Effect of Spatial Organization and Population Ratios on the Dynamics of Quorum Sensing and Quorum Quenching in Bacteria Communities

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Date
2024-02-05
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Virginia Tech
Abstract

Quorum sensing (QS) is a type of microbial communication used by bacteria to coordinate their behavior based on population density, regulating complex processes like biofilm formation and virulence, among other behaviors. Quorum quenching (QQ), on the other hand, disrupts this communication, usually by degradation of the QS signaling molecule. QQ offers a potential strategy for controlling bacterial behaviors linked to pathogenicity and biofouling. Despite significant advances in understanding and modeling the spatial-temporal behavior of QS, predictive modeling of QQ remains nascent, with a notable gap in the quantitative assessment of QQ's impact on QS. Here we show quantitative evaluation and characterization of the effect of QQ on QS in agar-based experiments, combined with an experimentally validated computational model. This research utilizes green fluorescence in E. coli MG 1655 as an indicator of QS activation, focusing on the degradation of Acyl-Homoserine Lactone (AHL), a key QS molecule in Gram-negative bacteria linked to pathogenicity, by the AiiA enzyme in engineered AiiA-producing Salmonella Typhimurium 14028. Our findings suggest that QQ more effectively influences QS in spatial configurations of the populations with larger interaction surfaces and shorter diffusion distances. Contrary to our initially held hypothesis, the primary effect of QQ is not a delay in QS onset but rather an attenuation of QS activity, with the area-under-the-curve of fluorescence serving as a quantitative metric. This study also introduces, to the best of our knowledge, one of the first instances of experimentally validated predictive modeling for QQ, applied to agar-based experimental setups. We posit that the quantitative experimental characterization and modeling framework presented in this research will enhance the understanding of bacterial community interactions. Enhanced comprehension of QQ and QS behaviors holds significant promise for advancing practical applications, particularly in mitigating or diminishing undesirable QS-associated activities. This is especially relevant in areas like biofouling, waste treatment, and the reduction of infections and progression of diseases in plants and animals, areas increasingly important as concerns about drug resistance in microbes and food security escalates.

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Keywords
quorum sensing, quorum quenching, fluorescence microscopy, flagellated bacteria, agent-based modeling, computational biology, motility in agar, agar-based quorum sensing exploration
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