Application and perspective to metagenomics in the pollution of marine antibiotic resistance

MA Jian-qiao; CAI Yi-wei; LI Gui-ying; AN Tai-cheng

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China Environmental Science ›› 2026, Vol. 46 ›› Issue (3) : 1673-1681.

Environmental Toxicology and Environmental Health

Application and perspective to metagenomics in the pollution of marine antibiotic resistance

MA Jian-qiao, CAI Yi-wei, LI Gui-ying, AN Tai-cheng

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Abstract

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.

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metagenomics / marine environment / antibiotic resistance / transmission mechanism / environmental driving factors

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MA Jian-qiao, CAI Yi-wei, LI Gui-ying, AN Tai-cheng. Application and perspective to metagenomics in the pollution of marine antibiotic resistance[J]. China Environmental Science. 2026, 46(3): 1673-1681

References

[1] Cai Y, Sun T, Li G, et al. Traditional and emerging water disinfection technologies challenging the control of antibiotic-resistant bacteria and antibiotic resistance genes [J]. ACS ES&T Engineering, 2021,1(7): 1046-1064.
[2] Cai Y, Liu J, Li G, et al. Formation mechanisms of viable but nonculturable bacteria through induction by light-based disinfection and their antibiotic resistance gene transfer risk: A review [J]. Critical Reviews in Environmental Science and Technology, 2022,52(20): 3651-3688.
[3] Garcillán-Barcia Maria P, de la Cruz F, Rocha Eduardo P C. The extended mobility of plasmids [J]. Nucleic Acids Research, 2025, 53(14):gkaf652.
[4] 王艺霓,蔡仪威,孙彤,等.海产养殖水体中复杂组分致光催化剂杀菌失活的机理研究 [J]. 生态环境学报, 2025,34(1):89-98. Wang Y N, Cai Y W, Sun T, et al. The deactivation mechanism of photocatalyst inactivation of bacteria caused by complex components in mariculture water [J]. Ecology and Environmental Sciences, 2025, 34(1):89-98.
[5] Chen C Q, Zheng L, Zhou J L, et al. Persistence and risk of antibiotic residues and antibiotic resistance genes in major mariculture sites in Southeast China [J]. Science of The Total Environment, 2017,580: 1175-1184.
[6] Yang H, Liu R, Liu H, et al. Evidence for long-term anthropogenic pollution: The hadal trench as a depository and indicator for dissemination of antibiotic resistance genes [J]. Environmental Science & Technology, 2021,55(22):15136-15148.
[7] Davis B C, Brown C, Gupta S, et al. Recommendations for the use of metagenomics for routine monitoring of antibiotic resistance in wastewater and impacted aquatic environments [J]. Critical Reviews in Environmental Science and Technology, 2023,53(19):1731-1756.
[8] 李建辉,张莹莹,黄魁,等.宏基因组学解析蚯蚓粪中微生物种群及耐药基因的组成 [J]. 中国环境科学, 2020,40(12):5375-5382. Li J H, Zhang Y Y, Huang K, et al. Composition of microbial community and antibiotic resistance genes in vermicomposts revealed by metagenomic analysis [J]. China Environmental Science, 2020,40 (12):5375-5382.
[9] 邢月,程艳,程刚,等.西北内陆河抗生素抗性基因赋存特征及其影响因素 [J]. 中国环境科学, 2023,43(6):3077-3086. Xing Y, Cheng Y, Cheng G, et al. Distribution characteristics and influencing factors of antibiotic resistance genes in inland rivers of Northwest China [J]. China Environmental Science, 2023,43(6):3077-3086.
[10] Neo O, Singh N, Cazares A. A river of resistant genes uncovered by metagenomics [J]. Nature Reviews Microbiology, 2024,23(1):8.
[11] Aishwarya P V, Mohan A S, Philip R, et al. Metagenomic phage biodiversity: New insight into the tropical estuarine ecosystem process and microbial risk assessment [J]. Regional Studies in Marine Science, 2021,46:101894.
[12] Zhang J, Lei H, Huang J, et al. Co-occurrence and co-expression of antibiotic, biocide, and metal resistance genes with mobile genetic elements in microbial communities subjected to long-term antibiotic pressure: Novel insights from metagenomics and metatranscriptomics [J]. Journal of Hazardous Materials, 2025,489:137559.
[13] Davis B C, Vikesland P J, Pruden A. Evaluating quantitative metagenomics for environmental monitoring of antibiotic resistance and establishing detection limits [J]. Environmental Science & Technology, 2025,59(12):6192-6202.
