Scientific Program

Conference Series Ltd invites all the participants across the globe to attend 3rd International Conference on Proteomics & Bioinformatics Courtyard by Marriott Philadelphia Downtown, USA.

Day 1 :

  • Track 1: Proteomics an Overview

Session Introduction

Gavin Conant

University of Missouri, USA

Title: Protein interactions and the spatial organization of cellular functions

Time : 11:00 - 11:20

Speaker
Biography:

Gavin Conant received his PhD from the Department of Biology at the University of New Mexico and went on to postdoctoral studies at the University of Leipzig and Trinity College, Dublin. He is currently an assistant professor at the University of Missouri.

Abstract:

Protein-protein interactions have been extensively studied at the structural, functional, network and evolutionary levels. Yet one of their properties is so elementary as to be occasionally overlooked: they result in the spatial co-localization of their component proteins. We have recently explored the potential impact of such co-localization on metabolism and cellular organization. It has long been believed that cells are organized to allow metabolic channeling between sequential enzymes. I will discuss how indirect protein interactions between enzymes and non-enzymatic mediator proteins may help achieve such channeling in a modular fashion. I will also illustrate how the potential metabolic role of these interactions is supported by genome-scale flux and gene essentiality data. Extending on this idea of spatial organization, I will discuss a new approach for modeling the protein organization of the cellular interior that is based on a discrete lattice. Using this model, I will present evidence that the set of know binary protein interactions from yeast give rise to emergent structures, such as micro-clusters of related enzymes and robustness to over expression. I suggest that this lattice model, while clearly incomplete, indicates that some degree of the complex organization of the cell may be derived from simple rules of aggregation and interaction. Finally, I will present evolutionary evidence for the ancient character of most human protein-protein interactions, again suggesting that they may play important functional roles.

Michael H. Hecht

Princeton University, USA

Title: Synthetic biology using genomes and proteomes designed De Novo

Time : 11:20 - 11:40

Speaker
Biography:

Michael Hecht grew up in New York City. He received a BA in Chemistry from Cornell University and a Ph.D. in Biology from MIT. He then did post-doctoral research in Biochemistry at Duke Medical School. In 1990, Hecht joined the faculty at Princeton, where is a Professor of Chemistry and holds an affiliated appointment in Molecular Biology. He teaches courses ranging from Introductory Chemistry to graduate seminars on protein folding and design. In addition to teaching and research, Prof. Hecht is the Master of Forbes College, one of the six residential colleges at Princeton University.

Abstract:

The entire collection of genes and proteins in all living systems comprises a minuscule fraction of sequence space. (For example, the collection of all 100-residue proteins would contain 20100 =10130 sequences -- far grater than the number of atoms in the universe.) From this enormous diversity of possible sequences, billions of years of evolution have selected a very small collection of 'molecular parts' that sustain living organisms (only ~4,000 genes in E. coli and ~23,000 in humans.) These considerations might lead one to assume that sequences capable of sustaining life must be unusual or somehow special. Is this true? Or can sequences designed ‘from scratch’ sustain the growth of living cells? To address these questions, we designed and constructed a collection containing millions of artificial proteins (a model 'proteome') encoded by a library of synthetic genes (an artificial 'genome'). Structural studies show that many (perhaps most) of our novel proteins fold into stable 3-dimensional structures. Next, we used genetic selections to demonstrate that several of these novel proteins provide biochemical functions essential for the growth of E. coli. Thus, artificial sequences that never existed in nature possess activities that sustain life. This initial foray into artificial genomics suggests (i) the molecular toolkit for life need not be limited to genes and proteins that already exist in nature; (ii) the construction of artificial genomes composed of non-natural sequences is within reach; and (iii) it may be possible to devise synthetic organisms using de novo designed proteins encoded by novel genomes.

Speaker
Biography:

Jörg D. Hoheisel is Head of the Division of Functional Genome Analysis and Chairman of the Scientific Council at the Deutsches Krebsforschungszentrum (DKFZ; German Cancer Research Center) in Heidelberg, Germany. Apart from publishing more than 300 scientific papers, the division filed 47 patents. Jörg Hoheisel is co-founder of four companies; another three companies were set-up by former group members. Prior to joining DKFZ, Jörg Hoheisel worked for five years at the Imperial Cancer Research Fund in London, UK, the initial two years funded by an EMBO fellowship. Before, he had obtained his PhD at the University of Constance, Germany.

Abstract:

Based on a total internal reflection configuration, a fluorescence-linked, single-molecule sensitive analytical platform was established that permits the detection of individual binding events on standard protein arrays. Apart from the unsurpassed sensitivity, the process permits truly quantitative measurements, since the number of binding events can be counted, thereby improving on relative measurements, which do not yield absolute values. Also, a universally applicable labelling and purification process was established to prepare biologically active proteins with a stoichiometric 1:1 ratio of attached dye-label. The process was initially used for the detection of tuberculosis markers in human plasma and urine samples. No sample preparation had to be done; no signal amplification step was required; and no washing steps were needed during analysis. Biological samples containing about 600 antigen molecules per microliter produced a distinct signal. In extension, we now use the process also for quantitative measurements of both expression and structural variations of proteins by means of complex antibody microarrays of more than a thousand cancer-specific binder molecules. Body liquids as well as tissue and cell extracts are being studied for the identification of personal differences. For the development of new therapeutic approaches, we pursue particularly the identification of structural variations of protein isoforms that are specific for a disease status and do not occur in healthy patients.

Speaker
Biography:

Mathivanan obtained his Ph.D. from Johns Hopkins University, USA and Institute of Bioinformatics, India in proteomics and bioinformatics. He undertook his postdoctoral studies at the Ludwig Institute for Cancer Research, Australia. He received a NHMRC fellowship to study exosomes in cancer. He is currently a group head in La Trobe University, Melbourne, Australia. He has published more than 32 papers in international peerreviewed journals and serving as an editorial board member of repute. His research articles have been cited at an average of 85 citations per article.

Abstract:

Exosomes are 40-100-nm-diameter nanovesicles of endocytic origin that are released from diverse cell types. To better understand the biological role of exosomes and to avoid confounding data arising from proteinaceous contaminants, it is important to work with highly purified material. Here, we describe an immunoaffinity capture method using the colon epithelial cell-specific A33 antibody to purify colorectal cancer cell (LIM1215)-derived exosomes. LC-MS/MS revealed 394 unique exosomal proteins of which 112 proteins (28%) contained signal peptides and a significant enrichment of proteins containing coiled coil, RAS, and MIRO domains. A comparative protein profiling analysis of LIM1215-, murine mast cell-, and human urine-derived exosomes revealed a subset of proteins common to all exosomes such as endosomal sorting complex required for transport (ESCRT) proteins, tetraspanins, signaling, trafficking, and cytoskeletal proteins. A conspicuous finding of this comparative analysis was the presence of host cell-specific (LIM1215 exosome) proteins such as A33, cadherin-17, carcinoembryonic antigen, epithelial cell surface antigen (EpCAM), proliferating cell nuclear antigen, epidermal growth factor receptor, mucin 13, misshapen-like kinase 1, keratin 18, mitogen-activated protein kinase 4, claudins (1, 3, and 7), centrosomal protein 55 kDa, and ephrin-B1 and -B2. Furthermore, we report the presence of the enzyme phospholipid scramblase implicated in transbilayer lipid distribution membrane remodeling. The LIM1215-specific exosomal proteins identified in this study may provide insights into colon cancer biology and potential diagnostic biomarkers.

Break: Lunch 12:20 - 13:00 @ Mezzanine Level Foyer

Cenk Suphioglu

Deakin University, Australia

Title: Effect of zinc and DHA on the epigenetic regulation of human neuronal cells

Time : 13:00 - 13:20

Speaker
Biography:

Suphioglu graduated with PhD from the University of Melbourne in 1994 and has over 18 years of research experience (h-index: 22) and an international recognition on the (i) molecular and environmental analysis of pollen, latex and nut allergens, (ii) molecular analysis of phosphoinositide 3-kinase (PI3-K) isoforms in cardiovascular disease and (iii) importance of omega-3 fatty acids and zinc in human neuronal cell survival and epigenetics. Prof Suphioglu has more than 76 publications and several patents. He is currently the Associate Head of School (Development), Course Leader of Bachelor of Biomedical Science and Head of the NeuroAllergy Research Laboratory (NARL).

