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<p>Gut microbiota exert significant influences on host physiology through bioactive molecules such as indole derivatives. The characteristic aromatic heterocycle substructure shared among various indole derivatives is intrinsically associated with the activation of aryl hydrocarbon receptor (AhR), suggesting a potential structure-activity relationship (SAR). Here, we develop a substructure–activity relationship mass spectrometry pipeline aiming at elucidating SAR information encompassed within mass spectrometry data, further applying it to identify the unknown gut microbiome-derived, indole-like derivatives with AhR agonistic potential. A total of 22 metabolites exhibiting activity-related substructures are identified, four of which were previously uncharacterized. Notably, the discovered sulfonated and methylthiolated compounds represent two previously underexplored microbiome-mediated reactions. Subsequent assays validate their AhR agonistic activities and downstream immune regulatory effects in male mice. Overall, this study presents an exploratory framework for MS data mining focusing on activity-guided substructure prioritization, enabling the discovery of bioactive microbiota-derived molecules and distinct microbiome-mediated reactions.</p>

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Activity-guided substructure prioritization accelerates discovery of gut microbiota-derived immune-regulating metabolites

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月26日

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  • Haoduo Zhao,
  • Liang Chi,
  • Zhenfa Zhang,
  • Yun-Chung Hsiao,
  • Chih-Wei Liu,
  • Yifei Yang,
  • R. Balfour Sartor,
  • Kun Lu

摘要

Gut microbiota exert significant influences on host physiology through bioactive molecules such as indole derivatives. The characteristic aromatic heterocycle substructure shared among various indole derivatives is intrinsically associated with the activation of aryl hydrocarbon receptor (AhR), suggesting a potential structure-activity relationship (SAR). Here, we develop a substructure–activity relationship mass spectrometry pipeline aiming at elucidating SAR information encompassed within mass spectrometry data, further applying it to identify the unknown gut microbiome-derived, indole-like derivatives with AhR agonistic potential. A total of 22 metabolites exhibiting activity-related substructures are identified, four of which were previously uncharacterized. Notably, the discovered sulfonated and methylthiolated compounds represent two previously underexplored microbiome-mediated reactions. Subsequent assays validate their AhR agonistic activities and downstream immune regulatory effects in male mice. Overall, this study presents an exploratory framework for MS data mining focusing on activity-guided substructure prioritization, enabling the discovery of bioactive microbiota-derived molecules and distinct microbiome-mediated reactions.