[14] Cui G, Liu Z, Xu W, et al. Metagenomic exploration of antibiotic resistance genes and their hosts in aquaculture waters of the semi- closed Dongshan Bay (China) [J]. Science of The Total Environment, 2022,838:155784.
[15] Kong M, Zhang Y, Ma Y, et al. Antibiotics and antibiotic resistance change bacterial community compositions in marine sediments [J]. Environmental Research, 2024,244:118005.
[16] Haro-Moreno J M, López-Pérez M, Rodriguez-Valera F. Enhanced recovery of microbial genes and genomes from a marine water column using long-read metagenomics [J]. Frontiers in Microbiology, 2021,12:708782.
[17] Kerfahi D, Harvey B P, Kim H, et al. Whole community and functional gene changes of biofilms on marine plastic debris in response to ocean acidification [J]. Microbial Ecology, 2023,85(4): 1202-1214.
[18] Yin X, Zheng J, Liu Y, et al. Metagenomic evidence for increasing antibiotic resistance in progeny upon parental antibiotic exposure as the cost of hormesis [J]. Chemosphere, 2022,309:136738.
[19] Xu N, Qiu D, Zhang Z, et al. A global atlas of marine antibiotic resistance genes and their expression [J]. Water Research, 2023,244:120488.
[20] Zhao Y, Yang Q E, Zhou X, et al. Antibiotic resistome in the livestock and aquaculture industries: Status and solutions [J]. Critical Reviews in Environmental Science and Technology, 2021,51(19):2159-2196.
[21] Jurgensen S K, Roux S, Schwenck S M, et al. Viral community analysis in a marine oxygen minimum zone indicates increased potential for viral manipulation of microbial physiological state [J]. The ISME Journal, 2022,16(4):972-982.
[22] He L X, He L Y, Gao F Z, et al. Antibiotics, antibiotic resistance genes and microbial community in grouper mariculture [J]. Science of The Total Environment, 2022,808:152042.
[23] Moon K, Jeon J H, Kang I, et al. Freshwater viral metagenome reveals novel and functional phage-borne antibiotic resistance genes [J]. Microbiome, 2020,8(1):75.
[24] Su H, Hu X, Xu W, et al. Diversity, abundances and distribution of antibiotic resistance genes and virulence factors in the South China Sea revealed by metagenomic sequencing [J]. Science of The Total Environment, 2022,814:152803.
[25] Hemamalini N, Shanmugam S A, Kathirvelpandian A, et al. A critical review on the antimicrobial resistance, antibiotic residue and metagenomics-assisted antimicrobial resistance gene detection in freshwater aquaculture environment [J]. Aquaculture Research, 2022, 53(2):344-366.
[26] Serrana J M, Nascimento F J A, Dessirier B, et al. Environmental drivers of the resistome across the Baltic Sea [J]. Microbiome, 2025, 13(1):92.
[27] 李十盛,高会,赵富强,等.水产养殖环境中抗生素抗性基因的研究进展 [J]. 中国环境科学, 2021,41(11):5314-5325. Li S S, Gao H, Zhao F Q, et al. Research progress on the occurrence and influencing factors of antibiotic resistance genes in aquaculture environment [J]. China Environmental Science, 2021,41(11):5314-5325.
[28] Nogueira T and Botelho A. Metagenomics and other omics approaches to bacterial communities and antimicrobial resistance assessment in aquacultures [J]. Antibiotics, 2021,10(7):787.
[29] Quijada N M, Cobo-Díaz J F, Valentino V, et al. The food-associated resistome is shaped by processing and production environments [J]. Nature Microbiology, 2025,10(8):1854-1867.
[30] Pedron R, Esposito A, Bianconi I, et al. Genomic and metagenomic insights into the microbial community of a thermal spring [J]. Microbiome, 2019,7(1):8.
[31] Zhao W, Zeng W, Pang B, et al. Oxford nanopore long-read sequencing enables the generation of complete bacterial and plasmid genomes without short-read sequencing [J]. Frontiers in Microbiology, 2023,14:1179966.
[32] Barthélémy D, Belmonte E, Pilla L D, et al. Direct comparative analysis of a pharmacogenomics panel with PacBio Hifi® Long-Read and Illumina Short-Read Sequencing [J]. Journal of Personalized Medicine, 2023,13(12):1655.
[33] Hiraoka S, Sumida T, Hirai M, et al. Diverse DNA modification in marine prokaryotic and viral communities [J]. Nucleic Acids Research, 2022,50(3):1531-1550.
[34] Farukh M. Comparative genomic analysis of selenium utilization traits in different marine environments [J]. Journal of Microbiology, 2020, 58(2):113-122.
