Bharat B. Chattoo, Ph.D.
Professor, Faculty of Science M.S.University of Baroda, India
Biology of plant infection by Magnaporthe oryzae
The rice blast disease caused by the ascomycetous fungus Magnaporthe oryzae is a major constraint in rice production. Rice-M.oryzae is also emerging as a good model patho-system to investigate how the fungus invades and propagates within the host. Identification and characterisation of genes critical for fungal pathogenesis provides opportunities to explore their use as possible targets for development of strategies for combating fungal infection and to better understand the complex process of host-pathogen interaction.
We have used insertional mutagenesis and RNAi based approaches to identify pathogenesis related genes in this fungus. A large number of mutants were isolated using Agrobacterium tumefaciens mediated transformation (ATMT). Characterisation of several interesting mutants is in progress. We have identified a novel gene, MGA1, required for the development of appressoria. The mutant mga1 is unable to infect and is impaired in glycogen and lipid mobilization required for appressorium development. The glycerol content in the mycelia of the mutant was significantly lower as compared to wild type and it was unable to tolerate hyperosmotic stress. A novel ABC transporter was identified in this fungus. The abc4 mutant did not form functional appressoria, was non-pathogenic and showed increased sensitivity to certain antifungal molecules implying the role of ABC4 in multidrug resistance (MDR). Another mutant MoSUMO (MGG_05737) was isolated using a Split Marker technique; the mutant showed defects in growth, germination and infection. Immuno-fluorescence microscopy revealed that MoSumo is localized to septa in mycelia and nucleus as well as septa in spores. Two Dimensional Gel Electrophoresis showed differences in patterns of protein expression between Wild Type B157 and MoΔSumo mutant. We also isolated and charaterised mutants in MoALR2 (MGG_08843) and MoMNR2 (MGG_09884). Our results indicate that both MoALR2 and MoMNR2 are Mg2+ transporters, and the reduction in the levels of CorA transporters caused defects in surface hydrophobicity, cell wall stress tolerance, sporulation, appressorium formation and infection are mediated through changes in the key signaling cascades in the knock-down transformants. (Work supported by the Department of Biotechnology, Government of India)
Deepthy Menon, Ph.D.
Associate Professor, Centre for Nanosciences & Molecular Medicine, Health Sciences Campus, Amrita University, Kochi, India
Nanobioengineering of implant materials for improved cellular response and activity
Deepthy Menon, Divyarani V V, Chandini C Mohan, Manitha B Nair, Krishnaprasad C & Shantikumar V Nair
Abstract
Current trends in biomaterials research and development include the use of surfaces with topographical features at the nanoscale (dimensions < 100 nm), which influence biomolecular or cellular level reactions in vitro and in vivo. Progress in nanotechnology now makes it possible to precisely design and modulate the surface properties of materials used for various applications in medicine at the nanoscale. Nanoengineered surfaces, owing to their close resemblance with extracellular matrix, possess the unique capacity to directly affect protein adsorption that ultimately modulates the cellular adhesion and proliferation at the site of implantation. Taking advantage of this exceptional ability, we have nanoengineered metallic surfaces of Titanium (Ti) and its alloys (Nitinol -NiTi), as well as Stainless Steel (SS) by a simple hydrothermal method for generating non-periodic, homogeneous nanostructures. The bio- and hemocompatibility of these nanotextured metallic surfaces suggest their potential use for orthopedic, dental or vascular implants. The applicability of nanotextured Ti implants for orthopedic use was demonstrated in vivo in rat models, wherein early-stage bone formation at the tissue-implant interface without any fibrous tissue intervention was achieved. This nanoscale topography also was found to critically influence bacterial adhesion in vitro, with decreased adherence of staphylococcus aureus. The same surface nanotopography also was found to provide enhanced proliferation and functionality of vascular endothelial cells, suggesting its prospective use for developing an antithrombotic stent surface for coronary applications. Clinical SS & NiTi stents were also modified based on this strategy, which would offer a suitable solution to reduce the probability of late stent thrombosis associated with bare metallic stents. Thus, we demonstrate that nanotopography on implant surfaces has a critical influence on the fate of cells, which in turn dictates the long term success of the implant.
Acknowledgement: Authors gratefully acknowledge the financial support from Department of Biotechnology, Government of India through the Bioengineering program.
Jaap Heringa, Ph.D.
Director & Professor of Bioinformatics, IBIVU VU University Amsterdam, The Netherlands
Modeling strategy based on Petri-nets
In my talk I will introduce a formal modeling strategy based on Petri-nets, which are a convenient means of modeling biological processes. I will illustrate the capabilities of Petri-nets as reasoning vehicles using two examples: Haematopoietic stem cell differentiation in mice, and vulval development in C. elegance. The first system was modeled using a Boolean implementation, and the second using a coarse-grained multi-cellular Petri-net model. Concepts such as the model state space, attractor states, and reasoning to adapt the model to the biological reality will be discussed.
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.
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.