School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China.
State Key Laboratory of Chemical Engineering, Tianjin University, Tianjin, 300072, China.
Nat Commun. 2022 Jun 2;13(1):3079. doi: 10.1038/s41467-022-30741-6.
Quorum sensing (QS) is a cell-cell communication mechanism that connects members in various microbial systems. Conventionally, a small number of QS entries are collected for specific microbes, which is far from being able to fully depict communication-based complex microbial interactions in human gut microbiota. In this study, we propose a systematic workflow including three modules and the use of machine learning-based classifiers to collect, expand, and mine the QS-related entries. Furthermore, we develop the Quorum Sensing of Human Gut Microbes (QSHGM) database ( http://www.qshgm.lbci.net/ ) including 28,567 redundancy removal entries, to bridge the gap between QS repositories and human gut microbiota. With the help of QSHGM, various communication-based microbial interactions can be searched and a QS communication network (QSCN) is further constructed and analysed for 818 human gut microbes. This work contributes to the establishment of the QSCN which may form one of the key knowledge maps of the human gut microbiota, supporting future applications such as new manipulations to synthetic microbiota and potential therapies to gut diseases.
群体感应 (QS) 是一种细胞间通讯机制，连接着各种微生物系统中的成员。传统上，只收集了少数特定微生物的 QS 条目，这远远不能充分描述人类肠道微生物群中基于通信的复杂微生物相互作用。在这项研究中，我们提出了一个系统工作流程，包括三个模块，并使用基于机器学习的分类器来收集、扩展和挖掘与 QS 相关的条目。此外，我们开发了人类肠道微生物群体感应 (QSHGM) 数据库 (http://www.qshgm.lbci.net/)，其中包括 28567 个冗余去除条目，以弥合 QS 存储库和人类肠道微生物群之间的差距。借助 QSHGM，可以搜索各种基于通信的微生物相互作用，并进一步构建和分析 818 个人类肠道微生物的 QS 通信网络 (QSCN)。这项工作有助于建立 QSCN，它可能成为人类肠道微生物群的关键知识图谱之一，支持未来的应用，如新的对合成微生物群的操作和对肠道疾病的潜在治疗。
