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. 2022 Jun 2;13:3079. doi: 10.1038/s41467-022-30741-6

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© The Author(s) 2022

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 5 — a QSCN for 818 human gut microbes based on nine languages (AHLs, DSFs, HAQs, CAI-1, AIPs, Dialkylresorcinols, Photopyrones, indole, and AI-2). Generally recognized intraspecies and interspecies languages are marked in blue and red, respectively. Note that the network diagram was generated using EVenn⁶⁴. b Microbial genus distribution for six typical QS languages, i.e., AHLs, CAI-1, HAQs, DSFs, Indole, and AI-2. c Hierarchical clustering of nine QS languages found in 210 human gut microbial genus. The constructions are classified into ten genus-level clusters based on their phyla and taxonomy. Microbial genus from Firmicutes is colored in blue; Actinobacteria, cyan; Proteobacteria, green; Bacteroidetes, yellowish. Heatmap on the outermost layer indicates QS languages distribution in each cluster, existence is colored in blue; no existence, gray. Source data are provided as a Source Data file.