| Popis: |
The preruminant microbiome has the potential to set the stage for later life feed efficiency and is critical to proper development within the rumen. We hypothesized that the rumen microbiome is established at or near birth and is subject to maternal influences that can influence preruminant and postruminant microbial profiles. Our objective was to determine how mode of delivery and rearing affected the development of the rumen microbiome. Bred mature Charolais cows were randomly allocated to one of the three treatment groups: control (CON; n = 8), bottle reared (BOT; n = 8), and caesarian section (CSET; n = 8), where CON was vaginal birth and raised by their dam; BOT was vaginal birth, then removed 24-h post-parturition, and raised on commercial milk replacer; and CSET was born via caesarian section and raised by their respective dams. Calf rumen fluid was collected from calves at 1, 3, and 28 d of age via oral lavage and metagenomic shotgun sequencing was performed using the Illumina NextSeq 500 platform. Sequence data were analyzed utilizing Metataxa2 for taxonomic assignment followed by QIIME to determine α- and β-diversity differences. A total of 1,113 taxa had differential abundance when comparing day while 66 taxa had differential abundance across treatment groups. There were no differences across treatment group richness (P > 0.05), but day 28 was significantly more rich (P = 0.003) compared with days 1 and 3 with no difference between days 1 and 3 (P = 0.58). No differences in β-diversity were detected across treatment group with the exception of greater variance in the BOT and CSET compared with the CON (P = 0.048). Microbial profiles of day 1 are more similar to each other than day 3 or 28 (P = 0.03); day 3 is more similar to each other than day 1 or 28 (P = 0.03); and day 28 is more similar to each other than day 1 or 3 (P = 0.03). These data suggest that while treatment group did not have a large impact on microbial diversity, several specific taxa were affected by treatment group. Day affects the microbial diversity both within and among samples. Understanding how these profiles shift with age is critical to understanding key intervention periods for optimal alteration of the microbiome. |
