Feed efficiency and enteric methane emissions indices are inconsistent with the outcomes of the rumen microbiome composition.

ABSTRACT

The correlation between enteric methane emissions (eME) and feed efficiency (FE) in cattle is linked to the anaerobic fermentation of feedstuffs that occurs in the rumen. Several mathematical indices have been developed to predict feed efficiency and identify low methane emitters in herds. To investigate this, the current study aimed to evaluate the rumen microbial composition in the same group of animals ranked according to six different indices (three indices for FE and three for eME). Thirty-three heifers were ranked into three groups, each consisting of 11 animals, based on FE (feed conversion efficiency - FCE, residual weight gain - RG, and residual feed intake - RFI) and eME indices (production, yield, and intensity). Rumen fluids were collected using a stomach tube and analyzed using 16S rRNA and 18S rRNA, targeting rumen bacteria, archaea, and protozoa. The sequencing analysis revealed that the presence of unique microbial species in the rumen varies across animals ranked by the FE and eME indices. The High RG group harbored 17 unique prokaryotic taxa, while the High FCE group contained only seven. Significant differences existed in the microbial profiles of the animals based on the FE and eME indices. For instance, Raoultibacter was more abundant in the Intermediate RFI group but less so in the Intermediate RG and Intermediate FCE groups. The abundance of Entodinium was higher while Diplodinium was lower in the High FCE group, in contrast to the High RG and High RFI groups. Methanobrevibacter exhibited similar abundances across eME indices. However, the heifers did not demonstrate the same production, yield, and intensity of eME. The present findings underscore the importance of standardizing the FE and eME indices. This standardization is crucial for ensuring consistent and reliable assessments of the composition and function of the rumen microbiome across different herds.