Research in the lab

Decoding Evolutionary Strategies to Control Emerging Pathogens

My team employs an integrative systems biology framework to study two central, interconnected questions critical to public health: (1) how pathogens evolve to evade host defenses and escape our interventions, and (2) how we can leverage this knowledge to develop intervention strategies, ultimately translating this knowledge into first-in-class therapeutics. To this end, my team integrates computational biology and wet experiments , which bridges large-scale computational genomics with experimental validation. By capturing a systems-level view of evolutionary trajectories, my team will uncover the complex adaptive strategies driving pathogenesis, thereby enabling us to anticipate and prepare for potential outbreaks in advance.

PATHOGEN'S EVOLUTION

MAED web : Real-time pathogen evolution surveillance at residue resolution

Pathogens continuously evolve. Each generation writes a new chapter in the ongoing arms race against host defenses and clinical interventions. Understanding these adaptive strategies is essential for predicting emerging threats; however, these strategies remain significantly understudied. To address this critical knowledge gap, my team is establishing the Microbial Adaptive Evolution Detection (MAED) web, which is based on the concept that pathogens’ genomes serve as historical archives, recording successful genetic innovations made for survival. By tracking these evolutionary trajectories, we can capture snapshots of adaptive strategies in emerging pathogens and identify a core subset of genes as potential targets for new intervention strategies. Ultimately, the MAED server will identify early evolutionary signals linked to outbreaks, environmental shifts, and vaccine escape, providing the invaluable data needed to respond to emerging public health challenges promptly.

EXPERIMENTAL CHARACTERIZATION

Characterizing the emerging variants of life-threatening pathogens

MAED has identified critical adaptive evolutionary trajectories in many bacterial pathogens, e.g., Salmonella enterica, Acinetobacter baumannii, and Klebsiella pneumoniae. To confirm the biological relevance of these findings, my team will characterize the phenotypic consequences of the identified variants using multidisciplinary techniques. By unmasking hidden threats and their molecular mechanisms, my team aims to stay one step ahead of emerging pathogens, thereby providing the precise targets needed to develop first-in-class therapeutics and prevent future outbreaks.