Dysregulation of <i>Escherichia coli</i> α-hemolysin expression alters the course of acute and persistent urinary tract infection
Bibliographic record
Abstract
Urinary tract infections (UTIs) are among the most common bacterial infections, causing considerable morbidity in females. Infection is highly recurrent despite appropriate antibiotic treatment. Uropathogenic Escherichia coli (UPEC), the most common causative agent of UTIs, invades bladder epithelial cells (BECs) and develops into clonal intracellular bacterial communities (IBCs). Upon maturation, IBCs disperse, with bacteria spreading to neighboring BECs to repeat this cycle. This process allows UPEC to gain a foothold in the face of innate defense mechanisms, including micturition, epithelial exfoliation, and the influx of polymorphonuclear leukocytes. Here, we investigated the mechanism and dynamics of urothelial exfoliation in the early acute stages of infection. We show that UPEC α-hemolysin (HlyA) induces Caspase-1/Caspase-4-dependent inflammatory cell death in human urothelial cells, and we demonstrate that the response regulator (CpxR)-sensor kinase (CpxA) two-component system (CpxRA), which regulates virulence gene expression in response to environmental signals, is critical for fine-tuning HlyA cytotoxicity. Deletion of the cpxR transcriptional response regulator derepresses hlyA expression, leading to enhanced Caspase-1/Caspase-4- and NOD-like receptor family, pyrin domain containing 3-dependent inflammatory cell death in human urothelial cells. In vivo, overexpression of HlyA during acute bladder infection induces more rapid and extensive exfoliation and reduced bladder bacterial burdens. Bladder fitness is restored fully by inhibition of Caspase-1 and Caspase-11, the murine homolog of Caspase-4. Thus, we have discovered that fine-tuning of HlyA expression by the CpxRA system is critical for enhancing UPEC fitness in the urinary bladder. These results have significant implications for our understanding of how UPEC establishes persistent colonization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".