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Record W4321446353 · doi:10.1128/mbio.03434-22

Ent2 Governs Morphogenesis and Virulence in Part through Regulation of the Cdc42 Signaling Cascade in the Fungal Pathogen Candida albicans

2023· article· en· W4321446353 on OpenAlexafffund
Emma Lash, Victoria Prudent, P.J. Stogios, Alexei Savchenko, Suzanne M. Noble, Nicole Robbins, Leah E. Cowen

Bibliographic record

VenuemBio · 2023
Typearticle
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsUniversity of CalgaryUniversity of Toronto
FundersNational Institute of Allergy and Infectious DiseasesU.S. Department of Health and Human ServicesGovernment of CanadaNational Institutes of HealthCanadian Institutes of Health ResearchGenome CanadaCanadian Institute for Advanced Research
KeywordsCandida albicansVirulenceFungal pathogenPathogenMicrobiologyBiologyOpportunistic pathogenOrganismYeastCDC42Human pathogenMorphogenesisSignal transductionCell biologyGeneticsGene

Abstract

fetched live from OpenAlex

Candida albicans is a leading human fungal pathogen that can cause life-threatening infections in immunocompromised individuals, with mortality rates of ~40%. The ability of this organism to grow in both yeast and filamentous forms is critical for the establishment of systemic infection. Genomic screens have identified many genes required for this morphological transition, yet our understanding of the mechanisms that regulate this key virulence trait remains incomplete. In this study, we characterized Ent2 as a core regulator of C. albicans morphogenesis. We show that Ent2 regulates hyphal morphogenesis through an interaction between its ENTH domain and the Cdc42 GAP, Rga2, which signals through the Cdc42-Cla4 signaling pathway. Finally, we show that the Ent2 protein, and specifically its ENTH domain, is required for virulence in a mouse model of systemic candidiasis. Overall, this work identifies Ent2 as a key regulator of filamentation and virulence in C. albicans.

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)0.001
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 score0.137
Threshold uncertainty score0.239

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.028
GPT teacher head0.274
Teacher spread0.246 · 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

Citations4
Published2023
Admission routes2
Has abstractyes

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