Evidence map›Paper›PMID 39098937›Full record

ArticleMicrobial cell factories2024

Robustness quantification of a mutant library screen revealed key genetic markers in yeast.

Cecilia Trivellin, Luca Torello Pianale, Lisbeth Olsson

Abstract read
In one paragraph

Article in Microbial cell factories, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Cecilia TrivellinDepartment of Life Sciences, Division of Industrial Biotechnology, Chalmers University of Technology, 412 96, Gothenburg, Sweden.
Luca Torello PianaleDepartment of Life Sciences, Division of Industrial Biotechnology, Chalmers University of Technology, 412 96, Gothenburg, Sweden.
Lisbeth OlssonDepartment of Life Sciences, Division of Industrial Biotechnology, Chalmers University of Technology, 412 96, Gothenburg, Sweden. lisbeth.olsson@chalmers.se.

Funding

Novo Nordisk Fonden DISTINGUISHED INVESTIGATOR 2019, #0055044
6 · The paper itself

Abstract

backgroundMicrobial robustness is crucial for developing cell factories that maintain consistent performance in a challenging environment such as large-scale bioreactors. Although tools exist to assess and understand robustness at a phenotypic level, the underlying metabolic and genetic mechanisms are not well defined, which limits our ability to engineer more strains with robust functions.

resultsThis study encompassed four steps. (I) Fitness and robustness were analyzed from a published dataset of yeast mutants grown in multiple environments. (II) Genes and metabolic processes affecting robustness or fitness were identified, and 14 of these genes were deleted in Saccharomyces cerevisiae CEN.PK113-7D. (III) The mutants bearing gene deletions were cultivated in three perturbation spaces mimicking typical industrial processes. (IV) Fitness and robustness were determined for each mutant in each perturbation space. We report that robustness varied according to the perturbation space. We identified genes associated with increased robustness such as MET28, linked to sulfur metabolism; as well as genes associated with decreased robustness, including TIR3 and WWM1, both involved in stress response and apoptosis.

conclusionThe present study demonstrates how phenomics datasets can be analyzed to reveal the relationship between phenotypic response and associated genes. Specifically, robustness analysis makes it possible to study the influence of single genes and metabolic processes on stable microbial performance in different perturbation spaces. Ultimately, this information can be used to enhance robustness in targeted strains.

Indexed as

Saccharomyces cerevisiaeGene DeletionGene LibraryGenetic MarkersMutationPhenotypeSaccharomyces cerevisiae ProteinsGenetic MarkersSaccharomyces cerevisiae ProteinsBioprocessesHigh-throughputMET28Microbial robustnessPerturbations

Identifiers

PMID39098937
PMCPMC11298085

What Socratic holds

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.