The catheterized bladder environment promotes Efg1- and Als1-dependent <i>Candida albicans</i> infection
Bibliographic record
Abstract
ABSTRACT Catheter-associated urinary tract infections (CAUTIs) account for 40% of all hospital-acquired infections. Given that 20-50% of all hospitalized patients receive a catheter, CAUTIs are one of the most common hospital-acquired infections and a significant medical complication as they result in increased morbidity, mortality, and an estimated annual cost of $340-370 million. Candida spp . – specifically Candida albicans – are a major causative agent of CAUTIs (17.8%), making it the second most common CAUTI uropathogen. Despite this frequent occurrence, the cellular and molecular details of C. albicans infection in the CAUTI microenvironment are poorly understood. Here, we characterize fungal virulence mechanisms and fungal biofilm formation during CAUTI for the first time. We found that the catheterized bladder environment triggers Candida virulence programs and robust biofilm formation through Efg1-dependent hyphal morphogenesis and Als1, an Efg1-downstream effector. Additionally, we show that the adhesin Als1 is necessary for in vitro and in vivo C. albicans biofilm formation dependent on the presence of fibrinogen (Fg), a coagulation factor released in the bladder due to the mechanical damage caused by urinary catheterization. Furthermore, in the presence of Fg, overexpression of ALS1 in C. albicans led to enhanced colonization and dissemination, while deletion of ALS1 reduced both outcomes during CAUTIs. Our study ultimately unveils the mechanism that contributes to fungal CAUTI, which may provide more effective targets for future therapies to prevent these infections.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".