Abstract:

Dietary intake of zinc and omega-3 fatty acids (DHA) have health benefits for a number of human diseases. However, the molecular basis of these health benefits remains unclear. In this study, we aimed to identify novel protein candidates that are differentially expressed in human neuronal cell line M17 in response to zinc and DHA that would explain the molecular basis of this interaction. Two-dimensional gel electrophoresis and mass spectrometry were applied to identify major protein expression changes in the protein lysates of human Ml7 neuronal cells that had been grown in the presence and absence of zinc and DHA. Four protein spots, which had significant differential expression, were identified as human histones H3 and H4. Both H3 and H4 were down-regulated by zinc and up-regulated by DHA. These proteomic findings were further supported by Western immunoblot and real-time PCR analyses. In addition, zinc and DHA influenced post-translational modifications (e.g. acetylation, methylation, phosphorylation) of histones H3 and H4. Specifically, we identified that while zinc reduced acetylation, DHA increased acetylation of histones, suggesting importance of zinc and DHA in the epigenetic regulation of neuronal cell gene expression. In summary, we show that dietary zinc and DHA cause a global effect on gene expression, which is mediated by the expression and post-translational modification of histones. Such novel information provides possible clues to the molecular mechanism of action of DHA and zinc in the brain that may contribute to the future treatment, prevention and management of neurodegenerative diseases such as Alzheimer’s disease.

Speaker
Biography:

Youyuan Li completed his Ph.D in Biochemical from East China University of Science and Technology (ECUST). His research interest is application of proteomics and bioinformatics in industrial bio-processes optimization. In 2002, Li joined the faculty at School of Biotechnology, ECUST. He teaches courses ranging from Bioinformatics to Fermentation Engineering.

Abstract:

Peptide Mass Fingerprinting (PMF) plays an irreplaceable role in nowadays tandem proteomics due to its higher sample throughput, higher level of specificity for single peptides and lower level of sensitivity to unsuspected post-translational modifications compared to MS/MS. The PMF method would become more attractive if we could improve the accuracy of protein identification. With this motivation, we have proposed and evaluated a feature-matching based uniform approach using support vector machines (SVMs) to incorporate individual concepts and conclusions for accurate PMF. The SVMs approach focused on the inherent attributes and critical issues of theoretical spectrum (peptides), experimental spectrum (peaks) and spectrum (masses) alignment. The experimental peak intensity was introduced to the algorithm. An optimal SVMs model with 491 out of 35,640 feature-matching patterns outperformed Mascot, MS-Fit, ProFound and Aldente with a high-performance evaluation on a standard PMF set of 225 items. Now, the approach is extended with a web server, FMP, to identify protein from MS1 data. The web implementation contains several features: (i) a local secondary database PUD (Peptide Uniqueness Database) have been constructed to provide each theoretical peptide’s sequence and mass uniqueness to generate SVMs features; (ii) a model named Matched Peak Intensity Redistribution (MPIR) was used to handle mass modification type (fixed and variable) and cleavage type(proper, theoretical missed and random missed) to recalculate peak intensity for each matched theoretical peptide;(iii) 17 select SVMs features are firstly calculated in crude ranking procedure to efficiently reduce the number of candidate proteins from ten thousands to tens; (iv) robust protein prediction by a set of 491 selective and well-evaluated SVMs features; (v) dynamical interface to easily monitor the identification pipeline; and (vi) double prediction tags and probabilities plus detailed statistics to describe protein identification result.

E. Rajasekaran

Karunya University, India

Title: Scale for nature of hydrophobic interactions in proteins

Time : 13:40 - 14:00

Speaker
Biography:

E Rajasekaran has completed his Ph.D from Indian Institute of Technology, Delhi and postdoctoral studies from University of Nebraska. He is working as associate professor in Karunya University, Tamil Nadu. He has published more than 50 papers in bioinformatics journals.

Abstract:

There exists several works for measurement of hydrophobic interactions in proteins. Many hydrophobic parameters are used to scale the hydrophobicity of proteins. They vary from one another. One could not come to a unified principle of hydrophobic measurement. Most of the attempts were at residue level. Carbon is the element contributes towards this hydrophobic interaction. A study on carbon content in proteome reveal that globular protein exist maximum with 31.45% of carbon. This is taken as a scale of measurement. Using this scale, a program (CARd) has been developed and applied for several biological phenomena that arise due to proteins. It reveals the hydrophobic features clearly. Studies on protein’s half life, protein growth, pattern prediction, epitope prediction and disease state of proteins reveal that this new method is proper. This method explains several biological phenomena that take place due to proteins. This gives reason why some regions are disorder in proteins. This also explains the toxicity of proteins. Analyses leading to understand the mutational effect on biological activities are positive and encourage to work further. One can extend this new development for solving genetic disorders. The 3D structure analysis using this scale will give further insight into the existence of different state of protein in different activity. Protein stabilization, active site improvement and reverse transcription in solving disease are given importance as future work.

Chanchal Das Gupta

Jadavpur University, India

Title: Regularity in the amino acid sequences of proteins

Time : 14:00 - 14:20

Speaker
Biography:

Chanchal Das Gupta received Ph.D. (Biophysics) from Calcutta University. Post doctoral research on the role of RecA protein in recombination at Yale University, USA (1978-82). He worked as Professor, Calcutta University and IISER-Kolkata till 2012. Senior Fellow (Indian National Science Academy) at Jadavpur University, Kolkata, India.

Abstract:

The transit of proteins from linear to tertiary states should be exactly tractable because the tertiary states have unambiguous crystalline forms. Since the amino acids interact in the water environment, the solution for the folding problem should give due consideration to the hydrophobic / hydrophilic indices of the amino acids, as mentioned in many studies. Representing amino acids by these indices, we find two different kinds of regularity in amino acid sequence of cytosolic and membrane proteins. If we take the mean hydrophobicity for every few percent of amino acids in proteins and plot them in a cumulative fashion from the N to the C termini, we get two different kind of smooth graphs for cytosolic and membrane proteins.. More than 100 cytosolic proteins and 30 membrane proteins of widely varying number of amino acids and structures could be represented in two such smooth graphs with small standard errors. What we know so far, for cytosolic proteins, is that this regularity comes from a simple working principle which can be based on our observation on the kinetics of folding of a number of proteins starting from the N-termini and extending to the C-termini through a sequential interaction with the same set of nucleotides in the peptidyl transferase center (PTC) of the ribosome.

Speaker
Biography:

Habes M. Alkhraisat is Assistant Professor of Computer Science in the Department of Computer Science at the Al-Balqa Applied University. He received his BA from Al-Balqa Applied University in 2001, master degree of computer science from University of Jordan in 2003, and a Ph.D. from Saint Petersburg Electro Technical University in 2008.

Abstract:

Prediction of protein function is of significance in studying biological processes. The prediction of protein function is one of the most demanding tasks in the study of bioinformatics. One approach for function prediction is to classify a protein into functional family. Classification of protein structures helps to understand relationships between protein structure and function. Machine learning methods greatly help to improve the classification of protein function. This paper presents a method for classifying the proteins based on the secondary structure. Support vector machine (SVM) is a useful method for such classification, which may involve proteins with diverse sequence distribution. We have developed SVM classification of a protein into functional domains from its secondary structure.

Speaker
Biography:

Franca Fraternali is a Professor in Bioinformatics and Computational Biology in King's College London, UK. Her research interest is in Structural Bioinformatics of Proteins and Nucleic acids; Protein Structure Prediction; Molecular Dynamics of folded and misfolded proteins; Systems Biology; Statistical Analysis of Protein Interaction Networks.

