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Transcriptional profiling reveals molecular basis and novel genetic targets for improved resistance to multiple fermentation inhibitors in Saccharomyces cerevisiae

Overview of attention for article published in Biotechnology for Biofuels and Bioproducts, January 2016
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Title
Transcriptional profiling reveals molecular basis and novel genetic targets for improved resistance to multiple fermentation inhibitors in Saccharomyces cerevisiae
Published in
Biotechnology for Biofuels and Bioproducts, January 2016
DOI 10.1186/s13068-015-0418-5
Pubmed ID
Authors

Yingying Chen, Jiayuan Sheng, Tao Jiang, Joseph Stevens, Xueyang Feng, Na Wei

Abstract

Lignocellulosic biomass is a promising source of renewable biofuels. However, pretreatment of lignocellulosic biomass generates fermentation inhibitors that adversely affect the growth of industrial microorganisms such as Saccharomyces cerevisiae and prevent economic production of lignocellulosic biofuels. A critical challenge on developing S. cerevisiae with improved inhibitor resistance lies in incomplete understanding of molecular basis for inhibitor stress response and limited information on effective genetic targets for increasing yeast resistance to mixed fermentation inhibitors. In this study, we applied comparative transcriptomic analysis to determine the molecular basis for acetic acid and/or furfural resistance in S. cerevisiae. We recently developed a yeast strain YC1 with superior resistance to acetic acid, furfural, and their mixture through inverse metabolic engineering. In this study, we first determined transcriptional changes through RNA sequencing in YC1 versus the wild-type strain S-C1 under three different inhibitor conditions, including acetic acid alone, furfural alone, and mixture of acetic acid and furfural. The genes associated with stress responses of S. cerevisiae to single and mixed inhibitors were revealed. Specifically, we identified 184 consensus genes that were differentially regulated in response to the distinct inhibitor resistance between YC1 and S-C1. Bioinformatic analysis next revealed key transcription factors (TFs) that regulate these consensus genes. The top TFs identified, Sfp1p and Ace2p, were experimentally tested as overexpression targets for strain optimization. Overexpression of the SFP1 gene improved specific ethanol productivity by nearly four times, while overexpression of the ACE2 gene enhanced the rate by three times in the presence of acetic acid and furfural. Overexpression of SFP1 gene in the resistant strain YC1 further resulted in 42 % increase in ethanol productivity in the presence of acetic acid and furfural, suggesting the effect of Sfp1p in optimizing the yeast strain for improved tolerance to mixed fermentation inhibitor. Transcriptional regulation underlying yeast resistance to acetic acid and furfural was determined. Two transcription factors, Sfp1p and Ace2p, were uncovered for the first time for their functions in improving yeast resistance to mixed fermentation inhibitors. The study demonstrated an omics-guided metabolic engineering framework, which could be developed as a promising strategy to improve complex microbial phenotypes.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 137 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 3 2%
Spain 1 <1%
Thailand 1 <1%
United States 1 <1%
Unknown 131 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 38 28%
Student > Master 20 15%
Researcher 19 14%
Student > Bachelor 14 10%
Student > Doctoral Student 6 4%
Other 15 11%
Unknown 25 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 46 34%
Biochemistry, Genetics and Molecular Biology 43 31%
Chemical Engineering 7 5%
Energy 3 2%
Engineering 3 2%
Other 6 4%
Unknown 29 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 January 2016.
All research outputs
#17,286,379
of 25,374,647 outputs
Outputs from Biotechnology for Biofuels and Bioproducts
#997
of 1,578 outputs
Outputs of similar age
#243,806
of 402,001 outputs
Outputs of similar age from Biotechnology for Biofuels and Bioproducts
#33
of 56 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,578 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 402,001 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 56 others from the same source and published within six weeks on either side of this one. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.