Vural Özdemir Ph.D.
Sanjeeva Srivastava Ph.D.
Rohit Manchanda, Ph.D.
Professor, Biomedical Engineering Group, IIT-Bombay, India
Modelling the syncytial organization and neural control of smooth muscle: insights into autonomic physiology and pharmacology
We have been studying computationally the syncytial organization and neural control of smooth muscle in order to help explain certain puzzling findings thrown up by experimental work. This relates in particular to electrical signals generated in smooth muscles, such as synaptic potentials and spikes, and how these are explicable only if three-dimensional syncytial biophysics are taken fully into account. In this talk, I shall provide an illustration of outcomes and insights gleaned from such an approach. I shall first describe our work on the mammalian vas deferens, in which an analysis of the effects of syncytial coupling led us to conclude that the experimental effects of a presumptive gap junction uncoupler, heptanol, on synaptic potentials were incompatible with gap junctional block and could best be explained by a heptanol-induced inhibition of neurotransmitter release, thus compelling a reinterpretation of the mechanism of action of this agent. I shall outline the various lines of evidence, based on indices of syncytial function, that we adduced in order to reach this conclusion. We have now moved on to our current focus on urinary bladder biophysics, where the questions we aim to address are to do with mechanisms of spike generation. Smooth muscle cells in the bladder exhibit spontaneous spiking and spikes occur in a variety of distinct shapes, making their generation problematic to explain. We believe that the variety in shapes may owe less to intrinsic differences in spike mechanism (i.e., in the complement of ion channels participating in spike production) and more to features imposed by syncytial biophysics. We focus especially on the modulation of spike shape in a 3-D coupled network by such factors as innervation pattern, propagation in a syncytium, electrically finite bundles within and between which the spikes spread, and some degree of pacemaker activity by a sub-population of the cells. I shall report two streams of work that we have done, and the tentative conclusions these have enabled us to reach: (a) using the NEURON environment, to construct the smooth muscle syncytium and endow it with synaptic drive, and (b) using signal-processing approaches, towards sorting and classifying the experimentally recorded spikes.
Sanjeeva Srivastava, Ph.D.
Assistant Professor, Proteomics Lab, IIT-Bombay, India
Identification of Potential Early Diagnostic Biomarkers for Gliomas and Various Infectious Diseases using Proteomic Technologies
The spectacular advancements achieved in the field of proteomics research during the last decade have propelled the growth of proteomics for clinical research. Recently, comprehensive proteomic analyses of different biological samples such as serum or plasma, tissue, CSF, urine, saliva etc. have attracted considerable attention for the identification of protein biomarkers as early detection surrogates for diseases (Ray et al., 2011). Biomarkers are biomolecules that can be used for early disease detection, differentiation between closely related diseases with similar clinical manifestations as well as aid in scrutinizing disease progression. Our research group is performing in-depth analysis of alteration in human proteome in different types of brain tumors and various pathogenic infections to obtain mechanistic insight about the disease pathogenesis and host immune responses, and identification of surrogate protein markers for these fatal human diseases.
Applying 2D-DIGE in combination with MALDI-TOF/TOF MS we have analyzed the serum and tissue proteome profiles of glioblastoma multiforme; the most common and lethal adult malignant brain tumor (Gollapalli et al., 2012) (Figure 1). Results obtained were validated by employing different immunoassay-based approaches. In serum proteomic analysis we have identified some interesting proteins like haptoglobin, ceruloplasmin, vitamin-D binding protein etc. Moreover, proteomic analysis of different grades (grade-I to IV) of gliomas and normal brain tissue was performed and differential expressions of quite a few proteins such as SIRT2, GFAP, SOD, CDC42 have been identified, which have significant correlation with the tumor growth. While proteomic analysis of cerebrospinal fluid from low grade (grade I & II) vs. high grade (grade III & IV) gliomas revealed modulation of CSF levels of apolipoprotein E, dickkopf related protein 3, vitamin D binding protein and albumin in high grade gliomas. The prospective candidates identified in our studies provide a mechanistic insight of glioma pathogenesis and identification of potential biomarkers. We are also studying the role of JAK/STAT interactome and therapeutic potential of STAT3 inhibitors in gliomas using proteomics approach. Several candidates of the JAK/STAT interactome were identified with altered expression and a significant correlation was observed between STAT3 and PDK1 transcript expression level.