[35] Rathour R, Gupta J, Mishra A, et al. A comparative metagenomic study reveals microbial diversity and their role in the biogeochemical cycling of Pangong lake [J]. Science of The Total Environment, 2020, 731:139074.
[36] Blumberg K L, Ponsero A J, Bomhoff M, et al. Ontology-enriched specifications enabling findable, accessible, interoperable, and reusable marine metagenomic datasets in cyberinfrastructure systems [J]. Frontiers in Microbiology, 2021,12:765268.
[37] Bolger A M, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data [J]. Bioinformatics, 2014,30(15):2114-2120.
[38] Chen S, Zhou Y, Chen Y, et al. fastp: an ultra-fast all-in-one FASTQ preprocessor [J]. Bioinformatics, 2018,34(17):i884-i890.
[39] Langmead B, Salzberg S L. Fast gapped-read alignment with Bowtie 2 [J]. Nature Methods, 2012,9(4):357-359.
[40] Li D, Liu C M, Luo R, et al. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph [J]. Bioinformatics, 2015,31(10):1674-1676.
[41] Zhou Y, Liu M, Yang J. Recovering metagenome-assembled genomes from shotgun metagenomic sequencing data: Methods, applications, challenges, and opportunities [J]. Microbiological Research, 2022,260:127023.
[42] Uritskiy G V, Diruggiero J and Taylor J. MetaWRAP—a flexible pipeline for genome-resolved metagenomic data analysis [J]. Microbiome, 2018,6(1):158.
[43] Qiu Z, Yuan L, Lian C A, et al. BASALT refines binning from metagenomic data and increases resolution of genome-resolved metagenomic analysis [J]. Nature Communications, 2024,15(1):2179.
[44] Hyatt D, Chen G L, Locascio P F, et al. Prodigal: prokaryotic gene recognition and translation initiation site identification [J]. BMC Bioinformatics, 2010,11(1):119.
[45] Zhang W, Li Y, Chu Y, et al. Deep-sea ecosystems as an unexpected source of antibiotic resistance genes [J]. Marine Drugs, 2025,23(1):17.
[46] Zhao S, Ye Z, Stanton R. Misuse of RPKM or TPM normalization when comparing across samples and sequencing protocols [J]. RNA, 2020,26(8):903-909.
[47] Aroney S T N, Newell R J P, Nissen J N, et al. CoverM: read alignment statistics for metagenomics [J]. Bioinformatics, 2025,41(4): btaf147.
[48] Kvesić M, Kalinić H, Dželalija M, et al. Microbiome and antibiotic resistance profiling in submarine effluent-receiving coastal waters in Croatia [J]. Environmental Pollution, 2022,292:118282.
[49] Parks D H, Chuvochina M, Rinke C, et al. GTDB: an ongoing census of bacterial and archaeal diversity through a phylogenetically consistent, rank normalized and complete genome-based taxonomy [J]. Nucleic Acids Research, 2021,50(D1):D785-D794.
[50] Wood D E, Lu J, Langmead B. Improved metagenomic analysis with Kraken 2 [J]. Genome Biology, 2019,20(1):257.
[51] Chaumeil P-A, Mussig A J, Hugenholtz P, et al. GTDB-Tk v2: memory friendly classification with the genome taxonomy database [J]. Bioinformatics, 2022,38(23):5315-5316.
[52] Menzel P, Ng K L, Krogh A. Fast and sensitive taxonomic classification for metagenomics with Kaiju [J]. Nature Communications, 2016,7(1):11257.
[53] Zhang H, Wang Y, Liu P, et al. Unveiling the occurrence, hosts and mobility potential of antibiotic resistance genes in the deep ocean [J]. Science of The Total Environment, 2022,816:151539.
[54] Yin X, Zheng X, Li L, et al. ARGs-OAP v3.0: Antibiotic-resistance gene database curation and analysis pipeline optimization [J]. Engineering, 2023,27:234-241.
[55] Arango-Argoty G, Garner E, Pruden A, et al. DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data [J]. Microbiome, 2018,6(1):23.
[56] Lu J, Wu J and Wang J. Metagenomic analysis on resistance genes in water and microplastics from a mariculture system [J]. Frontiers of Environmental Science & Engineering, 2021,16(1):4.
[57] Wang L, Li Y, Zhao Z, et al. Tidal flat aquaculture pollution governs sedimentary antibiotic resistance gene profiles but not bacterial community based on metagenomic data [J]. Science of The Total Environment, 2022,833:155206.
[58] Liu S, Rodriguez J S, Munteanu V, et al. Analysis of metagenomic data [J]. Nature Reviews Methods Primers, 2025,5(1):5.
[59] An T, Cai Y, Li G, et al. Prevalence and transmission risk of colistin and multidrug resistance in long-distance coastal aquaculture [J]. ISME Communications, 2023,3(1):115.
