Sarah J. Weintraub, Zekun Li, Carter L. Nakagawa, Joseph H. Collins, Eric M. Young
{"title":"用比较转录组学阐明产油酵母生物学","authors":"Sarah J. Weintraub, Zekun Li, Carter L. Nakagawa, Joseph H. Collins, Eric M. Young","doi":"10.1002/bit.28891","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>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 <i>Yarrowia lipolytica</i>, <i>Debaryomyces hansenii</i>, and <i>Debaryomyces subglobosus</i> 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 <i>Yarrowia</i> upregulates lipid biosynthesis during nitrogen starvation and provides new evidence that riboflavin overproduction in <i>Debaryomyces</i> 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.</p></div>","PeriodicalId":9168,"journal":{"name":"Biotechnology and Bioengineering","volume":"122 3","pages":"677-697"},"PeriodicalIF":3.5000,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Oleaginous Yeast Biology Elucidated With Comparative Transcriptomics\",\"authors\":\"Sarah J. Weintraub, Zekun Li, Carter L. Nakagawa, Joseph H. Collins, Eric M. Young\",\"doi\":\"10.1002/bit.28891\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>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 <i>Yarrowia lipolytica</i>, <i>Debaryomyces hansenii</i>, and <i>Debaryomyces subglobosus</i> 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 <i>Yarrowia</i> upregulates lipid biosynthesis during nitrogen starvation and provides new evidence that riboflavin overproduction in <i>Debaryomyces</i> 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.</p></div>\",\"PeriodicalId\":9168,\"journal\":{\"name\":\"Biotechnology and Bioengineering\",\"volume\":\"122 3\",\"pages\":\"677-697\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biotechnology and Bioengineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/bit.28891\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOTECHNOLOGY & APPLIED MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biotechnology and Bioengineering","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/bit.28891","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
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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