11:00 am - 12:00 pm
A graduate exam seminar is a presentation of the student’s final research project for their degree.
This is an ALES MSc Final Exam Seminar by Klevis Haxhiaj. This seminar is open to the general public to attend.
Meeting ID: 962 1132 8443
Thesis Topic: Blood and Urinary Metabotyping Reveals Potential Screening Biomarkers for Identifying Dairy Cows at Risk of Subclinical Mastitis During the Dry Off Period
MSc with Drs. Burim Ametaj and David Wishart.
Subclinical mastitis (SCM) remains one of the most important infectious diseases of dairy cows associated with considerable losses in milk production and financial revenue. Currently, most SCM research and practical methods focus on diagnosing this intramammary infection (IMI) by counting somatic cells (SCC) in milk throughout lactation. Therefore, this study aimed to identify metabolic alterations in the serum and urine of pre-SCM cows during the dry period, along with developing panels of screening biomarkers for lab and pen-side tests. Early identification of susceptible cows will enable better preventative and management strategies.
A combination of flow injection liquid chromatography coupled with tandem mass spectrometry (FIA/LC-MS/MS) analyses were used to 580 blood and urine samples collected from 145 Holstein cows at –8 and –4 wks before the expected date of calving. Cows enrolled in this nested-case control study were then monitored for the development of postpartum diseases. Fifteen cows were free of any condition (CON), and just 10 cows presented only high SCC after calving and were free of other diseases. Metabolomics identified 126 serum metabolites from which 59 at –8 wks and 47 at –4 wks were found altered (P ≤ 0.05) in pre-SCM cows compared to CON. The main metabolite classes were related to lipid metabolism, such as acylcarnitines (ACs), lysophosphatidylcholines (LPCs), phosphatidylcholines (PCs) and sphingomyelins (SMs). Others were amino acids (AAs), methyl donor compounds, organic acids (OAs), and several carbohydrate species. Univariate, multivariate, and machine learning analysis indicated that a panel of 4 serum metabolites including alanine, leucine, betaine, and ornithine (AUC = 0.92; P < 0.001) at –8 wks and alanine, pyruvate, methylmalonate, and lactate (AUC = 0.92, P < 0.01) at –4 wks before parturition might serve as screening biomarkers for SCM. On the other hand, a total of 82 metabolites were found in the urine samples, and only 27 compounds (P ≤ 0.05) were different for each sampling period. The most discriminating metabolites were ACs, several AAs and their derivatives, glucose, and OAs. Further regression analysis showed ADMA, proline, leucine, and homovanillate (AUC = 0.88; P = 0.02) at –8 wks and ADMA, spermidine, methylmalonic acid and citrate (AUC = 0.88, P = 0.03) at –4 wks as specific biomarkers for SCM.
Overall, these data indicated systemic metabolic alterations and differentiation of SCM cows against CON and provided more information on the pathobiology of SCM. These screening biomarkers also offer the potential to develop lab and pen-side tests to identify cows at risk of SCM during the dry period. Our whole cows’ health status dataset demonstrated that many other cows were positive with SCM and one or more other diseases, including ketosis, leukosis, retained placenta, lameness, and milk fever. This complicates the development of lab and pen-side tests and warrants more research to explore the possibility of identifying specific metabolites for SCM only that can separate these cows from the other diseases.