(597j) Invited Talk: Correlating microbiota structure with the exo-metabolome
AIChE Annual Meeting
2022
2022 Annual Meeting
Food, Pharmaceutical & Bioengineering Division
Systems Biology for Engineering Microbes
Thursday, November 17, 2022 - 9:48am to 10:06am
A soup of biomolecules and metabolites characterizes microbial niches âthe exon-metabolome. The exon-metabolome powerfully regulates the physiology of the native bacterial species in an existing niche, but perhaps more crucially, it can determine the transport properties of invading foreign species. The ability to influence cell transport lends defensive functions to specific prominent metabolites, enabling them to shape the microbiota structure. I will discuss our work that reveals the molecular mechanisms by which one key component of the exon-metabolome, indole, selectively controls bacterial access to niches rich in indole. We find that the metabolite attracts one type of bacteria while repelling another from the niche. It does so by activating major bacterial receptors in a signal transduction network that biases cell motility. In Escherichia coli, we show that the activation of one type of receptor causes the cell to swim toward indole-rich niches. In contrast, activating a different receptor causes the cell to swim away from those niches. Net transport outcomes are dominated by the kinetics of the biphasic receptor activation [1]. Next, I will discuss our FRET-based experiments in live cells that helped identify molecular determinants in the receptors of this unique biphasic behavior. Biophysical experiments on single cells further revealed an additional mode of action: indole influences bacterial transport by controlling the energy source that powers motility [2]. By differentially affecting cell energetics, which modulates growth, indoleâs impact on communities appears to extend beyond transport. This work offers a basis for understanding the complex functions of metabolites in community formation and subsequent growth. The data is expected to guide models for predicting microbiota structure from metabolite profiles and designing novel communities.
[1] Yang et al, PNAS, 2020
[2] Gupta et al, PNAS Nexus, 2022