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Record W4366828057 · doi:10.1101/2023.04.23.537879

Screening non-conventional yeasts for organic acid tolerance and engineering <i>Pichia occidentalis</i> for production of <i>cis</i> , <i>cis</i> -muconic acid

2023· preprint· en· W4366828057 on OpenAlexafffund
Michael E. Pyne, J. Bagley, Lauren Narcross, Kaspar Kevvai, Kealan Exley, Meghan Davies, Qingzhao Wang, Malcolm Whiteway, Vincent J. J. Martin

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolic Engineering and Bioproduction
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCommodity chemicalsSaccharomyces cerevisiaeAdipic acidYeastMuconic acidMetabolic engineeringFermentationBioproductionBioproductsTiterBioprocessBiochemistryBiologyPichiaChemistryFood scienceBiotechnologyBiofuelPichia pastorisGeneticsRecombinant DNAOrganic chemistryEnzymeGeneCatalysis

Abstract

fetched live from OpenAlex

ABSTRACT Saccharomyces cerevisiae is a workhorse of industrial biotechnology owing to the organism’s prominence in alcohol fermentation and the suite of sophisticated genetic tools available to manipulate its metabolism. However, S. cerevisiae is not suited to overproduce many bulk bioproducts, as toxicity constrains production at high titers. Here we employ a high-throughput assay to screen 108 publicly accessible yeast strains for tolerance to 20 g L −1 adipic acid (AA), a nylon precursor. We identify 15 tolerant yeasts and select Pichia occidentalis for production of cis,cis-muconic acid (CCM), a precursor to AA. By developing a genome editing toolkit for P. occidentalis, we demonstrate fed-batch production of CCM with a maximum titer (38.8 g L −1 ), yield (0.134 g g −1 glucose) and productivity (0.511 g L −1 h −1 ) that surpasses all metrics achieved using S. cerevisiae. This work brings us closer to the industrial bioproduction of AA and underscores the importance of host selection in bioprocessing.

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 categoriesMeta-epidemiology (narrow)
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 score0.112
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
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 head0.009
GPT teacher head0.206
Teacher spread0.197 · 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.

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

Citations2
Published2023
Admission routes2
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicMicrobial Metabolic Engineering and BioproductionFrench-language works237,207