|NOL, P - Animal And Plant Health Inspection Services (APHIS), National Wildlife Center|
|ELLIS, C - Animal And Plant Health Inspection Services (APHIS), National Wildlife Center|
|STAHL, R - Animal And Plant Health Inspection Services (APHIS), National Wildlife Center|
|HAICK, H - Israel Institute Of Technology|
|RHYAN, J - Animal And Plant Health Inspection Services (APHIS), National Wildlife Center|
|VERCAUTEREN, K - Animal And Plant Health Inspection Services (APHIS), National Wildlife Center|
|MCCOLLUM, M - Animal And Plant Health Inspection Service (APHIS)|
|SALMAN, M - Colorado State University|
Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 5/1/2014
Publication Date: 6/16/2014
Citation: Nol, P., Ellis, C.K., Stahl, R.S., Haick, H., Rhyan, J.C., Vercauteren, K.C., Mccollum, M.P., Waters, W.R., Palmer, M.V., Salman, M.D. 2014. Analysis of breath volatile organic compounds as a screening tool for detection of Tuberculosis in cattle [abstract]. Abstract No. 93.
Technical Abstract: • Keywords: bovine tuberculosis; Mycobacterium bovis; breath analysis; volatile organic compound; gas chromatography; mass spectrometry; NaNose • Introduction: This presentation describes two studies exploring the use of breath VOCs to identify Mycobacterium bovis infection in cattle. • Methods: Study 1- breath samples were collected onto sorbent cartridges from ten M. bovis-positive cattle and four negative cattle from a naturally infected dairy in southern Colorado, USA. Additionally, breath was collected from 13 negative cattle at a dairy in northern Colorado. Samples were analyzed using gas chromatography/mass spectrometry (GC/MS). A nanotechnology-based array of sensors (NaNose) was tailored based on the GC/MS results for detection of breath from M. bovis-infected cattle. Sensor responses were used as inputs for a discriminant factor analysis pattern recognition algorithm. Study 2- Samples were analyzed using GC/MS. Breath samples from 23 male dairy calves (7 non-infected and 16 M. bovis-infected) were collected 90 days post experimental inoculation with 104 cfu M. bovis. Chromatographic data were analyzed using standard analytical chemical and metabolomic analyses, principle components analysis, and a linear discriminant algorithm. • Results: Study 1-GC/MS analysis identified two VOCs associated with infection and two with apparently non-infected animals. The NaNose identified all infected cattle with 21% false positives in the controls. Study 2- Linear discriminant analysis models based on ions identified as significantly different across treatment groups allowed for classification of M. bovis-infected cattle vs. controls. • Conclusion: The findings provide proof of concept that breath-derived volatile organic compound analysis can be used to differentiate between healthy and M. bovis-infected cattle.