Design of a High-Throughput Real-Time PCR System for Detection of Bovine Respiratory and Enteric Pathogens

Bovine respiratory and enteric diseases have a profound negative impact on animal, health, welfare, and productivity. A vast number of viruses and bacteria are associated with the diseases. Pathogen detection using real-time PCR (rtPCR) assays performed on traditional rtPCR platforms are costly and time consuming and by that limit the use of diagnostics in bovine medicine. To diminish these limitations, we have developed a high-throughput rtPCR system (BioMark HD; Fluidigm) for simultaneous detection of the 11 most important respiratory and enteric viral and bacterial pathogens. The sensitivity and specificity of the rtPCR assays on the high-throughput platform was comparable with that of the traditional rtPCR platform. Pools consisting of positive and negative individual field samples were tested in the high-throughput rtPCR system in order to investigate the effect of an individual sample in a pool. The pool tests showed that irrespective of the size of the pool, a high-range positive individual sample had a high influence on the cycle quantification value of the pool compared with the influence of a low-range positive individual sample. To validate the test on field samples, 2,393 nasal swab and 2,379 fecal samples were tested on the high-throughput rtPCR system as pools in order to determine the occurrence of the 11 pathogens in 100 Danish herds (83 dairy and 17 veal herds). In the dairy calves, Pasteurella multocida (38.4%), rotavirus A (27.4%), Mycoplasma spp. (26.2%), and Trueperella pyogenes (25.5%) were the most prevalent pathogens, while P. multocida (71.4%), Mycoplasma spp. (58.9%), Mannheimia haemolytica (53.6%), and Mycoplasma bovis (42.9%) were the most often detected pathogens in the veal calves. The established high-throughput system provides new possibilities for analysis of bovine samples, since the system enables testing of multiple samples for the presence of different pathogens in the same analysis test even with reduced costs and turnover time.

Abstract licence: CC BY

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.