Rumen Microbiota Predicts Feed Efficiency of Primiparous Nordic Red Dairy Cows

Abstract

Efficient feed utilization in dairy cows is crucial for economic and environmental reasons. The rumen microbiota plays a significant role in feed efficiency, but studies utilizing microbial data to predict host phenotype are limited. In this study, 87 primiparous Nordic Red dairy cows were ranked for feed efficiency during their early lactation based on residual energy intake, and the rumen liquid microbial ecosystem was subsequently evaluated using 16S rRNA amplicon and metagenome sequencing. The study used amplicon data to build an extreme gradient boosting model, demonstrating that taxonomic microbial variation can predict efficiency (r_test = 0.55). Prediction interpreters and microbial network revealed that predictions were based on microbial consortia and the efficient animals had more of the highly interacting microbes and consortia. Rumen metagenome data was used to evaluate carbohydrate-active enzymes and metabolic pathway differences between efficiency phenotypes. The study showed that an efficient rumen had a higher abundance of glycoside hydrolases, while an inefficient rumen had more glycosyl transferases. Enrichment of metabolic pathways was observed in the inefficient group, while efficient animals emphasized bacterial environmental sensing and motility over microbial growth. The results suggest that inter-kingdom interactions should be further analyzed to understand their association with the feed efficiency of animals.

Keywords: feed efficiency; metagenomics; prediction; rumen bacteria; ruminants.

Figure 1

Contour surface of REI estimates (darker areas indicate a low REI neighborhood) on Bray–Curtis distance-based NMDS sample coordinates.

Figure 2

Accumulated local effects plot for all predictors with component values on x-axis and impact on prediction on y-axis. Only the archetype components (Arch) where the difference between maximum and minimum local effect is >1.5 are highlighted by color and labeled. In addition, Arch2 that appears in the surrogate model is highlighted. On each axis the average value is zero and the component values are scaled to unit standard deviation.

Figure 3

Simplified surrogate model representing the main findings as an inference tree. Archetype component (Arch) name, number of cows, statistical significance test, the split thresholds given at nodes, and the child branches. Leave scatter plots show the original REI (on the x-axis) and the model predicted REI (y-axis) for each animal (blue circle) and the simplified tree prediction for the group as a horizontal line. Gray ascending line is the fitted overall regression line.

Figure 4

The rumen bacterial composition at genus level of samples ordered according to their REI estimate, indicating (A) original composition and (B) reconstructed REI associated composition.

Figure 4

The rumen bacterial composition at genus level of samples ordered according to their REI estimate, indicating (A) original composition and (B) reconstructed REI associated composition.

Figure 5

Co-occurrence network based on the reconstructed abundance data. In the network the hub scores and the associations to REI are also indicated. The co-occurrence clusters are named based on their main hub taxa and their archetype component (Arch) association is indicated in parentheses. The single negative correlation is indicated as an orange edge linking the Paraprevotella to the Prevotella.

Figure 6

Abundances of CAZy families that were identified as significantly (FDR < 0.05) different between H-REI and L-REI groups.

Figure 7

Term-gene graph showing enriched KEGG pathways connected to their orthologs. Red color indicates enriched pathways in L-REI individuals, and blue indicates enrichment in H-REI individuals. The KEGG pathways are solid and the orthologs are semi-transparent, respectively. The term node size reflects the negative logarithm of the enrichment test p-value, which ranged from 10⁻⁶ (e.g., Proteasome) to 0.002 (Long-term potentiation; Mitophagy-animal). Few terms were shortened for visual clarity: Long-term potentiation (L.-t. potentiation), Protein processing in endoplasmic reticulum (Protein processing in ER), mRNA surveillance pathway (mRNA surveillance), and Progesterone-mediated oocyte maturation (Pr. oocyte maturation). Human disease terms were not included.