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Series GSE69682 Query DataSets for GSE69682
Status Public on Jun 03, 2016
Title Transcriptome Engineering Promotes a Fermentative Transcriptional State
Organism Saccharomyces cerevisiae
Experiment type Expression profiling by high throughput sequencing
Summary Purpose: The ability to rationally manipulate the transcriptional states of cells would be of great use in medicine and bioengineering. We have developed a novel algorithm, NetSurgeon, which utilizes genome-wide gene regulatory networks to identify interventions that force a cell toward a desired expression state.
Results: We used NetSurgeon to select transcription factor deletions aimed at improving ethanol production in S. cerevisiae cultures that are catabolizing xylose. We reasoned that interventions that move the transcriptional states of cells utilizing xylose toward the fermentative state typical of cells that are producing ethanol rapidly (while utilizing glucose) might improve xylose fermentation. Some of the interventions selected by NetSurgeon successfully promoted a fermentative transcriptional state in the absence of glucose, resulting in strains with a 2.7-fold increase in xylose import rates, a 4-fold improvement in xylose integration into central carbon metabolism, or a 1.3-fold increase in ethanol production rate.
Conclusions: We conclude by presenting an integrated model of transcriptional regulation and metabolic flux that will enable future metabolic engineering efforts aimed at improving xylose fermentation to prioritize functional regulators of central carbon metabolism.
 
Overall design Mutant and wildtype S. cerevisiae cells were put into 48 hour aerobic batch fermentations of synthetic complete medium supplmented with 2% glucose and 5% xylose and culture samples were taken at 4 hours and 24 hours for transcriptional profiling performed by RNA-Seq analysis. In addition, wildtype S. cerevisiae cells were grown in various single carbon sources for 12 hours and culture samples were taken for transcriptional profiling performed by RNA-Seq analysis.
 
Contributor(s) Michael DG, Maier EJ, Brown H, Gish SR, Fiore C, Brown RH, Brent MR
Citation(s) 27810962
Submission date Jun 09, 2015
Last update date May 15, 2019
Contact name Ezekiel John Maier
E-mail(s) zmaier@cse.wustl.edu
Organization name Washington University
Department Computer Science
Lab Michael Brent
Street address 4444 Forest Park Ave
City Saint Louis
State/province MO
ZIP/Postal code 63112
Country USA
 
Platforms (3)
GPL13272 Illumina Genome Analyzer IIx (Saccharomyces cerevisiae)
GPL13821 Illumina HiSeq 2000 (Saccharomyces cerevisiae)
GPL17342 Illumina HiSeq 2500 (Saccharomyces cerevisiae)
Samples (90)
GSM1706746 H2217-WT-ETH.1p3-12-1-12.16.09-239-5-1
GSM1706747 H2217-WT-ETH.1p3-12-2-12.16.09-239-6-2
GSM1706748 H2217-WT-ETH.1p3-12-3-12.16.09-239-7-3
Relations
BioProject PRJNA286183
SRA SRP059270

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE69682_RAW.tar 17.6 Mb (http)(custom) TAR (of CUFF, TXT)
GSE69682_expression.mtr.txt.gz 1.9 Mb (ftp)(http) TXT
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file
Processed data are available on Series record
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