Abstract:

  • Track 2: Current Issues on Proteomics and Bioinformatics

Session Introduction

Alexander Shekhtman

State University of New York at Albany, USA

Title: Study of protein interactions by using in-cell NMR spectroscopy

Time : 14:20 - 14:40

Speaker
Biography:

Alexander Shekhtman has completed his Ph.D at the age of 30 from the State University of New York at Albany and postdoctoral studies from the Rockefeller University in New York. He is an Associate Professor in the Department of Chemistry at the State University of New York at Albany and CEO of Palm Biologicals, LLC. He has published more than 50 papers in peer reviewed journals and is a series editor of Methods in Molecular Biology.

Abstract:

In the past few decades, most of the biological processes, such as protein-protein/ligand interactions and atomic resolution structures, have been studied under physiological or “near-physiological” conditions using in vitro NMR spectroscopy. With the advent of in-cell NMR spectroscopy, most of the biological interactions can now be studied within a cellular environment and provide information at atomic level resolution under physiological conditions. The critical components and considerations required to study protein-protein structural interactions inside a living cell by using NMR spectroscopy (STINT-NMR) will be described. STINT-NMR entails sequentially expressing two (or more) proteins within a single bacterial cell in a time-controlled manner and monitoring their interactions by using in-cell NMR spectroscopy. The resulting spectra provide a complete titration of the interaction and define structural details of the interacting surfaces at the level of single amino acid residues. We discuss the advantages and limitations of STINT-NMR, the differences between studying macromolecular interactions in vitro and in vivo (in-cell), the design of STINT-NMR experiments, focusing on selecting appropriate overexpression plasmid vectors, sample requirements and instrumentation, and the analysis of STINT-NMR data, with specific examples drawn from published works. Applications of STINT-NMR, including an in-cell methodology to posttranslationally modify interactor proteins and an in-cell NMR assay for screening small molecule interactor libraries (SMILI-NMR) are presented.

Speaker
Biography:

Gerry Lushington is a chemical informatics research scientist with more than 130 peer-reviewed publications addressing diverse foci including protein structure prediction, structure-based drug design, QSAR, molecular diversity profiling, molecular pathway analysis and proteomics profiling. Lushington has a long track record of cross-disciplinary collaboration and is currently the principal consultant at LiS Consulting. He is the informatics section editor for the journal Combinatorial Chemistry & High Throughput Screening, and is an advisory board member for the Journal of Clinical Bioinformatics, BioMed Central, the Enzyme Inhibition Journal and Current Bioactive Compounds.

Abstract:

In the decade since science first scratched the surface of comprehensive biochemistry via complete characterization of human coding DNA, new paradigms have emerged as more practical platforms for future medical discovery. Prominent among these are chemical genomics and chemical proteomics which collectively embody small molecule / biochemical target interaction knowledge arising from general associative and receptor-specific binding characterization. This complete interaction space might theoretically provide humanity with all requisite knowledge from which to optimize personal therapeutics with minimized side effects, but this matrix of millions of distinct target isoforms crossed by millions of known, potentially bioactive organic molecules is unattainable in vitro. Fortunately, representative subsets of the encompassing data (such as are accruing in PubChem) should enable well-crafted informatics techniques to bridge the expanse. Unlike machine learning methods that pursue bioactivity classification across supersets of general ligand and target features, we have found it productive to assess relationships via clustering techniques (wherein activity is treated as a feature rather than an endpoint) that elucidate analogies among subsets of active ligand-target pairs while functionally distinguishing mechanistically unrelated instances. We have developed a protocol to pursue this based on biclustering across an activity-modulated feature space. Our preliminary test cases yield insight with respect to two mechanistically convoluted assays: cytotoxicity within the IEC-6 intestinal epithelial cell line, and human oral bioavailability profiling. The method has natural extensions to mechanistic clustering across target families, with applications to target selectivity optimization and side-effect prediction.

Break: Coffee Break 15:00 - 15:15 @ Salon Ballroom Foyer

Maciej Kurpisz

Poznan Medical University, Poland

Title: Is sperm proteomic approach helpful to delineate human infertility?!

Time : 15:15 - 15:35

Speaker
Biography:

Maciej Kurpisz, male, geneticist and clinical physician graduated from Poznan Medical University (Poland) in 1980. Dr Kurpisz (MD, PhD) has been nominated a full professor (since 1996) and Head of the Department of Reproductive Biology and Stem Cells, Polish Academy of Sciences, Poznan, Poland. He was trained in Department of Immunology, London UK, Oregon Research Primate Center and Jones Institute in Reproductive Medicine, USA. He was also a Visiting Professor in Deutsches RheumaforschungsZentrum, Berlin and Hyogo Medical College, Japan. He has published almost 300 papers including 10 books and/or monographies. His interests cover: immunology, genetics, infertility, anti-aging, stem cell biology.

Abstract:

We have been studied immune reactivity between sperm antigens and antisperm antibodies developed in infertile males, infertile females and prepubertal boys with testicular failure dissecting human biological material of serum, seminal plasma, cervical mucus and peritoneal fluid samples. Pre-selection of antisperm antibodies reactivities was approached mainly using recommended by WHO – IBT (immunobead) test, however other tests of antibody detection (sperm agglutination, flow cytometry, ELISA, Western immunoblotting) were also applied. By using Western immunoblotting we have found extensive cross-reactivity between sperm entities and somatic cells epitopes (lymphocytes, erythrocytes) as well as variety of infectious microorganisms, possibly due to common carbohydrate epitopes. This phenomenon focused our attention on accurate biological delineation of sperm antigens due to immune reactions by using 2-D gels and mass spectrometry characterizing sperm entities among surface sperm antigenic extracts and total cell lysates in order to follow revealed autoimmune reactions. Altogether we have identified 35 different sperm antigenic entities in accessible databases out of which 10 appeared to be sperm specific. Seventeen sperm entities were detected by sera samples from immune infertile males while 18 by antisperm antibody positive seminal plasma. Additionally, 6 amino acid sequences indicated novel (hypothetical) sperm proteins. Peculiar reactions were found while female circulating (serum) antisperm antibodies were applied. In most of cases non-specific reactions were revealed pointing out earlier literature dedicated to low avidity and specificity of humoral reactions raised in females toward sperm antigens. The potential utility of sperm proteomic approach to delineate background of infertility causes or possible application at immunocontraceptive approaches shall be discussed.

Speaker
Biography:

Chandrajit Lahiri has completed his PhD from Bose Institute, Kolkata, India and postdoctoral studies from the Indian Institute of Science, Bangalore, India and later from Technical University of Munich, Germany. He is an Associate Professor in the Department of Bioinformatics at Karunya University based at the southernmost state of India. He has shifted his field of study from Chemistry and Biochemistry through Molecular Microbiology to Evolutionary and Structural Bioinformatics and lately Network Biology. He is serving as a representative member of the International Complex Systems Society from India and editorial board member of some journals of international repute.

Abstract:

Bacteria are endowed with a unique family of protein pair known as the two-component system (TCS) to sense various environmental signals encompassing pH, temperature, light, chemo- attractants and osmolarity. A series of histidyl-aspartyl phosphorelays of these TCS allow bacteria to modulate the expression of the downstream genes which controls a broad variety of phenotypes spanning morphogenesis, central metabolism, cell differentiation, motility through bio film formation and even virulence of pathogenic bacteria. Considering the functional importance of the TCS in the physiological processes and virulence per se of pathogenic bacteria, the nonconventional cross-talk between non-cognate pairs has been shown in vitro and biochemical kinetics and mathematical modelling have also been done. However, such studies were focused to elucidate their cross-interaction in parts and little had been focused on integrating the total TCS of bacteria with an aim to bring out the mechanism of signal integration as a whole. This might help the bacteria to better adapt to or identify an environment. We have attempted to delineate the global picture of all the interacting two component systems in an organism using sets of graph theoretical parameters. These might serve as models to give a bird’s eye view of the gross behaviour of the TCS interactions already established individually in vitro and/or in vivo. Our models correctly predict the order of the dynamic behaviour of the systems. Moreover, the effects of knock-outs on the signalling network have also been predicted from our newly introduced parameter.