We have also investigated the changes in human serum proteome in different infectious diseases including falciparum and vivax malaria (Ray et al., 2012a; Ray et al., 2012b), dengue (Ray et al., 2012c) and leptospirosis (Srivastava et al., 2012). Although, quite a few serum proteins were found to be commonly altered in different infectious diseases and might be a consequence of inflammation mediated acute phase response signaling, uniquely modulated candidates were identified in each pathogenic infection indicating the some inimitable responses. Further, a panel of identified proteins consists of six candidates; serum amyloid A, hemopexin, apolipoprotein E, haptoglobin, retinol-binding protein and apolipoprotein A-I was used to build statistical sample class prediction models employing PLSDA and other classification methods to predict the clinical phenotypic classes and 91.37% overall prediction accuracy was achieved (Figure 2). ROC curve analysis was carried out to evaluate the individual performance of classifier proteins. The excellent discrimination among the different disease groups on the basis of differentially expressed proteins demonstrates the potential diagnostic implications of this analytical approach.
Keywords: Diagnostic biomarkers, Gliomas, Infectious Diseases, Proteomics, Serum proteome
Acknowledgments: This disease biomarker discovery research was supported by Department of Biotechnology, India grant (No. BT/PR14359/MED/30/916/2010), Board of Research in Nuclear Sciences (BRNS) DAE young scientist award (2009/20/37/4/BRNS) and a startup grant 09IRCC007 from the IIT Bombay. The active support from Advanced Center for Treatment Research and Education in Cancer (ACTREC), Tata Memorial Hospital (TMH), and Seth GS Medical College and KEM Hospital Mumbai, India in clinical sample collection process is gratefully acknowledged.
References :
- Ray S, Reddy PJ, Jain R, Gollapalli K. Moiyadi A, Srivastava S. Proteomic technologies for the identification of disease biomarkers in serum: advances and challenges ahead. Proteomics 11: 2139-61, 2011.
- Gollapalli K, Ray S, Srivastava R, Renu D, Singh P, Dhali S, Dikshit JB, Srikanth R, Moiyadi A, Srivastava S. Investigation of serum proteome alterations in human glioblastoma multiforme. Proteomics 12(14): 2378-90, 2012.
- Ray S, Renu D, Srivastava R, Gollapalli K, Taur S, Jhaveri T, Dhali S, Chennareddy S, Potla A, Dikshit JB, Srikanth R, Gogtay N, Thatte U, Patankar S, Srivastava S. Proteomic investigation of falciparum and vivax malaria for identification of surrogate protein markers. PLoS One 7(8): e41751, 2012a.
- Ray S, Kamath KS, Srivastava R, Raghu D, Gollapalli K, Jain R, Gupta SV, Ray S, Taur S, Dhali S, Gogtay N, Thatte U, Srikanth R, Patankar S, Srivastava S. Serum proteome analysis of vivax malaria: An insight into the disease pathogenesis and host immune response. J Proteomics 75(10): 3063-80, 2012b.
- Srivastava R, Ray S, Vaibhav V, Gollapalli K, Jhaveri T, Taur S, Dhali S, Gogtay N, Thatte U, Srikanth R, Srivastava S. Serum profiling of leptospirosis patients to investigate proteomic alterations. J Proteomics 76: 56-68, 2012.
- Ray S, Srivastava R, Tripathi K, Vaibhav V, Srivastava S. Serum proteome changes in dengue virus-infected patients from a dengue-endemic area of India: towards new molecular targets? OMICS 16(10): 527-36, 2012c.
* Correspondence: Dr. Sanjeeva Srivastava, Department of Biosciences and Bioengineering, IIT Bombay, Mumbai 400 076, India: E-mail: sanjeeva@iitb.ac.in; Phone: +91-22-2576-7779, Fax: +91-22-2572-3480
Nader Pourmand, Ph.D.
