Evidence mapPaperPMID 41535683Full record

ArticleNature communications2026

Identification of antimicrobial peptides from ancient gut microbiomes.

Sizhe Chen, Yue Yuan, Yun Wang, Ye Peng, Hein Min Tun, Zhimin Jiang, Yinglei Miao, Sunjae Lee, Xiaole Yin, Xiaotao Shen and 6 more

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Sizhe Chen *Microbiota I-Center (MagIC), Hong Kong SAR, China.ORCID http://orcid.org/0009-0008-0937-4873
Yue Yuan *Department of Geriatrics, Yunnan Geriatric Medical Center, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
Yun WangMicrobiota I-Center (MagIC), Hong Kong SAR, China.
Ye PengMicrobiota I-Center (MagIC), Hong Kong SAR, China.ORCID http://orcid.org/0000-0003-3791-2305
Hein Min TunMicrobiota I-Center (MagIC), Hong Kong SAR, China.ORCID http://orcid.org/0000-0001-7597-5062
Zhimin JiangNational Key Laboratory of Veterinary Public Health and Safety, Key Laboratory for Prevention and Control of Avian Influenza and Other Major Poultry Diseases, Ministry of Agriculture and Rural Affairs, College of Veterinary Medicine, China Agricultural University, Beijing, China.ORCID http://orcid.org/0000-0002-9797-6493
Yinglei MiaoDepartment of Geriatrics, Yunnan Geriatric Medical Center, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.ORCID http://orcid.org/0000-0001-8193-5198
Sunjae LeeSchool of Life Sciences, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea.ORCID http://orcid.org/0000-0002-6428-5936
Xiaole YinSchool of civil and environmental engineering, Nanyang Technological University, Singapore, Singapore.ORCID http://orcid.org/0000-0002-8357-4629
Xiaotao ShenSingapore Phenome Center, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
Orlando DeLeonDepartment of Medicine, Section of Gastroenterology, Hepatology and Nutrition, University of Chicago, Chicago, IL, USA.
Eugene B ChangDepartment of Medicine, Section of Gastroenterology, Hepatology and Nutrition, University of Chicago, Chicago, IL, USA.
Francis Ka Leung ChanMicrobiota I-Center (MagIC), Hong Kong SAR, China.
Yang SunDepartment of Geriatrics, Yunnan Geriatric Medical Center, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China. sunyang_doctor@vip.sina.com.ORCID http://orcid.org/0000-0001-8914-5879
Siew Chien NgMicrobiota I-Center (MagIC), Hong Kong SAR, China. siewchienng@cuhk.edu.hk.ORCID http://orcid.org/0000-0002-6850-4454
Qi SuMicrobiota I-Center (MagIC), Hong Kong SAR, China. qisu@cuhk.edu.hk.ORCID http://orcid.org/0000-0001-9100-387X

Funding

China Association for Science and Technology (China Association for Science & Technology) 2025 Youth Science and Technology Talent Development Program
6 · The paper itself

Abstract

Fecal coprolites preserve ancient microbiomes and are a potential source of extinct but highly efficacious antimicrobial peptides (AMPs). Here, we develop AMPLiT (AMP Lightweight Identification Tool), an efficient tool deployable to portable hardware for AMP screening in metagenomic datasets. AMPLiT demonstrates AUPRC performances of 0.9486 ± 0.0003 and reasonable overall training time of 3200 ± 53 s. By computationally utilizing AMPLiT, we analyze seven ancient human coprolite metagenomes, identifying 160 AMP candidates. Of 40 representative peptides synthesized, 36 (90%) peptides demonstrate measurable antimicrobial activity at 100 μM or less in vitro. Strikingly, approximately two-thirds of these peptides are sourced from Segatella copri, a dominant ancient gut commensal that is conspicuously underrepresented in modern populations, particularly those with Westernized lifestyles. Representative S. copri-derived AMPs exhibit disruptions against membranes of pathogenic bacteria, coupled with low cytotoxicity and hemolytic risk. In vivo, lead peptides demonstrate potent antibacterial and wound-healing efficacy comparable to traditional antibiotics, especially in combating gram-positive pathogens. Our findings highlight the ancient gut microbiomes as sources of novel AMPs, offering valuable insights into the historical role of S. copri in human health and its decline in contemporary populations.

Indexed as

Antimicrobial PeptidesGastrointestinal MicrobiomeAnimalsAnti-Bacterial AgentsFecesHumansMetagenomeMicrobial Sensitivity TestsAnti-Bacterial AgentsAntimicrobial Peptides

Identifiers

PMID41535683
PMCPMC12917264

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.