Bacteria
Thermoactinomyces vulgaris
BAA02473.1
6.
Bacteria
Bacillus licheniformis
CAA01355.1
7.
Bacteria
Streptomyces coelicolor
NP_631084.1
8.
Bacteria
Herpetosiphon aurantiacus
YP_001546825.1
9.
Bacteria
Chloroflexus sp.
ACM55170.1
10.
Bacteria
Cellvibrio gilvus
YP_004599853.1
11.
Fungi
Cryptococcus sp.
BAA12011.1
12.
Fungi
Schwanniomyces occidentalis
CAA43995.1
13.
Fungi
Mycosphaerella graminicola
EGP90243.1
14.
Fungi
Aureobasidium pullulans
AEH03024.1
15.
Fungi
Lipomyces kononenkoae
AAO12212.1
16.
Fungi
Aspergillus flavus
AAF14264.1
17.
Fungi
Melampsora larici-populina
EGG02960.1
18.
Fungi
Schizosaccharomyces japonicus
EEB05101.1
19.
Fungi
Verticillium albo-atrum
EEY19672.1
20.
Fungi
Paracoccidioides brasiliensis
EEH15936.1
21.
Plant
Solanum tuberosum
AAA91884.1
22.
Plant
Hordeum vulgare
AAA98615.1
23.
Plant
Oryza sativa
CAA39776.1
24.
Plant
Phaseolus vulgaris
BAA33879.1
25.
Plant
Hyacinthus orientalis
BAE47517.2
26.
Plant
Pyrococcus sp.
BAA21130.1
27.
Plant
Avena fatua
CAA09323.1
28.
Plant
AEE84990.1
29.
Plant
Spirochaeta thermophila
YP_006045635.1
30.
Plant
Malus domestica
AAF63239.1
For phylogenetic analysis [12] four major profiles were
created. Profile one is of bacterial origin, second is of
fungal origin, third is of plants origin, and fourth is joint
profile of bacterial, fungal and plants origin.
Phylogenetic analysis of bacterial profile showed two
major clusters (Fig. 1). Cluster I consist of six species
which was further divided into two subclusters. Subcluster
I contains four species (Streptomyces venezuelae,
Streptomyces coelicolor, Streptomyces limosus and
Cellvibrio gilvus). Subcluster II contains two species
(Herpetosiphon aurantiacus and Chloroflexus sp.). Cluster
II consist of three species namely Bacillus licheniformis,
Geobacillus stearothermophilus, and Bacillus sp.
Thermoactinomyces vulgariscerevisiae was distantly
related and not included in any cluster.
Fig. 3: Phylogenetic analysis of plant profile using UPGMA method
Phylogenetic analysis of plant profile show two major
clusters (Fig. 3). Cluster I consists of six species which is
further divided into two subclusters. Subcluster I contains
four species (Hordeum vulgare, Avena fatua, Oryza sativa
and Hyacinthus orientalis). Subcluster II contains two
species (Phaseolus vulgaris and Arabidopsis thaliana).
Cluster II consist of two species namely Solanum
tuberosum and Malus domestica. Spirochaeta thermophila
and Pyrococcus sp. were distantly related and not included
in any cluster.
Fig. 1: Phylogenetic analysis of bacterial profile using UPGMA method
Phylogenetic analysis of fungal profile showed
two major clusters (Fig. 2). Cluster I consist of six
species namely Aureobasidium pullulans, Aspergillus
flavus, Schwanniomyces occidentalis, Cryptococcus
sp., Schizosaccharomyces japonicus and Lipomyces
kononenkoae. Cluster II consist of four species namely
Melampsora larici-populina, Mycosphaerella graminicola,
Verticillium albo-atrum and Paracoccidioides brasiliensis.
