We are interdisciplinary research team aimed at advancing the understanding of bacterial signal transduction and exploiting this knowledge to combat antimicrobial resistance (AMR). We integrate structural biology, microbiology, biochemistry, biophysics, and computational approaches to uncover how bacterial pathogens sense, process, and respond to environmental cues.
A central focus of our research is second-messenger signaling, particularly c-di-GMP, c-di-AMP, and magic spot nucleotides ((p)ppGpp/MSN), which govern critical survival pathways such as biofilm formation, persistence, quorum sensing, virulence, and stress adaptation. We study these mechanisms in clinically relevant pathogens, with an emphasis on ESKAPE pathogens leverage our discoveries to inform the development of next-generation antibiotics (NGAs).
1. Fundamental mechanisms of bacterial signaling
We aim to make foundational discoveries in bacterial signal transduction by identifying and characterizing novel second-messenger effectors and deciphering how they regulate cellular decision-making at the molecular level.
2. Targeting survival pathways such as biofilms, quorum sensing, virulence, and persistence
Our work seeks to exploit second-messenger signaling networks to develop anti-biofilm and anti-c-di-GMP/MSN strategies, with the long-term goal of enabling new classes of antibacterial therapies, particularly against ESKAPE pathogens.
3. Bacterial “Social-IQ” and collective behavior
We investigate the molecular basis of bacterial collective intelligence—referred to as the Bacterial Social-IQ Score—by studying how second messengers control quorum sensing, persistence, and biofilm formation. By correlating Social-IQ scores with the presence and function of second-messenger effectors, we aim to uncover new regulatory principles governing bacterial survival.
4. Translational signaling diagnostics
At BSBE, IIT Dharwad, we also pursue LC-MS-based quantitative profiling of second messengers (including c-di-GMP and related molecules) from patient-derived samples. This approach aims to enable early diagnosis and improved understanding of biofilm-associated chronic infections caused by pathogenic bacteria.