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
Autor: | Joy Scaria, Renee R. Anderson, Donna J. Kelly, Milton Thomas, Jing Wu, Patrick K. Mitchell, Shelley C. Rankin, Brian V. Lubbers, Durda Slavic, Daniel B. Paulsen, Karen Olsen, Deborah Reed, Rinosh Mani, Laura B. Goodman, Sarah M. Nemser, Gregory H. Tyson, Orhan Sahin, Yugendar R. Bommineni, Claire R. Burbick, Olgica Ceric, Tracie Jenkins, Jing Cui, Nagaraja R. Thirumalapura, Shipra Mohan, Laura Peak, Rebecca P. Wilkes, Martha Pulido, Susan Sanchez, G. Kenitra Hendrix, Sara D. Lawhon, Alma Roy, Brett T. Webb, Rebecca J. Franklin-Guild, Lanny W. Pace, Anil J. Thachil, Melanie Prarat, Yan Zhang, Linto Antony, Megan E. Jacob, Deepanker Tewari, Sarmila Dasgupta, Renate Reimschuessel, Akhilesh Ramachandran, Amar Patil |
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Rok vydání: | 2018 |
Předmět: |
Veterinary Medicine
Salmonella Veterinary medicine medicine.medical_specialty Canada 040301 veterinary sciences Biology medicine.disease_cause Antimicrobial resistance 0403 veterinary science 03 medical and health sciences Antibiotic resistance medicine Animals One Health 030304 developmental biology 2. Zero hunger Whole genome sequencing 0303 health sciences Whole-genome sequencing lcsh:Veterinary medicine Surveillance General Veterinary Bacteria Whole Genome Sequencing Animal Sources SCCmec Public health 04 agricultural and veterinary sciences General Medicine Bacterial Infections Monitoring program United States 3. Good health lcsh:SF600-1100 Laboratories Research Article |
Zdroj: | BMC Veterinary Research BMC Veterinary Research, Vol 15, Iss 1, Pp 1-13 (2019) |
ISSN: | 1746-6148 |
Popis: | 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. Electronic supplementary material The online version of this article (10.1186/s12917-019-1864-2) contains supplementary material, which is available to authorized users. |
Databáze: | OpenAIRE |
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