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Characterization of variations within the rumen metaproteome of Holstein dairy cattle relative to morning feed offering.

ABSTRACT: Few studies have utilized proteomic techniques to progress our knowledge of protein-mediated pathways within the rumen microbial community, and no previous research has used these techniques to investigate the patterns or variations of these proteins within this community. It was hypothesized that there would be fluctuations of rumen microbial protein abundances due to feed intake-mediated nutrient availability and that these could be identified using non gel-based proteomic techniques. This study investigated the fluctuations of bovine rumen metaproteome utilizing three mid to late-lactation Holsteins. Rumen fluid was collected at three timepoints on three days relative to their first morning feed offering (0?h, 4?h, and 6?h). Samples were pooled within timepoint within cow across day, analyzed using LC-MS/MS techniques, and analyzed for variations across hour of sampling using PROC MIXED of SAS with orthogonal contrasts to determine linear and quadratic effects. A total of 658 proteins were characterized across 19 microbial species, with 68 proteins identified from a variety of 15 species affected by time of collection. Translation-related proteins such as 50S and 30S ribosomal protein subunit variants and elongation factors were positively correlated with hour of sampling. Results suggest that as nutrients become more readily available, microbes shift from conversion-focused biosynthetic routes to more encompassing DNA-driven pathways.

SUBMITTER: Honan MC

PROVIDER: S-EPMC7035244 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Characterization of variations within the rumen metaproteome of Holstein dairy cattle relative to morning feed offering.

Honan Mallory C MC Greenwood Sabrina L SL

Scientific reports 20200221 1

Few studies have utilized proteomic techniques to progress our knowledge of protein-mediated pathways within the rumen microbial community, and no previous research has used these techniques to investigate the patterns or variations of these proteins within this community. It was hypothesized that there would be fluctuations of rumen microbial protein abundances due to feed intake-mediated nutrient availability and that these could be identified using non gel-based proteomic techniques. This stu ...[more]

PMID: 32081893

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Project description:Mitigation of greenhouse gas emissions is relevant for reducing the environmental impact of ruminant production. In this study, the rumen microbiome from Holstein cows was characterized through a combination of 16S rRNA gene and shotgun metagenomic sequencing. Methane production (CH4 ) and dry matter intake (DMI) were individually measured over 4-6 weeks to calculate the CH4 yield (CH4 y = CH4 /DMI) per cow. We implemented a combination of clustering, multivariate and mixed model analyses to identify a set of operational taxonomic unit (OTU) jointly associated with CH4 y and the structure of ruminal microbial communities. Three ruminotype clusters (R1, R2 and R3) were identified, and R2 was associated with higher CH4 y. The taxonomic composition on R2 had lower abundance of Succinivibrionaceae and Methanosphaera, and higher abundance of Ruminococcaceae, Christensenellaceae and Lachnospiraceae. Metagenomic data confirmed the lower abundance of Succinivibrionaceae and Methanosphaera in R2 and identified genera (Fibrobacter and unclassified Bacteroidales) not highlighted by metataxonomic analysis. In addition, the functional metagenomic analysis revealed that samples classified in cluster R2 were overrepresented by genes coding for KEGG modules associated with methanogenesis, including a significant relative abundance of the methyl-coenzyme M reductase enzyme. Based on the cluster assignment, we applied a sparse partial least-squares discriminant analysis at the taxonomic and functional levels. In addition, we implemented a sPLS regression model using the phenotypic variation of CH4 y. By combining these two approaches, we identified 86 discriminant bacterial OTUs, notably including families linked to CH4 emission such as Succinivibrionaceae, Ruminococcaceae, Christensenellaceae, Lachnospiraceae and Rikenellaceae. These selected OTUs explained 24% of the CH4 y phenotypic variance, whereas the host genome contribution was ~14%. In summary, we identified rumen microbial biomarkers associated with the methane production of dairy cows; these biomarkers could be used for targeted methane-reduction selection programmes in the dairy cattle industry provided they are heritable.

