Natural compounds from freshwater mussels disrupt fungal virulence determinants and influence fluconazole susceptibility in the presence of macrophages in <i>Cryptococcus neoformans</i>
Bibliographic record
Abstract
ABSTRACT Cryptococcus neoformans is a human fungal pathogen responsible for fatal infections, especially in patients with a depressed immune system. Overexposure to antifungal drugs due to prolonged treatment regimens and structure-similar applications in agriculture have weakened the efficacy of current antifungals in the clinic. The rapid evolution of antifungal resistance urges the discovery of new compounds that inhibit fungal virulence determinants, rather than directly killing the pathogen, as alternative strategies to overcome disease and reduce selective pressure toward resistance. Here, we evaluated the efficacy of freshwater mussel extracts (crude and clarified) against the production of well-defined virulence determinants (i.e., thermotolerance, melanin, capsule, and biofilm) and fluconazole resistance in C. neoformans . We demonstrated the extracts’ influence on fungal thermotolerance, capsule production, and biofilm formation, as well as susceptibility to fluconazole in the presence of macrophages. Additionally, we measured the inhibitory activity of extracts against commercial peptidases (family representatives of cryptococcal orthologs) related to fungal virulence determinants and fluconazole resistance, and integrated these phenotypic findings with quantitative proteomics profiling. Our approach defined distinct signatures of each treatment and validated a new mechanism of anti-virulence action toward the polysaccharide capsule from a selected extract following fractionation. By understanding the mechanisms driving the antifungal activity of mussels, we may develop innovative treatment options to overcome fungal infections and promote susceptibility to fluconazole in resistant strains. IMPORTANCE As the prevalence and severity of global fungal infections rise, along with an increasing incidence of antifungal resistance, new strategies to combat fungal pathogens and overcome resistance are urgently needed. Critically, our current methods to overcome fungal infections are limited and drive the evolution of resistance forward; however, an anti-virulence approach to disarm virulence factors of the pathogen and promote host cell clearance is promising. Here, we explore the efficacy of natural compounds derived from freshwater mussels against classical fungal virulence determinants, including thermotolerance, capsule production, stress response, and biofilm formation. We integrate our phenotypic discoveries with state-of-the-art mass spectrometry-based proteomics to identify mechanistic drivers of these antifungal properties and propose innovative avenues to reduce infection and support the treatment of resistant strains.
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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".