Abstract
Genetic material from rumen microorganisms can be found within the oral cavity, and hence there is potential in using the oral microbiome as a proxy of the ruminal microbiome. Feed intake (FI) influences the composition of rumen microbiota and might directly influence the oral microbiome in dairy cattle. Ruminal content samples (RS) from 29 cows were collected at the beginning of the study and also 42 d later (RS0 and RS42, respectively). Additionally, 18 oral samples were collected through buccal swabbing at d 42 (OS42) from randomly selected cows. Samples were used to characterize and compare the taxonomy and functionality of the oral microbiome using Nanopore sequencing and to evaluate the feasibility of using the oral microbiome to estimate FI. Up to 186 taxonomical features were found differentially abundant (DA) between RS and OS42. Similar results were observed when comparing OS42 to RS collected at different days. Microorganisms associated with the liquid fraction of the rumen were less abundant in OS42 as these were probably swallowed after regurgitation. Up to 1,102 KEGGs were found to be DA between RS and OS42 and these results differed when comparing time of collection, but differentially abundant KEGGs were mainly associated to metabolism in both situations. Models based on the oral microbiome and rumen microbiome differed in their selection of microbial groups and biological pathways to predict FI. In the rumen, fiber-associated microorganisms are considered suitable indicators of feed intake. On the other hand, biofilm formers like Gammaproteobacteria or Bacteroidia classes are deemed appropriate proxies for predicting feed intake from oral samples. Models from RS exhibited some predictive ability to estimate FI, but OS significantly outperformed them. The best lineal model to estimate FI was obtained with the relative abundance of taxonomical feature at genera level, achieving an average R2 equal to 0.88 within the training data, and a root mean square error equal to 3.46 ± 0.83 (standard deviation; SD) kg of DM/ as well as a Pearson correlation coefficient between observed and estimated FI of 0.48 ± 0.30 in the test data. The results from this study suggest that oral microbiome has potential to predict FI in dairy cattle, and it encourages validating this potential in other populations.
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