Evidence map›Paper›PMID 41803682›Full record

ArticleBMC microbiology2026

Microbial succession accompanies increased antibiotic resistance risk during grass carp (Ctenopharyngodon idella) spoilage under ambient household conditions.

Zehan Shen, Zuowu Zhang, Jingrong Gao, Jiao Chen, Qiuxiang Xu, Dongyi Li, Li Zeng, Dengmiao Cheng, Kai Wang, Jiayu Zhang and 1 more

Abstract read
In one paragraph

Article in BMC microbiology, 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
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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

11 authors.

Zehan Shen *Research Center for Eco-environmental Engineering, Dongguan University of Technology, Dongguan, 523808, China.
Zuowu Zhang *Research Center for Eco-environmental Engineering, Dongguan University of Technology, Dongguan, 523808, China.
Jingrong GaoSchool of Food and Pharmacy, Zhejiang Ocean University, Zhejiang, 316022, China.
Jiao ChenResearch Center for Eco-environmental Engineering, Dongguan University of Technology, Dongguan, 523808, China.
Qiuxiang XuResearch Center for Eco-environmental Engineering, Dongguan University of Technology, Dongguan, 523808, China.
Dongyi LiResearch Center for Eco-environmental Engineering, Dongguan University of Technology, Dongguan, 523808, China.
Li ZengResearch Center for Eco-environmental Engineering, Dongguan University of Technology, Dongguan, 523808, China.
Dengmiao ChengResearch Center for Eco-environmental Engineering, Dongguan University of Technology, Dongguan, 523808, China.
Kai WangResearch Center for Eco-environmental Engineering, Dongguan University of Technology, Dongguan, 523808, China.
Jiayu ZhangResearch Center for Eco-environmental Engineering, Dongguan University of Technology, Dongguan, 523808, China. zhangjiayu@dgut.edu.cn.
Jonathan W C WongResearch Center for Eco-environmental Engineering, Dongguan University of Technology, Dongguan, 523808, China. jwcwong@dgut.edu.cn.

Funding

Dongguan University of Technology Top Talent Professor Start Up Fund 221110133Guangdong Basic and Applied Basic Research Foundation 2024A1515140076National Natural Science Foundation of China 22206107Program for Guangdong Introducing Innovative and Entrepreneurial Teams of China 2023ZT10L060
6 · The paper itself

Abstract

Understanding fish spoilage mechanisms under household storage conditions is critical for food safety in regions with limited cold chain infrastructure, where ambient storage remains common practice. This study investigated the spoilage dynamics, microbial succession, and antibiotic resistance gene (ARG) proliferation in grass carp stored under simulated household conditions at 13.0 ± 3.4 °C using three packaging scenarios. The biogenic amine index (BAI) of fish exceeded 50 mg/kg within 16 h, marking early spoilage onset. After 64 h, K-values surpassed 60%, TVB-N exceeded the safety limit of 20 mg/100 g, and BAI reached over 220 mg/kg, indicating advanced spoilage. 16S rRNA amplicon sequencing demonstrated dramatic microbial community shifts from Cyanobacteriota-dominated fresh samples to Pseudomonadota-dominated spoilage communities, with Aeromonas emerging as the primary specific spoilage organism (SSO), increasing from 0.001% to 67.2% at 64 h. Pathogen abundance escalated from 0.06% to 72.2% in muscle tissues, posing substantial food safety risks. Distinct microbial community structures were observed across tissue types (muscle vs. gut) and packaging treatments, with storage time exerting the strongest selective pressure on community composition. Metagenomic analysis revealed progressive ARG enrichment, with surface samples exhibiting 2.6-fold higher total ARG abundance and 3.8-fold greater ARG type richness compared to the fresh gut baseline by 24 ~ 64 h. Rapid ARG enrichment was detected during early spoilage (24 h), representing a critical food safety concern. Notably, carbapenem resistance genes (e.g., OXA-12, cphA6) were substantially enriched, underscoring the high risk posed by these clinically relevant resistance genes. These findings demonstrate that grass carp stored under ambient household conditions maintain acceptable quality for < 16 h, necessitating immediate consumption or cold chain implementation to ensure food safety and minimize ARG dissemination.

Indexed as

BacteriaCarpsDrug Resistance, BacterialDrug Resistance, MicrobialMicrobiotaAnimalsAnti-Bacterial AgentsBiogenic AminesFood MicrobiologyFood PackagingFood SafetyFood StorageRNA, Ribosomal, 16SAnti-Bacterial AgentsBiogenic AminesRNA, Ribosomal, 16SAntibiotic resistance geneFish spoilageGrass carpMicrobial communitySpecific spoilage organism

Identifiers

PMID41803682
PMCPMC13085627

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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.