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)
Kal Ramnarayan, Ph.D.
Co-founder President & Chief Scientific Officer, Sapient Discovery, San Diego, CA, USA
A cost-effective approach to Protein Structure-guided Drug Discovery: Aided by Bioinformatics, Chemoinformatics and computational chemistry
With the mapping of the human genome completed almost a decade ago, efforts are still underway to understand the gene products (i.e., proteins) in the human biological and disease pathways. Deciphering such information is very important for the discovery and development of small molecule drugs as well as protein therapeutics for various human diseases for which no cure exists. As an example, with more than 500 members, the kinase family of protein targets continues to be an important and attractive class for drug discovery. While how many of the members in this family are actually druggable is still to be established, there are several ongoing efforts on this class of proteins across a broad spectrum of disease categories. Even though in general the protein structural topology might looks similar, there are issues with respect selectivity of identified small molecule inhibitors when, the lead molecule discovery is carried out at the ATP binding site. As an added complexity, allosteric modulators are needed for some of the members, but the actual site for such modulation on the protein target can not resolved with uncertainty. In this presentation we will describe a bioinformatics and computational based platform for small molecule discovery for protein targets that are involved in protein-protein interactions as well as targets like kinases and phosphatases. We will describe a computational approach in which we have used an informatics based platform with several hundred kinases to sort through in silico and identify inhibitors that are likely to be highly selective in the lead generation phase. We will discuss the implication of this approach on the drug discovery of the kinase and phosphatase classes in general and independent of the disease category.
Tejaswini Subbannayya, Nandini A. Sahasrabuddhe, Arivusudar Marimuthu, Santosh Renuse, Gajanan Sathe, Srinivas M. Srikanth, Mustafa A. Barbhuiya, Bipin Nair, Juan Carlos Roa, Rafael Guerrero-Preston, H. C. Harsha, David Sidransky, Akhilesh Pandey, T. S. Keshava Prasad and Aditi Chatterjee
Proteomic profiling of gallbladder cancer secretome – a source for circulatory biomarker discovery
Gallbladder cancer (GBC) is the fifth most common cancer of the gastrointestinal tract and one of the common malignancies that occur in the biliary tract (Misra et al. 2006; Lazcano-Ponce et al. 2001). It has a poor prognosis with survival of less than 5 years in 90% of the cases (Misra et al. 2003). The etiology is ill-defined. Several risk factors have been reported including cholelithiasis, obesity, female gender and exposure to carcinogens (Eslick 2010; Kumar et al. 2006). Poor prognosis in GBC is mainly due to late presentation of the disease and lack of reliable biomarkers for early diagnosis. This emphasizes the need to identify and characterize cancer biomarkers to aid in the diagnosis and prognosis of GBC. Secreted proteins are an important class of molecules which can be detected in body fluids and has been targeted for biomarker discovery. There are challenges faced in the proteomic interrogation of body fluids especially plasma such as low abundance of tumor secreted proteins, high complexity and high abundance of other proteins that are not released by the tumor cells (Tonack et al. 2009). Profiling of conditioned media from the cancer cell lines can be used as an alternate means to identify secreted proteins from tumor cells (Kashyap et al. 2010; Marimuthu et al. 2012). We analyzed the invasive property of 7 GBC cell lines (SNU-308, G-415, GB-d1, TGBC2TKB, TGBC24TKB, OCUG-1 and NOZ). Four cell lines were selected for analysis of the cancer secretome based on the invasive property of the cells. We employed isobaric tags for relative and absolute quantitation (iTRAQ) labeling technology coupled with high resolution mass spectrometry to identify and characterize secretome from the panel of 4GBC cancer cells mentioned above. In total, we have identified around 2,000 proteins of which 175 were secreted at differential abundance across all the four cell lines. This secretome analysis will act as a reservoir of candidate biomarkers. Currently, we are investigating and validating these candidate markers from GBC cell secretome. Through this study, we have shown mass spectrometry-based quantitative proteomic analysis as a robust approach to investigate secreted proteins in cancer cells.