Bacterial Hsp90 promotes virulence factor production through maintenance of NRPS megaenzymes
Bibliographic record
Abstract
Abstract Pathogenic bacteria produce virulence factors critical to host infection. Here, we demonstrate the crucial role of the bacterial Hsp90 chaperone in the production of two major virulence factors, the colibactin genotoxin in Escherichia coli and the pyoverdine siderophore in Pseudomonas aeruginosa . Colibactin, a hybrid polyketide/non-ribosomal peptide (PK-NRP), and pyoverdine, a non-ribosomal peptide (NRP), are metabolites produced by complex biosynthetic pathways involving large cytoplasmic enzymes called megasynthases. Using comparative proteomics, we found that megasynthase abundance was markedly reduced in hsp90 deletion mutants of E. coli and P. aeruginosa compared to wild-type strains. This reduction was independent of transcriptional or translational regulation. We further revealed an interplay between Hsp90 and the HslUV protease in controlling megasynthase levels. Remarkably, we found that Hsp90 stabilizes additional NRP and PK-NRP megasynthases, suggesting a general role for Hsp90 as a chaperone of these enzymes. These findings open new avenues for enhancing the biosynthesis of complex metabolites for biotechnological applications through proteostasis modulation, and may also have implications for combating bacterial 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 | 0.000 | 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".