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.
Shantikumar Nair, Ph.D.
Professor & Director, Amrita Center for Nanosciences & Molecular Medicine, Amrita University, India
Spatially Distributed and Hierarchical Nanomaterials in Biotechnology
Although nano materials are well investigated in biotechnology in their zero-, one- and two-dimensional forms, three-dimensional nanomaterials are relatively less investigated for their biological applications. Three dimensional nano materials are much more complex with several structural and hierarchical variables controlling their mechanical, chemical and biological functionality. In this talk examples are given of some complex three dimensional systems including, scaffolds, aggregates, fabrics and membranes. Essentially three types of hierarchies are considered: one-dimensional hierarchy, two-dimensional hierarchy and three-dimensional hierarchy each giving rise to unique behaviors.
Satheesh Babu T. G., Ph.D.
Associate Professor, Department of Sciences, School of Engineering, Amrita University, Coimbatore, India
Nanomaterials for ‘enzyme-free’ biosensing
Enzyme based sensors have many draw backs such as poor storage stability, easily affected by the change in pH and temperature and involves complicated enzyme immobilization procedures. To address this limitation, an alternative approach without the use of enzyme, “non-enzymatic” has been tried recently. Choosing the right catalyst for direct electrochemical oxidation / reduction of a target molecule is the key step in the fabrication of non-enzymatic sensors.
Non-enzymatic sensors for glucose, creatinine, vitamins and cholesterol are fabricated using different nanomaterials, such as nanotubes, nanowires and nanoparticles of copper oxide, titanium dioxide, tantalum oxide, platinum, gold and graphenes. These sensors selectively catalyse the targeted analyte with very high sensitivity. These nanomaterials based sensors combat the drawbacks of enzymatic sensors.
Akhilesh Pandey, Ph.D.
Professor, Johns Hopkins University School of Medicine, Baltimore, USA
A draft map of the human proteome
We have generated a draft map of the human proteome through a systematic and comprehensive analysis of normal human adult tissues, fetal tissues and hematopoietic cells as an India-US initiative. This unique dataset was generated from 30 histologically normal adult tissues, fetal tissues and purified primary hematopoietic cells that were analyzed at high resolution in the MS mode and by HCD fragmentation in the MS/MS mode on LTQ-Orbitrap Velos/Elite mass spectrometers. This dataset was searched against a 6-frame translation of the human genome and RNA-Seq transcripts in addition to standard protein databases. In addition to confirming a large majority (>16,000) of the annotated protein-coding genes in humans, we obtained novel information at multiple levels: novel protein-coding genes, unannotated exons, novel splice sites, proof of translation of pseudogenes (i.e. genes incorrectly annotated as pseudogenes), fused genes, SNPs encoded in proteins and novel N-termini to name a few. Many proteins identified in this study were identified by proteomic methods for the first time (e.g. hypothetical proteins or proteins annotated based solely on their chromosomal location). We have generated a catalog of proteins that show a more tissue-restricted pattern of expression, which should serve as the basis for pursuing biomarkers for diseases pertaining to specific organs. This study also provides one of the largest sets of proteotypic peptides for use in developing MRM assays for human proteins. Identification of several novel protein-coding regions in the human genome underscores the importance of systematic characterization of the human proteome and accurate annotation of protein-coding genes. This comprehensive dataset will complement other global HUPO initiatives using antibody-based as well as MRM mass spectrometry-based strategies. Finally, we believe that this dataset will become a reference set for use as a spectral library as well as for interesting interrogations pertaining to biomedical as well as bioinformatics questions.
