Simulated colonic fluid replicates the <i>in vivo</i> growth capabilities of <i>Citrobacter rodentium cpxRA</i> mutants and uncovers additive effects of Cpx regulated genes on fitness
Bibliographic record
Abstract
Abstract Citrobacter rodentium is an attaching and effacing (A/E) pathogen used to model enteropathogenic and enterohemorrhagic Escherichia coli infections in mice. During colonization, C. rodentium must adapt to stresses in the gastrointestinal tract such as antimicrobial peptides, pH changes, and bile salts. The Cpx envelope stress response (ESR) is a two-component system used by some bacteria to remediate stress by modulating gene expression and is necessary for C. rodentium pathogenesis in mice. Here, we utilized simulated colonic fluid (SCF) to mimic the gastrointestinal environment which we show strongly induces the Cpx ESR and highlights a fitness defect specific to the Δ cpxRA mutant. While investigating genes in the Cpx regulon that may contribute to C. rodentium pathogenesis, we found that the absence of the Cpx ESR resulted in higher expression of the LEE master regulator, ler , and the genes yebE, ygiB, bssR , and htpX relied on CpxRA for proper expression. We then determined that CpxRA and select gene mutants were essential for proper growth in SCF when in the presence of extraneous stressors and in competition. Although none of the Cpx-regulated gene mutants exhibited marked virulence phenotypes in vivo , the Δ cpxRA mutant had reduced colonization and attenuated virulence, as previously determined, which replicated the in vitro growth phenotypes specific to SCF. Overall, these results indicate that the Δ cpxRA virulence defect is not due to any single Cpx regulon gene examined. Instead, attenuation may be the result of defective growth in the colonic environment resulting from the collective impact of multiple Cpx-regulated genes.
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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".