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Abstract
In type II CRISPR systems, the guide RNA (gRNA) comprises a CRISPR RNA (crRNA) and a hybridized trans-acting CRISPR RNA (tracrRNA), both being essential in guided DNA targeting functions. Although tracrRNAs are diverse in sequence and structure across type II CRISPR systems, the programmability of crRNA-tracrRNA hybridization for Cas9 is not fully understood. Here, we reveal the programmability of crRNA-tracrRNA hybridization for Streptococcus pyogenes Cas9, and in doing so, redefine the capabilities of Cas9 proteins and the sources of crRNAs, providing new biosensing applications for type II CRISPR systems. By reprogramming the crRNA-tracrRNA hybridized sequence, we show that engineered crRNA-tracrRNA interactions can not only enable the design of orthogonal cellular computing devices but also facilitate the hijacking of endogenous small RNAs/mRNAs as crRNAs. We subsequently describe how these re-engineered gRNA pairings can be implemented as RNA sensors, capable of monitoring the transcriptional activity of various environment-responsive genomic genes, or detecting SARS-CoV-2 RNA in vitro, as an Atypical gRNA-activated Transcription Halting Alarm (AGATHA) biosensor.
In type II CRISPR systems, the guide RNA (gRNA) comprises a CRISPR RNA (crRNA) and a hybridized trans-acting CRISPR RNA (tracrRNA), both being essential in guided DNA targeting functions. Here the authors investigate the programmability of crRNA-tracrRNA hybridization for Cas9 and apply this to biosensing.
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Details
; Wan Xinyi 2
; Yang Zhugen 3
; Peng Shuguang 4 ; Li Mengxi 2 ; Cooper, Jonathan M 5
; Xie Zhen 4
; French, Christopher E 6 ; Wang, Baojun 7
1 Zhejiang University, College of Chemical and Biological Engineering & Hangzhou Innovation Center, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X); University of Edinburgh, Centre for Synthetic and Systems Biology, School of Biological Sciences, Edinburgh, UK (GRID:grid.4305.2) (ISNI:0000 0004 1936 7988)
2 University of Edinburgh, Centre for Synthetic and Systems Biology, School of Biological Sciences, Edinburgh, UK (GRID:grid.4305.2) (ISNI:0000 0004 1936 7988)
3 Research Centre for Biological Computation, Zhejiang Laboratory, Hangzhou, China (GRID:grid.510538.a) (ISNI:0000 0004 8156 0818); Cranfield University, Cranfield Water Science Institute, School of Water, Environment and Energy, Cranfield, UK (GRID:grid.12026.37) (ISNI:0000 0001 0679 2190)
4 Tsinghua University, Center for Synthetic and System Biology, Department of Automation, Beijing National Research Centre for Information Science and Technology, Beijing, China (GRID:grid.12527.33) (ISNI:0000 0001 0662 3178)
5 University of Glasgow, Division of Biomedical Engineering, James Watt School of Engineering, Glasgow, UK (GRID:grid.8756.c) (ISNI:0000 0001 2193 314X)
6 University of Edinburgh, Centre for Synthetic and Systems Biology, School of Biological Sciences, Edinburgh, UK (GRID:grid.4305.2) (ISNI:0000 0004 1936 7988); Zhejiang University International Campus, Zhejiang University-University of Edinburgh Joint Research Centre for Engineering Biology, Haining, China (GRID:grid.4305.2)
7 Zhejiang University, College of Chemical and Biological Engineering & Hangzhou Innovation Center, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X); University of Edinburgh, Centre for Synthetic and Systems Biology, School of Biological Sciences, Edinburgh, UK (GRID:grid.4305.2) (ISNI:0000 0004 1936 7988); Research Centre for Biological Computation, Zhejiang Laboratory, Hangzhou, China (GRID:grid.510538.a) (ISNI:0000 0004 8156 0818); Zhejiang University International Campus, Zhejiang University-University of Edinburgh Joint Research Centre for Engineering Biology, Haining, China (GRID:grid.510538.a)




