Oleaginous Yeast Biology Elucidated With Comparative Transcriptomics

Extremophilic yeasts have favorable metabolic and tolerance traits for biomanufacturing- like lipid biosynthesis, flavinogenesis, and halotolerance - yet the connection between these favorable phenotypes and strain genotype is not well understood. To this end, this study compares the phenotypes and gene expression patterns of biotechnologically relevant yeasts Yarrowia lipolytica, Debaryomyces hansenii, and Debaryomyces subglobosus grown under nitrogen starvation, iron starvation, and salt stress. To analyze the large data set across species and conditions, two approaches were used: a "network-first" approach where a generalized metabolic network serves as a scaffold for mapping genes and a "cluster-first" approach where unsupervised machine learning co-expression analysis clusters genes. Both approaches provide insight into strain behavior. The network-first approach corroborates that Yarrowia upregulates lipid biosynthesis during nitrogen starvation and provides new evidence that riboflavin overproduction in Debaryomyces yeasts is overflow metabolism that is routed to flavin cofactor production under salt stress. The cluster-first approach does not rely on annotation; therefore, the coexpression analysis can identify known and novel genes involved in stress responses, mainly transcription factors and transporters. Therefore, this work links the genotype to the phenotype of biotechnologically relevant yeasts and demonstrates the utility of complementary computational approaches to gain insight from transcriptomics data across species and conditions.

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Publication Details

Journal
Biotechnology and Bioengineering
Published
2024-12-10
DOI
https://doi.org/10.1002/bit.28891
Citations
2
Primary Topic
Microbial Metabolic Engineering and Bioproduction
Type
article
Field-Weighted Citation Impact
0.47

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article

Oleaginous Yeast Biology Elucidated With Comparative Transcriptomics

Sarah J. Weintraub, Carter L. Nakagawa, Eric M. Young, Joseph H. Collins et al.
2 citations
Biotechnology and Bioengineering
Microbial Metabolic Engineering and Bioproduction
0.47
article

Oleaginous Yeast Biology Elucidated With Comparative Transcriptomics

Sarah J. Weintraub, Carter L. Nakagawa, Eric M. Young, Joseph H. Collins, Zekun Li
article en
2 citations

Abstract

Extremophilic yeasts have favorable metabolic and tolerance traits for biomanufacturing- like lipid biosynthesis, flavinogenesis, and halotolerance - yet the connection between these favorable phenotypes and strain genotype is not well understood. To this end, this study compares the phenotypes and gene expression patterns of biotechnologically relevant yeasts Yarrowia lipolytica, Debaryomyces hansenii, and Debaryomyces subglobosus grown under nitrogen starvation, iron starvation, and salt stress. To analyze the large data set across species and conditions, two approaches were used: a "network-first" approach where a generalized metabolic network serves as a scaffold for mapping genes and a "cluster-first" approach where unsupervised machine learning co-expression analysis clusters genes. Both approaches provide insight into strain behavior. The network-first approach corroborates that Yarrowia upregulates lipid biosynthesis during nitrogen starvation and provides new evidence that riboflavin overproduction in Debaryomyces yeasts is overflow metabolism that is routed to flavin cofactor production under salt stress. The cluster-first approach does not rely on annotation; therefore, the coexpression analysis can identify known and novel genes involved in stress responses, mainly transcription factors and transporters. Therefore, this work links the genotype to the phenotype of biotechnologically relevant yeasts and demonstrates the utility of complementary computational approaches to gain insight from transcriptomics data across species and conditions.

Biotechnology and BioengineeringVol. 122(3)
Worcester Polytechnic Institute (US)
National Science Foundation, U.S. Department of Energy, Office of the Director of National Intelligence, Joint Genome Institute, Office of Science, Intelligence Advanced Research Projects Activity
Openalex Percentile: Top 34%
Microbial Metabolic Engineering and Bioproduction
0.47
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