Time-Course Analysis of Gene Expression During theSaccharomyces cerevisiaeHypoxic Response

Bendjilali, Nasrine; MacLeon, Samuel; Kalra, Gurmannat; Willis, Stephen D.; Hossian, A K M Nawshad; Avery, Erica; Wojtowicz, Olivia; Hickman, Mark J.

doi:10.1534/g3.116.034991

Cited by 40 publications

(49 citation statements)

References 54 publications

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“…As expected, many O 2 -regulated genes play a role in cellular respiration, other aspects of metabolism, and in ribosomal processes 13 .…”

Section: Representative Resultssupporting

confidence: 74%

“…Also, genes exhibit variable kinetics with both increases and decreases in expression. Many genes exhibit a peak increase or decrease at 30 min, likely due to a transient stress response 13 .…”

Section: Representative Resultsmentioning

confidence: 99%

“…In order to mimic natural hypoxia, these metabolites were not added to the media. In the short time that cells were exposed to hypoxia without the presence of these essential metabolites, there was no noticeable increase in cell death (data not shown) nor a prolonged stress response 13 .…”

Section: Introductionmentioning

confidence: 92%

“…Several microarray studies performed in S. cerevisiae show that the mRNA levels of hundreds of genes change in response to hypoxia 5–12 . Recently, RNA-seq was used to characterize gene expression changes over time during hypoxia 13 . Here, the experimental details are presented and discussed.…”

Section: Introductionmentioning

confidence: 99%

“…Specific time points should be chosen that will capture the major changes of the response. In this study, time points between 0 and 4 h were observed, because past experiments revealed widespread changes in gene expression during this period 13 .…”

Section: Introductionmentioning

confidence: 99%

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Measuring mRNA Levels Over Time During the Yeast S. cerevisiae Hypoxic Response

Willis

Hossian

Evans

et al. 2017

JoVE

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Complex changes in gene expression typically mediate a large portion of a cellular response. Each gene may change expression with unique kinetics as the gene is regulated by the particular timing of one of many stimuli, signaling pathways or secondary effects. In order to capture the entire gene expression response to hypoxia in the yeast S. cerevisiae, RNA-seq analysis was used to monitor the mRNA levels of all genes at specific times after exposure to hypoxia. Hypoxia was established by growing cells in ~100% N2 gas. Importantly, unlike other hypoxic studies, ergosterol and unsaturated fatty acids were not added to the media because these metabolites affect gene expression. Time points were chosen in the range of 0–4 h after hypoxia because that period captures the major changes in gene expression. At each time point, mid-log hypoxic cells were quickly filtered and frozen, limiting exposure to O2 and concomitant changes in gene expression. Total RNA was extracted from cells and used to enrich for mRNA, which was then converted to cDNA. From this cDNA, multiplex libraries were created and eight or more samples were sequenced in one lane of a next-generation sequencer. A post-sequencing pipeline is described, which includes quality base trimming, read mapping and determining the number of reads per gene. DESeq2 within the R statistical environment was used to identify genes that change significantly at any one of the hypoxic time points. Analysis of three biological replicates revealed high reproducibility, genes of differing kinetics and a large number of expected O2-regulated genes. These methods can be used to study how the cells of various organisms respond to hypoxia over time and adapted to study gene expression during other cellular responses.

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“…As expected, many O 2 -regulated genes play a role in cellular respiration, other aspects of metabolism, and in ribosomal processes 13 .…”

Section: Representative Resultssupporting

confidence: 74%

Section: Representative Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Measuring mRNA Levels Over Time During the Yeast S. cerevisiae Hypoxic Response

Willis

Hossian

Evans

et al. 2017

JoVE

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Mitonuclear epistasis, genotype‐by‐environment interactions, and personalized genomics of complex traits in Drosophila

et al. 2018

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Mitochondrial function requires the coordinated expression of dozens of gene products from the mitochondrial genome and hundreds from the nuclear genomes. The systems that emerge from these interactions convert the food we eat and the oxygen we breathe into energy for life, while regulating a wide range of other cellular processes. These facts beg the question of whether the gene‐by‐gene interactions (G x G) that enable mitochondrial function are distinct from the gene‐by‐environment interactions (G x E) that fuel mitochondrial activity. We examine this question using a Drosophila model of mitonuclear interactions in which experimental combinations of mtDNA and nuclear chromosomes generate pairs of mitonuclear genotypes to test for epistatic interactions (G x G). These mitonuclear genotypes are then exposed to altered dietary or oxygen environments to test for G x E interactions. We use development time to assess dietary effects, and genome wide RNAseq analyses to assess hypoxic effects on transcription, which can be partitioned in to mito, nuclear, and environmental (G x G x E) contributions to these complex traits. We find that mitonuclear epistasis is universal, and that dietary and hypoxic treatments alter the epistatic interactions. We further show that the transcriptional response to alternative mitonuclear interactions has significant overlap with the transcriptional response to alternative oxygen environments. Gene coexpression analyses suggest that these shared genes are more central in networks of gene interactions, implying some functional overlap between epistasis and genotype by environment interactions. These results are discussed in the context of evolutionary fitness, the genetic basis of complex traits, and the challenge of achieving precision in personalized medicine. © 2018 The Authors. IUBMB Life published by Wiley Periodicals, Inc. on behalf of International Union of Biochemistry and Molecular Biology, 70(12):1275–1288, 2018

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Modulation of green to red photoconversion of GFP during fluorescent microscopy by carbon source and oxygen availability

Bidiuk

Agaphonov

Alexandrov

2020

Yeast

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Studies have reported on the ability of green fluorescent proteins to photoconvert into a red fluorescent form under various conditions, such as the presence of oxidants, hypoxia, as well as under benign conditions using irradiation with a 405 nm laser. Here, we show that in Saccharomyces cerevisiae yeast green fluorescent protein (GFP) (S65T) fused to different cellular proteins can easily photoconvert into a red form when cells are grown in media with nonfermentable carbon sources. This photoconversion occurs during standard microscopy between glass slide and coverslip but is completely prevented by imaging on pads of solid medium or in a large volume of medium on an inverted microscope. The observed effect was due to rapid hypoxia of cells with respiratory metabolism in standard conditions for upright microscopy.Photoconversion could be prevented by antioxidant treatment, suggesting that it proceeds via the effects of reactive oxidative species emerging in response to oxygen deficiency. Our results show the need for caution during upright microscopy imaging in conditions where there is active respiration and demonstrate simple approaches to prevent unwanted GFP photoconversion. They also provide easy means of performing photoconversion experiments on existing GFP-bearing cell lines, at least in the case of yeast.

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Time-Course Analysis of Gene Expression During theSaccharomyces cerevisiaeHypoxic Response

Cited by 40 publications

References 54 publications

Measuring mRNA Levels Over Time During the Yeast <em>S. cerevisiae</em> Hypoxic Response

Measuring mRNA Levels Over Time During the Yeast <em>S. cerevisiae</em> Hypoxic Response

Mitonuclear epistasis, genotype‐by‐environment interactions, and personalized genomics of complex traits in Drosophila

Modulation of green to red photoconversion of GFP during fluorescent microscopy by carbon source and oxygen availability

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