Author
Kudva, Indira | |
PERERA, ANN - Iowa State University | |
BAIS, PRETTI - The Jackson Laboratory | |
MANOHAR, JOHN - Pathovacs, Inc | |
REECY, JAMES - Iowa State University |
Submitted to: Meeting Abstract
Publication Type: Abstract Only Publication Acceptance Date: 6/16/2015 Publication Date: 9/15/2015 Citation: Kudva, I.T., Perera, A.M., Bais, P., Manohar, J., Reecy, J. 2015. Blood metabolome profiles of cattle colonized with Escherichia coli O157 [abstract]. 9th International Shiga Toxin (Verocytotoxin) - producing Escherichia Coli Conference. Abstract No. D-18. Interpretive Summary: Technical Abstract: Metabolomics is being increasingly used for diagnosis of asymptomatic/difficult-to-diagnose diseases in humans including parasitic (i.e. protozoan, schistosomal), viral (i.e. cytomegalovirus), bacterial (i.e. cystic fibrosis caused by Pseudomonas), genetic (i.e. autism) and cancer (i.e. gastric cancer) as it yields consistent, reliable, and reproducible biomarkers. Besides tissue samples, metabolomes of body fluids such as urine, saliva and blood/plasma have been analyzed. Cattle, the primary reservoirs for STEC also remain asymptomatic throughout colonization. Hence, we extrapolated this approach to cattle with the goal of identifying metabolomic biomarkers that would allow for rapid identification of STEC-colonized cattle. As a proof-of-principle we applied metabolomics, using Gas Chromatography-Mass Spectrometry (GC-MS) and Fourier Transform-Ion Cyclotron Resonance (FT-ICR) mass spectrometry, to identify differential abundances of metabolites in blood samples of an animal experimentally colonized with E.coli O157 (O157). Bovine whole blood samples were collected before, during and after O157 colonization as correlated with fecal culture for O157. Each sample representing a single sampling time was analyzed in triplicate. Our GC-MS analysis detected 242 metabolites in the bovine blood samples. 42/242 metabolites significantly changed between the three time points with a FDR (False Discovery Rate) threshold of 10%. The hierarchical cluster analysis and PCA showed clear separation between the metabolic profiles of the samples taken at three time points thus providing an opportunity to identify cattle harboring O157. We are further investigating the consistency of the metabolome profiles in additional bovine blood samples from O157 and non-O157 STEC-colonized cattle. |