Project description:Our aim was to simultaneously investigate the gut bacteria typical characteristic and conduct rumen metabolites profiling of high production dairy cows when compared to low-production dairy cows. The bacterial differences in rumen fluid and feces were identified by 16S rDNA gene sequencing. The metabolite differences were identified by metabolomics profiling with liquid chromatography mass spectrometry (LC-MS). The results indicated that the high-production dairy cows presented a lower rumen bacterial richness and species evenness when compared to low-production dairy cows. At the phylum level, the high-production cows increased the abundance of Proteobacteria and decreased the abundance of Bacteroidetes, SR1, Verrucomicrobia, Euryarchaeota, Planctomycetes, Synergistetes, and Chloroflexi significantly (p < 0.05). At the genus level, the rumen fluid of the high-production group was significantly enriched for Butyrivibrio, Lachnospira, and Dialister (p < 0.05). Meanwhile, rumen fluid of high-production group was depleted for Prevotella, Succiniclasticum, Ruminococcu, Coprococcus,YRC22, CF231, 02d06, Anaeroplasma, Selenomonas, and Ruminobacter significantly (p < 0.05). A total of 92 discriminant metabolites were identified between high-production cows and low-production cows. Compared to rumen fluid of low-production dairy cows, 10 differential metabolites were found up-regulated in rumen fluid of high-production dairy cows, including 6alpha-Fluoropregn-4-ene-3,20-dione, 3-Octaprenyl-4-hydroxybenzoate, disopyramide, compound III(S), 1,2-Dimyristyl-sn-glycerol, 7,10,13,16-Docosatetraenoic acid, ferrous lactate, 6-Deoxyerythronolide B, vitamin D2, L-Olivosyl-oleandolide. The remaining differential metabolites were found down-regulated obviously in high-production cows. Metabolic pathway analyses indicated that most increased abundances of rumen fluid metabolites of high-yield cows were related to metabolic pathways involving biosynthesis of unsaturated fatty acids, steroid biosynthesis, ubiquinone and other terpenoid-quinone biosynthesis. Most down-regulated metabolic pathways were relevant to nucleotide metabolism, energy metabolism, lipid metabolism and biosynthesis of some antibiotics.

Project description:BackgroundInbreeding depression refers to the decrease in mean performance due to inbreeding. Inbreeding depression is caused by an increase in homozygosity and reduced expression of (on average) favourable dominance effects. Dominance effects and allele frequencies differ across loci, and consequently inbreeding depression is expected to differ along the genome. In this study, we investigated differences in inbreeding depression across the genome of Dutch Holstein Friesian cattle, by estimating dominance effects and effects of regions of homozygosity (ROH).MethodsGenotype (75 k) and phenotype data of 38,792 cows were used. For nine yield, fertility and udder health traits, GREML models were run to estimate genome-wide inbreeding depression and estimate additive, dominance and ROH variance components. For this purpose, we introduced a ROH-based relationship matrix. Additive, dominance and ROH effects per SNP were obtained through back-solving. In addition, a single SNP GWAS was performed to identify significant additive, dominance or ROH associations.ResultsGenome-wide inbreeding depression was observed for all yield, fertility and udder health traits. For example, a 1% increase in genome-wide homozygosity was associated with a decrease in 305-d milk yield of approximately 99 kg. For yield traits only, including dominance and ROH effects in the GREML model resulted in a better fit (P?<?0.05) than a model with only additive effects. After correcting for the effect of genome-wide homozygosity, dominance and ROH variance explained less than 1% of the phenotypic variance for all traits. Furthermore, dominance and ROH effects were distributed evenly along the genome. The most notable region with a favourable dominance effect for yield traits was on chromosome 5, but overall few regions with large favourable dominance effects and significant dominance associations were detected. No significant ROH-associations were found.ConclusionsInbreeding depression was distributed quite equally along the genome and was well captured by genome-wide homozygosity. These findings suggest that, based on 75 k SNP data, there is little benefit of accounting for region-specific inbreeding depression in selection schemes.

Dataset Information

Characterization of variations within the rumen metaproteome of Holstein dairy cattle relative to morning feed offering.

Publications

Characterization of variations within the rumen metaproteome of Holstein dairy cattle relative to morning feed offering.

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