# Metabolite sensing in a polymicrobial infection

> **NIH NIH R01** · GEORGIA INSTITUTE OF TECHNOLOGY · 2021 · $363,788

## Abstract

Project Summary
Many bacterial infections are caused by diverse microbial communities. These polymicrobial infections often
result in higher bacterial burdens and more severe disease than single-species infections, a phenomenon called
“synergy”. While synergy between bacteria has been recognized for over a century, the molecular mechanisms
that cause it have proven difficult to elucidate. My laboratory has focused on synergistic interactions between
the opportunistic oral pathogen Aggregatibacter actinomycetemcomitans (Aa) and the human oral commensal
bacterium Streptococcus gordonii (Sg). In the previous grant cycle, we showed that synergy in Aa/Sg co-
infections is caused by several processes involving Aa's utilization of, and response to, the Sg metabolites L-
lactate and H2O2. The goal of this renewal is two-fold: 1) to determine how the Aa-Sg synergy mechanisms that
we have discovered impact robustness to environmental disturbances and to determine precisely how the spatial
organization of these species impacts such interactions during infection (Specific Aims 1 & 2); and 2) to utilize
high-throughput genomics to define the metabolic interactions that occur between Aa and a range of co-infecting
bacteria (Specific Aim 3).

## Key facts

- **NIH application ID:** 10213693
- **Project number:** 5R01DE020100-08
- **Recipient organization:** GEORGIA INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** Marvin Whiteley
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $363,788
- **Award type:** 5
- **Project period:** 2011-08-01 → 2023-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10213693

## Citation

> US National Institutes of Health, RePORTER application 10213693, Metabolite sensing in a polymicrobial infection (5R01DE020100-08). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10213693. Licensed CC0.

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