Characterization of rumen microbiome and metabolome from oro-esophageal tubing and rumen cannula in Holstein dairy cows

Abstract

Less invasive rumen sampling methods, such as oro-esophageal tubing, became widely popular for exploring the rumen microbiome and metabolome. However, it remains unclear if such methods represent well the rumen contents from the rumen cannula technique. Herein, we characterized the microbiome and metabolome in the rumen content collected by an oro-esophageal tube and by rumen cannula in ten multiparous lactating Holstein cows. The 16S rRNA gene was amplified and sequenced using the Illumina MiSeq platform. Untargeted metabolome was characterized using gas chromatography of a time-of-flight mass spectrometer. Bacteroidetes, Firmicutes, and Proteobacteria were the top three most abundant phyla representing ~ 90% of all samples. Although the pH of oro-esophageal samples was greater than rumen cannula, we found no difference in alpha and beta-diversity among their microbiomes. The overall metabolome of oro-esophageal samples was slightly different from rumen cannula samples yet more closely related to the rumen cannula content as a whole, including its fluid and particulate fractions. Enrichment pathway analysis revealed a few differences between sampling methods, such as when evaluating unsaturated fatty acid pathways in the rumen. The results of the current study suggest that oro-esophageal sampling can be a proxy to screen the 16S rRNA rumen microbiome compared to the rumen cannula technique. The variation introduced by the 16S rRNA methodology may be mitigated by oro-esophageal sampling and the possibility of increasing experimental units for a more consistent representation of the overall microbial population. Studies should consider an under or over-representation of metabolites and specific metabolic pathways depending on the sampling method.

Figure 1

Rumen pH (A) and upstream denoising pipeline output metrics displaying total sequences (B) number of chimeras (C) unused sequences (D) amongst oro-esophageal tubing and the respective fractions from rumen cannula. Statistical differences across group means were declared at P ≤ 0.05. Different superscripts mean groups differ through the Tukey–Kramer test performed at P ≤ 0.05 significance level.

Figure 2

Descriptive analyses of the rumen microbiome composition at the phylum (A) and genus (B) taxonomy levels in high-producing Holstein cows. Rumen sampling was performed using an oro-esophageal tubing procedure to compare microbiome differences with samples collected from the rumen cannula. The latter was represented as a whole (fluid and particulate) and with the two fractions separated. Data show that the 16S rRNA sequencing technique has large variation independently of the sampling method, suggesting this issue may be mitigated through oro-esophageal sampling that allows a considerable increase in experimental units for a more consistent representation of the overall microbial population.

Figure 3

Downstream analyses for alpha-diversity microbiome metrics displaying Chao1 (A), Inverse Simpson (B), Shannon Index (C), rarity index [low (D) and rare (E) mean relative abundances] microbial taxa amongst oro-esophageal tubing and the respective fractions from rumen cannula. Statistical differences across group means were declared at P ≤ 0.05.

Figure 4

Principal coordinate analysis (PCoA) of the bacterial community composition using: (A) prevalence interval for microbiome evaluation (PIME) filtered data to remove noise from taxa not prevalent within sample groups; (B) using all microbial taxa (ASV) from centered-log ratio normalization; and the latter (C) at the phylum, and (D) genus taxonomy levels. Statistical differences for permutational multivariate analysis of variance (PERMANOVA) were declared at P ≤ 0.05.

Figure 5

Partial least square-discriminant analysis (PLS-DA) of ruminal metabolites from ruminal samples collected through an oro-esophageal tubing and the respective fractions from the rumen cannula. A 2-D representation of differences in known (A) and unknown (B) metabolome composition is displayed for the illustration of how closely related the oro-esophageal tubing metabolome samples are to the respective fractions from the rumen cannula. A 3-D representation of known (C) and unknown (D) metabolome composition is displayed to demonstrate that there are still differences between the oro-esophageal tubing procedure and rumen cannula metabolome samples that need to be considered in future studies.

Figure 6

Hierarchical clustering heatmap showing top 50 metabolites detected through analysis of variance to differ in rumen sampling methods. Color differences indicate the Pearson correlation of metabolite ion abundances and sampling method. Wards clustering method was used to assess similarity among sampling methods and is displayed at the top portion of the heatmap. Statistical differences were declared at P ≤ 0.05. Heatmap was produced on Metaboanalyst 5.0 (https://www.metaboanalyst.ca/).

Figure 7

Enrichment pathway analysis was performed in Metaboanalyst 5.0 using the KEGG pathway database^–. The figure displays the top 25 most enriched pathways (A) that differed between the oro-esophageal tubing procedure and a complete sample from the rumen cannula (fluid and particulate together). (B) graphical visualization of metabolite differences between the two sampling techniques within some of the top 25 most enriched pathways. Statistical differences were declared at P ≤ 0.05.