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Record W4391645052 · doi:10.1128/spectrum.02841-23

Natural compounds from freshwater mussels disrupt fungal virulence determinants and influence fluconazole susceptibility in the presence of macrophages in <i>Cryptococcus neoformans</i>

2024· article· en· W4391645052 on OpenAlexafffund
Davier Gutierrez‐Gongora, Michael Woods, Ryan S. Prosser, Jennifer Geddes‐McAlister

Bibliographic record

VenueMicrobiology Spectrum · 2024
Typearticle
Languageen
FieldMedicine
TopicFungal Infections and Studies
Canadian institutionsUniversity of Guelph
FundersCanadian Institutes of Health ResearchMinistry of Colleges and UniversitiesNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsGovernment of Canada
KeywordsCryptococcus neoformansVirulenceFluconazoleMicrobiologyCryptococcosisBiologyCryptococcusAntifungalGeneGenetics

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.419
Threshold uncertainty score0.753

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.260
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2024
Admission routes2
Has abstractyes

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