Spatiotemporal Dynamics of Collective Antibiotic Resistance in Microbial Communities

NIH RePORTER · NIH · R35 · $318,252 · view on reporter.nih.gov ↗

Abstract

Project Summary Antibiotic resistance is among the most serious threats to global public health in the 21st century. Bacteria have a remarkable ability to evolve resistance to antibiotics, regardless of their class or mechanism of action. Unfortunately, the pace of drug discovery lags far behind the rapid pace of emerging resistance. As a result, there is an urgent need to understand how bacteria respond to antibiotics on multiple length scales, ranging from the molecular level to the scale of entire microbial communities, in hopes of prolonging the efficacy of current drugs or uncovering new potential therapies. In addition, it is critical to understand how antibiotic resistance determinants evolve and spread in microbial populations. A number of recent studies suggest that the response of cellular communities to antibiotics is often a collective phenomenon, indicating that a detailed characterization of molecular mechanisms—while essential—may not be sufficient to predict large-scale microbial behavior and evolution. In this proposal, we outline an integrated research program aimed at understanding how collective interactions in bacterial communities impact the dynamics and evolution of antibiotic resistance across multiple length scales, ranging from the large-scale behavior of spatially extended communities to the single-cell architecture of biofilms. If successful, our work will uncover new quantitative principles of microbial ecology, provide experimental model systems for testing predictions of evolutionary theory, and clarify the role of community dynamics in shaping the bacterial response to antibiotics. These results will enrich our understanding of how cellular cooperation is disseminated in spatially complex environments, with potential implications for basic evolutionary biology as well as other health-related fields, such as cancer biology, where multi-cellular coordination may underlie disease. In the long term, the findings may even open the door to innovative therapies aimed at destabilizing community structure in bacterial infections.

Key facts

NIH application ID
9987664
Project number
5R35GM124875-04
Recipient
UNIVERSITY OF MICHIGAN AT ANN ARBOR
Principal Investigator
Kevin Wood
Activity code
R35
Funding institute
NIH
Fiscal year
2020
Award amount
$318,252
Award type
5
Project period
2017-09-01 → 2022-07-31