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Controlling heterologous gene expression in yeast cell factories on different carbon substrates and across the diauxic shift: a comparison of yeast promoter activities

Overview of attention for article published in Microbial Cell Factories, June 2015
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  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (53rd percentile)

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Title
Controlling heterologous gene expression in yeast cell factories on different carbon substrates and across the diauxic shift: a comparison of yeast promoter activities
Published in
Microbial Cell Factories, June 2015
DOI 10.1186/s12934-015-0278-5
Pubmed ID
Authors

Bingyin Peng, Thomas C Williams, Matthew Henry, Lars K Nielsen, Claudia E Vickers

Abstract

Predictable control of gene expression is necessary for the rational design and optimization of cell factories. In the yeast Saccharomyces cerevisiae, the promoter is one of the most important tools available for controlling gene expression. However, the complex expression patterns of yeast promoters have not been fully characterised and compared on different carbon sources (glucose, sucrose, galactose and ethanol) and across the diauxic shift in glucose batch cultivation. These conditions are of importance to yeast cell factory design because they are commonly used and encountered in industrial processes. Here, the activities of a series of "constitutive" and inducible promoters were characterised in single cells throughout the fermentation using green fluorescent protein (GFP) as a reporter. The "constitutive" promoters, including glycolytic promoters, transcription elongation factor promoters and ribosomal promoters, differed in their response patterns to different carbon sources; however, in glucose batch cultivation, expression driven by these promoters decreased sharply as glucose was depleted and cells moved towards the diauxic shift. Promoters induced at low-glucose levels (P HXT7 , P SSA1 and P ADH2 ) varied in induction strength on non-glucose carbon sources (sucrose, galactose and ethanol); in contrast to the "constitutive" promoters, GFP expression increased as glucose decreased and cells moved towards the diauxic shift. While lower than several "constitutive" promoters during the exponential phase, expression from the SSA1 promoter was higher in the post-diauxic phase than the commonly-used TEF1 promoter. The galactose-inducible GAL1 promoter provided the highest GFP expression on galactose, and the copper-inducible CUP1 promoter provided the highest induced GFP expression following the diauxic shift. The data provides a foundation for predictable and optimised control of gene expression levels on different carbon sources and throughout batch fermentation, including during and after the diauxic shift. This information can be applied for designing expression approaches to improve yields, rates and titres in yeast cell factories.

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The data shown below were collected from the profiles of 3 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 526 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 <1%
Portugal 1 <1%
Singapore 1 <1%
India 1 <1%
Thailand 1 <1%
Denmark 1 <1%
Unknown 517 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 116 22%
Researcher 80 15%
Student > Master 60 11%
Student > Bachelor 59 11%
Student > Doctoral Student 18 3%
Other 64 12%
Unknown 129 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 202 38%
Agricultural and Biological Sciences 116 22%
Chemical Engineering 17 3%
Engineering 12 2%
Chemistry 11 2%
Other 35 7%
Unknown 133 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 29 June 2015.
All research outputs
#13,387,125
of 23,301,510 outputs
Outputs from Microbial Cell Factories
#813
of 1,641 outputs
Outputs of similar age
#120,334
of 264,600 outputs
Outputs of similar age from Microbial Cell Factories
#15
of 30 outputs
Altmetric has tracked 23,301,510 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,641 research outputs from this source. They receive a mean Attention Score of 4.5. This one is in the 49th percentile – i.e., 49% 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 264,600 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 53% of its contemporaries.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.