[60] Cai Y, Chen C, Sun T, et al. Mariculture waters as yet another hotbed for the creation and transfer of new antibiotic-resistant pathogenome [J]. Environment International, 2024,187:108704.
[61] Ghosh A, Saha R, Bhadury P. Metagenomic insights into surface water microbial communities of a South Asian mangrove ecosystem [J]. PeerJ, 2022,10:e13169.
[62] Zhang Y J, Hu H W, Yan H, et al. Salinity as a predominant factor modulating the distribution patterns of antibiotic resistance genes in ocean and river beach soils [J]. Science of The Total Environment, 2019,668:193-203.
[63] Nielsen M C, Wang N, Jiang S C. Acquisition of antibiotic resistance genes on human skin after swimming in the ocean [J]. Environmental Research, 2021,197:110978.
[64] Verasoundarapandian G, Wong C Y, Shaharuddin N A, et al. A review and bibliometric analysis on applications of microbial degradation of hydrocarbon contaminants in arctic marine environment at metagenomic and enzymatic levels [J]. International Journal of Environmental Research and Public Health, 2021,18(4):1671.
[65] Komijani M, Shamabadi N S, Shahin K, et al. Heavy metal pollution promotes antibiotic resistance potential in the aquatic environment [J]. Environmental Pollution, 2021,274:116569.
[66] Wen L, Dai J, Song J, et al. Antibiotic resistance genes (ARGs) and their eco-environmental response in the Bohai Sea sediments [J]. Marine Pollution Bulletin, 2024,208:116979.
[67] 彭韵,李蕾,伍迪,等.微生物群落对氨胁迫响应的宏基因组学研究 [J]. 中国环境科学, 2022,42(2):777-786. Peng Y, Li L, Wu D, et al. Metagenomic analysis on the responses of microbial community to ammonia stress [J]. China Environmental Science, 2022,42(2):777-786.
[68] Gabashvili E, Kobakhidze S, Chkhikvishvili T, et al. Metagenomic and recombination analyses of antimicrobial resistance genes from recreational waters of black sea coastal areas and other marine environments unveil extensive evidence for their both intrageneric and intergeneric transmission across genetically very diverse microbial communities [J]. Marine Genomics, 2022,61:100916.
[69] Di Cesare A, Pinnell L J, Brambilla D, et al. Bioplastic accumulates antibiotic and metal resistance genes in coastal marine sediments [J]. Environmental Pollution, 2021,291:118161.
[70] Talat A, Bashir Y, Khalil N, et al. Antimicrobial resistance transmission in the environmental settings through traditional and UV-enabled advanced wastewater treatment plants: a metagenomic insight [J]. Environmental Microbiome, 2025,20(1):27.
[71] Li L G, Huang Q, Yin X, et al. Source tracking of antibiotic resistance genes in the environment — Challenges, progress, and prospects [J]. Water Research, 2020,185:116127.
[72] Zhao Y, Li L, Huang Y, et al. Global soil antibiotic resistance genes are associated with increasing risk and connectivity to human resistome [J]. Nature Communications, 2025,16(1):7141.
[73] Sun R, Li T, Qiu S, et al. Occurrence of antibiotic resistance genes carried by plastic waste from mangrove wetlands of the South China Sea [J]. Science of The Total Environment, 2023,864:161111.
[74] Sabatino R, Di Cesare A, Dzhembekova N, et al. Spatial distribution of antibiotic and heavy metal resistance genes in the Black Sea [J]. Marine Pollution Bulletin, 2020,160:111635.
[75] Bai Y, Ruan X, Li R, et al. Metagenomics-based antibiotic resistance genes diversity and prevalence risk revealed by pathogenic bacterial host in Taihu Lake, China [J]. Environmental Geochemistry and Health, 2022,44(8):2531-2543.
[76] Zhang Z, Zhang Q, Wang T, et al. Assessment of global health risk of antibiotic resistance genes [J]. Nature Communications, 2022,13(1):1553.
[77] Jin G, Wang X, Cui R, et al. Comprehensive assessment of antibiotic impacts and risk thresholds on aquatic microbiomes and resistomes [J]. Water Research, 2025,276:123262.
[78] Du C, Yang F, Li X, et al. Metagenomic analysis of microbial community structure and distribution of resistance genes in Daihai Lake, China [J]. Environmental Pollution, 2022,302:119065.
[79] Wang Y, Xu N, Chen B, et al. Metagenomic analysis of antibiotic- resistance genes and viruses released from glaciers into downstream habitats [J]. Science of The Total Environment, 2024,908:168310.