Director, UCSC Genome Technology Center,University of California, Santa Cruz
Biosensor and Single Cell Manipulation using Nanopipettes
Approaching sub-cellular biological problems from an engineering perspective begs for the incorporation of electronic readouts. With their high sensitivity and low invasiveness, nanotechnology-based tools hold great promise for biochemical sensing and single-cell manipulation. During my talk I will discuss the incorporation of electrical measurements into nanopipette technology and present results showing the rapid and reversible response of these subcellular sensors to different analytes such as antigens, ions and carbohydrates. In addition, I will present the development of a single-cell manipulation platform that uses a nanopipette in a scanning ion-conductive microscopy technique. We use this newly developed technology to position the nanopipette with nanoscale precision, and to inject and/or aspirate a minute amount of material to and from individual cells or organelle without comprising cell viability. Furthermore, if time permits, I will show our strategy for a new, single-cell DNA/ RNA sequencing technology that will potentially use nanopipette technology to analyze the minute amount of aspirated cellular material.
Michelle Hermiston, MD, Ph.D.
Assistant Professor, Department of Pediatrics University of California San Francisco, USA
Interrogating Signaling Networks at the Single Cell Level In Primary Human Patient Samples
Multiparameter phosphoflow cytometry is a highly sensitive proteomic approach that enables monitoring of biochemical perturbations at the single cell level. By combining antisera to cell surface markers and key intracellular proteins, perturbations in signaling networks, cell survival and apoptosis mediators, cell cycle regulators, and/or modulators of other cellular processes can be analyzed in a highly reproducible and sensitive manner in the basal state and in response to stimulation or drug treatment. Advantages of this approach include the ability to identify the biochemical consequences of genetic and/or epigenetic changes in small numbers of cells, to map potential interplay between various signaling networks simultaneously in a single cell, and to interrogate potential mechanisms of drug resistance or response in a primary patient sample. Application of this technology to patients with acute lymphoblastic leukemia or the autoimmune disease systemic lupus erythematosus (SLE) will be discussed.
R. Manjunath, Ph.D.
Associate Professor, Dept of Biochemistry, Indian Institute of Science, Bengaluru, India
REGULATION OF THE MHC COMPLEX AND HLA SOLUBILISATION BY THE FLAVIVIRUS, JAPANESE ENCEPHALITIS VIRUS
Viral encephalitis caused by Japanese encephalitis virus (JEV) and West Nile Virus (WNV) is a mosquito-borne disease that is prevalent in different parts of India and other parts of South East Asia. JEV is a positive single stranded RNA virus that belongs to the Flavivirus genus of the family Flaviviridae. The genome of JEV is about 11 kb long and codes for a polyprotein which is cleaved by both host and viral encoded proteases to form 3 structural and 7 non-structural proteins. It is a neurotropic virus which infects the central nervous system (CNS) and causes death predominantly in newborn children and young adults. JEV follows a zoonotic life-cycle involving mosquitoes and vertebrate, chiefly pigs and ardeid birds, as amplifying hosts. Humans are infected when bitten by an infected mosquito and are dead end hosts. Its structural, pathological, immunological and epidemiological aspects have been well studied. After entry into the host following a mosquito bite, JEV infection leads to acute peripheral neutrophil leucocytosis in the brain and leads to elevated levels of type I interferon, macrophage-derived chemotactic factor, RANTES,TNF-α and IL-8 in the serum and cerebrospinal fluid.
Major Histocompatibility Complex (MHC) molecules play a very important role in adaptive immune responses. Along with various classical MHC class I molecules, other non-classical MHC class I molecules play an important role in modulating innate immune responses. Our lab has shown the activation of cytotoxic T-cells (CTLs) during JEV infection and CTLs recognize non-self peptides presented on MHC molecules and provide protection by eliminating infected cells. However, along with proinflammatory cytokines such as TNFα, they may also cause immunopathology within the JEV infected brain. Both JEV and WNV, another related flavivirus have been shown to increase MHC class I expression. Infection of human foreskin fibroblast cells (HFF) by WNV results in upregulation of HLA expression. Data from our lab has also shown that JEV infection upregulates classical as well as nonclassical (class Ib) MHC antigen expression on the surface of primary mouse brain astrocytes and mouse embryonic fibroblasts.
