Back

Microbiota comparison of individual and pooled cow fecal samples from PEI dairy farms

Sanchez, J.

2025-05-30 microbiology
10.1101/2025.05.29.656927 bioRxiv
Show abstract

The aim of this study was to compare the microbiota diversity captured in individual versus pooled fecal samples from dairy cattle and evaluate the feasibility of using pooled sampling to assess the microbiota of dairy cattle at the herd level. A cross-sectional study used animals from 28 Prince Edward Island (PEI) dairy farms in Canada. The farms were visited between July and December 2020. Both free-stall and tie-stall housing systems were eligible. Manure samples from dry and lactating cows were obtained. Then, approximately 20g of fecal samples from each group were pooled. DNA extractions on all subsamples were performed using the Qiagen PowerMax Soil Kit and submitted for 16S rRNA gene amplification and sequencing. Operational taxonomic units were determined, and four alpha diversity indices were computed. A total of 128 and 132 manure samples from pos and prepartum cows, respectively, were analyzed. Mixed-effects random slope models were employed, incorporating herd-level random effects to estimate the correlation among individual samples and between individual and pooled samples. The estimated Shannon observed features, Pielou evenness and Faith PD were 5.9, 580, 0.93 and 44.1 from the individual and 5.93, 587, 0.93 and 45.5 from the pooled samples, respectively. All alpha diversity metrics were not significantly different between individual and pooled samples. Overall, pooled sampling does not significantly affect diversity and provides comparable results with individual samples, though it tends to show slightly higher diversity in some indices. This sampling strategy could be used in microbiota studies of dairy herds.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.