Reconstructing the Mosaic Glycolytic Pathway of the Anaerobic Eukaryote <i>Monocercomonoides</i>
Bibliographic record
Abstract
All eukaryotes carry out glycolysis, interestingly, not all using the same enzymes. Anaerobic eukaryotes face the challenge of fewer molecules of ATP extracted per molecule of glucose due to their lack of a complete tricarboxylic acid cycle. This may have pressured anaerobic eukaryotes to acquire the more ATP-efficient alternative glycolytic enzymes, such as pyrophosphate-fructose 6-phosphate phosphotransferase and pyruvate orthophosphate dikinase, through lateral gene transfers from bacteria and other eukaryotes. Most studies of these enzymes in eukaryotes involve pathogenic anaerobes; Monocercomonoides, an oxymonad belonging to the eukaryotic supergroup Excavata, is a nonpathogenic anaerobe representing an evolutionarily and ecologically distinct sampling of an anaerobic glycolytic pathway. We sequenced cDNA encoding glycolytic enzymes from a previously established cDNA library of Monocercomonoides and analyzed the relationships of these enzymes to those from other organisms spanning the major groups of Eukaryota, Bacteria, and Archaea. We established that, firstly, Monocercomonoides possesses alternative versions of glycolytic enzymes: fructose-6-phosphate phosphotransferase, both pyruvate kinase and pyruvate orthophosphate dikinase, cofactor-independent phosphoglycerate mutase, and fructose-bisphosphate aldolase (class II, type B). Secondly, we found evidence for the monophyly of oxymonads, kinetoplastids, diplomonads, and parabasalids, the major representatives of the Excavata. We also found several prokaryote-to-eukaryote as well as eukaryote-to-eukaryote lateral gene transfers involving glycolytic enzymes from anaerobic eukaryotes, further suggesting that lateral gene transfer was an important factor in the evolution of this pathway for denizens of this environment.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".