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

doi:10.1186/s12917-019-1864-2

. 2019 May 6;15(1):130.

doi: 10.1186/s12917-019-1864-2.

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 Ceric¹, Gregory H Tyson², Laura B Goodman³, Patrick K Mitchell³, Yan Zhang⁴, Melanie Prarat⁴, Jing Cui⁴, Laura Peak⁵, Joy Scaria⁶, Linto Antony⁶, Milton Thomas⁶, Sarah M Nemser², Renee Anderson³, Anil J Thachil³, Rebecca J Franklin-Guild³, Durda Slavic⁷, Yugendar R Bommineni⁸, Shipra Mohan⁸, Susan Sanchez⁹, Rebecca Wilkes¹⁰, Orhan Sahin¹¹, G Kenitra Hendrix¹², Brian Lubbers¹³, Deborah Reed¹⁴, Tracie Jenkins¹⁴, Alma Roy⁵, Daniel Paulsen⁵, Rinosh Mani¹⁵, Karen Olsen¹⁶, Lanny Pace¹⁷, Martha Pulido¹⁷, Megan Jacob¹⁸, Brett T Webb¹⁹, Sarmila Dasgupta²⁰, Amar Patil²⁰, Akhilesh Ramachandran²¹, Deepanker Tewari²², Nagaraja Thirumalapura²², Donna J Kelly²³, Shelley C Rankin²⁴, Sara D Lawhon²⁵, Jing Wu²⁵, Claire R Burbick²⁶, Renate Reimschuessel²

Affiliations

¹ 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.
² 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.
³ Population Medicine & Diagnostic Sciences, Cornell University, Ithaca, New York, USA.
⁴ Ohio Department of Agriculture, Ohio Animal Disease Diagnostic Laboratory, Reynoldsburg, OH, USA.
⁵ School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA, USA.
⁶ Veterinary and Biomedical Sciences, South Dakota State University, Brookings, SD, USA.
⁷ Animal Health Laboratory, University of Guelph, Guelph, Canada.
⁸ Florida Department of Agriculture and Consumer Services, Bronson Animal Disease Diagnostic Laboratory, Kissimmee, FL, USA.
⁹ Athens Veterinary Diagnostic Laboratory, Department of Infectious Diseases, College of Veterinary Medicine, The University of Georgia, Athens, GA, USA.
¹⁰ Tifton Veterinary Diagnostic and Investigational Laboratory, The University of Georgia, Tifton, GA, USA.
¹¹ Department of Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, USA.
¹² Animal Disease Diagnostic Laboratory, Purdue University, West Lafayette, IN, USA.
¹³ Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS, USA.
¹⁴ Breathitt Veterinary Center, Murray State University, Murray, KY, USA.
¹⁵ Veterinary Diagnostic Laboratory, Michigan State University, East Lansing, MI, USA.
¹⁶ Veterinary Diagnostic Laboratory, University of Minnesota, St. Paul, MN, USA.
¹⁷ Veterinary Research and Diagnostic Lab System, Mississippi State University, Starkville, MS, USA.
¹⁸ North Carolina State University College of Veterinary Medicine, Raleigh, NC, USA.
¹⁹ Veterinary Diagnostic Laboratory, North Dakota State University, Fargo, ND, USA.
²⁰ New Jersey Department of Agriculture, Animal Health Diagnostic Laboratory, Ewing Township, NJ, USA.
²¹ Oklahoma Animal Disease Diagnostic Laboratory, Oklahoma State University, Stillwater, OK, USA.
²² Pennsylvania Department of Agriculture, Pennsylvania Veterinary Laboratory, Harrisburg, PA, USA.
²³ Pennsylvania Animal Diagnostic Laboratory, New Bolton Center, University of Pennsylvania, Kenneth Square, PA, USA.
²⁴ School of Veterinary Medicine, The Ryan Veterinary Hospital Clinical Microbiology Laboratory, University of Pennsylvania, Philadelphia, PA, USA.
²⁵ Texas A&M University, College Station, TX, USA.
²⁶ College of Veterinary Medicine, Washington Animal Disease Diagnostic Laboratory, Washington State University, Pullman, WA, USA.

PMID: 31060608
PMCID: PMC6501310
DOI: 10.1186/s12917-019-1864-2

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 et al. BMC Vet Res. 2019.

. 2019 May 6;15(1):130.

doi: 10.1186/s12917-019-1864-2.