There are no reports that have discussed the expression of these molecules on other cells like endothelial and astrocyte that play an important role in viral invasion in humans. We have studied the expression of human classical class I molecules HLA-A, -B, -C and the non-classical HLA molecules, HLA-E as well as HLA-F in immortalized human brain microvascular endothelial cells (HBMEC), human endothelial cell line (ECV304), human glioblastoma cell line (U87MG) and human foreskin fibroblast cells (HFF). Nonclassical MHC molecules such as mouse Qa-1b and its human homologue, HLA-E have been shown to be the ligand for the inhibitory NK receptor, NKG2A/CD94 and may bridge innate and adaptive immune responses. We show that JEV infection of HBMEC and ECV 304 cells upregulates the expression of HLA-A, and –B antigens as well as HLA-E and HLA-F. Increased expression of total HLA-E upon JEV infection was also observed in other human cell lines as well like, human amniotic epithelial cells, AV-3, FL and WISH cells. Further, we show for the first time that soluble HLA-E (sHLA-E) was released from infected ECV and HBMECs. In contrast, HFF cells showed only upregulation of cell-surface HLA-E expression while U87MG, a human glioblastoma cell line neither showed any cell-surface induction nor its solubilization. This shedding of sHLA-E was found to be dependent on matrix metalloproteinase (MMP) and an important MMP, MMP-9 was upregulated during JEV infection. Treatment with IFNγ resulted in the shedding of sHLA-E from ECV as well as U87MG but not from HFF cells. Also, sHLA-E was shed upon treatment with IFNβ and both IFNβ and TNFα, when present together caused an additive increase in the shedding of sHLA-E. HLA-E is an inhibitory ligand for CD94/NKG2A receptor of Natural Killer cells. Thus, MMP mediated solubilization of HLA-E from infected endothelial cells may have important implications in JEV pathogenesis including its ability to compromise the blood brain barrier.
Karmeshu, Ph.D.
Dean & Professor, School of Computer & Systems Sciences & School of Computational & Integrative Sciences, Jawaharlal Nehru University, India.
Interspike Interval Distribution of Neuronal Model with distributed delay: Emergence of unimodal, bimodal and Power law
The study of interspike interval distribution of spiking neurons is a key issue in the field of computational neuroscience. A wide range of spiking patterns display unimodal, bimodal ISI patterns including power law behavior. A challenging problem is to understand the biophysical mechanism which can generate the empirically observed patterns. A neuronal model with distributed delay (NMDD) is proposed and is formulated as an integro-stochastic differential equation which corresponds to a non-markovian process. The widely studied IF and LIF models become special cases of this model. The NMDD brings out some interesting features when excitatory rates are close to inhibitory rates rendering the drift close to zero. It is interesting that NMDD model with gamma type memory kernel can also account for bimodal ISI pattern. The mean delay of the memory kernels plays a significant role in bringing out the transition from unimodal to bimodal ISI distribution. It is interesting to note that when a collection of neurons group together and fire together, the ISI distribution exhibits power law.
