Consensus pan-genome assembly of the specialised wine bacterium Oenococcus oeni
Bibliographic record
Abstract
BACKGROUND: Oenococcus oeni is a lactic acid bacterium that is specialised for growth in the ecological niche of wine, where it is noted for its ability to perform the secondary, malolactic fermentation that is often required for many types of wine. Expanding the understanding of strain-dependent genetic variations in its small and streamlined genome is important for realising its full potential in industrial fermentation processes. RESULTS: Whole genome comparison was performed on 191 strains of O. oeni; from this rich source of genomic information consensus pan-genome assemblies of the invariant (core) and variable (flexible) regions of this organism were established. Genetic variation in amino acid biosynthesis and sugar transport and utilisation was found to be common between strains. Furthermore, we characterised previously-unreported intra-specific genetic variations in the natural competence of this microbe. CONCLUSION: By assembling a consensus pan-genome from a large number of strains, this study provides a tool for researchers to readily compare protein-coding genes across strains and infer functional relationships between genes in conserved syntenic regions. This establishes a foundation for further genetic, and thus phenotypic, research of this industrially-important species.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".