Direct Evidence That Genetic Variation in Glycerol-3-Phosphate and Malate Dehydrogenase Genes (<i>Gpdh</i> and <i>Mdh1</i>) Affects Adult Ethanol Tolerance in <i>Drosophila melanogaster</i>
Bibliographic record
Abstract
Many studies of alcohol adaptation in Drosophila melanogaster have focused on the Adh polymorphism, yet the metabolic elimination of alcohol should involve many enzymes and pathways. Here we evaluate the effects of glycerol-3-phosphate dehydrogenase (Gpdh) and cytosolic malate dehydrogenase (Mdh1) genotype activity on adult tolerance to ethanol. We have created a set of P-element-excision-derived Gpdh, Mdh1, and Adh alleles that generate a range of activity phenotypes from full to zero activity. Comparisons of paired Gpdh genotypes possessing 10 and 60% normal activity and 66 and 100% normal activity show significant effects where higher activity increases tolerance. Mdh1 null allele homozygotes show reductions in tolerance. We use piggyBac FLP-FRT site-specific recombination to create deletions and duplications of Gpdh. Duplications show an increase of 50% in activity and an increase of adult tolerance to ethanol exposure. These studies show that the molecular polymorphism associated with GPDH activity could be maintained in natural populations by selection related to adaptation to alcohols. Finally, we examine the interactions between activity genotypes for Gpdh, Mdh1, and Adh. We find no significant interlocus interactions. Observations on Mdh1 in both Gpdh and Adh backgrounds demonstrate significant increases in ethanol tolerance with partial reductions (50%) in cytosolic MDH activity. This observation strongly suggests the operation of pyruvate-malate and, in particular, pyruvate-citrate cycling in adaptation to alcohol exposure. We propose that an understanding of the evolution of tolerance to alcohols will require a system-level approach, rather than a focus on single enzymes.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".