Systematic Analysis of Two-Component Systems in Citrobacter rodentium Reveals Positive and Negative Roles in Virulence
Bibliographic record
Abstract
Citrobacter rodentium is a murine pathogen used to model intestinal infections caused by the human diarrheal pathogens enterohemorrhagic and enteropathogenic Escherichia coli During infection, bacteria use two-component systems (TCSs) to detect changing environmental cues within the host, allowing for rapid adaptation by altering the expression of specific genes. In this study, 26 TCSs were identified in C. rodentium, and quantitative PCR (qPCR) analysis showed that they are all expressed during murine infection. These TCSs were individually deleted, and the in vitro and in vivo effects were analyzed to determine the functional consequences. In vitro analyses only revealed minor differences, and surprisingly, type III secretion (T3S) was only affected in the ΔarcA strain. Murine infections identified 7 mutants with either attenuated or increased virulence. In agreement with the in vitro T3S assay, the ΔarcA strain was attenuated and defective in colonization and cell adherence. The ΔrcsB strain was among the most highly attenuated strains. The decrease in virulence of this strain may be associated with changes to the cell surface, as Congo red binding was altered, and qPCR revealed that expression of the wcaA gene, which has been implicated in colanic acid production in other bacteria, was drastically downregulated. The ΔuvrY strain exhibited increased virulence compared to the wild type, which was associated with a significant increase in bacterial burden within the mesenteric lymph nodes. The systematic analysis of virulence-associated TCSs and investigation of their functions during infection may open new avenues for drug development.
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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 | 0.001 | 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) | 0.000 | 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".