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通过人工智能辅助流程鉴定肠道微生物胆汁酸代谢酶

Identification of gut microbial bile acid metabolic enzymes via an AI-assisted pipeline.

作者信息

Ding Yong, Luo Xi, Guo Jiasheng, Xing Baiying, Lin Haoyu, Ma Haohan, Wang Yicun, Li Meng, Ye Chuan, Yan Sen, Lin Kangjie, Zhang Jinxin, Zhuo Yingying, Nie Qixing, Yang Donghui, Zhang Zhipeng, Pang Yanli, Wang Kai, Ma Ming, Lai Luhua, Jiang Changtao

机构信息

Department of Immunology, School of Basic Medical Sciences, State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing 100191, China; NHC Key Laboratory of Medical Immunology, Peking University, Beijing, China.

Department of Physiology and Pathophysiology, Center for Obesity and Metabolic Disease Research, School of Basic Medical Sciences, Peking University, Beijing 100191, China.

出版信息

Cell. 2025 Jul 31. doi: 10.1016/j.cell.2025.07.017.

DOI:10.1016/j.cell.2025.07.017
PMID:40780197
Abstract

The modifications of bile acids (BAs) are fundamental to their role in host physiology and pathology. Identifying their synthetases is crucial for uncovering the diversity of BAs and developing targeted interventions, yet it remains a significant challenge. To address this hurdle, we developed an artificial intelligence (AI)-assisted workflow, bile acid enzyme announcer unit tool (BEAUT), which predicted over 600,000 candidate BA metabolic enzymes that we compiled into the human generalized microbial BA metabolic enzyme (HGBME) database (https://beaut.bjmu.edu.cn). We identified a series of uncharacterized BA enzymes, including monoacid acylated BA hydrolase (MABH) and 3-acetoDCA synthetase (ADS). Notably, ADS can produce an unreported skeleton BA, 3-acetoDCA, with a carbon-carbon bond extension. After determining its bacterial source and catalytic mechanism, we found that 3-acetoDCA is widely distributed among populations and regulates the microbial interactions in the gut. In conclusion, our work offers alternative insights into the relationship between microbial BAs and the host from an enzymatic perspective.

摘要

胆汁酸(BAs)的修饰对于其在宿主生理和病理过程中的作用至关重要。识别它们的合成酶对于揭示胆汁酸的多样性和开发靶向干预措施至关重要,但这仍然是一项重大挑战。为了克服这一障碍,我们开发了一种人工智能(AI)辅助工作流程,即胆汁酸酶宣告单元工具(BEAUT),它预测了超过60万种候选BA代谢酶,我们将其汇编成人类广义微生物BA代谢酶(HGBME)数据库(https://beaut.bjmu.edu.cn)。我们鉴定出了一系列未被表征的BA酶,包括单酸酰化BA水解酶(MABH)和3-乙酰去氧胆酸合成酶(ADS)。值得注意的是,ADS可以产生一种未报道的骨架BA,即3-乙酰去氧胆酸,其具有碳-碳键延伸。在确定其细菌来源和催化机制后,我们发现3-乙酰去氧胆酸在人群中广泛分布,并调节肠道中的微生物相互作用。总之,我们的工作从酶学角度为微生物胆汁酸与宿主之间的关系提供了新的见解。

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