Evidence map›Paper›PMID 39953051›Full record

ArticleNPJ biofilms and microbiomes2025

Comparative study of gut microbiota reveals the adaptive strategies of gibbons living in suboptimal habitats.

Li-Ying Lan, Tai-Cong Liu, Shao-Ming Gao, Qi Li, Li Yang, Han-Lan Fei, Xu-Kai Zhong, Yu-Xin Wang, Chang-Yue Zhu, Christoph Abel and 3 more

Abstract readComparative Study
In one paragraph

Article in NPJ biofilms and microbiomes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

13 authors.

Li-Ying LanSchool of Life Sciences, Sun Yat-sen University, Guangzhou, P.R. China.ORCID http://orcid.org/0000-0002-9017-5335
Tai-Cong LiuSchool of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou, P.R. China.ORCID http://orcid.org/0000-0003-4010-6259
Shao-Ming GaoSchool of Life Sciences, Sun Yat-sen University, Guangzhou, P.R. China.ORCID http://orcid.org/0000-0001-7219-6485
Qi LiSchool of Life Sciences, Sun Yat-sen University, Guangzhou, P.R. China.ORCID http://orcid.org/0000-0002-0320-731X
Li YangSchool of Life Sciences, Sun Yat-sen University, Guangzhou, P.R. China.ORCID http://orcid.org/0000-0003-1654-4806
Han-Lan FeiCollege of Life Sciences, China West Normal University, Nanchong, P.R. China.ORCID http://orcid.org/0000-0001-6945-5829
Xu-Kai ZhongSchool of Life Sciences, Sun Yat-sen University, Guangzhou, P.R. China.
Yu-Xin WangSchool of Life Sciences, Sun Yat-sen University, Guangzhou, P.R. China.
Chang-Yue ZhuSchool of Life Sciences, Sun Yat-sen University, Guangzhou, P.R. China.
Christoph AbelBehavioral Ecology and Sociobiology Unit, German Primate Center, Leibniz Institute for Primate Research, Göttingen, Germany.ORCID http://orcid.org/0000-0002-0539-1739
Peter M KappelerBehavioral Ecology and Sociobiology Unit, German Primate Center, Leibniz Institute for Primate Research, Göttingen, Germany.ORCID http://orcid.org/0000-0002-4801-487X
Li-Nan HuangSchool of Life Sciences, Sun Yat-sen University, Guangzhou, P.R. China. eseshln@mail.sysu.edu.cn.ORCID http://orcid.org/0000-0002-4881-7920
Peng-Fei FanSchool of Life Sciences, Sun Yat-sen University, Guangzhou, P.R. China. fanpf@mail.sysu.edu.cn.ORCID http://orcid.org/0000-0003-4747-5727

Funding

National Natural Science Foundation of China (National Science Foundation of China) 32201269
6 · The paper itself

Abstract

Wild animals face numerous challenges in less ideal habitats, including the lack of food as well as changes in diet. Understanding how the gut microbiomes of wild animals adapt to changes in food resources within suboptimal habitats is critical for their survival. Therefore, we conducted a longitudinal sampling of three gibbon species living in high-quality (Nomascus hainanus) and suboptimal (Nomascus concolor and Hoolock tianxing) habitats to address the dynamics of gut microbiome assembly over one year. The three gibbon species exhibited significantly different gut microbial diversity and composition. N. hainanus showed the lowest alpha diversity and highest nestedness, suggesting a more specialized and potentially stable microbial community in terms of composition, while H. tianxing displayed high species turnover and low nestedness, reflecting a more dynamic microbial ecosystem, which may indicate greater sensitivity to environmental changes or a flexible response to habitat variability. The gut microbial community of N. concolor was influenced by homogeneous selection in the deterministic process, primarily driven by Prevotellaceae. In contrast, the gut microbial communities of H. tianxing and N. hainanus were influenced by dispersal limitation in the stochastic process, driven by Acholeplasmataceae and Fibrobacterota, respectively. Further, the microbial response patterns to leaf feeding in N. hainanus differed from those of the other two gibbon species. In conclusion, this first cross-species comparative study provides initial insights into the different ecological adaptive strategies of gut microbiomes from a point of community assembly, which could contribute to the long-term conservation of wild primates. In this study, we conducted longitudinal sampling of three gibbon species living in high-quality (Nomascus hainanus) and suboptimal (Nomascus concolor and Hoolock tianxing) habitats to address the dynamics of gut microbiome (composition, alpha diversity, beta diversity and assembly process) over one year.

Indexed as

BacteriaEcosystemGastrointestinal MicrobiomeHylobatesAdaptation, PhysiologicalAnimalsBiodiversityFecesPhylogenyRNA, Ribosomal, 16SRNA, Ribosomal, 16S

Identifiers

PMID39953051
PMCPMC11828964

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.