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      Transmission of antibiotic resistance at the wildlife-livestock interface

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          Abstract

          Antibiotic-resistant microorganisms (ARMs) are widespread in natural environments, animals (wildlife and livestock), and humans, which has reduced our capacity to control life threatening infectious disease. Yet, little is known about their transmission pathways, especially at the wildlife-livestock interface. This study investigated the potential transmission of ARMs and antibiotic resistance genes (ARGs) between cattle and wildlife by comparing gut microbiota and ARG profiles of feral swine ( Sus scrofa), coyotes ( Canis latrans), cattle ( Bos taurus), and environmental microbiota. Unexpectedly, wild animals harbored more abundant ARMs and ARGs compared to grazing cattle. Gut microbiota of cattle was significantly more similar to that of feral swine captured within the cattle grazing area where the home range of both species overlapped substantially. In addition, ARMs against medically important antibiotics were more prevalent in wildlife than grazing cattle, suggesting that wildlife could be a source of ARMs colonization in livestock.

          Abstract

          Analysis of microbiome data from feral swine, coyotes, domesticated cattle, and the surrounding environment reveals that wild animals harbor more abundant antibiotic-resistant organisms than livestock, and might act as a source of antibiotic-resistant microbes in outbreaks.

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          MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

          The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.
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            QIIME allows analysis of high-throughput community sequencing data.

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              Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform.

              Rapid advances in sequencing technology have changed the experimental landscape of microbial ecology. In the last 10 years, the field has moved from sequencing hundreds of 16S rRNA gene fragments per study using clone libraries to the sequencing of millions of fragments per study using next-generation sequencing technologies from 454 and Illumina. As these technologies advance, it is critical to assess the strengths, weaknesses, and overall suitability of these platforms for the interrogation of microbial communities. Here, we present an improved method for sequencing variable regions within the 16S rRNA gene using Illumina's MiSeq platform, which is currently capable of producing paired 250-nucleotide reads. We evaluated three overlapping regions of the 16S rRNA gene that vary in length (i.e., V34, V4, and V45) by resequencing a mock community and natural samples from human feces, mouse feces, and soil. By titrating the concentration of 16S rRNA gene amplicons applied to the flow cell and using a quality score-based approach to correct discrepancies between reads used to construct contigs, we were able to reduce error rates by as much as two orders of magnitude. Finally, we reprocessed samples from a previous study to demonstrate that large numbers of samples could be multiplexed and sequenced in parallel with shotgun metagenomes. These analyses demonstrate that our approach can provide data that are at least as good as that generated by the 454 platform while providing considerably higher sequencing coverage for a fraction of the cost.
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                Author and article information

                Contributors
                kcjeong@ufl.edu
                Journal
                Commun Biol
                Commun Biol
                Communications Biology
                Nature Publishing Group UK (London )
                2399-3642
                15 June 2022
                15 June 2022
                2022
                : 5
                : 585
                Affiliations
                [1 ]GRID grid.15276.37, ISNI 0000 0004 1936 8091, Emerging Pathogens Institute, , University of Florida, ; Gainesville, FL 32611 USA
                [2 ]GRID grid.15276.37, ISNI 0000 0004 1936 8091, Department of Animal Sciences, , University of Florida, ; Gainesville, FL 32611 USA
                [3 ]GRID grid.47894.36, ISNI 0000 0004 1936 8083, Department of Fish, Wildlife, and Conservation Biology, , Colorado State University, ; Fort Collins, CO 80523 USA
                [4 ]GRID grid.413759.d, ISNI 0000 0001 0725 8379, National Wildlife Research Center, United States Department of Agriculture, , Animal and Plant Health Inspection Service, Wildlife Services, ; 4101 Laporte Ave., Fort Collins, CO 80521 USA
                [5 ]GRID grid.15276.37, ISNI 0000 0004 1936 8091, Range Cattle Research and Education Center, Wildlife Ecology and Conservation, , University of Florida, ; Ona, FL 33865 USA
                [6 ]GRID grid.413759.d, ISNI 0000 0001 0725 8379, Center for Epidemiology and Animal Health, United States Department of Agriculture, , Animal and Plant Health Inspection Service, Veterinary Services, ; 2150 Center Dr., Fort Collins, CO 80523 USA
                Author information
                http://orcid.org/0000-0002-9535-2193
                http://orcid.org/0000-0003-4337-0426
                Article
                3520
                10.1038/s42003-022-03520-8
                9200806
                35705693
                7fabe41f-9377-4cf6-b6a5-27b308055846
                © The Author(s) 2022

                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
                : 26 July 2021
                : 23 May 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/100005825, United States Department of Agriculture | National Institute of Food and Agriculture (NIFA);
                Award ID: 2015-68003-22971
                Award Recipient :
                Funded by: USDA National Feral Swine Damage Management Program cooperative agreements, number 2017-9200-391, 2018-9200-0391 USDA’s Animal and Plant Health Inspection Service National Feral Swine Damage Management Program
                Categories
                Article
                Custom metadata
                © The Author(s) 2022

                environmental microbiology,antimicrobials
                environmental microbiology, antimicrobials

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