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Record W2166117618 · doi:10.1128/mbio.00495-12

The Evolutionary Rewiring of Ubiquitination Targets Has Reprogrammed the Regulation of Carbon Assimilation in the Pathogenic Yeast Candida albicans

2012· article· en· W2166117618 on OpenAlexaff
Doblin Sandai, Zhikang Yin, Laura Selway, David Stead, Janet L. Walker, Michelle D. Leach, Iryna Bohovych, Iuliana V. Ene, Stavroula Kastora, Susan Budge, Carol A. Munro, Frank C. Odds, Neil A. R. Gow, Alistair J. P. Brown

Bibliographic record

VenuemBio · 2012
Typearticle
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsUniversity of Toronto
FundersNational Cancer InstituteBiotechnology and Biological Sciences Research CouncilEuropean CommissionNational Institute of General Medical SciencesWellcome Trust
KeywordsCatabolite repressionGlyoxylate cycleCandida albicansCorpus albicansBiologySaccharomyces cerevisiaeAssimilation (phonology)YeastBiochemistryUbiquitinMicrobiologyEnzymeGeneMutant

Abstract

fetched live from OpenAlex

Microbes must assimilate carbon to grow and colonize their niches. Transcript profiling has suggested that Candida albicans, a major pathogen of humans, regulates its carbon assimilation in an analogous fashion to the model yeast Saccharomyces cerevisiae, repressing metabolic pathways required for the use of alterative nonpreferred carbon sources when sugars are available. However, we show that there is significant dislocation between the proteome and transcriptome in C. albicans. Glucose triggers the degradation of the ICL1 and PCK1 transcripts in C. albicans, yet isocitrate lyase (Icl1) and phosphoenolpyruvate carboxykinase (Pck1) are stable and are retained. Indeed, numerous enzymes required for the assimilation of carboxylic and fatty acids are not degraded in response to glucose. However, when expressed in C. albicans, S. cerevisiae Icl1 (ScIcl1) is subjected to glucose-accelerated degradation, indicating that like S. cerevisiae, this pathogen has the molecular apparatus required to execute ubiquitin-dependent catabolite inactivation. C. albicans Icl1 (CaIcl1) lacks analogous ubiquitination sites and is stable under these conditions, but the addition of a ubiquitination site programs glucose-accelerated degradation of CaIcl1. Also, catabolite inactivation is slowed in C. albicans ubi4 cells. Ubiquitination sites are present in gluconeogenic and glyoxylate cycle enzymes from S. cerevisiae but absent from their C. albicans homologues. We conclude that evolutionary rewiring of ubiquitination targets has meant that following glucose exposure, C. albicans retains key metabolic functions, allowing it to continue to assimilate alternative carbon sources. This metabolic flexibility may be critical during infection, facilitating the rapid colonization of dynamic host niches containing complex arrays of nutrients. IMPORTANCE Pathogenic microbes must assimilate a range of carbon sources to grow and colonize their hosts. Current views about carbon assimilation in the pathogenic yeast Candida albicans are strongly influenced by the Saccharomyces cerevisiae paradigm in which cells faced with choices of nutrients first use energetically favorable sugars, degrading enzymes required for the assimilation of less favorable alternative carbon sources. We show that this is not the case in C. albicans because there has been significant evolutionary rewiring of the molecular signals that promote enzyme degradation in response to glucose. As a result, this major pathogen of humans retains enzymes required for the utilization of physiologically relevant carbon sources such as lactic acid and fatty acids, allowing it to continue to use these host nutrients even when glucose is available. This phenomenon probably enhances efficient colonization of host niches where sugars are only transiently available.

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 score0.003

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.029
GPT teacher head0.275
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 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

Citations117
Published2012
Admission routes1
Has abstractyes

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