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      Antimicrobial use and production system shape the fecal, environmental, and slurry resistomes of pig farms

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          Abstract

          Background

          The global threat of antimicrobial resistance (AMR) is a One Health problem impacted by antimicrobial use (AMU) for human and livestock applications. Extensive Iberian swine production is based on a more sustainable and eco-friendly management system, providing an excellent opportunity to evaluate how sustained differences in AMU impact the resistome, not only in the animals but also on the farm environment. Here, we evaluate the resistome footprint of an extensive pig farming system, maintained for decades, as compared to that of industrialized intensive pig farming by analyzing 105 fecal, environmental and slurry metagenomes from 38 farms.

          Results

          Our results evidence a significantly higher abundance of antimicrobial resistance genes (ARGs) on intensive farms and a link between AMU and AMR to certain antimicrobial classes. We observed differences in the resistome across sample types, with a higher richness and dispersion of ARGs within environmental samples than on those from feces or slurry. Indeed, a deeper analysis revealed that differences among the three sample types were defined by taxa-ARGs associations. Interestingly, mobilome analyses revealed that the observed AMR differences between intensive and extensive farms could be linked to differences in the abundance of mobile genetic elements (MGEs). Thus, while there were no differences in the abundance of chromosomal-associated ARGs between intensive and extensive herds, a significantly higher abundance of integrons in the environment and plasmids, regardless of the sample type, was detected on intensive farms.

          Conclusions

          Overall, this study shows how AMU, production system, and sample type influence, mainly through MGEs, the profile and dispersion of ARGs in pig production.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s40168-020-00941-7.

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          Most cited references60

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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              Basic local alignment search tool.

              A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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                Author and article information

                Contributors
                ana.carvajal@unileon.es
                Journal
                Microbiome
                Microbiome
                Microbiome
                BioMed Central (London )
                2049-2618
                19 November 2020
                19 November 2020
                2020
                : 8
                : 164
                Affiliations
                [1 ]GRID grid.4807.b, ISNI 0000 0001 2187 3167, Department of Animal Health, Faculty of Veterinary, , Universidad de León, ; León, Spain
                [2 ]GRID grid.6435.4, ISNI 0000 0001 1512 9569, Teagasc Food Research Centre, ; Moorepark, Fermoy, Co. Cork, Ireland
                [3 ]GRID grid.7872.a, ISNI 0000000123318773, APC Microbiome Institute, , University College Cork, ; Co. Cork, Ireland
                [4 ]GRID grid.4807.b, ISNI 0000 0001 2187 3167, Department of Food Hygiene and Technology, Faculty of Veterinary, , Universidad de León, ; León, Spain
                [5 ]GRID grid.4807.b, ISNI 0000 0001 2187 3167, Institute of Food Science and Technology, , Universidad de León, ; León, Spain
                [6 ]VistaMilk SFI Research Centre, Fermoy, Co. Cork, Ireland
                Author information
                http://orcid.org/0000-0001-8961-636X
                Article
                941
                10.1186/s40168-020-00941-7
                7678069
                33213522
                2eedc834-98cc-4c5f-9d22-bb3d4451e8aa
                © The Author(s) 2020

                Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 19 June 2020
                : 17 October 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100003176, Ministerio de Educación, Cultura y Deporte;
                Award ID: FPU 16/03485
                Award ID: FPU 17/00466
                Award ID: BEAGAL-18-106
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100008431, Consejería de Educación, Junta de Castilla y León;
                Award ID: LE131-18
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100014440, Ministerio de Ciencia, Innovación y Universidades;
                Award ID: AGL2016-78085-P
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100010661, Horizon 2020 Framework Programme;
                Award ID: No 818368
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2020

                antimicrobial resistance,feces,farm environment,mobilome,one health,sustainable farming,swine

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