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dCas9-mediated transcriptional activation of tissue inhibitor of metalloproteinases

Overview of attention for article published in Metalloproteinases In Medicine, September 2017
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Title
dCas9-mediated transcriptional activation of tissue inhibitor of metalloproteinases
Published in
Metalloproteinases In Medicine, September 2017
DOI 10.2147/mnm.s146752
Pubmed ID
Authors

Tyler Duellman, Andrea Doll, Xi Chen, Rie Wakamiya, Jay Yang

Abstract

Selective gene activation with the dCas9 (deactivated clustered regularly interspaced short palindromic repeats [CRISPR] associated protein 9)/CRISPR targeting of a transcriptional activator effector is now well established. However, the optimal targeting of guide RNA (gRNA) for a given gene is largely a matter of trial and error. We explored the optimal targeting site for tissue inhibitor of metalloproteinases (TIMPs) by first screening multiple gRNA target sites using a luciferase-based promoter-reporter system and next confirmed the effective TIMP induction in the mouse motor neuron-like neuron-enriched spinal cord 34 (NSC34) cells. Screening of many gRNAs targeting the 1-1.9 kB promoter regions of TIMP1-3 identified several hot-spots for optimal gene induction, however, no general pattern defining the optimal target site with respect to the proximity of known transcription factor binding sites or distance from the start ATG was apparent. TIMP2 with a larger basal transcriptional activity showed a greater fold-induction with gRNA compared with TIMP1 or 3 supporting the importance of an open-chromatin for best gRNA-mediated transcriptional induction. The rank order of induction potency for different gRNA identified in the promoter-reporter screening held true for the NSC34 cells. Co-activation with multiple gRNAs greatly increased the gene induction.

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The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 23%
Student > Ph. D. Student 4 18%
Student > Doctoral Student 3 14%
Other 2 9%
Student > Bachelor 2 9%
Other 3 14%
Unknown 3 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 32%
Agricultural and Biological Sciences 6 27%
Business, Management and Accounting 1 5%
Nursing and Health Professions 1 5%
Neuroscience 1 5%
Other 2 9%
Unknown 4 18%