High-throughput Phenotyping of Rumen Microbial Contents Using Buccal Swabs

Authors: Young, Juliana; SKARLUKPKA, JOSEPH - University Of Wisconsin; TASSINARI, RAFAEL - Federal University Of Goias; FISCHER, AMELIE - The French Livestock Institute; Kalscheur, Kenneth; McClure, Jennifer; Weimer, Paul; SUEN, GARRET - University Of Wisconsin; Bickhart, Derek

Submitted to: American Dairy Science Association Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 2/24/2020
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: The rumen microbial community is the agent that allows cattle and other ruminants to process complex plant polymers into volatile fatty acids. Traditional methods to sample rumen microbes often involve labor-intensive techniques, thereby limiting the number of animals that could be sampled in a specific study. In order to statistically detect the effects of inter-animal variation that impacts rumen microbial composition, many hundreds of rumen samples would be required for each trial. In this study, we tested the viability of using buccal swabs as a proxy of the rumen microbial contents in a timecourse experiment on eight cannulated cows. Rumen contents and buccal swabs were collected at six equally spaced timepoints, with the first timepoint being 2 hours prior to feeding. Simpson diversity and Shannon evenness estimates of the microbial counts of each sample revealed that the first timepoint had the lowest diversity and highest evenness (Tukey HSD < 0.05) out of all other timepoints. Principal component analysis confirmed that the buccal swab samples from the first timepoint were the most similar to paired rumen samples taken at the same times. Using a Random Forest Classifier analysis, we estimated the Gini importance scores for individual microbial taxa as a proxy of their uniqueness to the rumen or oral environments of the cows. Using these estimates, we identified 18 oral-only microbial taxa that are contaminants and could be removed from future comparisons using this method. Finally, we attempted to estimate the exact relative abundance of rumen microbial taxa from buccal swab samples using paired rumen-swab data in a Random Forest Regression model. The model was found to have moderate (~ 38%) accuracy in cross-validation studies, suggesting that there are other factors such as salivary flow that could impact microbial data from buccal swabs. Our data suggests that buccal swabs can serve as fast and suitable proxies for rumen microbial contents of dairy cattle, but that additional factors must be measured to improve direct regression of results to those of the rumen.