Bacteria rely on chemosensory systems (CSS) to perceive and adapt to their chemical environments, where they help in chemotaxis. These systems, often mediated through two-component signaling modules and large transmembrane receptor complexes, play key roles in motility, biofilm formation, pathogenicity, and metabolic regulation.
Our lab's preliminary work has focused on characterizing the diversity, organization, and evolutionary dynamics of bacterial chemosensory pathways across a broad phylogenetic landscape, with a special emphasis on organisms from the Myxobacteria (phylum Myxococcota) and Vibrio (order Vibrionales) lineages. We are particularly interested in utilizing comparative genomics, phylogenetics, domain architecture, synteny, and evolutionary trajectories. We aim to trace the origin, diversification, and functions of chemosensory arrays and their methyl-accepting chemotaxis proteins (MCP), with a focus on those linked with alternative cellular functions.
Additionally, we are integrating experimental approaches to validate computational predictions and reveal novel behavioral phenotypes in response to defined chemical stimuli.
Our lab investigates the diversity, function, and evolutionary dynamics of bacterial biosynthetic gene clusters (BGCs), which encode the molecular machinery for the production of secondary metabolites—natural products with roles in microbial competition, symbiosis, and host interaction. For this project also, our focus is on Myxobacteria (phylum Myxococcota) organisms. We are particularly focused on BGC prediction using state-of-the-art tools such as antiSMASH and DeepBGC, where we predict and annotate BGCs from complete and draft bacterial genomes. We are also in the process of making newer tools to identify and improve novel BGC identification and functional annotation.
Through comparative genomics and phylogenetic analysis, we explore the mechanisms behind BGC diversification—including horizontal gene transfer, gene duplication, and recombination—and how these processes drive metabolic innovation in microbial lineages.
Medicinal plants host diverse microbial consortia in their roots and rhizosphere that significantly influence their biochemical pathways. Understanding these plant-microbe interactions is crucial for enhancing the efficacy and sustainability of plant-derived therapeutics. Our lab is conducting fundamental computational research to dive into the complex symbiotic relationships between medicinal plants and their associated microbial communities. We aim to uncover how these interactions shape plant health, metabolite production, and therapeutic properties.
To do so, we sequence the nuclear and organellar genomes of select medicinal plant species to catalog genes involved in secondary metabolite biosynthesis and stress responses. This provides a genomic foundation for understanding how plants modulate microbial colonization and metabolite output. Simultaneously, we also perform sequencing of root-associated microbial communities (rhizobiome), enabling us to identify bacterial and fungal taxa enriched in the roots of medicinal plants. This approach helps us map community structure, functional gene content, and potential biosynthetic gene clusters from symbiotic microbes. By integrating host plant genomes with metagenomic data, we are building interaction networks that reveal how specific microbial populations may influence or be influenced by host gene expression and metabolite profiles.
This line of research sits at the intersection of genomics, microbiology, and natural product discovery, with potential to revolutionize how we cultivate and harness medicinal plants in agriculture and therapeutics, along with benchmarking their medicinal properties.
We believe that science advances through collaboration. If you have an interesting idea or project and think our computational expertise could complement yours, we’d love to hear from you.
We welcome opportunities to collaborate across disciplines and institutions.
To explore a potential collaboration, please reach out to us at sharmaG@bt.iith.ac.in.