Increased Fitness of <i>Pseudomonas fluorescens</i> Pf0-1 Leucine Auxotrophs in Soil
Bibliographic record
Abstract
The annotation process of a newly sequenced bacterial genome is largely based on algorithms derived from databases of previously defined RNA and protein-encoding gene structures. This process generally excludes the possibility that the two strands of a given stretch of DNA can each harbor a gene in an overlapping manner. While the presence of such structures in eukaryotic genomes is considered to be relatively common, their counterparts in prokaryotic genomes are just beginning to be recognized. Application of an in vivo expression technology has previously identified 22 discrete genetic loci in Pseudomonas fluorescens Pf0-1 that were specifically activated in the soil environment, of which 10 were present in an antisense orientation relative to previously annotated genes. This observation led to the hypothesis that the physiological role of overlapping genetic structures may be relevant to growth conditions outside artificial laboratory media. Here, we examined the role of one of the overlapping gene pairs, iiv19 and leuA2, in soil. Although iiv19 was previously demonstrated to be preferentially activated in the soil environment, its absence did not alter the ability of P. fluorescens to colonize or survive in soil. Surprisingly, the absence of the leuA2 gene conferred a fitness advantage in the soil environment when leucine was supplied exogenously. This effect was determined to be independent of the iiv19 gene, and further analyses revealed that amino acid antagonism was the underlying mechanism behind the observed fitness advantage of the bacterium in soil. Our findings provide a potential mechanism for the frequent occurrence of auxotrophic mutants of Pseudomonas spp. in the lungs of cystic fibrosis patients.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".