Sulphur‐Acquisition Pathways for Cysteine Synthesis Confer a Fitness Advantage to Bacteria in Plant Extracts
Bibliographic record
Abstract
Bacteria and plants are closely associated with human society, in fields such as agriculture, public health, the food industry, and waste disposal. Bacteria have evolved nutrient-utilisation systems adapted to achieve the most efficient growth in their major habitats. However, empirical evidence to support the significance of bacterial nutrient utilisation in adaptation to plants is limited. Therefore, we investigated the genetic and nutritional factors required for bacterial growth in plant extracts by screening an Escherichia coli gene-knockout library in vegetable-based medium. Mutants lacking genes involved in sulphur assimilation, whereby sulphur is transferred from sulphate to cysteine, exhibited negligible growth in vegetable-based medium or plant extracts, owing to the low cysteine levels. The reverse transsulphuration pathway from methionine, another pathway for donating sulphur to cysteine, occurring in bacteria such as Bacillus subtilis, also played an important role in growth in plant extracts. These two sulphur-assimilation pathways were more frequently observed in plant-associated than in animal-associated bacteria. Sulphur-acquisition pathways for cysteine synthesis thus play a key role in bacterial growth in plant-derived environments such as plant residues and plant exudates.
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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) | 0.001 | 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) | 0.001 | 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".