Microbes in diverse natural communities communicate via quorum sensing (QS) signals that act as microbial languages. QS-based communications have been reconstructed in two-strain microbiota for promising consortium-based applications. However, investigation and synthesis of multiple QS signals transmission in the QS communication network (QSCN) are less explored. In this study, QS language “interpreter” was proposed and constructed in five Escherichia coli strains to simulate the linear and circular QSCN among natural microbial communities. Specifically, by combining strain-level microscopic and bulk-level macroscopic measurements, we investigate the performances and dynamics of synthetic three-strain QS language “interpreter” ecosystems that are in response to dramatic environmental changes. Results of micro- and macroscopic experiments showed that the existence of complex QS language “interpreter” ecosystems promote the stability maintenance of microbial community. Furthermore, a comprehensive kinetic computational model was developed for the optimization of tunable directed QSCN. Finally, the perspectives of the QSCN for the effective control of microbial communities were discussed and summarized. This study revealed the dynamic control of complex microbial communications, contributing to ecosystem-based engineering and microbiome-based therapeutics.
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