Extensive remodeling of sugar metabolism through gene loss and horizontal gene transfer in a eukaryotic lineage
Bibliographic record
Abstract
BACKGROUND: In yeasts belonging to the subphylum Saccharomycotina, genes encoding components of the main metabolic pathways, like alcoholic fermentation, are usually conserved. However, in fructophilic species belonging to the floral Wickerhamiella and Starmerella genera (W/S clade), alcoholic fermentation was uniquely shaped by events of gene loss and horizontal gene transfer (HGT). RESULTS: Because HGT and gene losses were first identified when only eight W/S-clade genomes were available, we collected publicly available genome data and sequenced the genomes of 36 additional species. A total of 63 genomes, representing most of the species described in the clade, were included in the analyses. Firstly, we inferred the phylogenomic tree of the clade and inspected the genomes for the presence of HGT-derived genes involved in fructophily and alcoholic fermentation. We predicted nine independent HGT events and several instances of secondary loss pertaining to both pathways. To investigate the possible links between gene loss and acquisition events and evolution of sugar metabolism, we conducted phenotypic characterization of 42 W/S-clade species including estimates of sugar consumption rates and fermentation byproduct formation. In some instances, the reconciliation of genotypes and phenotypes yielded unexpected results, such as the discovery of fructophily in the absence of the cornerstone gene (FFZ1) and robust alcoholic fermentation in the absence of the respective canonical pathway. CONCLUSIONS: These observations suggest that reinstatement of alcoholic fermentation in the W/S clade triggered a surge of innovation that goes beyond the utilization of xenologous enzymes, with fructose metabolism playing a key role.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".