Microbial consortia have been utilised for centuries to produce fermented foods and have great potential in applications such as therapeutics, biomaterials, fertilisers, and biobased production. Working together, microbes become specialized and perform complex tasks more efficiently, strengthening both cooperation and stability of the microbial community. However, imbalanced proportions of microbial community members can lead to unoptimized and diminished yields in biotechnology. To address this, we developed a burden-aware RNA-based multicellular feedback control system that stabilises and tunes coculture compositions. The system consists of three modules: a quorum sensing-based communication module to provide information about the densities of cocultured strains, an RNA-based comparator module to compare the ratio of densities of both strains to a pre-set desired ratio, and a customisable growth module that relies either on heterologous gene expression or on CRISPRi knockdowns to tune growth rates. We demonstrated that heterologous expression burden could be used to stabilise composition in a two-member E. coli coculture. This is the first coculture composition controller that does not rely on toxins or syntrophy for growth regulation and uses RNA sequestration to stabilise and control coculture composition. This work provides a fundamental basis to explore burden-aware multicellular feedback control strategies for robust stabilisation of synthetic community compositions.

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Paradoxical signaling occurs when the same signaling molecule can trigger antagonistic cell functions. For example, T-Cells secret cytokine IL-2 which promotes T-Cell proliferation and also affects cell death. It has been shown that cells with this signaling capability have bi-stable population dynamics and can achieve identical levels of population homeostasis independent of initial cell concentrations. These capabilities are desirable in the context of synthetic population control circuits designed for application in therapeutic treatment of various diseases. It thus becomes important to understand the dependence of the cell system on the intracellular paradoxical components and to develop accurate models to provide insight into optimal design characteristics. Here, we create a model that integrates three IL-2 driven intracellular mechanisms that trigger 1) T-cell proliferation 2) T-cell apoptosis and 3) IL-2 production. Using this model, we are able to explore the internal mechanisms necessary for paradoxical signaling in T-Cells. It was shown that the intracellular mechanisms considered were sufficient to produce population dynamic characteristics of paradoxical signaling consistent with published systems level models and data. Furthermore, analysis of parameters revealed dependency of population homeostatic stability on the production and activation of the specific intracellular proteins considered.