The <i>pcnB</i> gene sustains <i>Shigella flexneri</i> virulence
Bibliographic record
Abstract
ABSTRACT The enteropathogen Shigella flexneri employs a Type Three Secretion System (T3SS) to colonize intestinal epithelial cells. Genes encoding the T3SS are located on a large IncFII virulence plasmid, pINV. T3SS expression comes at the expense of slowed Shigella growth and is therefore strictly controlled by both transcriptional and post-transcriptional mechanisms. Following up on a recent genome-wide screen, we here show that the chromosomal gene pcnB, encoding the poly-A polymerase I (PAP-I), slows Shigella growth at 37°C, while at the same time promotes early colonization of a human epithelial enteroid model. Proteomic profiling revealed that pcnB drives global increase of the Shigella T3SS virulence program. Accordingly, pcnB sustains pINV replication to a level optimal for Shigella virulence. This is achieved through increased degradation of the antisense RNA CopA, involved in plasmid replication control. The pcnB effect on pINV replication was found to also ensure longer-term intraepithelial expansion of Shigella following human intestinal epithelium invasion. Our findings exemplify how an optimal pINV level is necessary for the execution of Shigella ’s infection cycle. AUTHOR SUMMARY Bacterial infections represent a major global threat. Understanding the genetic determinants promoting infections is crucial to overcome this threat. Shigella is an intracellular bacterial pathogen that invades and disseminates in the intestinal epithelium, causing bacillary dysentery in humans. Shigella’s ability to cause disease relies on the delivery of effector proteins into the host cells through an injection machinery, with most of the genes involved in this process located on a large virulence plasmid. Here we show that the chromosomal gene pcnB sustains an optimal virulence plasmid level. This is crucial for Shigella to maximize virulence protein expression and thereby efficiently invade, replicate and spread within the intestinal epithelium.
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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) | 0.002 | 0.001 |
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".