Speaker
Biography:

Sandra Rodriguez Zas is a Professor of Bioinformatics in the Departments of Animal Sciences and Statistics at the University of Illinois, Urbana- Champaign. She received her M.Sc. and Ph.D. in Quantitative Genetics from the University of Wisconsin-Madison. She is the director of the Bioinformatics Core of the Proteomics Center for Cell-Cell Signaling at the University of Illinois. Dr. Rodriguez Zas is the chair of the M.Sc. in Bioinformatics program at the University of Illinois and received a fellow appointment from the National Center for Supercomputing. Her research centers on applying advanced statistical and computational tools to further mine proteomic, genomic and transcriptomic experiments and understand the molecular architecture of complex traits in human, biomedical models, and livestock species.

Abstract:

Mass spectrometry (MS) has become a standard technique to identify peptides. In tandem mass spectrometry (MS/MS) experiments, the proteins are extracted from the sample and digested. Subsequent ionization produces first precursor and then fragment ions. This process results in a spectra graph relating the intensity of the fragment ions (that indicates the ion abundance) to the mass/charge (m/z) ratio. Peptide and protein identification depends on the ability of the MS/MS technique to detect fragment ions and this is correlated with the intensity recorded in the mass spectra. A methodical identification and validation of sequence structural factors that may influence the ion fragment abundance was undertaken. A robust characterization of the factors was attained by considering a large data set and models that accommodated the interdependence among the ion fragment observations within protein. A total of 61,543 peptides identified based on 6,352,528 ion fragments were considered. The data set was partitioned into 10 independent data sets with comparable distribution of structural factor levels. A stepwise model selection approach was applied and the factors consistently validated across data sets were identified. The structural factors consistently associated with ion fragment intensity included neutral mass loss, proton mobility, the charge and number of Proline and basic residues in the precursor and fragment ion. The identified trends can be used to adjust the spectra profiles. Our findings demonstrate the multidimensional character of fragment ion abundance in mass spectrometry experiments.

Biography:

Doel Ray is presently working as Project Investigator under Bio-CARe (Biotechnology Career Advancement and Re-orientation) Programme of Department of Biotechnology (DBT), Govt. of India at NIPGR, New Delhi. In 2009, she was selected in DBT’s Research Associateship Program. Exploring the fascinating field of signal transduction has been her humble endeavor during research spanning the last decade, ranging from stress-related signaling in parasitic protist (Ph.D from Saha Institute of Nuclear Physics, Kolkata) to the application of cutting-edge technologies like proteomics to dissect stress-tolerance in plants. She has publications in reputed journals and has presented her work in various international conferences.

Abstract:

Water-deficit or dehydration is the most crucial factor that is detrimental to plant growth, development, and productivity. With progressive global climate change, shortage of water resources and worsening eco-environment, the situation is likely to turn more serious. The nucleus not only hosts the genome but also administers its transcription and the regulated expression of proteins, thereby playing vital role as modulator of cellular phenotype. A nucleus-specific proteome was developed in IR-64, a dehydration-susceptible cultivar of rice and critically compared with that of dehydration-tolerant Rasi. 2-DE coupled with MS/MS led to the identification of around hundred dehydration-responsive proteins (DRPs), presumably involved in signaling and gene regulation, cell defense and rescue, transcriptional regulation and chromatin remodeling, among others. More than three-fourth of the dataset are predicted as nuclear-localized. The cohorts of identified proteins, interacting in a concerted manner have been mapped into a functional association network. The relatively low overlap of the DRPs between the two cultivars suggest that their differential response may be due to the qualitative and quantitative differences of DRPs involved in common regulatory pathways, though there might be alternative pathways involved in dehydration response that make a plant susceptible or tolerant. The findings indicate that well-orchestrated reactive oxygen species management and protein quality control mechanism may render better dehydration adaptation. To assess the stress-responsive mechanisms operative in the nucleus of different plants, a comparative analysis of various proteome datasets was performed. It revealed limited conservation of regulatory proteins but conserved induction of proteins involved in stress response.

  • Track 3: Molecular and Cellular Proteomics
Speaker
Biography:

Abstract:

Xu Li

The University of Texas M. D. Anderson Cancer Center, USA

Title: Interaction network of human FOX protein family

Time : 16:35 - 16:55

Speaker
Biography:

Xu Li obtained his Ph.D degree from University of Southern California School of Pharmacy in 2009. After a brief postdoctoral research on cancer signaling and drug discovery at the City of Hope National Cancer Center, Dr. Li joined the Department of Experimental Radiation Oncology, MD Anderson Cancer Center in 2011. His research focuses on using large scale mass spectrometry-based proteomics to identify novel molecular markers and drug targets for cancer therapeutics. He has published 11 peer reviewed articles in journals including Science Signaling, Genes & Development and Journal of Biological Chemistry.

Abstract:

The study of protein-protein interaction has provided immense insight into protein functions. Widely used in large-scale proteomic studies, one-step purification using endogenous antibodies or one epitope tag still has its limitations, especially when used to detect interacting proteins in the presence of abundant non-specific binding proteins. In an effort to understand the diverse regulation and functions of FOrkhead boX (FOX) family proteins, we have used a modified Tandem Affinity Purification followed by MASS spectrometry (TAP-MASS) method to study 37 human FOX family members, which comprise all of the 19 FOX subfamilies, from both soluble and chromatin fractions. With a total of 102 TAP-MASS assays, we have identified 17,894 FOX interacting proteins. The data analysis has been performed with several different filtration algorithms and incorporated the protein CCI network, a protein interaction network based on 3,290 endogenous purifications, to get a linearized complex distribution. In this way, we have uncovered ~2,000 high confidential FOX-interacting proteins and several high confidential FOX-interacting complexes, which have been further validated by functional annotations and biochemical analysis. With this proteomic data set, we have found that FOX proteins form heterodimers across subfamilies and co-regulate each other’s transcriptional activities. Moreover, we have discovered that a number of FOX family members bind to homeobox proteins or other transcription factors and these interactions correlate with the abilities of these FOX proteins to induce cell proliferation, EMT and tumorigenesis. Together, our findings suggest that FOX family proteins have many previously underappreciated roles in regulating cellular functions.

V. Ivanov

Russian Academy of Sciences, Russia

Title: Generation of peptides by the model plant Physcomitrella patens

Time : 16:55 - 17:15

Speaker
Biography:

V. Ivanov was born on September 18, 1937. Graduated from the Chemistry Department of Moscow State University (1960). In 1988 was elected as a Member of the Russian Academy of Sciences (RAS), in 1989 - as Director of Shemyakin@Ovchinnikov Institute of Bioorganic Chemistry. Author of over 400 publications on synthesis, structure and function of biologically active peptides - antibiotics, toxins, hormones, vaccines. At present the main research effort is directed at peptidomic research, i.e. structural analysis of peptide pools present in living cells, tissues and organisms followedby elucidation of their function. Awardee of the Great Lomonosov medal of RAS “For Outstanding Contributions to Bioorganic Chemistry”.

Abstract:

A systemic study of the peptidome, proteome and transcriptome of Physcomitrella patens moss was carried out. Three major forms of the plant, the mature leafy shoots (gametophores), the early filamentous form (protonemata) and the single cells (protoplasts) were homogenized, extracted by 1 M acetic acid/10% acetonitrile, the respective extracts subjected to fractionation and mass-spectral analysis under conditions minimizing instrument artefacts and post-mortem proteolysis. In protonemata and gametophores over 4000 peptides derived from 800 protein precursors were identified. About 1000 of them as well as 490 precursors are common to the two plant forms. Most of them belong to the photosynthetic system. Preparation of protoplasts from the moss protonemata is accompanied by massive degradation of proteins, resulting in over 20 thousand of peptides appearing as fragments of 1500 protein precursors. Participation of the precursor in generation of peptides correlates with the level of its expression. The remarkable intensity of peptide generation in protoplasts is considered as a molecular expression of the cell stress induced by cell wall removal, followed by distortion of cell shape. Proteolytic mechanisms leading to the observed sets of peptides will be discussed. Physiological significance of peptide pools discovered in this study requires further study. A novel test system was developed for that purpose, based on measurement of spore germination in the presence of tested compound. Several of the identified peptides were synthesized by solid phase technique, subjected to the above test and showed significant activity.

