Plant-Based Biosensors for Detecting CRISPR-Mediated Genome Engineering

Guoliang Yuan, Md Mahmudul Hassan, Tao Yao, Haiwei Lu, Michael Melesse Vergara, Jesse L. Labbé, Wellington Muchero, Changtian Pan, Jin Gui Chen, Gerald A. Tuskan, Yiping Qi, Paul E. Abraham, Xiaohan Yang

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

CRISPR/Cas has recently emerged as the most reliable system for genome engineering in various species. However, concerns about risks associated with the CRISPR/Cas technology are increasing on potential unintended DNA changes that might accidentally arise from CRISPR gene editing. Developing a system that can detect and report the presence of active CRISPR/Cas tools in biological systems is therefore very necessary. Here, we developed four real-time detection systems that can spontaneously indicate the presence of active CRISPR-Cas tools for genome editing and gene regulation including CRISPR/Cas9 nuclease, base editing, prime editing, and CRISPRa in plants. Using the fluorescence-based molecular biosensors, we demonstrated that the activities of CRISPR/Cas9 nuclease, base editing, prime editing, and CRISPRa can be effectively detected in transient expression via protoplast transformation and leaf infiltration (in Arabidopsis, poplar, and tobacco) and stable transformation in Arabidopsis.

Original languageEnglish
Pages (from-to)3600-3603
Number of pages4
JournalACS Synthetic Biology
Volume10
Issue number12
DOIs
StatePublished - Dec 17 2021

Funding

This work was funded by the Genomic Science Program of the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (BER) as part of the Secure Ecosystems Engineering and Design research program in the Secure Biosystems Design Scientific Focus Area (SFA). Oak Ridge National Laboratory is managed by UT-Battelle, LLC for the U.S. Department of Energy under Contract Number DE-AC05-00OR22725. This work was also supported by the National Science Foundation Plant Genome Research Program (Award No. IOS-1758745 and IOS-2029889).

Keywords

  • CRISPR
  • biosensor
  • detection
  • genome editing
  • transient gene expression

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