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      Uncovering the diverse hosts of tigecycline resistance gene tet(X4) in anaerobic digestion systems treating swine manure by epicPCR

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          Highlights

          • A single-cell based epicPCR was developed to identify bacterial hosts of tet(X4) gene.

          • Nineteen genera in anaerobic digesters were identified as tet(X4) hosts by epicPCR.

          • Previously unknown tet(X4) hosts were found in sixteen genera.

          • Firmicutes and Caldatribacteriota were new phyla hosting tet(X4).

          Abstract

          The tet(X4) gene is a clinically important tigecycline resistance gene and has shown high persistence in livestock-related environments. However, the bacterial hosts of tet(X4) remain unknown due to the lack of appropriate approaches. Herein, a culture-independent and high-throughput epicPCR (emulsion, paired isolation, and concatenation polymerase chain reaction) method was developed, optimized, and demonstrated for the identification of bacterial hosts carrying tet(X4) from environmental samples. Considering the high sequence similarity between tet(X4) and other tet(X)-variant genes, specific primers and amplification conditions were screened and optimized to identify tet(X4) accurately and link tet(X4) with the 16S rRNA gene, which were further validated using artificially constructed bacterial communities. The epicPCR targeting tet(X4) was applied for the identification of bacterial hosts carrying this resistance gene in anaerobic digestion systems treating swine manure. A total of 19 genera were identified as tet(X4) hosts, which were distributed in the phyla Proteobacteria, Bacteroidota, Firmicutes, and Caldatribacteriota. Sixteen genera and two phyla that were identified have not been previously reported as tet(X4) bacterial hosts. The results indicated that a far more diverse range of bacteria was involved in harboring tet(X4) than previously realized. Compared with the tet(X4) hosts determined by correlation-based network analysis and metagenomic binning, epicPCR revealed a high diversity of tet(X4) hosts even at the phylum level. The epicPCR method developed in this study could be effectively employed to reveal the presence of tet(X4) bacterial hosts from a holistic viewpoint.

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          Most cited references74

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          Cutadapt removes adapter sequences from high-throughput sequencing reads

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            The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

            SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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              UPARSE: highly accurate OTU sequences from microbial amplicon reads.

              Amplified marker-gene sequences can be used to understand microbial community structure, but they suffer from a high level of sequencing and amplification artifacts. The UPARSE pipeline reports operational taxonomic unit (OTU) sequences with ≤1% incorrect bases in artificial microbial community tests, compared with >3% incorrect bases commonly reported by other methods. The improved accuracy results in far fewer OTUs, consistently closer to the expected number of species in a community.
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                Author and article information

                Contributors
                Journal
                Water Res X
                Water Res X
                Water Research X
                Elsevier
                2589-9147
                01 March 2023
                01 May 2023
                01 March 2023
                : 19
                : 100174
                Affiliations
                [a ]State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
                [b ]CAS Key Laboratory of Environmental Biotechnology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
                [c ]Beijing Key Laboratory of Detection Technology for Animal-Derived Food Safety, College of Veterinary Medicine, China Agricultural University, Beijing, 100193, China
                [d ]College of Engineering, China Agricultural University, Beijing 100083, China
                [e ]University of Chinese Academy of Sciences, Beijing 100049, China
                Author notes
                [* ]Correspondence author: State Key Lab. of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China. zhangyu@ 123456rcees.ac.cn
                Article
                S2589-9147(23)00010-5 100174
                10.1016/j.wroa.2023.100174
                10006855
                36915394
                9d87e4a2-65ba-4e8a-a41b-1572da0e093a
                © 2023 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 13 December 2022
                : 23 February 2023
                : 25 February 2023
                Categories
                Full Paper

                antibiotic resistance genes,tet(x)-variant genes,livestock waste,single-cell technology

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