Biography:

Manuela Piazzi received her PhD in 2009 from the University of Bologna. Following the completion of her PhD, she initiated her post-doctoral studies in Mass Spectrometry analysis in the laboratory of Anthony Whetton at the University of Manchester, School of Enabling Science (UK), before returning to the University of Bologna, cellular Signaling laboratory, under the direction of Lucio Cocco. Currently, she is a Researcher Assistant Professor at the University of Bologna, where she is responsible for the Mass Spectrometry-Proteomic Unit of the Cell Biology Laboratory, Rizzoli Orthopedic Institute, Bologna. She has published more than 10 papers in peer-reviewed journals.

Abstract:

In the last years, the study of protein interactomes, meaning the complex map of molecular interactions among proteins, genes, and RNA, has gained increasing popularity. The ability of mass spectrometry to identify thousands of proteins as well as to quantify protein expression and post-translational modifications using labelling technologies has proven the invaluable in deciphering the whole proteome of an organism. In order to study the protein interactome, researcher biologists need comprehensive tools that allow analysis of bias, reproducibility, statistical significance and biologically significant pattern in the data set. Thus, genomic catalogues of proteinprotein interactions are a rich source of information to explore the relationships between proteins. A variety of bioinformatic software has been released to allow biologists to compile novel molecular pathways and networks. Here, two examples of protein interactome analysis are compared; the analysis of protein interacting with the interferon-induced, double-stranded RNA-activated protein kinase (PKR) and those interacting with the 1-phosphatidylinositol 4,5-bisphosphate phosphodiesterase beta-1, isoform b (PI-PLCβ1b), within the nuclear compartment. Advantages and limits of affinity purification mass spectrometry are discussed, along with data analysis redundancy and statistical reproducibility. Moreover, analysis of protein interaction networks, the integration of data and the comparison of results from different bioinformatic programs, are reported.

Doel Ray

National Institute of Plant Genome Research, India

Title: Comparative proteomics of dehydration-responsive changes in the nucleus reveals genotype-specific adaptation

Time : 17:35 - 17:55

Biography:

Doel Ray is presently working as Project Investigator under Bio-CARe (Biotechnology Career Advancement and Re-orientation) Programme of Department of Biotechnology (DBT), Govt. of India at NIPGR, New Delhi. In 2009, she was selected in DBT’s Research Associateship Program. Exploring the fascinating field of signal transduction has been her humble endeavor during research spanning the last decade, ranging from stress-related signaling in parasitic protist (Ph.D from Saha Institute of Nuclear Physics, Kolkata) to the application of cutting-edge technologies like proteomics to dissect stress-tolerance in plants. She has publications in reputed journals and has presented her work in various international conferences.

Abstract:

Water-deficit or dehydration is the most crucial factor that is detrimental to plant growth, development, and productivity. With progressive global climate change, shortage of water resources and worsening eco-environment, the situation is likely to turn more serious. The nucleus not only hosts the genome but also administers its transcription and the regulated expression of proteins, thereby playing vital role as modulator of cellular phenotype. A nucleus-specific proteome was developed in IR-64, a dehydration-susceptible cultivar of rice and critically compared with that of dehydration-tolerant Rasi. 2-DE coupled with MS/MS led to the identification of around hundred dehydration-responsive proteins (DRPs), presumably involved in signaling and gene regulation, cell defense and rescue, transcriptional regulation and chromatin remodeling, among others. More than three-fourth of the dataset are predicted as nuclear-localized. The cohorts of identified proteins, interacting in a concerted manner have been mapped into a functional association network. The relatively low overlap of the DRPs between the two cultivars suggest that their differential response may be due to the qualitative and quantitative differences of DRPs involved in common regulatory pathways, though there might be alternative pathways involved in dehydration response that make a plant susceptible or tolerant. The findings indicate that well-orchestrated reactive oxygen species management and protein quality control mechanism may render better dehydration adaptation. To assess the stress-responsive mechanisms operative in the nucleus of different plants, a comparative analysis of various proteome datasets was performed. It revealed limited conservation of regulatory proteins but conserved induction of proteins involved in stress response.

Rajesh Kumar Jha

CSIR-Central Drug Research Institute, India

Title: Intimacy of integrin β8 with embryo implantation
Speaker
Biography:

Rajesh Kumar Jha has completed his Ph.D. from Devi Ahilya University, Indore, M.P., India and postdoctoral studies from Cleveland Clinic Foundation, Cleveland, Ohio, USA. He is a scientist in CSIR-Central Drug Research Institute, Lucknow, U.P., India. He has authored papers in sperm and embryo implantation biology area. He has received various grants such as Cleveland Clinic Research Program grant, CCF, Ohio USA, Department of Science and Technology, New Delhi, India and Indian Council of Medical Research. Currently, he is working on female reproductive biology using rodent model employing various proteomics tools.

Abstract:

Embryo Implantation is a well known complex process that requires intricate interaction between the adhesion competent blastocyst and a receptive endometrium. The acquisition of receptivity of endometrial luminal epithelial cells involves various structural and molecular changes in the plasma membrane and cytoskeleton. Integrins, the mediator of cell to cell and cell to matrix interactions are associated with the embryo implantation process, where they possibly control blastocyst and uterus interaction. During early pregnancy, integrin β8 has been shown to interact with transforming growth factor-β (TGF-β) at the feto-maternal interface. However, the precise role of integrin β8 in the uterus and its association with the embryo implantation is not yet elucidated. Therefore, we attempted to ascertain the role of integrin β8 during the window of an embryo implantation process by its protein expression inhibition analysis. Further, we explored the role of ovarian steroids on integrin β8 expression using delayed implantation and non-pregnant ovariectomized mice model. We found that integrin β8 is up-regulated during early peri-implantation stage of the window of embryo implantation and predominant to the sites of embryo implantation of peri-implantation stage. Bio-neutralization and mRNA silencing of the uterine integrin β8 at pre-implantation stage inhibited the embryo implantation and subsequent pregnancy, which suggests its crucial role during embryo implantation. Integrin β8 can regulate its downstream signaling molecules STAT-3, integrin β8, TGF-β1, Vav and Rac-1 activity in the uterus during embryo implantation. Integrin β8 can be regulated by the ovarian steroid, 17-β estradiol in progesterone primed receptive uterus. In this study, we have elucidated the indispensable regulatory role of integrin β8 during the window of embryo implantation.

  • Track 4: Applications of Proteomics
Speaker
Biography:

Svetlana Amirova has completed her PhD at the age of 26 years from Keele University UK and postdoctoral studies from University of Leicester and University of Exeter both in UK. She is a visiting assistant professor for Bioinformatics and Systems biology in University of Texas at El Paso. She has published 15 papers in reputed journals and presented her work at multiple international conferences in UK and USA.

Abstract:

In this study, the first complete predictive model of polyamine metabolism in the yeast Saccharomyces cerevisiae is developed, using a Systems Biology approach incorporating enzyme kinetics, statistical analysis, control engineering and experimental molecular biology of translation. The polyamine molecules putrescine, spermidine and spermine are involved in a number of important cellular processes such as transcriptional silencing, translation, protection from reactive oxygen species and coenzyme A synthesis. Components of the polyamine pathway are also potential targets for cancer therapeutics, as unregulated polyamine synthesis can trigger uncontrolled cell proliferation. Conversely, polyamine depletion can cause apoptosis, and during development, defects leading to mental retardation in humans. Controlling polyamine concentrations is thus a significant regulatory challenge for the cell, because there are multiple cellular requirements for polyamines as well as a need to homeostatically maintain their concentration within a certain non-toxic range. In the cell, polyamine concentrations are regulated by multiple mechanisms, including feedback control of Spe1(the enzyme catalysing the first step in the polyamine biosynthesis pathway) by the protein antizyme, which is synthesized via a +1 ribosomal frame shift during translation of the antizyme mRNA. The aim of our systemslevel analysis is to uncover the design principles (relative importance of the different control mechanisms, robustness and fragility of control, effects of frame shifting changes in feedback loops, etc) underlying the dynamic regulation of polyamine biosynthesis in health and disease states. Applications of this study are pharmacology; toxicology, preclinical drug development for cancer and neurodegenerative disorders: anticancer drug development and Snyder-Robinson Syndrome.

