{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Zhang W"],"funding":["the innovational Found for the scientific and technological personnel of Hainan Province","the International Partnership Program of Chinese Academy of Sciences for Big Science","the National Key R&D Program of China"],"pagination":["17"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11766751"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["23(1)"],"pubmed_abstract":["The deep-sea ecosystem, a less-contaminated reservoir of antibiotic resistance genes (ARGs), has evolved antibiotic resistance for microbes to survive and utilize scarce resources. Research on the diversity and distribution of these genes in deep-sea environments is limited. Our metagenomics study employed short-read-based (SRB) and assembled-contig-based (ACB) methods to identify ARGs in deep-sea waters and sediments and assess their potential pathogenicity. SRB prediction was found to be more effective for studying the abundance and diversity of these genes, while combining both methods better illustrated the relationship of ARGs with the hosts. Deep-sea waters (DSW) and trenches had the highest diversity of ARGs, including β-lactams, multidrug resistance genes, and rifamycins. Mobile ge"],"journal":["Marine drugs"],"pubmed_title":["Deep-Sea Ecosystems as an Unexpected Source of Antibiotic Resistance Genes."],"pmcid":["PMC11766751"],"funding_grant_id":["2022YFC2805400","2022YFC2805505","KJRC2023C37","183446KYSB20210002"],"pubmed_authors":["Zhang W","Liu H","Jing H","Li Y","Chu Y","Xia Q"],"additional_accession":[]},"is_claimable":false,"name":"Deep-Sea Ecosystems as an Unexpected Source of Antibiotic Resistance Genes.","description":"The deep-sea ecosystem, a less-contaminated reservoir of antibiotic resistance genes (ARGs), has evolved antibiotic resistance for microbes to survive and utilize scarce resources. Research on the diversity and distribution of these genes in deep-sea environments is limited. Our metagenomics study employed short-read-based (SRB) and assembled-contig-based (ACB) methods to identify ARGs in deep-sea waters and sediments and assess their potential pathogenicity. SRB prediction was found to be more effective for studying the abundance and diversity of these genes, while combining both methods better illustrated the relationship of ARGs with the hosts. Deep-sea waters (DSW) and trenches had the highest diversity of ARGs, including β-lactams, multidrug resistance genes, and rifamycins. Mobile ge","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Dec","modification":"2025-04-03T23:23:40.245Z","creation":"2025-04-03T23:23:40.245Z"},"accession":"S-EPMC11766751","cross_references":{"pubmed":["39852519"],"doi":["10.3390/md23010017"]}}