Enhancing the one health initiative by using whole genome sequencing to monitor antimicrobial resistance of animal pathogens: Vet-LIRN collaborative project with veterinary diagnostic laboratories in United States and Canada

Olgica Ceric, Veterinary Laboratory Investigation and Response Network (Vet-LIRN), Center for Veterinary Medicine, United States Food and Drug Administration, 8401 Muirkirk Rd, Laurel, MD, 20708, USA. Olgica.Ceric@fda.hhs.gov.
Gregory H. Tyson, Veterinary Laboratory Investigation and Response Network (Vet-LIRN), Center for Veterinary Medicine, United States Food and Drug Administration, 8401 Muirkirk Rd, Laurel, MD, 20708, USA.
Laura B. Goodman, Population Medicine & Diagnostic Sciences, Cornell University, Ithaca, New York, USA.
Patrick K. Mitchell, Population Medicine & Diagnostic Sciences, Cornell University, Ithaca, New York, USA.
Yan Zhang, Ohio Department of Agriculture, Ohio Animal Disease Diagnostic Laboratory, Reynoldsburg, OH, USA.
Melanie Prarat, Ohio Department of Agriculture, Ohio Animal Disease Diagnostic Laboratory, Reynoldsburg, OH, USA.
Jing Cui, Ohio Department of Agriculture, Ohio Animal Disease Diagnostic Laboratory, Reynoldsburg, OH, USA.
Laura Peak, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA, USA.
Joy Scaria, Veterinary and Biomedical Sciences, South Dakota State University, Brookings, SD, USA.
Linto Antony, Veterinary and Biomedical Sciences, South Dakota State University, Brookings, SD, USA.
Milton Thomas, Veterinary and Biomedical Sciences, South Dakota State University, Brookings, SD, USA.
Sarah M. Nemser, Veterinary Laboratory Investigation and Response Network (Vet-LIRN), Center for Veterinary Medicine, United States Food and Drug Administration, 8401 Muirkirk Rd, Laurel, MD, 20708, USA.
Renee Anderson, Population Medicine & Diagnostic Sciences, Cornell University, Ithaca, New York, USA.
Anil J. Thachil, Population Medicine & Diagnostic Sciences, Cornell University, Ithaca, New York, USA.
Rebecca J. Franklin-Guild, Population Medicine & Diagnostic Sciences, Cornell University, Ithaca, New York, USA.
Durda Slavic, Animal Health Laboratory, University of Guelph, Guelph, Canada.
Yugendar R. Bommineni, Florida Department of Agriculture and Consumer Services, Bronson Animal Disease Diagnostic Laboratory, Kissimmee, FL, USA.
Shipra Mohan, Florida Department of Agriculture and Consumer Services, Bronson Animal Disease Diagnostic Laboratory, Kissimmee, FL, USA.
Susan Sanchez, Athens Veterinary Diagnostic Laboratory, Department of Infectious Diseases, College of Veterinary Medicine, The University of Georgia, Athens, GA, USA.
Rebecca Wilkes, Tifton Veterinary Diagnostic and Investigational Laboratory, The University of Georgia, Tifton, GA, USA.
Orhan Sahin, Department of Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, USA.
G Kenitra Hendrix, Animal Disease Diagnostic Laboratory, Purdue University, West Lafayette, IN, USA.
Brian Lubbers, Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS, USA.
Deborah Reed, Breathitt Veterinary Center, Murray State University, Murray, KY, USA.
Tracie Jenkins, Breathitt Veterinary Center, Murray State University, Murray, KY, USA.
Alma Roy, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA, USA.
Daniel Paulsen, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA, USA.
Rinosh Mani, Veterinary Diagnostic Laboratory, Michigan State University, East Lansing, MI, USA.
Karen Olsen, Veterinary Diagnostic Laboratory, University of Minnesota, St. Paul, MN, USA.
Lanny Pace, Veterinary Research and Diagnostic Lab System, Mississippi State University, Starkville, MS, USA.
Martha Pulido, Veterinary Research and Diagnostic Lab System, Mississippi State University, Starkville, MS, USA.
Megan Jacob, North Carolina State University College of Veterinary Medicine, Raleigh, NC, USA.
Brett T. Webb, Veterinary Diagnostic Laboratory, North Dakota State University, Fargo, ND, USA.

Document Type

Article

Publication Date

5-6-2019

Abstract

BACKGROUND: Antimicrobial resistance (AMR) of bacterial pathogens is an emerging public health threat. This threat extends to pets as it also compromises our ability to treat their infections. Surveillance programs in the United States have traditionally focused on collecting data from food animals, foods, and people. The Veterinary Laboratory Investigation and Response Network (Vet-LIRN), a national network of 45 veterinary diagnostic laboratories, tested the antimicrobial susceptibility of clinically relevant bacterial isolates from animals, with companion animal species represented for the first time in a monitoring program. During 2017, we systematically collected and tested 1968 isolates. To identify genetic determinants associated with AMR and the potential genetic relatedness of animal and human strains, whole genome sequencing (WGS) was performed on 192 isolates: 69 Salmonella enterica (all animal sources), 63 Escherichia coli (dogs), and 60 Staphylococcus pseudintermedius (dogs). RESULTS: We found that most Salmonella isolates (46/69, 67%) had no known resistance genes. Several isolates from both food and companion animals, however, showed genetic relatedness to isolates from humans. For pathogenic E. coli, no resistance genes were identified in 60% (38/63) of the isolates. Diverse resistance patterns were observed, and one of the isolates had predicted resistance to fluoroquinolones and cephalosporins, important antibiotics in human and veterinary medicine. For S. pseudintermedius, we observed a bimodal distribution of resistance genes, with some isolates having a diverse array of resistance mechanisms, including the mecA gene (19/60, 32%). CONCLUSION: The findings from this study highlight the critical importance of veterinary diagnostic laboratory data as part of any national antimicrobial resistance surveillance program. The finding of some highly resistant bacteria from companion animals, and the observation of isolates related to those isolated from humans demonstrates the public health significance of incorporating companion animal data into surveillance systems. Vet-LIRN will continue to build the infrastructure to collect the data necessary to perform surveillance of resistant bacteria as part of fulfilling its mission to advance human and animal health. A One Health approach to AMR surveillance programs is crucial and must include data from humans, animals, and environmental sources to be effective.

Publication Source (Journal or Book title)

BMC veterinary research

First Page

130

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