26
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Characterization of the resistome in manure, soil and wastewater from dairy and beef production systems

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          It has been proposed that livestock production effluents such as wastewater, airborne dust and manure increase the density of antimicrobial resistant bacteria and genes in the environment. The public health risk posed by this proposed outcome has been difficult to quantify using traditional microbiological approaches. We utilized shotgun metagenomics to provide a first description of the resistome of North American dairy and beef production effluents, and identify factors that significantly impact this resistome. We identified 34 mechanisms of antimicrobial drug resistance within 34 soil, manure and wastewater samples from feedlot, ranch and dairy operations. The majority of resistance-associated sequences found in all samples belonged to tetracycline resistance mechanisms. We found that the ranch samples contained significantly fewer resistance mechanisms than dairy and feedlot samples, and that the resistome of dairy operations differed significantly from that of feedlots. The resistome in soil, manure and wastewater differed, suggesting that management of these effluents should be tailored appropriately. By providing a baseline of the cattle production waste resistome, this study represents a solid foundation for future efforts to characterize and quantify the public health risk posed by livestock effluents.

          Related collections

          Most cited references37

          • Record: found
          • Abstract: found
          • Article: not found

          The comprehensive antibiotic resistance database.

          The field of antibiotic drug discovery and the monitoring of new antibiotic resistance elements have yet to fully exploit the power of the genome revolution. Despite the fact that the first genomes sequenced of free living organisms were those of bacteria, there have been few specialized bioinformatic tools developed to mine the growing amount of genomic data associated with pathogens. In particular, there are few tools to study the genetics and genomics of antibiotic resistance and how it impacts bacterial populations, ecology, and the clinic. We have initiated development of such tools in the form of the Comprehensive Antibiotic Research Database (CARD; http://arpcard.mcmaster.ca). The CARD integrates disparate molecular and sequence data, provides a unique organizing principle in the form of the Antibiotic Resistance Ontology (ARO), and can quickly identify putative antibiotic resistance genes in new unannotated genome sequences. This unique platform provides an informatic tool that bridges antibiotic resistance concerns in health care, agriculture, and the environment.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Bacterial phylogeny structures soil resistomes across habitats

            Summary Ancient and diverse antibiotic resistance genes (ARGs) have previously been identified from soil 1–3 , including genes identical to those in human pathogens 4 . Despite the apparent overlap between soil and clinical resistomes 4–6 , factors influencing ARG composition in soil and their movement between genomes and habitats remain largely unknown 3 . General metagenome functions often correlate with the underlying structure of bacterial communities 7–12 . However, ARGs are hypothesized to be highly mobile 4,5,13 , prompting speculation that resistomes may not correlate with phylogenetic signatures or ecological divisions 13,14 . To investigate these relationships, we performed functional metagenomic selections for resistance to 18 antibiotics from 18 agricultural and grassland soils. The 2895 ARGs we discovered were predominantly novel, and represent all major resistance mechanisms 15 . We demonstrate that distinct soil types harbor distinct resistomes, and that nitrogen fertilizer amendments strongly influenced soil ARG content. Resistome composition also correlated with microbial phylogenetic and taxonomic structure, both across and within soil types. Consistent with this strong correlation, mobility elements syntenic with ARGs were rare in soil compared to sequenced pathogens, suggesting that ARGs in the soil may not transfer between bacteria as readily as is observed in the clinic. Together, our results indicate that bacterial community composition is the primary determinant of soil ARG content, challenging previous hypotheses that horizontal gene transfer effectively decouples resistomes from phylogeny 13,14 .
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              What is a resistance gene? Ranking risk in resistomes.

              Metagenomic studies have shown that antibiotic resistance genes are ubiquitous in the environment, which has led to the suggestion that there is a high risk that these genes will spread to bacteria that cause human infections. If this is true, estimating the real risk of dissemination of resistance genes from environmental reservoirs to human pathogens is therefore very difficult. In this Opinion article, we analyse the current definitions of antibiotic resistance and antibiotic resistance genes, and we describe the bottlenecks that affect the transfer of antibiotic resistance genes to human pathogens. We propose rules for estimating the risks associated with genes that are present in environmental resistomes by evaluating the likelihood of their introduction into human pathogens, and the consequences of such events for the treatment of infections.
                Bookmark

                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                20 April 2016
                2016
                : 6
                : 24645
                Affiliations
                [1 ]Department of Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University , Fort Collins, CO, USA
                [2 ]Department of Animal Sciences, College of Agricultural Sciences, Colorado State University , Fort Collins, CO, USA
                [3 ]Agriculture and Agri-Food Canada Research Centre , Lethbridge, AB, Canada
                [4 ]Department of Population Medicine & Diagnostic Sciences, Cornell University , Ithaca, NY, USA
                [5 ]Centre for Food-borne, Environmental Zoonotic Infectious Diseases, Public Health Agency of Canada, University of Saskatoon , Saskatchewan, Canada
                [6 ]Department of Computer Sciences, College of Natural Sciences, Colorado State University , Fort Collins, CO, USA
                [7 ]Department of Biochemistry and Molecular Genetics, School of Medicine, University of Colorado , Denver, CO, USA
                Author notes
                [*]

                These authors contributed equally to this work.

                Article
                srep24645
                10.1038/srep24645
                4837390
                27095377
                415ce089-b079-45cb-9f12-54e3c78c6700
                Copyright © 2016, Macmillan Publishers Limited

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 04 December 2015
                : 04 April 2016
                Categories
                Article

                Uncategorized
                Uncategorized

                Comments

                Comment on this article

                scite_
                0
                0
                0
                0
                Smart Citations
                0
                0
                0
                0
                Citing PublicationsSupportingMentioningContrasting
                View Citations

                See how this article has been cited at scite.ai

                scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.

                Similar content595

                Cited by58

                Most referenced authors1,439