John Stanley, Satheesh Babu, Ramacahandran T and Bipin Nair
Pt-Pd decorated TiO2 nanotube array for the non-enzymatic determination of glucose in neutral medium
Rapidly expanding diabetic population and the complications associated with elevated glycemic levels necessitates the need for a highly sensitive, selective and stable blood glucose measurement strategy. The high sensitivity and selectivity of enzymatic sensors together with viable manufacturing technologies such as screen-printing have made a great social and economic impact. However, the intrinsic nature of the enzymes leads to lack of stability and consequently reduces shelf life and imposes the need for stringent storage conditions. As a result much effort has been directed towards the development of ‘enzyme-free’ glucose sensors (Park et al. 2006). In this paper, a non-enzymatic amperometric sensor for selective and sensitive direct electrooxidation of glucose in neutral medium was fabricated based on Platinum-Palladium (Pt–Pd) nanoparticle decorated titanium dioxide (TiO2) nanotube arrays. Highly ordered TiO2 nanotube arrays were obtained using a single step anodization process (Grimes C A and Mor G K 2009) over which Pt–Pd nanoparticles where electrochemically deposited. Scanning Electron Microscopy (SEM) analysis revealed the diameter of the TiO2 nanotubes to be approximately 40 nm. Elemental analysis after electrochemical deposition confirms the presence of Pt–Pd. Electrochemical characterization of the sensor was carried out using cyclic voltammetry technique (−1.0 to +1.0V) in phosphate buffer saline (PBS) pH 7.4. All further glucose oxidation studies were performed in PBS (pH 7.4). The sensor exhibited good linear response towards glucose for a concentration range of 1 μM to 20mM with a linear regression coefficient of R = 0.998. The electrodes are found to be selective in the presence of other commonly interfering molecules such as ascorbic acid, uric acid, dopamine and acetamidophenol. Thus a nonenzymatic sensor with good selectivity and sensitivity towards glucose in neutral medium has been developed.
Vural Özdemir, MD, Ph.D., DABCP
Co-Founder, DELSA Global, Seattle, WA, USA
Crowd-Funded Micro-Grants to Link Biotechnology and “Big Data” R&D to Life Sciences Innovation in India
Vural Özdemir, MD, PhD, DABCP1,2*
- Data-Enabled Life Sciences Alliance International (DELSA Global), Seattle, WA 98101, USA;
- Faculty of Management and Medicine, McGill University, Canada;
ABSTRACT
Aims: This presentation proposes two innovative funding solutions for linking biotechnology and “Big Data” R&D in India with artisan small scale discovery science, and ultimately, with knowledge-based innovation:
- crowd-funded micro-grants, and
- citizen philanthropy
These two concepts are new, and inter-related, and can be game changing to achieve the vision of biotechnology innovation in India, and help bridge local innovation with global science.
Background and Context: Biomedical science in the 21(st) century is embedded in, and draws from, a digital commons and “Big Data” created by high-throughput Omics technologies such as genomics. Classic Edisonian metaphors of science and scientists (i.e., “the lone genius” or other narrow definitions of expertise) are ill equipped to harness the vast promises of the 21(st) century digital commons. Moreover, in medicine and life sciences, experts often under-appreciate the important contributions made by citizen scholars and lead users of innovations to design innovative products and co-create new knowledge. We believe there are a large number of users waiting to be mobilized so as to engage with Big Data as citizen scientists-only if some funding were available. Yet many of these scholars may not meet the meta-criteria used to judge expertise, such as a track record in obtaining large research grants or a traditional academic curriculum vitae. This presentation will describe a novel idea and action framework: micro-grants, each worth $1000, for genomics and Big Data. Though a relatively small amount at first glance, this far exceeds the annual income of the “bottom one billion” – the 1.4 billion people living below the extreme poverty level defined by the World Bank ($1.25/day).
We will present two types of micro-grants. Type 1 micro-grants can be awarded through established funding agencies and philanthropies that create micro-granting programs to fund a broad and highly diverse array of small artisan labs and citizen scholars to connect genomics and Big Data with new models of discovery such as open user innovation. Type 2 micro-grants can be funded by existing or new science observatories and citizen think tanks through crowd-funding mechanisms described herein. Type 2 micro-grants would also facilitate global health diplomacy by co-creating crowd-funded micro-granting programs across nation-states in regions facing political and financial instability, while sharing similar disease burdens, therapeutics, and diagnostic needs. We report the creation of ten Type 2 micro-grants for citizen science and artisan labs to be administered by the nonprofit Data-Enabled Life Sciences Alliance International (DELSA Global, Seattle: http://www.delsaglobal.org). Our hope is that these micro-grants will spur novel forms of disruptive innovation and life sciences translation by artisan scientists and citizen scholars alike.
Address Correspondence to:
Vural Özdemir, MD, PhD, DABCP
Senior Scholar and Associate Professor
Faculty of Management and Medicine, McGill University
1001 Sherbrooke Street West
Montreal, Canada H3A 1G5