Fig. 4: Phylogenetic analysis of joint profile of bacterial, fungal, and
plant sequences profile using UPGMA method
Fig. 2: Phylogenetic analysis of fungal profile using UPGMA method
When joint profile of bacteria, fungi and plant sequences
were taken for phylogenetic analysis two major sequence
clusters were constructed by phylogenetic analysis. One
cluster contains ten species of plants, nine species of
bacteria and four species of fungi, whereas the other one
89
Dhar D. V. et. al. INSIGHTS TO SEQUENCE INFORMATION OF ALPHA AMYLASE ENZYME FROM DIFFERENT SOURCE ORGANISMS
contains six species of fungi and one species of bacteria.
This suggests that bacteria and plants are more closely
related to each other in comparison to fungi in terms of
AAMs. Nine motifs are identified with their Pfam analysis
which is unique for their groups given in Table 2. The
amino acid composition result revealed that the average
frequency of amino acid glycine is 9.42 percent which is
very high in comparison to other amino acids and an
average frequency of cysteine is 1.22 which is very low in
all analyzed species (Fig.5).
Fig. 5 Individual Amino acid frequencies of α-amylase (given in percent) in different source organisms
Table 2: Motifs searched with MEME along with their Pfam analysis
Source
Motif
width
Motif
present in
number of
sequences
1.
Bacteria
41
7
YQPVSYAIRSKLGTRAEFANMVDACHAAGV
QVYADAVINHM
Alpha-amylase family
(catalytic domain)
2.
Bacteria
21
6
GFRIDAAKHIAAADFAAILSR
Pfam entry not found
3.
Bacteria
50
6
NHDTEGGGALLSYKDGWFYPLANVFML
AWPYGYPCVFSGYEFSNPDAGPP
DUF2798 family (Protein of
unknown function)
4.
Fungi
35
6
RKYCGGTWKGIIDKLDYIQGMGFTA
IWISPVVKNI
(catalytic domain)
5.
Fungi
32
10
NTKFGTADDLVSLSSALHERGMYLMVDAVLNH
(catalytic domain)
6.
Fungi
50
6
RFASQTSDTALAKNAAAFIMLxDGIPIIYY
GQEQHLSGGSDPANREALWL
(catalytic domain)
7.
Plant
41
9
HDTGSTQAMWPFPSDKVMQGYAYILTHP
GTPCIFYDHFFDW
(catalytic domain)
8.
Plant
50
9
NPDTGADFAAAPDIDHLNPRVQKELSEWLN
WLKTDVGFDGWRFDFAKGYS
( catalytic domain)
9.
Plant
36
10
ASKYGSKAELKSLIAAFHQKGIKAIADIV
INHRTAE
(catalytic domain)
Serial
no.
90
Motif
Pfam
4. CONCLUSION
REFERENCES
In- silico analysis of the sequences showed sequence
based similarities depending on their source organism.
MSA revealed three aspartic acid, two glycine,
one phenylalanine, one proline, one tyrosine, one
arginine and one glutamic acid residues are identically
conserved in all analyzed species, three glycine, three
aspartic acid, two proline, two histidine, one tyrosine,
one valine, one arginine residues are also identically found
in all the plant and bacterial sources, three aspartic acid,
two glycine, one proline, one tyrosine, one arginine, one
glutamic acid and one asparagine residues are identically
found in all plant and fungal sources while three glycine,
three aspartic acid, one phenylalanine, one proline, one
arginine and one glutamic acid residues are identically
found in bacterial and fungal α-amylases. This suggests
that these conserved amino acid residues have an important
function in α-amylase sequences and in its evolution from
lower organisms (bacteria) to higher organisms (plants).
Some motifs which are unique for their group are also
identified. In all species of bacteria, fungi and plants, an
average frequency of amino acid glycine is 9.42 percent
that is very high in comparison to other amino acids in
all analyzed species. This suggests that the amino acid
glycine plays a very important role in the composition of
α-amylases. Two major sequence clusters were constructed
by phylogenetic analysis. One cluster contains ten species
of plant, nine species of bacteria and four species of fungi,
whereas the other one contains six species of fungi and
one species bacteria. This classification can significantly
contribute in the understanding of the evolutionary
relations between the species at molecular level. However,
owing to the considerable importance of α-amylase, more
contribution is warranted for the detailed investigation of
the activity and functional analysis of enzymes.
