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mBio. 2010 Oct 12;1(4). pii: e00202-10. doi: 10.1128/mBio.00202-10.

Probing prokaryotic social behaviors with bacterial "lobster traps".

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Department of Chemistry and Biochemistry, The University of Texas at Austin, Austin, Texas, USA.


Bacteria are social organisms that display distinct behaviors/phenotypes when present in groups. These behaviors include the abilities to construct antibiotic-resistant sessile biofilm communities and to communicate with small signaling molecules (quorum sensing [QS]). Our understanding of biofilms and QS arises primarily from in vitro studies of bacterial communities containing large numbers of cells, often greater than 10(8) bacteria; however, in nature, bacteria often reside in dense clusters (aggregates) consisting of significantly fewer cells. Indeed, bacterial clusters containing 10(1) to 10(5) cells are important for transmission of many bacterial pathogens. Here, we describe a versatile strategy for conducting mechanistic studies to interrogate the molecular processes controlling antibiotic resistance and QS-mediated virulence factor production in high-density bacterial clusters. This strategy involves enclosing a single bacterium within three-dimensional picoliter-scale microcavities (referred to as bacterial "lobster traps") defined by walls that are permeable to nutrients, waste products, and other bioactive small molecules. Within these traps, bacteria divide normally into extremely dense (10(12) cells/ml) clonal populations with final population sizes similar to that observed in naturally occurring bacterial clusters. Using these traps, we provide strong evidence that within low-cell-number/high-density bacterial clusters, QS is modulated not only by bacterial density but also by population size and flow rate of the surrounding medium. We also demonstrate that antibiotic resistance develops as cell density increases, with as few as ~150 confined bacteria exhibiting an antibiotic-resistant phenotype similar to biofilm bacteria. Together, these findings provide key insights into clinically relevant phenotypes in low-cell-number/high-density bacterial populations.

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