No abstract

No abstract

Biting midges of the genus Culicoides (Diptera: Ceratopogonidae) were monitored at a Georgia (USA) site where epizootic hemorrhagic disease (EHD) and bluetongue (BT) viruses are enzootic among white-tailed deer (Odocoileus virginianus). Collections were made using a captive white-tailed deer and light traps from June 1993 through November 1994. We collected 210,482 females from the captive deer during morning and evening periods. Predominant species were C. lahillei (73%), C. stell!fer (16%), C. biguttatus (6%), C. niger (3%), C. spinosus (2%), and C. paraensis (0.2%). Other species were C. venustus, C. obsoletus/sanguisuga, C. haematopotus, C. guttipennis, and C. arboricola, which together represented <0.1% of the specimens collected. No C. variipennis, a known vector of EHD and BT viruses, were collected from the deer. An estimated 953,299 females were collected in 695 light-trap nights. The most common species in light-trap collections were C. spinosus (45%), C. biguttatus (27%) and C. stell(fer (24%). Culicoid.es variipennis was rare in the light-trap samples, representing <0.01% of the total collections. There was serological evidence from hunter-killed deer that local deer were infected with EHD and BT viruses during the study, particularly during 1994. A primary suspect vector was C. lahillei, which attacked the bait deer in large numbers during the summer and early fall of both 1993 and 1994. Based on their seasonality, relative abundance, and host-seeking activity, C. stell(fer and C. spinosus also were considered as possible vectors. However, virus isolation attempts on 113,716 Culicoides, including 62,530 C. lahillei and 32,769 C. stellzfer, were negative.

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.