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Investigating strain dependency in the production of aromatic compounds in Saccharomyces cerevisiae

Overview of attention for article published in Biotechnology & Bioengineering, June 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

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1 news outlet
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2 X users
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3 patents

Citations

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46 Dimensions

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82 Mendeley
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Title
Investigating strain dependency in the production of aromatic compounds in Saccharomyces cerevisiae
Published in
Biotechnology & Bioengineering, June 2016
DOI 10.1002/bit.26037
Pubmed ID
Authors

Miguel Suástegui, Weihua Guo, Xueyang Feng, Zengyi Shao

Abstract

Although Saccharomyces cerevisiae is the most highly domesticated yeast, strain dependency in biotechnological processes still remains as a common, yet poorly understood phenomenon. To investigate this, the entrance to the aromatic amino acid biosynthetic pathway was compared in four commonly used S. cerevisiae laboratory strains. The strains were engineered to accumulate shikimate by overexpressing a mutant version of the pentafunctional ARO1 enzyme with disrupted activity in the shikimate kinase subunit. Carbon tracing and (13) C metabolic flux analysis combined with quantitative PCR, revealed that precursor availability and shikimate production were dramatically different in the four equally engineered strains, which were found to be correlated with the strains' capacity to deal with protein overexpression burden. By implementing a strain-dependent approach, the genetic platform was reformulated, leading to an increase in yield and titer in all strains. The highest producing strain, INVSc1-SA3, produced 358 mg L(-1) of shikimate with a yield of 17.9 mg g(-1) glucose . These results underline the importance of strain selection in developing biological manufacturing processes, demonstrate the first case of high production of shikimate in yeast, and provide an appropriate platform for strain selection for future production of aromatic compounds. This article is protected by copyright. All rights reserved.

X Demographics

X Demographics

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

Mendeley readers

The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
China 1 1%
Unknown 80 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 26%
Researcher 18 22%
Student > Bachelor 7 9%
Student > Master 7 9%
Other 5 6%
Other 10 12%
Unknown 14 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 25 30%
Agricultural and Biological Sciences 22 27%
Chemical Engineering 7 9%
Engineering 3 4%
Chemistry 3 4%
Other 3 4%
Unknown 19 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 17 May 2022.
All research outputs
#2,485,774
of 25,374,917 outputs
Outputs from Biotechnology & Bioengineering
#174
of 6,450 outputs
Outputs of similar age
#43,280
of 366,924 outputs
Outputs of similar age from Biotechnology & Bioengineering
#3
of 47 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,450 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 97% 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 366,924 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 47 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.