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Transcriptional reprogramming in yeast using dCas9 and combinatorial gRNA strategies

Overview of attention for article published in Microbial Cell Factories, March 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

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6 X users
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1 patent
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1 Wikipedia page

Citations

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105 Dimensions

Readers on

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245 Mendeley
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Title
Transcriptional reprogramming in yeast using dCas9 and combinatorial gRNA strategies
Published in
Microbial Cell Factories, March 2017
DOI 10.1186/s12934-017-0664-2
Pubmed ID
Authors

Emil D. Jensen, Raphael Ferreira, Tadas Jakočiūnas, Dushica Arsovska, Jie Zhang, Ling Ding, Justin D. Smith, Florian David, Jens Nielsen, Michael K. Jensen, Jay D. Keasling

Abstract

Transcriptional reprogramming is a fundamental process of living cells in order to adapt to environmental and endogenous cues. In order to allow flexible and timely control over gene expression without the interference of native gene expression machinery, a large number of studies have focused on developing synthetic biology tools for orthogonal control of transcription. Most recently, the nuclease-deficient Cas9 (dCas9) has emerged as a flexible tool for controlling activation and repression of target genes, by the simple RNA-guided positioning of dCas9 in the vicinity of the target gene transcription start site. In this study we compared two different systems of dCas9-mediated transcriptional reprogramming, and applied them to genes controlling two biosynthetic pathways for biobased production of isoprenoids and triacylglycerols (TAGs) in baker's yeast Saccharomyces cerevisiae. By testing 101 guide-RNA (gRNA) structures on a total of 14 different yeast promoters, we identified the best-performing combinations based on reporter assays. Though a larger number of gRNA-promoter combinations do not perturb gene expression, some gRNAs support expression perturbations up to ~threefold. The best-performing gRNAs were used for single and multiplex reprogramming strategies for redirecting flux related to isoprenoid production and optimization of TAG profiles. From these studies, we identified both constitutive and inducible multiplex reprogramming strategies enabling significant changes in isoprenoid production and increases in TAG. Taken together, we show similar performance for a constitutive and an inducible dCas9 approach, and identify multiplex gRNA designs that can significantly perturb isoprenoid production and TAG profiles in yeast without editing the genomic context of the target genes. We also identify a large number of gRNA positions in 14 native yeast target pomoters that do not affect expression, suggesting the need for further optimization of gRNA design tools and dCas9 engineering.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 245 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
China 1 <1%
Belgium 1 <1%
Unknown 243 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 65 27%
Student > Master 35 14%
Researcher 34 14%
Student > Bachelor 24 10%
Other 13 5%
Other 28 11%
Unknown 46 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 105 43%
Agricultural and Biological Sciences 59 24%
Engineering 7 3%
Immunology and Microbiology 6 2%
Chemical Engineering 6 2%
Other 9 4%
Unknown 53 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 10 August 2023.
All research outputs
#3,562,433
of 24,770,025 outputs
Outputs from Microbial Cell Factories
#155
of 1,764 outputs
Outputs of similar age
#62,962
of 312,972 outputs
Outputs of similar age from Microbial Cell Factories
#4
of 39 outputs
Altmetric has tracked 24,770,025 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,764 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 91% 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 312,972 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 79% of its contemporaries.
We're also able to compare this research output to 39 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 92% of its contemporaries.