Broad-Spectrum Inhibitor of Bacterial Polyphosphate Homeostasis Attenuates Virulence Factors and Helps Reveal Novel Physiology of Klebsiella pneumoniae and Acinetobacter baumannii
Bibliographic record
Abstract
Acinetobacter baumannii and Klebsiella pneumoniae currently rank amongst the most antibiotic-resistant pathogens, responsible for millions of infections each year. In the wake of this crisis, anti-virulence therapeutics targeting bacterial polyphosphate (polyP) homeostasis have been lauded as an attractive alternative to traditional antibiotics. In this work, we show that the small molecule gallein, a known G-protein βγ subunit modulator, also recently proven to have dual-specificity polyphosphate kinase (PPK) inhibition in Pseudomonas aeruginosa, in turn exhibits broad-spectrum PPK inhibition in other priority pathogens. Gallein treatment successfully attenuated virulence factors of K. pneumoniae and A. baumannii including biofilm formation, surface associated motility, and offered protection against A. baumannii challenge in a Caenorhabditis elegans model of infection. This was highlighted most importantly in the critically understudied A. baumannii, where gallein treatment phenocopied a ppk1 knockout strain of a previously uncharacterized PPK1. Subsequent analysis revealed a unique instance of two functionally and phenotypically distinct PPK1 isoforms encoded by a single bacterium. Finally, gallein was administered to a defined microbial community comprising over 30 commensal species of the human gut microbiome, demonstrating the non-disruptive properties characteristic of anti-virulence treatments as microbial biodiversity was not adversely influenced. Together, these results emphasize that gallein is a promising avenue for the development of broad-spectrum anti-virulence therapeutics.
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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 | 0.001 |
| 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".