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Record W4410108166 · doi:10.1101/2025.05.04.652153

Coordinated regulation of Mdr1- and Cdr1-mediated protection from antifungals by the Mrr1 transcription factor in emerging <i>Candida</i> spp

2025· preprint· en· W4410108166 on OpenAlexfundno aff
Dhanabala-Subhiksha Rajesh-Khanna, Carolina G. Piña Páez, Elora G. Dolan, Kiran S. Mirpuri, Jason Stajich, Deborah A. Hogan

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldMedicine
TopicFungal Infections and Studies
Canadian institutionsnot available
FundersNational Institute of General Medical SciencesCanadian Institute for Advanced ResearchUniversity of California, RiversideDartmouth CollegeNational Cancer InstituteNational Institutes of HealthNational Science Foundation
KeywordsTranscription factorTranscription (linguistics)BiologyMicrobiologyGeneticsGenePhilosophy

Abstract

fetched live from OpenAlex

ABSTRACT Infections caused by the emerging pathogenic yeast Clavispora (Candida) lusitaniae can be difficult to manage due to multi-drug resistance. Resistance to the frontline antifungal fluconazole (FLZ) in Candida spp. is commonly acquired through gain-of-function (GOF) mutations in the gene encoding the transcription factor Mrr1. These activated Mrr1 variants enhance FLZ efflux via upregulation of the multi-drug transporter gene MDR1 . Recently, it was reported that, unlike in the well-studied Candida albicans species, C. lusitaniae and Candida parapsilosis with activated Mrr1 also have high expression of CDR1 , which encodes another multi-drug transporter with overlapping but distinct transported substrate profiles and Cdr1-dependent FLZ resistance. To better understand the mechanisms of Mrr1 regulation of MDR1 and CDR1 , and other co-regulated genes, we performed CUT&RUN analysis of Mrr1 binding sites. Mrr1 bound the promoter regions of MDR1 and CDR1 as well as FLU1 , which encodes another transporter capable of FLZ efflux. Mdr1 and Cdr1 independently contributed to the decreased susceptibility of the MRR1 GOF strains against diverse clinical azoles and other antifungals, including 5-flucytosine. A consensus motif, CGGAGWTAR, enriched in Mrr1-bound C. lusitaniae DNA was also conserved upstream of MDR1 and CDR1 across species including C. albicans . CUT&RUN and RNA-seq data were used to define the Mrr1 regulon which includes genes involved in transport, stress responses, and metabolism. Activated and inducible Mrr1 bound similar regions in the promoters of Mrr1 regulon genes. Our studies provide new evolutionary insights into the coordinated regulation of multi-drug transporters and potential mechanism(s) that aid secondary resistance acquisition in emerging Candida . SIGNIFICANCE Understanding antifungal resistance in emerging Candida pathogens is essential to manage treatment failures and guide the development of new therapeutic strategies. Like other Candida species, the environmental opportunistic fungal pathogen Clavispora ( Candida ) lusitaniae can acquire resistance to the antifungal fluconazole by overexpression of the multi-drug efflux pump Mdr1 through gain-of-function mutations in the gene encoding the transcription factor Mrr1. Here, we show that C. lusitaniae Mrr1 also directly regulates CDR1, another major multi-drug transporter gene, along with MDR1. In strains with activated Mrr1, upregulation of MDR1 and CDR1 protects against diverse antifungals potentially aiding the rise of other resistance mutations. Mrr1 also regulates several stress response and metabolism genes thereby providing new perspectives into the physiology of drug-resistant strains. The identification of an Mrr1 binding motif that is conserved across strains and species will advance future efforts to understand multi-drug resistance across Candida species.

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 score0.001
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)0.0010.001

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 head0.015
GPT teacher head0.229
Teacher spread0.214 · 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
Published2025
Admission routes1
Has abstractyes

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