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)
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.
V. Nagaraja Ph.D.
Professor, Indian Institute of Science, Bengaluru, India
Perturbation of DNA topology in mycobacteria
To maintain the topological homeostasis of the genome in the cell, DNA topoisomerases catalyse DNA cleavage, strand passage and rejoining of the ends. Thus, although they are essential house- keeping enzymes, they are the most vulnerable targets; arrest of the reaction after the first trans-esterification step leads to breaks in DNA and cell death. Some of the successful antibacterial or anticancer drugs target the step ie arrest the reaction or stabilize the topo -DNA covalent complex. I will describe our efforts in this direction – to target DNA gyrase and also topoisomerase1 from mycobacteria. The latter, although essential, has no inhibitors described so far. The new inhibitors being characterized are also used to probe topoisomerase control of gene expression.
In the biological warfare between the organisms, a diverse set of molecules encoded by invading genomes target the above mentioned most vulnerable step of topoisomerase reaction, leading to the accumulation of double strand breaks. Bacteria, on their part appear to have developed defense strategies to protect the cells from genomic double strand breaks. I will describe a mechanism involving three distinct gyrase interacting proteins which inhibit the enzyme in vitro. However, in vivo all these topology modulators protect DNA gyrase from poisoning effect by sequestering the enzyme away from DNA.
Next, we have targeted a topology modulator protein, a nucleoid associated protein(NAP) from Mycobacterium tuberculosis to develop small molecule inhibitors by structure based design. Over expression of HU leads to alteration in the nucleoid architecture. The crystal structure of the N-terminal half of HU reveals a cleft that accommodates duplex DNA. Based on the structural feature, we have designed inhibitors which bind to the protein and affect its interaction with DNA, de-compact the nucleoid and inhibit cell growth. Chemical probing with the inhibitors reveal the importance of HU regulon in M.tuberculosis.
Srisairam Achuthan, Ph.D.
Senior Scientific Programmer, Research Informatics Division, Department of Information Sciences, City of Hope, CA, USA
Applying Machine learning for Automated Identification of Patient Cohorts
Srisairam Achuthan, Mike Chang, Ajay Shah, Joyce Niland
Patient cohorts for a clinical study are typically identified based on specific selection criteria. In most cases considerable time and effort are spent in finding the most relevant criteria that could potentially lead to a successful study. For complex diseases, this process can be more difficult and error prone since relevant features may not be easily identifiable. Additionally, the information captured in clinical notes is in non-coded text format. Our goal is to discover patterns within the coded and non-coded fields and thereby reveal complex relationships between clinical characteristics across different patients that would be difficult to accomplish manually. Towards this, we have applied machine learning techniques such as artificial neural networks and decision trees to determine patients sharing similar characteristics from available medical records. For this proof of concept study, we used coded and non-coded (i.e., clinical notes) patient data from a clinical database. Coded clinical information such as diagnoses, labs, medications and demographics recorded within the database were pooled together with non-coded information from clinical notes including, smoking status, life style (active / inactive) status derived from clinical notes. The non-coded textual information was identified and interpreted using a Natural Language Processing (NLP) tool I2E from Linguamatics.
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.
Sukhithasri V, Nisha N, Vivek V and Raja Biswas
The host innate immune system acts as the first line of defense against invading pathogens. During an infection, the host innate immune cells recognize unique conserved molecules on the pathogen known as Pathogen Associated Molecular Patterns (PAMPs). This recognition of PAMPs helps the host mount an innate immune response leading to the production of cytokines (Akira et al. 2006). Peptidoglycan, one of the most conserved and essential component of the bacterial cell wall is one such PAMP. Peptidoglycan is known to have potent proinflammatory properties (Gust et al. 2007). Host recognize peptidoglycan using Nucleotide oligomerization domain proteins (NODs). This recognition of peptidoglycan activates the NODs and triggers downstream signaling leading to the nuclear translocation of NF-κB and production of cytokines (McDonald et al. 2005). Pathogenic bacteria modify their peptidoglycan as a strategy to evade innate immune recognition, which helps it to establish infection in the host. These peptidoglycan modifications include O-acetylation and N-glycolylation of muramic acid and N-deacetylation of N-acetylglucosamine (Davis et al. 2011). Modification of mycobacterial peptidoglycan by N-glycolylation prevents the catalytic activity of lysozyme (Raymond et al. 2005). Additionally, mycobacterial peptidoglycan is modified by amidation for unknown reasons.
Here, we have investigated the role of amidated peptidoglycan in Mycobacterium sp in modulating the innate immune response. We isolated amidated peptidoglycan from Mycobacterium sp and non-amidated peptidoglycan from Escherichia coli. We made a comparative analysis of the cytokine response produced on stimulation of innate immune cells by peptidoglycan from E. Coli and Mycobacterium sp. Macrophages and whole blood were treated with peptidoglycan and the cytokines secreted into spent medium and plasma respectively were analyzed using ELISA. Our results show that peptidoglycan from Mycobacterium sp is less effective in stimulating innate immune cells to produce cytokines. This intrinsic modulation of the cytokine response suggests that mycobacteria modify their peptidoglycan by amidation to evade innate immune response.