title: Sampling and Pooling Methods for Capturing Herd Level Antibiotic Resistance in Swine Feces using qPCR and CFU Approaches.
abstract: The aim of this article was to define the sampling level and method combination that captures antibiotic resistance at pig herd level utilizing qPCR antibiotic resistance gene quantification and culture-based quantification of antibiotic resistant coliform indicator bacteria. Fourteen qPCR assays for commonly detected antibiotic resistance genes were developed, and used to quantify antibiotic resistance genes in total DNA from swine fecal samples that were obtained using different sampling and pooling methods. In parallel, the number of antibiotic resistant coliform indicator bacteria was determined in the same swine fecal samples. The results showed that the qPCR assays were capable of detecting differences in antibiotic resistance levels in individual animals that the coliform bacteria colony forming units (CFU) could not. Also, the qPCR assays more accurately quantified antibiotic resistance genes when comparing individual sampling and pooling methods. qPCR on pooled samples was found to be a good representative for the general resistance level in a pig herd compared to the coliform CFU counts. It had significantly reduced relative standard deviations compared to coliform CFU counts in the same samples, and therefore differences in antibiotic resistance levels between samples were more readily detected. To our knowledge, this is the first study to describe sampling and pooling methods for qPCR quantification of antibiotic resistance genes in total DNA extracted from swine feces.
authors.affiliation: The National Veterinary Institute, Technical University of Denmark, Frederiksberg C, Denmark.
authors.forename: Gunilla Veslemøy
authors.initials: GV
authors.lastname: Schmidt
authors.affiliation: The National Veterinary Institute, Technical University of Denmark, Frederiksberg C, Denmark.
authors.forename: Anders
authors.initials: A
authors.lastname: Mellerup
authors.affiliation: Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark.
authors.forename: Lasse Engbo
authors.initials: LE
authors.lastname: Christiansen
authors.affiliation: The National Veterinary Institute, Technical University of Denmark, Frederiksberg C, Denmark.
authors.forename: Marie
authors.initials: M
authors.lastname: Ståhl
authors.affiliation: Department of Veterinary Disease Biology, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg C, Denmark.
authors.forename: John Elmerdahl
authors.initials: JE
authors.lastname: Olsen
authors.affiliation: The National Veterinary Institute, Technical University of Denmark, Frederiksberg C, Denmark.
authors.forename: Øystein
authors.initials: Ø
authors.lastname: Angen
mesh_terms: D000818:Animals; D000900:Anti-Bacterial Agents / Q000494:pharmacology; D015169:Colony Count, Microbial; D004269:DNA, Bacterial / Q000032:analysis / Q000302:isolation & purification*; D004352:Drug Resistance, Microbial / Q000235:genetics*; D005243:Feces / Q000737:chemistry / Q000382:microbiology*; D006090:Gram-Negative Bacteria / Q000187:drug effects / Q000235:genetics / Q000302:isolation & purification*; D008826:Microbial Sensitivity Tests; D060888:Real-Time Polymerase Chain Reaction; D013048:Specimen Handling / Q000379:methods* / Q000662:veterinary; D013552:Swine / Q000382:microbiology*
chemical_list: D000900:Anti-Bacterial Agents; D004269:DNA, Bacterial