A stress-induced block in dicarboxylate uptake and utilization in Salmonella
Bibliographic record
Abstract
Abstract Bacteria have evolved to sense and respond to their environment by altering gene expression and metabolism to promote growth and survival. In this work we demonstrate that Salmonella displays an extensive (>30 hour) lag in growth when subcultured into media where dicarboxylates such as succinate are the sole carbon source. This growth lag is regulated in part by RpoS, the RssB anti-adaptor IraP, translation elongation factor P, and to a lesser degree the stringent response. We also show that small amounts of proline or citrate can trigger early growth in succinate media and that, at least for proline, this effect requires the multifunctional enzyme/regulator PutA. We demonstrate that activation of RpoS results in the repression of dctA , encoding the primary dicarboxylate importer, and that constitutive expression of dctA induced growth. This dicarboxylate growth lag phenotype is far more severe across multiple Salmonella isolates than in its close relative E. coli . Replacing 200 nt of the Salmonella dctA promoter region with that of E. coli was sufficient to eliminate the observed lag in growth. We hypothesize that this cis -regulatory divergence might be an adaptation to Salmonella ’s virulent lifestyle where levels of phagocyte-produced succinate increase in response to bacterial LPS. We found that impairing dctA repression had no effect on Salmonella ’s survival in acidified succinate or in macrophage but propose alternate hypotheses of fitness advantages acquired by repressing dicarboxylate uptake. Importance Bacteria have evolved to sense and respond to their environment to maximize their chance of survival. By studying differences in the responses of pathogenic bacteria and closely related non-pathogens, we can gain insight into what environments they encounter inside of an infected host. Here we demonstrate that Salmonella diverges from its close relative E. coli in its response to dicarboxylates such as the metabolite succinate. We show that this is regulated by stress response proteins and ultimately can be attributed to Salmonella repressing its import of dicarboxylates. Understanding this phenomenon may reveal a novel aspect of the Salmonella virulence cycle, and our characterization of its regulation yields a number of mutant strains that can be used to further study it.
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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 | 0.000 |
| 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".