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Dynamic regulation of gene expression using sucrose responsive promoters and RNA interference in Saccharomyces cerevisiae

Overview of attention for article published in Microbial Cell Factories, April 2015
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3 tweeters

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25 Dimensions

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90 Mendeley
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Title
Dynamic regulation of gene expression using sucrose responsive promoters and RNA interference in Saccharomyces cerevisiae
Published in
Microbial Cell Factories, April 2015
DOI 10.1186/s12934-015-0223-7
Pubmed ID
Authors

Thomas C Williams, Monica I Espinosa, Lars K Nielsen, Claudia E Vickers

Abstract

Engineering dynamic, environmentally- and temporally-responsive control of gene expression is one of the principle objectives in the field of synthetic biology. Dynamic regulation is desirable because many engineered functions conflict with endogenous processes which have evolved to facilitate growth and survival, and minimising conflict between growth and production phases can improve product titres in microbial cell factories. There are a limited number of mechanisms that enable dynamic regulation in yeast, and fewer still that are appropriate for application in an industrial setting. To address this problem we have identified promoters that are repressed during growth on glucose, and activated during growth on sucrose. Catabolite repression and preferential glucose utilisation allows active growth on glucose before switching to production on sucrose. Using sucrose as an activator of gene expression circumvents the need for expensive inducer compounds and enables gene expression to be triggered during growth on a fermentable, high energy-yield carbon source. The ability to fine-tune the timing and population density at which gene expression is activated from the SUC2 promoter was demonstrated by varying the ratio of glucose to sucrose in the growth medium. Finally, we also demonstrated that the system could also be used to repress gene expression (a process also required for many engineering projects). We used the glucose/sucrose system to control a heterologous RNA interference module and dynamically repress the expression of a constitutively regulated GFP gene. The low noise levels and high dynamic range of the SUC2 promoter make it a promising option for implementing dynamic regulation in yeast. The capacity to repress gene expression using RNA interference makes the system highly versatile, with great potential for metabolic engineering applications.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 90 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 1%
Chile 1 1%
Brazil 1 1%
India 1 1%
Denmark 1 1%
China 1 1%
Korea, Republic of 1 1%
United States 1 1%
Unknown 82 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 31%
Researcher 15 17%
Student > Master 11 12%
Student > Bachelor 10 11%
Student > Postgraduate 4 4%
Other 11 12%
Unknown 11 12%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 35 39%
Agricultural and Biological Sciences 32 36%
Engineering 3 3%
Chemical Engineering 2 2%
Environmental Science 1 1%
Other 4 4%
Unknown 13 14%

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 18 April 2015.
All research outputs
#9,479,987
of 12,378,406 outputs
Outputs from Microbial Cell Factories
#602
of 898 outputs
Outputs of similar age
#144,371
of 225,432 outputs
Outputs of similar age from Microbial Cell Factories
#7
of 10 outputs
Altmetric has tracked 12,378,406 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 898 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 28th percentile – i.e., 28% 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 225,432 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 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.