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This review summarizes the applications and future prospects of metagenomics in studying antibiotic resistance pollution in marine environments. Results demonstrate that metagenomic analysis enables comprehensive characterization of genetic composition in marine microbial communities, particularly regarding the distribution, diversity, and spatiotemporal dynamics of antibiotic resistance genes (ARGs). The analysis reveals that ARGs are ubiquitously present in marine waters, sediments, and organisms, influenced by multiple factors including pollution sources, environmental conditions, and anthropogenic activities. Metagenomics not only elucidates ARG dissemination mechanisms but also provides scientific foundations for ecological risk assessment and pollution mitigation; however, limitations persist in functional validation and interpretation of environmental driving mechanisms. Future research should leverage multi-omics integration, third-generation sequencing technologies, and advanced bioinformatics tools to enhance the depth and precision of marine ARG pollution studies. Concurrently, integration with big data, machine learning, and artificial intelligence technologies will establish metagenomics as an irreplaceable tool in marine antibiotic resistance research, offering critical insights for combating the global antibiotic resistance crisis.

, authors=Jian-qiao MA, Yi-wei CAI, Gui-ying LI, Tai-cheng AN^*, authorsList=Jian-qiao MA, Yi-wei CAI, Gui-ying LI, Tai-cheng AN, authorCompany=null, correspAuthors=Tai-cheng AN, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1314923058444464861, articleId=1314923056414421723, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=宏基因组学在海洋抗生素耐药性污染研究中的应用和展望, columnId=1234106394006311784, journalTitle=中国环境科学, columnName=环境毒理与健康, runingTitle=null, highlight=null, articleAbstract=

综述了宏基因组学在海洋抗生素耐药性污染研究中的应用与展望．结果表明，通过宏基因组分析，能够全面解析海洋微生物群落的基因组成，特别是抗生素耐药基因（ARGs）在海洋环境中的分布、多样性以及它们在时间和空间上的动态变化．分析发现：ARGs在海洋水体、沉积物和生物体中广泛存在，且受污染源、环境条件和人为活动等多重因素的影响．宏基因组学不仅能够揭示ARGs的传播机制，还可以为生态风险评估和ARGs污染治理提供科学依据，但在功能验证及环境驱动机制解析等方面仍存在局限．未来可进一步利用多组学整合分析、第三代测序技术和生物信息学工具等提升对海洋环境中ARGs污染的研究深度与精度．同时结合大数据、机器学习和人工智能技术，使得宏基因组学在海洋抗生素耐药性污染研究中具有不可替代的作用，以期更好应对全球抗生素耐药性危机．

, authors=马剑桥, 蔡仪威, 李桂英, 安太成^*, authorsList=马剑桥, 蔡仪威, 李桂英, 安太成, authorCompany=null, correspAuthors=安太成, authorNote=, correspAuthorsNote=, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=fUtFv6I9qe2fF3Z/Eb6IXA==, magXml=1UCPXytsDeyZmCR29e/rsQ==, pdfUrl=null, pdf=CAY+xpS3Qg6vjxVEdabf8w==, pdfFileSize=900971, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=FPFwmzDIFWN3yAfMqJzhxg==, mapNumber=null, fund=null)}, authors=[Author(id=1314923059023278818, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1314923056414421723, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=mjq200930@163.com, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1314923059149107940, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1314923056414421723, authorId=1314923059023278818, language=EN, stringName=Jian-qiao MA, firstName=Jian-qiao, middleName=null, lastName=MA, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, Institute of Environmental Health and Pollution Control, School of Environmental Science and Engineering, Guangdong University of Technology, Guangzhou 510006, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1314923059241382629, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1314923056414421723, authorId=1314923059023278818, language=CN, stringName=马剑桥, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=广东工业大学环境科学与工程学院，环境健康与污染控制研究院，广东省环境催化与健康风险控制重点实验室，粤港澳污染物暴露与健康联合实验室，广东 广州 510006, bio={"content":"

马剑桥（2000-），男，汉族，河南郑州人，广东工业大学硕士研究生，主要从事环境抗生素耐药性传播研究．发表论文1篇．mjq200930@163.com.

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马剑桥（2000-），男，汉族，河南郑州人，广东工业大学硕士研究生，主要从事环境抗生素耐药性传播研究．发表论文1篇．mjq200930@163.com.

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