MétaCan
Menu
Back to cohort
Record W2560515330 · doi:10.1038/ismej.2016.170

Identification of the fitness determinants of budding yeast on a natural substrate

2016· article· en· W2560515330 on OpenAlexafffund
Marie Filteau, Guillaume Charron, Christian R. Landry

Bibliographic record

VenueThe ISME Journal · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFermentation and Sensory Analysis
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsBiologyYeastAllantoinSaccharomyces cerevisiaeBotanyDeciduousMapleObligateEcologyGeneticsBiochemistry

Abstract

fetched live from OpenAlex

The budding yeasts are prime models in genomics and cell biology, but the ecological factors that determine their success in non-human-associated habitats is poorly understood. In North America Saccharomyces yeasts are present on the bark of deciduous trees, where they feed on bark and sap exudates. In the North East, Saccharomyces paradoxus is found on maples, which makes maple sap a natural substrate for this species. We measured growth rates of S. paradoxus natural isolates on maple sap and found variation along a geographical gradient not explained by the inherent variation observed under optimal laboratory conditions. We used a functional genomic screen to reveal the ecologically relevant genes and conditions required for optimal growth in this substrate. We found that the allantoin degradation pathway is required for optimal growth in maple sap, in particular genes necessary for allantoate utilization, which we demonstrate is the major nitrogen source available to yeast in this environment. Growth with allantoin or allantoate as the sole nitrogen source recapitulated the variation in growth rates in maple sap among strains. We also show that two lineages of S. paradoxus display different life-history traits on allantoin and allantoate media, highlighting the ecological relevance of this pathway.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.672
Threshold uncertainty score0.145

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 studies0.0000.000
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 head0.025
GPT teacher head0.251
Teacher spread0.226 · 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 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

Citations26
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueThe ISME JournalSame topicFermentation and Sensory AnalysisFrench-language works237,207