Microbial Genomics and Systems Biology

Microbial Genomics

We develop and apply next-generation genomic methods to study the molecular basis of microbial physiology (Galagan 2014, Nat Gen Rev). We have pioneered the use of ChIP-Seq combined with RNA-Seq to comprehensively map regulatory interactions in microbes (Jaini 2014, Molecular Genetics of Mycobacteria). Our results have revealed a previously unrecognized complexity in the behavior of bacterial transcription factor binding (Galagan 2013, Curr Topics in Microbiology and Immunology, Mejia-Almonte 2020 Nat Rev Gen). We are studying this unexpected behavior in different microbes through the develop of novel experimental, genomics, and computational methods. We also apply genomic screening for the development of novel biosensors.

Regulatory Networks

While comprehensive regulatory network maps have been created for multiple eukaryotic organisms, similar efforts in bacteria and other microbes have lagged behind. Remarkably, even for Escherichia coli - the most widely used and studied model organism in biology - a comprehensive regulatory map does not exist. We generated the first comprehensive regulatory network map for Mycobacterium tuberculosis (Galagan 2013 Nature) available at TBDB.bu.edu. We are now collaborating with the Collado-Vides group at RegulonDB and the Wade lab at Wadsworth to experimentally map the regulatory network of E. coli. We also collaborate with the Bel-Pedersen lab at TAMU to study the clock-controlled regulatory network in Neurospora crassa.

Biological Discovery

We use high-throughput genomics and network mapping as a platform for biological discovery. Through an iterative process of large-scale biology, computational analysis, hypothesis generation, and experimental validation, we seek to better understand the molecular basis of microbial physiology. We apply these approaches to studies ranging from basic processes in microbial evolution (McGuire 2012 BMC Genomics), the emergence of drug resistance in pathogenic bacteria (Galagan 2014, Nat Gen Rev), and the mechanisms of information processing in molecular networks.

We have a particular interest in understanding how complex behavior arises from the coordination of multiple regulators across diverse metabolic processes. Through a systems level approach, we identify biological programs not visible when studying processes in isolation. This approach, as one example, resolved a decades old mystery regarding acid resistance in E. coli (Aquino 2017 BMC Sys Biol).