New mechanistic insight into the digestion of complex dietary fibre by rumen microbiota using combinatorial high-resolution glycomic and transcriptomic analyses
Bibliographic record
Abstract
Abstract Background The rumen microbial community is considered the most efficient anaerobic digestive ecosystem known, yet less than half of the energy in low quality forages is actually metabolized. There is a knowledge gap regarding the specific factors that impede the ruminal digestion of plant cell walls or if rumen microbiota have the functional potential and activities to overcome these constraints. To address these issues, innovative experimental methods may provide a high-resolution understanding of the cell wall chemistries and higher-order structures that are resistant to microbial digestion and how they interact with the functional activities of the rumen microbial community. Results With this goal, we characterized the total tract indigestible residue (TTIR) from cattle fed a high-forage diet containing low-quality straw using two comparative glycomic approaches: ELISA-based glycome profiling and glycosidic linkage analysis. Using these techniques, we successfully detected numerous and diverse cell wall glycan epitopes in barley straw and TTIR and determined their relative abundance pre- and post-intestinal digestion. Of these, xyloglucans and heteroxylans were the most recalcitrant to digestion. Linkage analysis identified indigestible linkages consistent with the polysaccharide epitopes identified by ELISA-based glycome analysis. To determine if residual plant polysaccharides within TTIR could be metabolised, rumen microbiota from cannulated cattle fed barley straw were incubated with barley straw and TTIR in in vitro batch cultures. Transcript coding for carbohydrate-active enzymes (CAZymes) were identified and characterized for their contribution to cell wall digestion based on glycomic analyses, comparative gene expression profiles, and associated CAZyme families. High-resolution phylogenetic fingerprinting of these sequences revealed encoded enzymes with activities predicted to cleave the primary linkages within heteroxylan and arabinan. Conclusion This experimental platform provides unprecedented precision in the understanding of forage structure and digestibility, which can inform next-generation solutions to improve the growth of ruminants fed low quality forages and enhance the use of crop residues as a feedstock.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".