Functional genomics of chitin degradation by Vibrio parahaemolyticus reveals finely integrated metabolic contributions to support environmental fitness
Bibliographic record
Abstract
Vibrio species are marine prokaryotes that inhabit diverse ecological niches, colonizing abiotic and biotic surfaces. These bacteria are vital players in the global carbon cycle, assimilating billions of tonnes of chitin for carbon (and nitrogen) metabolites. Many bacterial proteins involved in the process-including chitinases, sugar transporters, and modifying enzymes-have been well studied. However, the genetic functional interplay and key drivers of Vibrio competitive survival in the presence of chitin as the dominant carbon source is not understood. To address this question, we carried out transposon sequencing (Tn-seq) to determine the genetic fitness of Vibrio parahaemolyticus mutants grown on chitin as a sole carbon source. Along with validating known Vibrio genes associated with chitin metabolism, our data newly identified vital roles for an unclassified OprD-like import chitoporin and a HexR family transcriptional regulator. Furthermore, we functionally implicated HexR in regulating multiple physiological processes involved in V. parahaemolyticus environmental survival including carbon assimilation and cell growth, biofilm formation, and cell motility. Under nutrient limiting conditions, our data revealed a requirement for HexR in filamentous cell morphology, a critical trait for V. parahaemolyticus environmental fitness. Therefore, a vital import porin and genomic regulation mediated by HexR support multiple physiological processes for Vibrio chitinolytic growth and environmental fitness.
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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) | 0.000 | 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".