The Role of Specialized Metabolites in Microbe-Microbe Interactions

We are using state-of-the-art mass spectrometry techniques together with natural products based workflows to identify and characterize specialized metabolites produced by microbes isolated from human microbiome communities. We are particularly interested in the functional roles of metabolites derived from opportunistic pathogens in the interactions between microbes and their host environments. This work is funded by an NIH K01 and the ALSAM Foundation.


Our high school and undergraduate research program introduces junior investigators to the techniques involved in natural product investigations by focusing on their research on soil bacteria. They investigate co-cultures of Streptomyces spp. to identify active compounds against the ESKAPE pathogens.

Genome-wide Metabolomics of Pseudomonas aeruginosa

P. aeruginosa is a common environmental gram-negative bacterium responsible for serious infections of immunocompromised persons including those with cystic fibrosis or traumatic burns. It is an incredibly well-studied opportunistic pathogen and is a model system to understand antibiotic resistance and microbial signaling pathways. However, over 50% of the P. aerunigosa genomes encodes for proteins of unknown function. Therefore, we are using genome-wide metabolomics of P. aeruginosa transposon libraries to generate and test hypotheses to elucidate the function of genes of unknown function.

Elucidating the Effect of Treatment on the Microbiome

The composition of an individual's microbiome is shaped by constant selective pressures including interactions between community members, clinical treatment, host response, and physiological changes throughout disease progression. The overall goal of this project is to elucidate the effect of exogenous pressures on the functional metabolic output of microbiome communities. We use in vitro cultivation systems to recapitulate microbiome communities and subject them to treatment that reflects clinical therapy. By measuring both the compositional as well as functional changes of this model microbiome community, we create a network of interactions that define microbiome dysbiosis. This work is funded by a Therapeutic Innovation Grant provided by the ALSAM Foundation.