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Record W3196331804 · doi:10.1101/2021.09.02.458602

Transcriptional control of hypoxic hyphal growth in the fungal pathogen <i>Candida albicans</i>

2021· preprint· en· W3196331804 on OpenAlexafffund
Manon Henry, Anaïs Burgain, Faïza Tebbji, Adnane Sellam

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2021
Typepreprint
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsUniversité de MontréalUniversité LavalMontreal Heart Institute
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchFonds de Recherche du Québec - SantéEuropean Bioinformatics Institute
KeywordsCandida albicansBiologyFilamentationCorpus albicansDNA microarrayGeneTranscription factorGeneticsCell biologyMicroarray analysis techniquesGenetic screenMutantFungal proteinGene expression profilingVirulenceTranscriptional regulationPhenotypeRegulation of gene expressionGene expression

Abstract

fetched live from OpenAlex

Abstract Background The ability of Candida albicans , an important human fungal pathogen, to develop filamentous forms is a crucial determinant for host invasion and virulence. Filamentation is triggered by different host environmental cues. Hypoxia, the dominant conditions that C. albicans encounters inside the human host, promote filamentation, however, the contributing mechanisms remain poorly characterized. Methods We performed a quantitative analysis of gene deletion mutants from different collections of protein kinases and transcriptional regulators in C. albicans to identify specific modulators of the hypoxic filamentation. We used genome-wide transcriptional profiling (Microarrays) and promoter occupancy (ChIP-chip) to characterize regulons of two transcription factors that were associated with the hypoxic filamentation. Genetic interactions were also used to assess functional relationships among the newly identified modulators of hypoxic filamentation and the well-known C. albicans core morphogenetic regulators. Results Our genetic screen uncovered two transcription factors, Ahr1 and Tye7, that act as prominent regulators of C. albicans filamentation specifically under hypoxia. Both ahr1 and tye7 mutants exhibited a hyperfilamentous phenotype specifically under an oxygen-depleted environment suggesting that these transcription factors act as negative regulators of hypoxic filamentation. By combining microarray and ChIP-chip data, we have characterized the set of genes that are directly modulated by Ahr1 and Tye7. We found that both Ahr1 and Tye7 modulate a different set of genes and biological processes. Our genetic epistasis analysis supports our genomic finding and suggests that Ahr1 and Tye7 act independently to modulate hyphal growth in response to hypoxia. Furthermore, our genetic interaction experiments uncovered that Ahr1 and Tye7 repress the hypoxic filamentation growth via the Efg1 and Ras1/Cyr1 pathways, respectively. Conclusion In sum, this investigation represents an informative resource toward the understanding of how hypoxia, the predominant condition inside the host, shapes the invasive filamentous growth of 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.013
GPT teacher head0.221
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2021
Admission routes2
Has abstractyes

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