MétaCan
Menu
Back to cohort
Record W3120420307 · doi:10.1186/s42523-021-00092-6

Metatranscriptomic analyses reveal ruminal pH regulates fiber degradation and fermentation by shifting the microbial community and gene expression of carbohydrate-active enzymes

2021· article· en· W3120420307 on OpenAlexafffund
Mengmeng Li, R.R. White, Le Luo Guan, Laura Harthan, M.D. Hanigan

Bibliographic record

VenueAnimal Microbiome · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Alberta
FundersNational Institute of Food and AgricultureAlberta Livestock and Meat AgencyU.S. Department of Agriculture
KeywordsRumenFirmicutesBiologyFermentationFood scienceBacteroidetesXylanaseCellulaseProteobacteriaDigestion (alchemy)RuminococcusMicrobiologyBiochemistryCelluloseEnzymeChemistryGene16S ribosomal RNAGut flora

Abstract

fetched live from OpenAlex

BACKGROUND: Volatile fatty acids (VFA) generated from ruminal fermentation by microorganisms provide up to 75% of total metabolizable energy in ruminants. Ruminal pH is an important factor affecting the profile and production of VFA by shifting the microbial community. However, how ruminal pH affects the microbial community and its relationship with expression of genes encoding carbohydrate-active enzyme (CAZyme) for fiber degradation and fermentation are not well investigated. To fill in this knowledge gap, six cannulated Holstein heifers were subjected to a continuous 10-day intraruminal infusion of distilled water or a dilute blend of hydrochloric and phosphoric acids to achieve a pH reduction of 0.5 units in a cross-over design. RNA-seq based transcriptome profiling was performed using total RNA extracted from ruminal liquid and solid fractions collected on day 9 of each period, respectively. RESULTS: Metatranscriptomic analyses identified 19 bacterial phyla with 156 genera, 3 archaeal genera, 11 protozoal genera, and 97 CAZyme transcripts in sampled ruminal contents. Within these, 4 bacteria phyla (Proteobacteria, Firmicutes, Bacteroidetes, and Spirochaetes), 2 archaeal genera (Candidatus methanomethylophilus and Methanobrevibacter), and 5 protozoal genera (Entodinium, Polyplastron, Isotricha, Eudiplodinium, and Eremoplastron) were considered as the core active microbes, and genes encoding for cellulase, endo-1,4-beta- xylanase, amylase, and alpha-N-arabinofuranosidase were the most abundant CAZyme transcripts distributed in the rumen. Rumen microbiota is not equally distributed throughout the liquid and solid phases of rumen contents, and ruminal pH significantly affect microbial ecosystem, especially for the liquid fraction. In total, 21 bacterial genera, 4 protozoal genera, and 6 genes encoding CAZyme were regulated by ruminal pH. Metabolic pathways participated in glycolysis, pyruvate fermentation to acetate, lactate, and propanoate were downregulated by low pH in the liquid fraction. CONCLUSIONS: The ruminal microbiome changed the expression of transcripts for biochemical pathways of fiber degradation and VFA production in response to reduced pH, and at least a portion of the shifts in transcripts was associated with altered microbial community structure.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.266
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations44
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueAnimal MicrobiomeSame topicRuminant Nutrition and Digestive PhysiologyFrench-language works237,207