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Enhanced xylose fermentation and ethanol production by engineered Saccharomyces cerevisiae strain

Overview of attention for article published in AMB Express, February 2015
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)

Mentioned by

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2 tweeters
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1 patent

Citations

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47 Dimensions

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120 Mendeley
Title
Enhanced xylose fermentation and ethanol production by engineered Saccharomyces cerevisiae strain
Published in
AMB Express, February 2015
DOI 10.1186/s13568-015-0102-y
Pubmed ID
Authors

Leonardo de Figueiredo Vilela, Verônica Parente Gomes de Araujo, Raquel de Sousa Paredes, Elba Pinto da Silva Bon, Fernando Araripe Gonçalves Torres, Bianca Cruz Neves, Elis Cristina Araújo Eleutherio

Abstract

We have recently demonstrated that heterologous expression of a bacterial xylose isomerase gene (xylA) of Burkholderia cenocepacia enabled a laboratorial Saccharomyces cerevisiae strain to ferment xylose anaerobically, without xylitol accumulation. However, the recombinant yeast fermented xylose slowly. In this study, an evolutionary engineering strategy was applied to improve xylose fermentation by the xylA-expressing yeast strain, which involved sequential batch cultivation on xylose. The resulting yeast strain co-fermented glucose and xylose rapidly and almost simultaneously, exhibiting improved ethanol production and productivity. It was also observed that when cells were grown in a medium containing higher glucose concentrations before being transferred to fermentation medium, higher rates of xylose consumption and ethanol production were obtained, demonstrating that xylose utilization was not regulated by catabolic repression. Results obtained by qPCR demonstrate that the efficiency in xylose fermentation showed by the evolved strain is associated, to the increase in the expression of genes HXT2 and TAL1, which code for a low-affinity hexose transporter and transaldolase, respectively. The ethanol productivity obtained after the introduction of only one genetic modification and the submission to a one-stage process of evolutionary engineering was equivalent to those of strains submitted to extensive metabolic and evolutionary engineering, providing solid basis for future applications of this strategy in industrial strains.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 <1%
Brazil 1 <1%
Unknown 118 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 20%
Student > Master 20 17%
Student > Ph. D. Student 17 14%
Student > Bachelor 14 12%
Student > Doctoral Student 9 8%
Other 17 14%
Unknown 19 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 41 34%
Biochemistry, Genetics and Molecular Biology 29 24%
Engineering 7 6%
Chemical Engineering 5 4%
Environmental Science 3 3%
Other 12 10%
Unknown 23 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 14 June 2018.
All research outputs
#4,268,447
of 14,800,128 outputs
Outputs from AMB Express
#95
of 932 outputs
Outputs of similar age
#62,162
of 214,791 outputs
Outputs of similar age from AMB Express
#1
of 1 outputs
Altmetric has tracked 14,800,128 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 932 research outputs from this source. They receive a mean Attention Score of 2.1. This one has done well, scoring higher than 89% of its peers.
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 214,791 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them