Speaker
Biography:

Jonathon Coren obtained his Ph.D. in Genetics from Cornell University in 1991. He did a postdoc at Thomas Jefferson University from 1991-1993. Jon next pursued a postdoc in Nat Sternberg's lab at DuPont Merck Pharmaceutical Company where he modified the P1 bacteriophage cloning system into a P1 Artificial Chromosome (PAC) system. He started as a tenure-track Assistant Professor at Southwestern Oklahoma State University in Weatherford, Oklahoma in 1999. Jon received a $100, 000 NIH R15 AREA grant HG002216-01A1 in September of 2001. He started teaching at Elizabethtown College in 2002 and was tenured and promoted to Associate Professor in 2006.

Abstract:

The Human Genome Project has ushered in the era of big science. The International HapMap Project’s original goal was to catalog the millions of single nucleotide polymorphisms (SNPs) present in the population into many haplotypes in an attempt to establish links between certain variants and specific diseases. All of this research has uncovered over 150 risk loci for more than 60 common diseases and traits. Genome-wide association studies (GWAS) are underway to identify candidate genes for various complex traits such as autism, bipolar disorder, diabetes, obesity and schizophrenia. We constructed an arrayed 115,000-member human genomic library in the PAC shuttle vector pJCPAC-Mam2 that can be propagated in both bacterial and human cells. Microgram quantities of a given PAC clone can be recovered in E. coli and then transfected into any human cell line of interest. Transient transfection of a p53-containing PAC clone into the p53-null Saos-2 human osteosarcoma cells demonstrated that both p53 mRNA and protein were produced. Additionally, expression of the p53 protein triggered apoptosis in a subset of the Saos-2 cells as evidenced by an Annexin V assay. When a p53-GFP PAC clone was transfected into Saos-2 cells, immunofluorescence studies demonstrated that the fusion protein was localized to the nucleus and that a subset of cells exhibited the hallmark blebbing that is associated with apoptosis. This library should serve as a valuable resource to validate potential disease genes identified by GWAS in both human cell lines and in animal models such as rats.

Speaker
Biography:

Kuruc is a serial entrepreneur, starting as a co-founder of Affinity Technology Inc., where he was President from 1990 until 1996 . After it was acquired by LigoTech, Inc., he held an executive business development role until becoming a co-founder of ProFACT Proteomics in 2004. From 1987 to 1990 he held various marketing and sales positions with Amicon Division of W. R. Grace & Co. (now Millipore), and prior to that, product and sales positions with industrial separations equipment suppliers.

Abstract:

ProFACT Proteomics has developed a proteomics separations and enrichment platform that streamlines proteomic workflows while also preserving biological integrity. Using these new tools, proteomic and molecular profiles can be derived from biofluids and naturally-sourced disease tissue or cellular models – a clear distinction to other functional platforms reliant on recombinant sources. New therapeutic compounds can be characterized to help refine lead candidate selection, discover novel biomarkers and provide additional mechanistic insight into suitable disease indications. Functional characterization and derivative molecular profiles can then help correlate proteins thus identified to drug candidates’ tissue-specific expression of enzymes, with the potential to gauge promiscuity and identify biomarkers. Furthermore, to enrich low abundance proteins, LC-MS strategies adopting on-bead digestion to improve peptide recovery and simplify proteomic workflows will be described. We envision that new functional annotation methods will complement conventional sequence annotation while addressing the problems of drug promiscuity and the subtleties of protein attributes when the same or similar underlying sequence can have multiple conformations and functions, and when different sequences sometime perform the same or similar function. Thus, new enrichment products make possible a way to efficiently sift through these biological complexities, localizing subproteomes of prospective protein biomarkers that can be correlated to structural and sequence relationships. Such an integrated approach has the potential for new and useful service to biomarker discovery and personalized medicine.

Speaker
Biography:

Uday Kishore carried out his PhD research from Delhi University, India and post-doctoral training at the Salk Institute, California and the University of Oxford, UK. He has been the recipient of fellowships/awards from the NASA, Wellcome Trust, Humboldt Foundation, Medical Research Council and European Commission. He has authored over 80 peer-reviewed research papers, 10 book chapters, 2 international patents, edited two books, and is currently writing a text book on host-pathogen interaction (Wiley-Blackwell). His research interests include understanding the roles of innate immunity (including complement system) in allergy, host-pathogen interaction, pregnancy, neuroinflammation and neurodegeneration, and autoimmunity.

Abstract:

Pulmonary surfactant protein SP-D is a carbohydrate and charge pattern recognition molecule that is a potent link between innate and adaptive immunity. We have shown previously that a recombinant fragment of human SP-D (rhSP-D) can down regulate immunological characteristics of allergy in murine model. The protective mechanisms include lowering the levels of IgE, suppression of eosinophilia and lung infiltration, reduction in airway hyperreactivity, and polarization of Th2 to Th1 immune response. We have now used in vitro, in vivo and ex vivo systems to dissect the underlying mechanisms through which SP-D offers resistance against allergenic challenge. We have recently also used proteomic and microarray profiling to characterize molecular mechanisms and pathways that are modulated by SP-D. These data will be discussed.

Speaker
Biography:

Bobbie-Jo Webb-Robertson completed her M.E. in Statistics and Operations Research and her PhD in Decision Sciences and Engineering Systems from Rensselaer Polytechnic Institute. She joined Pacific Northwest National Laboratory in 2002 and is currently working as a Senior Research Scientist in the Computational Biology and Bioinformatics group. Her research is primarily focused in the fields of proteomics and statistical data integration of high-throughput data. She is currently an author on over 55 peer-reviewed journal articles and in an executive editor of the Journal of Proteomics and Genomics Research.

Abstract:

High-throughput technologies currently have the capability to capture information at both global and targeted scales for the transcriptome, proteome and metabolome, as well as determining functional aspects of these biomolecules. The promise of data integration is that by utilizing these disparate data streams a more complete or accurate estimate of system behavior can be obtained. In the case of biomarker discovery to better diagnose and predict outcomes of disease, one goal is to identify the best subset of molecules that can separate specific phenotypes of interest. However, in a space of tens of thousands of variables (e.g., genes, proteins), feature selection approaches often yield over-trained models with poor predictive power. Moreover, feature selection algorithms are typically focused on single sources of information and do not evaluate the effect on downstream statistical integration models. Bayesian statistics has been shown to be an effective approach for statistical integration across multiple data streams using standard meta-learning approaches. We present a sampling strategy to evaluate potential variables spaces and using the Bayesian framework obtain probabilistic measures associated with one more potential variable and dataset collections to evaluate the confidence in potential solutions. In addition, using standard Bayesian statistical methods a marginal probability associated with individual features can be obtained to aid both in biomarker selection and in downstream analyses, such as pathway modeling. We utilize the Bayesian sampling feature selection approach on several disease-based proteomics datasets (diabetes and cancer) to demonstrate the flexibility and robust nature of the Bayesian sampling approach.

Speaker
Biography:

Natarajan has received her PhD from the University of Madras, India and post-doctorate from Michigan State University. She is a lead scientist on a risk assessment program at the Department of Agriculture (USDA) and serves as Adjunct Associate Professor at University of Maryland. She authored more than 93 publications, 4 U.S. patents, and presented her research in USA, Brazil, Egypt, France, India and China. She serves as a reviewer of 20 journals, Fulbright senior specialist grants, committee member of Ph.D. panels, and as an editorial board member of several journals. Dr. Natarajan received several honors and awards including Fulbright Senior Specialist Award and “Best Scientist of the year 2008”award from the Maryland Governor.

