Online

Honan, Mallory Cate

Animal and Veterinary Sciences

2019

M.S.

Proteomic technology has been increasingly incorporated into agricultural research, as characterization of proteomes can provide valuable information for potential biomarkers of health and physiological status of an animal. As dairy cattle are a dominant production animal in the USA, their biofluids such as milk, blood, urine, and rumen fluid have been examined by proteomic analysis. The research outlined herein was performed to further characterize the dynamics of specific proteomes and relate them to dairy cattle physiology. The first experiment evaluated the diurnal dynamicity of the rumen metaproteome in Holstein dairy cattle. Rumen fluid was collected from three mid to late lactation multiparous dairy cattle (207 ± 53.5 days in milk) at three time points relative to their first morning offering of a total mixed ration (TMR) (0 h, 4 h, and 6 h after feeding). Samples were processed and labeled using Tandem Mass tagging before being further fractionated with a high pH reversed-phase peptide fractionation kit. Samples were analyzed by LC-MS/MS and statistically analyzed for variations across hour of sampling using the MIXED procedure of SAS with orthogonal contrasts. A total of 242 proteins were characterized across 12 microbial species, with 35 proteins identified from a variety of 9 species affected by time of collection. Translation-related proteins were correlated positively with increasing hour of sampling while more specific metabolic proteins were negatively correlated with increasing hour of sampling. Results suggest that as nutrients become more readily available, microbes shift from conversion-focused biosynthetic routes to more encompassing DNA-driven pathways. The second experiment aimed to characterize the milk fat globule membrane (MFGM) proteomes of colostrum and transition milk for comparison from multi- (n = 10) and primiparous (n = 10) Holstein dairy cattle. Samples were collected at four timepoints post-partum (milkings 1, 2, 4, and 14). After isolation of the protein lysates from the MFGM, proteins were labeled using Tandem Mass tagging and analyzed using LC-MS/MS techniques. Protein identification was completed using MASCOT and Sequest in Proteome Discoverer 2.2. Protein abundance values were scaled and analyzed using the MIXED procedure in SAS to determine the effect of parity, milking number, and parity x milking number, and the adaptive false-discovery rate (FDR)-adjusted P values were determined using the MULTTEST procedure of SAS. There were 104 proteins identified within the MFGM. Statistical analysis revealed that 44.2% of proteins were affected by parity, 70.2% by milking number, and 32.7% by the variable of parity x milking number. There was a two-fold difference in calcium sensing S100 proteins in cows differing in parity possibly due to the multiparous mammary gland being more adapted to the physiological demand of lactation or the lesser requirement of calcium in primiparous cows because of a lower production rate.