Quorum sensing (QS) enables bacterial communication and collective behavior in response to self-secreted signaling molecules. Unlocking its genetic regulation will provide insight towards understanding its influence on pathogenesis, formation of biofilms, and many other phenotypes. There are few datasets available that link QS-mediated gene expression to its regulatory components and even fewer mathematical models that incorporate known mechanistic detail. By integrating these data with annotated sequence information, mathematical inferences can be pieced together that shed light on regulatory structure. A first principles model, developed here for the E. coli QS system, builds on known mechanistic detail and is used to develop a working model of LuxS-regulated (Lsr) activity. That is, our model is meant to discriminate among hypothetical mechanisms governing lsr transcriptional regulation. Our simulations are in qualitative agreement with experimentally observed data. Importantly, our results point to the importance of transcriptional regulator, LsrR, cycling on genetic control. We also found several experimental observations in E. coli and homologous systems that were not explained by current mechanistic understanding. For example, by comparing simulations with reports of the integrating host factor in Aggrigatibacter actinomycetemcomitans, we conclude that additional transcriptional components are likely involved. An iterative process of simulation and experiment, therefore, is needed to inform new experiments and incorporate new model detail, the benefit of which will more rapidly validate mechanistic understanding.
Keywords: LsrR; Mathematical model; autoinducer-2 quorum sensing; lsr intergenic region; lsr operon; quorum sensing.