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      The occurrence of antibiotic resistance genes in the microbiota of yak, beef and dairy cattle characterized by a metagenomic approach

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          Abstract

          Drug resistance has been partly driven by the overuse of antimicrobials in agricultural animal feed. Better understanding of antibiotic resistance in bovine gut is needed to assess its potential effects based on metagenomic approach and analysis. In this study, we collected 40 fecal samples to explore drug resistance derived from antibiotic use in the bacterial community by an analysis of the diversities and differences of antibiotic-resistant genes (ARGs) in the gut microbiota from yak, beef, and dairy cattle. Overall, 1688 genes were annotated, including 734 ARG subtypes. The ARGs were related to tetracyclines, quinolones, β-lactam, and aminoglycosides, in accordance with the antibiotics widely used in the clinic for humans or animals. The emergence, prevalence, and differences in resistance genes in the intestines of yaks, beef, and dairy cattle may be caused by the selective pressure of different feeding patterns, where yaks were raised without antibiotics for growth promotion. In addition, the abundance of ARGs in yak was lower than in beef and dairy cattle, whereas the abundance of integron, a kind of mobile genetic elements (MGEs) was higher in yaks than those in beef and dairy cattle. Furthermore, the results of this study could provide the basis for a comprehensive profile of various ARGs among yak, beef, and dairy cattle in future.

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          Most cited references58

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          Fast and sensitive protein alignment using DIAMOND.

          The alignment of sequencing reads against a protein reference database is a major computational bottleneck in metagenomics and data-intensive evolutionary projects. Although recent tools offer improved performance over the gold standard BLASTX, they exhibit only a modest speedup or low sensitivity. We introduce DIAMOND, an open-source algorithm based on double indexing that is 20,000 times faster than BLASTX on short reads and has a similar degree of sensitivity.
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            CD-HIT: accelerated for clustering the next-generation sequencing data

            Summary: CD-HIT is a widely used program for clustering biological sequences to reduce sequence redundancy and improve the performance of other sequence analyses. In response to the rapid increase in the amount of sequencing data produced by the next-generation sequencing technologies, we have developed a new CD-HIT program accelerated with a novel parallelization strategy and some other techniques to allow efficient clustering of such datasets. Our tests demonstrated very good speedup derived from the parallelization for up to ∼24 cores and a quasi-linear speedup for up to ∼8 cores. The enhanced CD-HIT is capable of handling very large datasets in much shorter time than previous versions. Availability: http://cd-hit.org. Contact: liwz@sdsc.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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              Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences.

              In 2001 and 2002, we published two papers (Bioinformatics, 17, 282-283, Bioinformatics, 18, 77-82) describing an ultrafast protein sequence clustering program called cd-hit. This program can efficiently cluster a huge protein database with millions of sequences. However, the applications of the underlying algorithm are not limited to only protein sequences clustering, here we present several new programs using the same algorithm including cd-hit-2d, cd-hit-est and cd-hit-est-2d. Cd-hit-2d compares two protein datasets and reports similar matches between them; cd-hit-est clusters a DNA/RNA sequence database and cd-hit-est-2d compares two nucleotide datasets. All these programs can handle huge datasets with millions of sequences and can be hundreds of times faster than methods based on the popular sequence comparison and database search tools, such as BLAST.
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                Author and article information

                Contributors
                infzjy@sina.com
                Journal
                J Antibiot (Tokyo)
                J Antibiot (Tokyo)
                The Journal of Antibiotics
                Nature Publishing Group UK (London )
                0021-8820
                1881-1469
                9 June 2021
                9 June 2021
                2021
                : 74
                : 8
                : 508-518
                Affiliations
                [1 ]Key Laboratory of New Animal Drug Project of Gansu Province, Lanzhou, Gansu Province 730050 PR China
                [2 ]Key Laboratory of Veterinary Pharmaceutical Development, Ministry of Agriculture, Lanzhou, Gansu Province 730050 PR China
                [3 ]GRID grid.410727.7, ISNI 0000 0001 0526 1937, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, , Chinese Academy of Agricultural Sciences, ; Lanzhou, Gansu Province 730050 PR China
                Article
                425
                10.1038/s41429-021-00425-2
                8313426
                34103703
                501b6131-280e-4062-9ce9-2643af621213
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 22 October 2020
                : 13 February 2021
                : 11 May 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001809, National Natural Science Foundation of China (National Science Foundation of China);
                Award ID: 3187520
                Award ID: 3187520
                Award ID: 3187520
                Award Recipient :
                Categories
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                Custom metadata
                © The Author(s), under exclusive licence to the Japan Antibiotics Research Association 2021

                Infectious disease & Microbiology
                antimicrobial resistance,computational biology and bioinformatics

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