Untargeted metabolomics data for the publication Weiss et al. 2022 "In vitro interaction network of a synthetic gut bacterial community"

This dataset contains the untargeted metabolomics data for the publication Weiss et al. 2022 "In vitro interaction network of a synthetic gut bacterial community". The dataset has also been submitted to MetaboLights repository with ID "MTBLS3535". Please refer to the MetaboLights repository for the most up-to-date datasets. Publication abstract: A key challenge in microbiome research is to predict the functionality of microbial communities based on community membership and (meta)-genomic data. As central microbiota functions are determined by bacterial community networks, it is important to gain insight into the principles that govern bacteria-bacteria interactions. Here, we focused on the growth and metabolic interactions of the Oligo-Mouse-Microbiota (OMM¹²) synthetic bacterial community, which is increasingly used as a model system in gut microbiome research. Using a bottom-up approach, we uncovered the directionality of strain-strain interactions in mono- and pairwise co-culture experiments as well as in community batch culture. Metabolic network reconstruction in combination with metabolomics analysis of bacterial culture supernatants provided insights into the metabolic potential and activity of the individual community members. Thereby, we could show that the OMM¹² interaction network is shaped by both exploitative and interference competition in vitro in nutrient-rich culture media and demonstrate how community structure can be shifted by changing the nutritional environment. In particular, <em>Enterococcus faecalis</em> KB1 was identified as an important driver of community composition by affecting the abundance of several other consortium members in vitro. As a result, this study gives fundamental insight into key drivers and mechanistic basis of the OMM¹² interaction network in vitro, which serves as a knowledge base for future mechanistic in vivo studies.本数据集为Weiss等人2022年发表的论文《合成肠道细菌群落的体外互作网络》配套的非靶向代谢组学（untargeted metabolomics）数据。本数据集已提交至MetaboLights数据库，编号为"MTBLS3535"。请前往MetaboLights数据库获取该数据集的最新版本。 【论文摘要】微生物组研究的核心挑战之一，是基于群落组成与（宏）基因组数据预测微生物群落的功能。由于菌群核心功能由细菌群落网络决定，解析调控细菌间互作的机制原理具有重要意义。本研究聚焦于寡糖小鼠菌群（Oligo-Mouse-Microbiota，OMM¹²）合成细菌群落的生长与代谢互作——该群落目前已被广泛用作肠道微生物组研究的模式系统。本研究采用自下而上的研究策略，解析了单菌株培养、双菌株共培养以及群落批量培养实验中的菌株互作方向性。通过代谢网络重构结合细菌培养上清的代谢组学分析，我们得以解析群落中各成员的代谢潜能与代谢活性。借此，我们证实：在富营养培养基的体外环境中，OMM¹²的群落互作网络由掠夺性竞争与干扰性竞争共同塑造；同时阐明了营养环境改变如何调控群落结构的变化。具体而言，本研究体外实验证实，粪肠球菌（Enterococcus faecalis）KB1可通过影响其他多个群落成员的丰度，成为调控群落组成的关键驱动因子。综上，本研究从体外实验层面解析了OMM¹²群落互作网络的关键驱动因子与分子机制，可为后续开展体内机制研究提供重要的知识基础。