Evidence map›Paper›PMID 41354765›Full record

ArticleCommunications biology2025

Age-dependent patterns of the gut microbiome, antibiotic resistome, and pathogenicity in captive koalas (Phascolarctos cinereus).

Hualong Su, Peiyun Han, Hongyu Yan, Chengcheng Wu, Shenzheng Zeng, Peng Zhang, Zhihui Wang, Jian Dong, Mincong Liang, Huang Jing and 7 more

Abstract read
In one paragraph

Article in Communications biology, 2025. 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

17 authors.

Hualong SuStat Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), China-ASEAN Belt and Road Joint Laboratory on Mariculture Technology, Guangdong Provincial Key Laboratory of Aquatic Economic Animals, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.ORCID http://orcid.org/0009-0006-8326-8687
Peiyun HanStat Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), China-ASEAN Belt and Road Joint Laboratory on Mariculture Technology, Guangdong Provincial Key Laboratory of Aquatic Economic Animals, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.
Hongyu YanStat Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), China-ASEAN Belt and Road Joint Laboratory on Mariculture Technology, Guangdong Provincial Key Laboratory of Aquatic Economic Animals, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.
Chengcheng WuStat Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), China-ASEAN Belt and Road Joint Laboratory on Mariculture Technology, Guangdong Provincial Key Laboratory of Aquatic Economic Animals, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.
Shenzheng ZengSchool of Marine Sciences, Sun Yat-sen University, Zhuhai, China.ORCID http://orcid.org/0000-0003-3282-0727
Peng ZhangChimelong Safari Park, Chimelong Group Co., Panyu, Guangzhou, China.
Zhihui WangChimelong Safari Park, Chimelong Group Co., Panyu, Guangzhou, China.
Jian DongChimelong Safari Park, Chimelong Group Co., Panyu, Guangzhou, China.
Mincong LiangSchool of Marine Sciences, Sun Yat-sen University, Zhuhai, China.
Huang JingSchool of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou, China.
Danhua ZhangInstitute of Ecology, College of Urban and Environmental Sciences, Peking University, Beijing, China.
Chen YangInstitute of Ecology, College of Urban and Environmental Sciences, Peking University, Beijing, China.
Naiyu XieState Key Laboratory of Marine Pollution (SKLMP), and Department of Chemistry, City University of Hong Kong, Hong Kong SAR, China.
Xinxin LiuStat Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), China-ASEAN Belt and Road Joint Laboratory on Mariculture Technology, Guangdong Provincial Key Laboratory of Aquatic Economic Animals, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.
Shaoping WengStat Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), China-ASEAN Belt and Road Joint Laboratory on Mariculture Technology, Guangdong Provincial Key Laboratory of Aquatic Economic Animals, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.
Guixin DongChimelong Safari Park, Chimelong Group Co., Panyu, Guangzhou, China. dgx@chimelong.com.ORCID http://orcid.org/0009-0009-0155-7656
Jianguo HeStat Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), China-ASEAN Belt and Road Joint Laboratory on Mariculture Technology, Guangdong Provincial Key Laboratory of Aquatic Economic Animals, School of Life Sciences, Sun Yat-sen University, Guangzhou, China. lsshjg@mail.sysu.edu.cn.ORCID http://orcid.org/0000-0003-2460-7061

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gut microbiome has a profound influence on koalas' health. Yet, the relationships among the gut bacteriome, virome, antibiotic resistome, and pathogenicity throughout different stages in koala's life remain elusive. Here, we presented a metagenome-resolved survey of gut microbiome utilizing 75 fecal samples from three groups of captive koalas. The diversity of bacteriome and virome were age-dependent, predominating in adult koalas. Lytic viruses increased with age as lysogenic viruses and bacterial hosts declined, and virus-to-microbe ratios rose, revealing concomitant age-related shifts in microbial communities, though causality remains unresolved. Antibiotic resistance genes (ARGs) were more prevalent in young koalas, unlike in humans, where they accumulate with age. Two ARG-carrying pathogens, Klebsiella pneumoniae and Escherichia coli, were identified and cultured, with K. pneumoniae and E. coli predominating in young koalas. One age-dependent lytic virus infecting K. pneumoniae only detected in young koalas, and two lysogenic viruses infecting E. coli identified the in young and adult koalas. Analyses showed a positive correlation between mobile genetic elements (MGEs) and virulence factors (VFs), which facilitated the widespread dissemination of VFs and impacted health. Collectively, this study advances the understanding of gut microbiome in health, providing solutions to the treatment and management of captive koalas.

Indexed as

BacteriaDrug Resistance, MicrobialGastrointestinal MicrobiomePhascolarctidaeAge FactorsAnimalsAnti-Bacterial AgentsFecesFemaleKlebsiella pneumoniaeMaleAnti-Bacterial Agents

Identifiers

PMID41354765
PMCPMC12783762

What OpenQuestion holds

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LicenceCC BY
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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.