Deciphering and Constructing the Quorum Sensing Language “Interpreter” Ecosystem for Microbial Community

Author:

Wu Shengbo1,Zhang Hong1,Zhou Yongsheng1,Xu Chengyang1,Yuan Boxin1,Wang Haijiao1,Chen Danlei1,Liu Chunjiang1,Caiyin Qinggele1,Wu Hao1,Yang Aidong2,Zhao Kun3,Qiao Jianjun1

Affiliation:

1. Tianjin University

2. University of Oxford

3. University of Electronic Science and Technology of China

Abstract

Abstract Background Microbes in diverse natural communities communicate via quorum sensing (QS) signals that act as microbial languages. However, earlier work on the investigation on microbial interactions and systematic stability mostly based on the diverse modelling-assistant ecological pairwise interactions (such as cooperation and competition) or metabolite-based interactions (such as division of labor and auxotrophies). The investigation and synthesis of multiple QS signals transmission in the QS communication network (QSCN) are less explored. The aim of this work is to decipher and construct another type of microbial interactions, i.e., QSCN, in the complex environment by considering cell heterogeneity, environmental interference and other factors, so as to provide the basis and guidance for the more practical applications of gut microbiota composed of different strains. Results In this study, to deepen the understanding of QS-based complex interactions, we firstly constructed and analyzed the directed QSCN including nine QS systems for a validated stable gut microbiome. Then, 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 single-cell 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. Data analysis and experimental results 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. Conclusion Microbial QS language “interpreter” is an interesting and broad conceptual advance for the construction of the large-scale microbial communities. The dynamic characteristics and transmission law of QS "interpreter" in microbial communication studied in this paper is an important basis for understanding microbial social communications. The findings in this study will help to optimize QS-based consortia and benefit their potential applications in ecosystem-based engineering and microbiome-based therapeutics.

Publisher

Research Square Platform LLC

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