Ganesh Sambasivam, Ph.D.
CSO & Co-Founder, Anthem Biosciences India
Preclinical Outsourcing to India
The outsourcing segment is witnessing rapid changes with respect to the nature of work outsourced and the location. Cost is the major driver but other considerations such as infrastructure and government policies can also be important drivers for decision making. The last couple of years have been a trying time for all CROs. The global economic meltdown has hit research budgets especially hard. The new challenges facing Contract Research Organizations call for a radically revised approach and a new model that would push the boundaries of this business further and would blur the line between client and vendor further. I believe the term Contract Research Organization (CRO), is a misnomer to begin with (often confused with Clinical Research Organization), has now morphed into a new type of company viz Contract Innovation Services (CIS). Clients are no longer just happy to outsource odds and ends of the development piece but are looking to their vendors for a massive amount of innovation input. This input is increasingly across both the chemistry and discovery domains. This new paradigm calls for CIS companies to develop new platforms, create intellectual propertythat is of service to clients andinnovate processes to meet new found customer expectations.
K. Satyamoorthy, Ph.D.
Director, Life Sciences Centre, Manipal University, India
Epigenetic Changes due to DNA Methylation in Human Epithelial Tumors
Extensive global hypomethylation in the genome and hypermthylation of selective tumor specific suppressor genes appears to be a hallmark of human cancers. Data suggests that hypermethylation of promoter region in genes is more closely related to subsequent gene expression; contrary to gene-body DNA methylation. The intricate balance between these two may contribute to the progressive process of development, differentiation and carcinogenesis. Epigenetic changes encompass, apart from DNA methylation, chromatin modifications through post-translational changes in histones and control by miRNAs. At the genome level, effects from these are compounded by copy number variations (CNVs) which may ultimately influence protein functions. From clinical perspective, changes in DNA methylation occur very early which are reversible and are influenced by environmental factors. Therefore, these can be potential resource for identifying therapeutic targets as well as biomarkers for early screening of cancer. Our current efforts in profiling genome wide DNA methylation changes in oral, cervical and breast cancers through DNA methylation microarray analysis has revealed number of alterations critical for survival, progression and metastatic behavior of tumors. Bioinformatics and functional analysis revealed several key regulatory molecules controlled by DNA methylation and suggests that DNA methylation changes in several CpG islands appear to co-segregate in the regions of miRNAs as well as in the CNVs. We have validated the signatures for methylation of CpG islands through bisufite sequencing for essential genes in clinical samples and have undertaken transcriptional and functional analysis in tumor cell lines. These results will be presented.
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.
Rajgopal Srinivasan, Ph.D.
Principal Scientist & Head Bio IT R&D, TCS Innovation Labs, India
Interpretation of Genomic Variation – Identifying Rare Variations Leading to Disease
Genome sequencing technologies are generating an abundance of data on human genetic variations. A big challenge lies in interpreting the functional relevance of such variations, especially in clinical settings. A first step in understanding the clinical relevance of genetic variations is to annotate the variants for region of occurrence, degree of conservation both within and across species, pattern of variation across related individuals, novelty of the variation and know effects of related variations. Several tools already exist for this purpose. However, these tools have their strengths and weaknesses. A second issue is the development of algorithms, which, given a rich annotation of variants are able to prioritize the variants as being relevant to the phenotype under investigation.
In my talk I will detail work that has been done in our labs to address both of the above problems. I will also illustrate the application of these tools that helped identify a rare mutation in the ATM gene leading to a diagnosis of AT in two infants.
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.