Abstract:

Soybean provides an economical source of protein for humans and animals. In order to address global demand, genetically modified (GMO) soybeans aiming to improve quality and yield have become prevalent. To ensure the safety of the crop for consumers it is important to determine the natural variation in seed protein constituents as well as any unintended changes that may occur in the GMO as a result of genetic modification. Understanding the natural variation of seed proteins in wild and cultivated soybeans that have been used in conventional soybean breeding programs is critical for determining unintended protein expression in GMO soybeans. In recent years, proteomic technologies have been used as an effective analytical tool for examining modifications of protein profiles. We have standardized and applied these technologies to determine and quantify the spectrum of proteins present in soybean. We used two-dimensional polyacrylamide gel electrophoresis (2D-PAGE), matrixassisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-TOF-MS/MS), and liquid chromatography mass spectrometry (LC-MS/MS) for the separation, quantification, and identification of different classes of soybean seed proteins. We have observed significant variations of different classes of proteins and profiled storage, allergen and anti-nutritional proteins between non-GMO, cultivated and wild soybean varieties. This information is useful for scientists and regulatory agencies to determine whether the unintended expression of proteins found in transgenic soybean is within the range of natural variation.

Speaker
Biography:

Lydia Finney leads research in the roles of metals in cell physiology, particularly utilizing x-ray fluorescence microscopy, as a Physicist at the Advanced Photon Source (APS). Prior to joining APS, Dr. Finney was a postdoctoral fellow in the Biosciences Division at Argonne National Laboratory from 2005-2007. She obtained her PhD with Dr. Thomas O'Halloran at Northwestern University in Inorganic Chemistry. She was awarded a Fannie and John Hertz Fellowship for her graduate studies, and more recently her work been featured in a C&EN News article on metalloproteomics. She has published over 30 peer-reviewed publications.

Abstract:

Metals like copper, zinc and iron are important nutrients to all life. Their special properties which make them so useful to us in things like batteries and catalysts also make them useful to living organisms. Using hard x-ray fluorescence microprobes at the Advanced Photon Source, we have been able to see, often for the first time, where the metals themselves are inside cells and tissues. Yet, many of the images we acquire lead us to new questions. Are these metals required for the activity of proteins? Which proteins are binding which metals inside the cell? With over a third of all proteins thought to bind metals, knowing which metals are bound and how that binding changes in response to the environment could have big implications. For instance, the mismanagement of metals is involved in many diseases, including Lou Gehrig’s disease, Wilson and Menkes disease, and possibly even Alzheimer’s disease. Metals are also an environmental toxin and they are used in drugs, like the platinum in cisplatin that treats prostate cancer. Knowing which metal is in which protein at a given point in time could lead to new insights into how they do their work. We have developed a new tool to investigate this, combining native two-dimensional gel electrophoresis and x-ray fluorescence imaging, to quantitatively measure the amount of sulfur, iron, zinc, and other metals at every point of the 2-D separation of proteins. By coupling this with mass-spectrometry, we have identified a novel protein (PA5217) as a zinc-binding protein in P. aeruginosa. Our finding highlights how this method not only determines changes in metal occupancy, but also identifies the associated protein.

Biography:

Gunther received his PhD from the University of Maryland, Baltimore in 2001. This was followed by two post–doctoral appointments; the first at GlaxoSmithKline and the second in the Fats, Oils and Animal Co-products Research Unit of the United States Department of Agriculture. Dr. Gunther is currently a research molecular biologist in the Molecular Characterization of Foodborne Pathogens Research Unit of the United States Department of Agriculture. His research focuses on utilizing comparative proteomic and genomic techniques to investigate the capabilities of Escherichia coli and Campylobacter species to persist in food and food processing environments.

Abstract:

To understand the nature and pathogenic potential of a bacterial strain it is necessary to be able to identify and measure the proteins expressed in any given situation. In this research the entire protein complements produced by Escherichia coli O157:H7 strain 48394OW and its naturally occurring curli producing variant 48394OR were compared to better understand the pathogenic abilities of these two closely related strains. A non-labeled proteomic comparison was performed utilizing the spectra counting and peptide fractionation abilities of a Q-Tof mass spectrometer to identify and quantitate the proteins produced by the two strains. The process reliably identified and measured the concentration of 418 proteins from strains 48394OW and 48394OR within three separate biological replicates. From these two sets, 59 proteins were identified that were preferentially expressed in strain 43894OW compared to 48394OR and 14 proteins that were conversely preferentially expressed in 48394OR. A subset of the preferentially expressed proteins was assayed to determine if their levels of gene transcription corresponded with the observed protein expression. From the resulting list of confirmed differentially expressed proteins, it was observed that the proteins contributing to acid survival: GadA and GadB, were overexpressed in 48394OW compared to 48394OR. The predicted enhanced acid resistance phenotype of 48394OW was confirmed by experimentation at pH 2.5. Additionally, a knockout mutation in the csgD genes of the 48394OR strain was constructed and suggested that CsgD had a repressive effect on acid survival in 43894OR.

Speaker
Biography:

Jun Zhu is a professor in Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai. He obtained his bachelor degree in Electronic Engineering in Tsinghua University in China, Master degree in Computer Sciences and Ph. D in Biomedical Sciences from State University of New York at Albany. He has working experiences in both biotech companies (Amgen and Merck Co.) and academic institutes. He has pioneered constructing integrative causal network in Bayesian network framework, which resulted multiple publications in high profile journals such as Nature, Nature Genetics, Genome Research.

Abstract:

GWAS have identified thousands of candidate variations for human diseases. However, distinguishing causal variations from a plethora of candidates is a big challenge. Even though meta-analyses of GWAS identified high confident candidates, it is still not clear what are mechanisms of these variations contribute to human diseases. To achieve comprehensive understanding of these candidate variations, we need a complete biological context within which to interpret potential functions of these variations. We developed RIMBANet, a general Bayesian network framework to integrate diverse types of data such as DNA variation and RNA expression data. Cells employ multiple levels of regulation, including transcriptional and translational regulation, that drive core biological processes and enable cells to respond to genetic and environmental changes. Metabolites represent the direct output of protein-mediated cellular processes, endogenous metabolite concentrations can closely reflect cellular physiological states, especially when integrated with other molecular-profiling data. We extended the framework to integrate more data types: endogenous metabolite concentration, miRNA expression variation, DNA mutations and DNA copy number variations, DNA-protein binding, protein-metabolite interaction, protein-protein interaction data, and more, to construct probabilistic causal networks that elucidate the complexity of cell regulation. The goals of our integrative analysis are not only to find causal regulators, but to uncover mechanisms by which these predicted causal regulators affect genes and metabolites whose transcriptional profiles, proteomic profiles or metabolite profiles are linked to phenotype differences. We applied the integrative approach to human GWAS results and other human data to elucidate mechanisms of metabolic diseases and cancers.

Jochen M. Schwenk

KTH - Royal Institute of Technology, Sweden

Title: Affinity proteomic plasma profiles in diseases and ageing
Speaker
Biography:

Jochen M. Schwenk is Associate Professor in Translational Proteomics at the KTH - Royal Institute of Technology in Stockholm, Sweden. He is a Group Leader within the Human Protein Atlas and Biobank Profiling at the Science for Life Laboratory. He studied Biochemistry at the University of Tuebingen, Germany and joined Prof. Mathias Uhlén and the Human Protein Atlas for his postdoctoral work, funded by the Wallenberg Foundation and F.Hoffmann-La Roche. Today his group is working on high-throughput and multiplexed methods for protein profiling body fluids with antibodies from the Human Protein Atlas.

