乔建军+郭菲+杨爱东:构建人类肠道菌群群体感应网络
  • 建立一个系统工作流程,包括3个模块(收集、扩展和挖掘)和基于机器学习的4个分类器,对人类肠道菌群的群体感应(QS)通讯系统进行收集挖掘;
  • 基于818个人类肠道微生物,构建了包含28567条去冗余QS条目的人类肠道微生物群体感应(QSHGM)数据库;
  • 借助QSHGM可以预测基于QS的微生物互作,进一步建立了可视化的QS通讯网络(QSCN),并对收集整理的9大类常见的QS进行了分析。
主编推荐语
mildbreeze
群体感应(QS)是微生物之间交流的一种主要方式。Nature Communications近期发表了来自天津大学乔建军团队、中南大学郭菲团队、牛津大学杨爱东团队的合作研究,建立了人类肠道菌群的QS数据库(http://www.qshgm.lbci.net/)和QS通讯网络,为进一步解析肠道菌群互作、构建合成菌群和开发微生态疗法具有重要参考意义。
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Machine learning aided construction of the quorum sensing communication network for human gut microbiota

机器学习辅助构建人类肠道菌群群体感应通信网络

10.1038/s41467-022-30741-6

2022-06-02, Article

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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.

First Authors:
Shengbo Wu

Correspondence Authors:
Aidong Yang,Fei Guo,Jianjun Qiao

All Authors:
Shengbo Wu,Jie Feng,Chunjiang Liu,Hao Wu,Zekai Qiu,Jianjun Ge,Shuyang Sun,Xia Hong,Yukun Li,Xiaona Wang,Aidong Yang,Fei Guo,Jianjun Qiao

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