Researchers from the Department of Mathematics, University of Utah, have presented a new approach on shaping bacterial quorum sensing (QS). The authors suggest the use of feedback loops to interpret the integrated signals by actively shifting the sensitivity in different pathways. They applied slow/fast analysis to decrease a single-cell model to a planar dynamical system including the concentrations of protein LuxU and a small non-coding RNA. It is showed that, in certain parameters, a feedback loop can lead to a bistable QS reaction. Also, a reduction of a population model to an effective single-cell model could be achieved by combining the slow/fast analysis with a contraction mapping theorem. The authors concluded that weight control mechanism allows bacteria to have a greater sensitivity of their social and physical environment.

Quorum sensing?

- The first debate came in the late 1960s and early 1970s: researchers reported that luminescence in Vibrio fischeri and Vibrio harveyi and genetic competence in Streptococcus pneumoniae needed production of extracellular molecules;

- Generally ignored for the following 10–20 years;

- Form of intercellular communication, which involves self-produced extracellular chemical signals, accumulating in a local environment to levels that are required to activate transcription of specific genes;

- Production and detection of diffusive signaling molecules, e.g. HSL;

- Allows microorganisms to track their cell density in order to regulate group behavior: e.g. virulence factors as biofilm formation.

Whiteley M, Diggle SP, Greenberg EP. Progress in and promise of bacterial quorum sensing research. Nature. 2017. 15;551(7680):313-320. doi: 10.1038/nature24624.

Abstract

Bacterial quorum sensing (QS) is a form of intercellular communication that relies on the production and detection of diffusive signaling molecules called autoinducers. Such a mechanism allows the bacteria to track their cell density in order to regulate group behavior, such as biofilm formation and bioluminescence. In a number of bacterial QS systems, including V. harveyi, multiple signaling pathways are integrated into a single phosphorylation–dephosphorylation cycle. In this paper, we propose a weight control mechanism, in which QS uses feedback loops to ‘decode’ the integrated signals by actively changing the sensitivity in different pathways. We first use a slow/fast analysis to reduce a single-cell model to a planar dynamical system involving the concentrations of phosphorylated signaling protein LuxU and a small non-coding RNA. In addition to identifying the weight control mechanism, we show that adding a feedback loop can lead to a bistable QS response in certain parameter regimes. We then combine the slow/fast analysis with a contraction mapping theorem in order to reduce a population model to an effective single-cell model, and show how the weight control mechanism allows bacteria to have a finer discrimination of their social and physical environment. 

Reference: Fan G, Bressloff PC. Modeling the Role of Feedback in the Adaptive Response of Bacterial Quorum Sensing. Bulletin of Mathematical Biology, doi.org/10.1007/s11538-019-00570-8.

https://link.springer.com/article/10.1007/s11538-019-00570-8