1. Suvd D, Fujimoto Z, Takase K, Matsumura M, Mizuno
H. Crystal structure of Bacillus stearothermophilus alphaamylase: possible factors determining the thermostability. J
Biochem, Mar;129(3):461-8, 2001.
ACKNOWLEDGEMENTS
We are thankful to department of biotechnology
DDU Gorakhpur University, Gorakhpur for providing
laboratory facilities & encouragement and to director
of UCST, Dehradun for their cooperation during the
study. We are grateful to head of Department of Forest
Pathology Division, FRI, Dehradun for his kind support
and necessary suggestions whenever I needed. We are also
thankful to Mr. Suresh Kumar Dwivedi, S.G.S.I.C., Hata,
Kushinagar for his cooperation during this work.
2. Franco OL, Rigden DJ, Melo FR, Grossi-De-Sa MF. Plant
alpha-amylase inhibitors and their interaction with insect
alpha-amylases. Eur J Biochem. Jan;269(2):397-412, 2002.
3. Abe A, Yoshida H, Tonozuka T, Sakano Y, Kamitori S.
Complexes of Thermoactinomyces vulgaris R-47 alphaamylase 1 and pullulan model oligossacharides provide
new insight into the mechanism for recognizing substrates
with alpha-(1,6) glycosidic linkages. FEBS J. Dec;272 (23):
6145–53, 2005.
4. Kadziola A, Gaard SAM, Svensson B, Haser R. Molecular
structure of a barley alpha-amylase-inhibitor complex:
implications for starch binding and catalysis. J. Mol. Biol.
April;278 (1): 205–17, 1998
5. Kadziola A, Abe J, Svensson B, Haser R. Crystal and
molecular structure of barley alpha-amylase. J. Mol. Biol.
May; 239 (1): 104–21, 1994.
6. Machius M, Wiegand G, Huber R. Crystal structure of
calcium-depleted Bacillus licheniformis alpha-amylase at
2.2 A resolution. J. Mol. Biol. March;246 (4): 545–59, 1995.
7. Philip M, Timothy L. Bailey. MEME-ChIP: motif analysis
of large DNA datasets, Bioinformatics 27(12):1696-1697,
2011.
8.
M. Punta, Coggill PC, R.Y. Eberhardt, J. Mistry, J. Tate, et.al.
Nucleic Acids Research Database Issue 40:D290-D301,
2012
9.
Tamura K, Dudley J, Nei M, Kumar S. MEGA4. Molecular
Evolutionary Genetics Analysis (MEGA) software version
4.0. Molecular Biology and Evolution., 24: 1596-1599,
2007.
10. Dixon, P.M. "The bootstrap and the jackknife: Describing
the precision of ecological indices," in Scheiner, S.M. and
Gurevitch, J., eds., Design and Analysis of Ecological
Experiments, New York: Chapman & Hall, pp 290-318.
1993.
11. Wang L, Jiang T. On the complexity of multiple sequence
alignment. J. Comput. Biol., 1, 337–348, 1994.
12.Feng D.F. and Doolittle R.F. Progressive sequence
alignment as a prerequisite to correct phylogenetic trees. J.
Mol. Evol., 25, 351–360, 1987.
91
Aim and Scope
INTERNATIONAL JOURNAL OF ADVANCED BIOTECHNOLOGY & BIOINFORMATICS is an
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Topics of interest cover different aspects of life sciences and biomedical research
including genomics, proteomics, metabolomics, bioinformatics, bioprocess technology,
drug designing and discovery, systems biology and others.
Inimitable attributes of the journal:
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and bioinformatics, with greater emphasis on the usefulness and applicability of
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DISCLAIMER:
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Advanced Biotechnology
and Bioinformatics
Publisher
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Website
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Chief Patron
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Editor-in-Chief
Executive Editor
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Volume 1, Issue 1, November 2012

Transcription

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