Abstract:

The growing number biobanks opens new possibilities to screen for protein biomarkers in plasma for diagnostics and patient care. To systematically explore protein profiles from body fluids, antibody suspension bead arrays have been developed with antibodies from the Human Protein Atlas (www.proteinatlas.org, [1]) to analyze non-fractioned, biotinylated and heattreated samples. Per day 384-plexed bead arrays [2] generate up to 150,000 immunoassays and this single-binder approach has so revealed interesting candidates from in plasma in the context of prostate cancer [3] and renal impairment [4]. Recently, the assay has been applied to other body fluids but also to larger scaled, hypothesis-free efforts: (i) A pilot study using 4,600 antibodies to profile a total of 600 samples from 20 disease such as cancer, cardiovascular and neurodegenerative diseases. (ii) Samples from 384 blood donors aged 5-85 were analyzed with 7,600 antibodies to identify the profiles’ age and/or gender associations. (iii) A recent focus has been the analysis of serum and plasma from cancer (384 samples, 5 cancer types) and cardiovascular disorders (384 samples, 4 categories) using 10,000 antibodies. To address off-target binding susceptibility of single-binder assays, candidate antibodies are being involved in sandwich assay developments and independent sample cohorts are being accessed to further describe the involvement of a biomarker candidate in a disease context. The overall strategy thus encompasses to statistically identify, replicate and verify antibody-derived profiles for further experimental and biological investigations, including also other body fluids.

Speaker
Biography:

Ajjamada C. Kushalappa is an Associate Professor at the McGill University. He has published 80 papers in refereed scientific journals. Current focus of his research is the application of non-target metabolomics and proteomics technologies to identify candidate genes for resistance against biotic stress. He was an invited speaker at several international and national conferences on metabolomics application to plant stress. He is a recipient of Dr. and Mrs. Bailey award by the Canadian Phytopathological Society for his exceptional and distinguished contribution to plant pathology.

Abstract:

Plants are subjected to several abiotic and biotic stresses. The resistance to pathogen stress can be qualitative or quantitative. The former, because of monogenic inheritance, has been successfully used in plant improvement. However, the latter, because of polygenic inheritance, has not been well exploited. Hundreds of quantitative trait loci (QTLs) for resistance have been identified but these contain several genes, including undesirable traits due to linkage drags. Integrated non-target metabolomics and proteomics, using high resolution mass spectrometry, were applied to identify the mechanisms of resistance in wheat against Fusarium graminearum. Near isogenic lines, with contrasting alleles at QTL-Fhb1, were pathogen or mock-inoculated, metabolites and proteins were analyzed using high resolution mass spectrometry. Mass spectral outputs were processed using MZmine for metabolites and MASCOT for proteins. The abundances were used to identify resistance-related metabolites and proteins, and mapped to metabolic pathways. Metabolites of the shunt phenylpropanoid pathway such as hydroxycinnamic acid amides, phenolic glucosides and flavonoids were significantly induced in the resistant NIL. Concurrently, the enzymes of phenylpropanoid biosynthesis such as cinnamyl alcohol dehydrogenase, caffeoyl-CoA O-methyltransferase, caffeic acid O-methyltransferase, flavonoid O-methyltransferase, agmatine coumaroyltransferase and peroxidase were also up-regulated. A protein coding gene (GENBANK No: CBH32656.1) near the Fhb1 locus was putatively annotated as hydroxycinnamoyl transferase that catalyzes the conjugation of hydroxycinnamic acid amides, whose high expression in resistant NIL was confirmed by quantitative RT-PCR using the sequence of wheat agmatine coumaroyltransferase. This demonstrates the potential of metabolo-proteomics approach to identify biotic stress resistance candidate genes. This gene can be used in plant improvement following further validation.

Speaker
Biography:

Malini Laloraya is a Ph.D. in Life Sciences (Devi Ahilya University, Indore). She was a Rockefeller Visiting Fellow at Population Council's Center for Biomedical Research, Rockefeller University, USA and a visiting faculty at University of Virginia and University of Florida, USA. She was a Raine Visiting Professorship at The University of Western Australia (April 2006 & 2008) sponsored by Raine Medical Research Foundation. She is currently a Scientist F (Professor equiv.) at Rajiv Gandhi Centre for Biotechnology, Trivandrum.

Abstract:

Proteins seldom work by themselves; they almost always interact with other biomolecules to accomplish their functions. Webs of such biomolecular interactions constitute the basis for life, and those occurring between proteins play exceptionally important roles. We have recently analyzed the web of protein interaction during hormone action and the consequences of such interactions. I will discuss interactions of hormone receptors with interacting protein and the structural elements involved in this association. I will also illustrate how these interactions cause exacerbation of hormone driven signals. A deep understanding of receptorprotein association as well as analyzing interacting partner expression could be the pivotal point in devising better therapies for managing events associated with them. Taking this approach further, I will discuss how interactome analysis can identify novel partners especially in relation to spatial compartmentation in the cell. I will exemplify how classical cytosolic proteins are identified to be a component of nuclear interactome. I will explain how a combined bioinformatics & proteomics approach can be used to predict their nuclear function. In addition, an integrative approach with bioinformatics and site-directed mutagenesis confirms the basis of these interactions. Finally, I will illustrate using in-vivo experiments how these interactions can be proven and their functional significance.

Speaker
Biography:

Anthony Addlagatta obtained his bachelor’s degree with specialization in industrial chemistry from Osmania University, Hyderabad, Masters and the Ph.D. degrees in Chemistry from the School of Chemistry, University of Hyderabad. He worked as a Senior Scientist at the Pacific Northwest National Laboratory, USA before joining Indian Institute of Chemical Technology (IICT) in the Centre for Chemical Biology. His current research focus is on the human health and biotechnology. His technical expertise include bioinformatics, protein engineering, molecular, structural, cellular and computational biology, structure based drug discovery, medicinal chemistry and biotechnology.

Abstract:

In nature almost all proteins from bacteria to humans, are synthesized with methionine as the starting amino acid coded by AUG. However, about 60-70 % of all the matured proteins lack this initiator methionine. Between the protein synthesis and the maturation processes, this amino acid is removed by the enzyme, methionine aminopeptidases (MetAP). Any alteration in this process is detrimental to the living cell. Based on this observation, MetAPs are regarded as good drug targets. However, the challenge in design of inhibitors specific against species based enzyme is high structural and sequence similarity in the active site. Surprisingly, only one amino acid (a cysteine) is conserved in the S1 pocket where the substrate methionine side chain binds. Using the structural biology, bioinformatics, molecular biology, biochemistry and proteomics approach, we have determined the role of this single amino acid in the substrate recognition for this class of enzymes. Further, we have developed species specific inhibitors. Results from this multi-tool approach to understand the protein function and design of specific inhibitors will be elaborated in the meeting.

Speaker
Biography:

Ibiba F. Oruambo obtained his Ph.D from New York University and completed his doctoral research thesis in the laboratory of organic chemistry and carcinogenesis in Nelson’s Institute of Environmental Medicine of New York University. He is currently a senior lecturer in Biochemistry and Environmental Toxicology in the Department of Chemistry, Rivers State University of Science and Technology, Nigeria. His research focuses on the biochemistry of chemical carcinogenesis and environmental toxicology as these relate to the effect on eukaryotic DNA and proteins. He is CEO of ENVIR-health Consultants, a consulting firm on environmental health issues. He has published over 24 papers in reputable international and Nigerian journals.

Abstract:

To determine whether or not Bonny Light Crude Oil (BLCO), when administered to albino rats for six consecutive days at 48 hours interval would result in a dose-related alteration in chromatin structure as obtained in its absorbance ratio, and subsequent impairment of its function such as DNA synthesis. Methodology and results: Twelve albino rats (Rattus norvegicus) were divided into four groups with group one serving as control, and group two to group four were administered with 2.5, 5.0 and 10.0 ml/kg bw of Bonny Light Crude Oil (BLCO) by intra peritoneal injection for six consecutive days. All the rats were sacrificed on the eighth day and their liver excised. The livers were all homogenized, and through differential and fractional centrifugation, the nuclei containing the chromatin were obtained. The chromatin DNA and protein absorbance ratio was determined at 260nm and 280nm by UV spectrophotometry. The results show that the chromatin ratio for control (untreated) rats was 0.95 while there were moderate increases in the ratio for treated rats. Significantly the 260nm/280nm absorbance ratio increases occurred at 260nm and not 280nm, showing that chromatin DNA was more altered than chromatin protein. Conclusion and application of findings: Bonny light crude oil probably induced DNA polymerization by unscheduled DNA synthesis in chromatin, which suggests genotoxicity especially carcinogenicity. This demonstrates probable adverse impact to human health on exposure to crude oil spillage and pollution in air, land and water bodies.