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PreprintCited by 13Antimicrobial Peptides and ActivitiesMicrobial Natural Products and BiosynthesisAntibiotic Resistance in Bacteria

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Unveiling the Evolution of Antimicrobial Peptides in Gut Microbes via Foundation Model-Powered Framework

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Li, Wenhui, Huang, Baicheng, Guo, Menghao, Zeng, Zihan, Cai, Tao, Feng, Linqing, Zhang, Xinpeng, Guo, Ling, Jiang, Xianyue, Yin, Yanbin, Wang, Ercheng, Huang, Xingxu, Zheng, Jinfang·2025·Cell Reports
DOI 10.1101/2025.01.13.632881

Preprint — published as 10.1016/j.celrep.2025.115773 · Paper page

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Abstract

Antimicrobial resistance poses a growing threat to public health, emphasizing the urgent need for novel therapeutic strategies. Antimicrobial peptides (AMPs), short peptide sequences with diverse mechanisms of action, offer a promising alternative due to their broad-spectrum activity against pathogens. Recent advances in protein language models (PLMs) have revolutionized protein structure prediction and functional annotation, highlighting their potential for AMP discovery and therapeutic development. In this context, we present AMP-SEMiner (Antimicrobial Peptide Structural Evolution Miner), an AI-driven framework designed to identify AMPs from metagenome-assembled genomes (MAGs). By integrating PLMs, structural clustering and evolutionary analysis into the framework, AMP-SEMiner can identify AMPs encoded by small open reading frames (smORFs) and encrypted peptides (EPs), significantly expanding the discovery space. Using this approach, we identified 1,670,600 AMP candidates from diverse habitats. Experimental validation of 29 candidates revealed antimicrobial activity in 18, with 13 surpassing antibiotics in effectiveness. Further analysis of AMPs from human gut microbiomes demonstrated both conserved and adaptive evolutionary strategies, ensuring their functional efficacy in the dynamic gut environment. These findings position AMP-SEMiner as a powerful tool for the discovery and characterization of novel AMPs, with significant potential to drive the development of new antimicrobial therapies.

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Metadata

Authors
Li, W., Huang, B., Guo, M., Zeng, Z., Cai, T., Feng, L., Zhang, X., Guo, L., Jiang, X., Yin, Y., Wang, E., Huang, X., & Zheng, J.
Affiliations
  • Tongji University (CN)
  • Zhejiang Lab (CN)
  • Research Center for Life Sciences Computing, Zhejiang Lab, Hangzhou 311121, Zhejiang, China
  • University of Nebraska–Lincoln (US)
  • ShanghaiTech University (CN)
Corresponding author
  • Wang, Ercheng
  • Huang, Xingxu
  • Zheng, Jinfang
ORCID
Venue
Cell Reports
Publisher
openRxiv
Published
2025-01-13
Volume
44
Issue
6
Pages
115773-115773
ISSN
2211-1247 (ISSN-L)
DOI
10.1101/2025.01.13.632881
OpenAlex
W4410801392
Cited by
13
References
1
Citations by year
2026: 8 · 2025: 5
FWCI
7.12
Type
journal article
Language
en
Open access
Licence
Locations
  • Cell Reports (publishedVersion, cc-by-nc)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
National Natural Science Foundation of China (82450113, 2024SSYS0007)
Topics
  • Life Sciences › Immunology and Microbiology › Microbiology › Antimicrobial Peptides and Activities
  • Life Sciences › Immunology and Microbiology › Applied Microbiology and Biotechnology › Microbial Natural Products and Biosynthesis
  • Health Sciences › Medicine › Microbiology (medical) › Antibiotic Resistance in Bacteria
Keywords
antimicrobial peptides, protein language models, metagenome-assembled genomes, small open reading frames, gut microbiota, antimicrobial resistance, structural clustering, alternative antimicrobial therapy
MeSH terms
Gastrointestinal Microbiome, Antimicrobial Peptides, Anti-Bacterial Agents, Humans, Evolution, Molecular

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