Authors

Affiliations

¹ 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.
² 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.
³ Population Medicine & Diagnostic Sciences, Cornell University, Ithaca, New York, USA.
⁴ Ohio Department of Agriculture, Ohio Animal Disease Diagnostic Laboratory, Reynoldsburg, OH, USA.
⁵ School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA, USA.
⁶ Veterinary and Biomedical Sciences, South Dakota State University, Brookings, SD, USA.
⁷ Animal Health Laboratory, University of Guelph, Guelph, Canada.
⁸ Florida Department of Agriculture and Consumer Services, Bronson Animal Disease Diagnostic Laboratory, Kissimmee, FL, USA.
⁹ Athens Veterinary Diagnostic Laboratory, Department of Infectious Diseases, College of Veterinary Medicine, The University of Georgia, Athens, GA, USA.
¹⁰ Tifton Veterinary Diagnostic and Investigational Laboratory, The University of Georgia, Tifton, GA, USA.
¹¹ Department of Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, USA.
¹² Animal Disease Diagnostic Laboratory, Purdue University, West Lafayette, IN, USA.
¹³ Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS, USA.
¹⁴ Breathitt Veterinary Center, Murray State University, Murray, KY, USA.
¹⁵ Veterinary Diagnostic Laboratory, Michigan State University, East Lansing, MI, USA.
¹⁶ Veterinary Diagnostic Laboratory, University of Minnesota, St. Paul, MN, USA.
¹⁷ Veterinary Research and Diagnostic Lab System, Mississippi State University, Starkville, MS, USA.
¹⁸ North Carolina State University College of Veterinary Medicine, Raleigh, NC, USA.
¹⁹ Veterinary Diagnostic Laboratory, North Dakota State University, Fargo, ND, USA.
²⁰ New Jersey Department of Agriculture, Animal Health Diagnostic Laboratory, Ewing Township, NJ, USA.
²¹ Oklahoma Animal Disease Diagnostic Laboratory, Oklahoma State University, Stillwater, OK, USA.
²² Pennsylvania Department of Agriculture, Pennsylvania Veterinary Laboratory, Harrisburg, PA, USA.
²³ Pennsylvania Animal Diagnostic Laboratory, New Bolton Center, University of Pennsylvania, Kenneth Square, PA, USA.
²⁴ School of Veterinary Medicine, The Ryan Veterinary Hospital Clinical Microbiology Laboratory, University of Pennsylvania, Philadelphia, PA, USA.
²⁵ Texas A&M University, College Station, TX, USA.
²⁶ College of Veterinary Medicine, Washington Animal Disease Diagnostic Laboratory, Washington State University, Pullman, WA, USA.

PMID: 31060608
PMCID: PMC6501310
DOI: 10.1186/s12917-019-1864-2

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.

Keywords: Antimicrobial resistance; One health; Surveillance; Whole-genome sequencing.

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Figures

**Fig. 1**
Phylogeny and Antimicrobial Resistance Gene Predictions in *E. coli.* Midpoint-rooted core genome phylogenetic tree of *E. coli* isolates with ARG predictions. Each column corresponds to the ARG listed along the top, with colors corresponding to the antibiotic class to which that gene confers resistance. A filled box indicates the detection of that gene

**Fig. 2**
Number of Human-related *S. enterica* Isolates by Host Organism. Red bars show the number of isolates from each host organism that were separated from a human isolate by 20 or fewer SNPs. Grey bars show the number of isolates separated from a human isolate by more than 20 SNPs

**Fig. 3**
Number of ARGs detected by Host Organism and Human-relatedness. Box-and-whisker plots showing the number of ARGs detected (a) in isolates from each host type and (b) is isolates separated from a human isolate by 20 or fewer (red) or more than twenty (grey) SNPs

**Fig. 4**
Heatmap of *S. enterica* ARGs by Serovar. Each row corresponds to a serovar, ordered by number of isolates. Each column is an ARG, clustered by co-occurrence as shown by the dendrogram. Darker colors indicate that a given gene is present in a higher proportion of isolates of that serovar

**Fig. 5**
Phylogeny and Antimicrobial Resistance Gene Predictions in *S. pseudintermedius.* Midpoint-rooted core genome phylogenetic tree of *S. pseudintermedius* isolates with ARG predictions. Each column corresponds to the ARG listed along the top, with colors corresponding to the antibiotic class to which that gene confers resistance. A filled box indicates the detection of that gene

**Fig. 6**
Geographical distribution and organization of Vet-LIRN WGS and Source laboratories. Twenty source laboratories (19 is the U.S. and one in Canada) (red) collected isolates. Four WGS labs (blue) selected five collaborating source labs each and sequenced a subset of the isolates submitted by their source labs. Remaining Vet-LIRN laboratories, currently not participating in the project, are shown in black. Additional labs became source labs in 2018. License for using and editing US Map Template for Power Point was purchased from Envato Pty Ltd., PO Box 16,122, Collins Street West, Victoria, 8007 Australia

See this image and copyright information in PMC

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References

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[1] CDC. Antibiotic Resistance Threats in the United States, 2013. Atlanta, Georgia 2013.

[2] CDC. Antibiotic Resistance Threats in the United States, 2013. Atlanta, Georgia 2013.

[3] Kahn LH. Antimicrobial resistance: a one health perspective. Trans R Soc Trop Med Hyg. 2017;111(6):255–260. doi: 10.1093/trstmh/trx050. - DOI - PubMed

[4] Kahn LH. Antimicrobial resistance: a one health perspective. Trans R Soc Trop Med Hyg. 2017;111(6):255–260. doi: 10.1093/trstmh/trx050. - DOI - PubMed

[5] NARMS. 2015 National Antimicrobial Ristance Monitoring System Integrated Report. In: FDA US, editor. Silver Spring, MD 2017.

[6] NARMS. 2015 National Antimicrobial Ristance Monitoring System Integrated Report. In: FDA US, editor. Silver Spring, MD 2017.

[7] DANMAP. DANMAP 2017 - Use of antimicrobial agents and occurrence of antimicrobial resistance in bacteria from food animals, food and humans in Denmark. In: National Food Institute SSI, National Veterinary Institute, editor. Denmark2017.

[8] DANMAP. DANMAP 2017 - Use of antimicrobial agents and occurrence of antimicrobial resistance in bacteria from food animals, food and humans in Denmark. In: National Food Institute SSI, National Veterinary Institute, editor. Denmark2017.

[9] Canada PHAo. Canadian Antimicrobial Resistance Surveillance System 2017 REPORT. In: Canada PHAo, editor. Ottawa, ON 2017.

[10] Canada PHAo. Canadian Antimicrobial Resistance Surveillance System 2017 REPORT. In: Canada PHAo, editor. Ottawa, ON 2017.

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