Dr. Sujay Chattopadhyay received his MTech in Biotechnology from Indian Institute of Technology, Kharagpur, India. He completed his PhD in Bioinformatics and Computational Biology from the Department of Theoretical Physics at Indian Association for the Cultivation of Science, Kolkata, India. He pursued his post-doctoral research in Department of Microbiology, University of Washington, Seattle, USA. In UW Microbiology, he later continued to work as an Acting Instructor followed by Research Assistant Professor. In USA, he performed computational biology research in the field of microbial evolution, primarily in E. coli and Samonella. Using these species as case studies, he developed multiple analytical tools and database:
(a) ‘Zonal Phylogeny Software’ and ‘TimeZone’ for gene-based and genome-wide mapping of adaptive mutational footprints;
(b) ‘PanCoreGen’ for profiling, detecting and annotating protein-coding genes in microbial genomes;
(c) Prototype microbial variome databases using E. coli and Salmonella.
He has also been a consultant for a Seattle, USA based molecular diagnostic start-up ID Genomics, for which he received a US patent (# 15/055,376 filed on February 26,2016) titled ‘Process and Kit for Predicting Antibiotic Resistance and Susceptibility of Bacteria’ for detecting high-resolution genotyping markers to aid clonal diagnostics.
Dr. Chattopadhyay is an Associate Professor at Amrita School of Biotechnology and his current research focuses on:
Similar to genome-wide association studies in humans, given a large sample size, the co-evolved loci or adaptive mutations in microbes (pathogens in particular) can in effect be predicted for their association to specific host-compartments, geographical locations, epidemic/endemic outbreaks, or disease phenotypes in hosts. The present pace of genome sequencing indicates that, by using affordable and rapid sequencing technologies, tens of thousands of microbial genomes will be sequenced during this decade, thereby enabling us perform such association studies in near future. This project plans to develop an analytical tool to detect co-evolution of genes across the genome, to be used to assess phylogenetic congruence for the entire tree (i.e. involving all isolates) or for any sub-tree (i.e. across specific phylogenetic clades) for a given species. This information will provide important insights to create genomic network of adaptive loci functioning within a particular bacterial lineage or across multiple lineages in parallel.
An important extension of within-species co-evolution studies would be to study cross-species interplay of such adaptive forces in a given habitat. His earlier work on Escherichia coli and Salmonella enterica subspecies I core genes demonstrated that there was a significant overlap in the functional trajectories of adaptive evolution in two species. Recent studies showed that specific virulence factors in S. typhimurium stimulate strong host inflammatory response, and eventually help the pathogen gain an advantage in its growth competition with the resident microbiota. Therefore, it would be important to study the role of co-evolving metabolic pathways in the interactions/competitions of microbiota in host-compartments, e.g. in the inflamed gut. Such a study can offer the possibility to identify new targets for intervention.
Occurrence of pseudogene formation via truncation mutation and gene deletion is a common phenomenon in bacterial world, especially in the evolution of the host-adapted/host-restricted bacterial pathogens. A general belief is that pseudogene formation and gene deletion are results of reductive evolution, following a ‘use-or-lose’ dynamics which suggests purging of traits that are of no use in the organism. Based on the preliminary studies on Salmonella, however, Dr. Chattopadhyay’s lab hypothesizes that accumulation of truncation mutations leading to pseudogene formation can often be result of adaptive evolution. We anticipate that such events rather follow a ‘die-or-lose’ dynamics indicating purging of traits that are otherwise deleterious to the organism.
The goal of this project is to understand the role of gene inactivation via truncation mutations in the (patho)adaptive evolution of bacteria. Events leading to evolutionary convergence are often adaptive and positively selected. Based on the detection of recent non-random convergent events of truncation mutations, the lab proposes a novel approach to distinguish adaptive truncation mutations from reductive ones. The primary focus in this study will be on Salmonella, along with other pathogens, for developing the analytical tool to decipher the adaptive significance of gene truncation mutations leading to the loss of protein function.
Most bacterial species, pathogens or commensals, are clonal in nature, represented by the strains with distinct phenotypes circulating as a limited number of genetically related (i.e. clonal) lineages. The stability of such (adapted) clonal lineages has been demonstrated to be strong enough, both temporally and spatially, to decipher consistent clonal association with important traits like specific virulence potentials or antibiotic resistance profiles.
Multilocus sequence typing (MLST) is presently the method of choice for determining the clonal structure of a bacterial species, and for numerous important pathogens the MLST schemes have been standardized. However, since the STs are discriminated based on the genetic relatedness of a set of housekeeping genes, they are neither uniform nor fine-tuned with respect to the pathotypes and resistance/susceptibility profiles of their representative strains. For example, in E. coli, ST73 includes pathogenic strains like CFT073 that causes pyelonephritis in humans, as well as commensal strains like ABU83972 and Nissle1917 that have been used as probiotics in humans. Also, MLST requires involvement of 7 loci, limiting its efficiency in terms cost and time. This work aims to detect potential candidate genes and mutations therein as high-resolution clonal markers for selected bacterial pathogens to associate specific virulence and/or multidrug resistance properties of interest.