In vivo high-throughput profiling of CRISPR-Cpf1 activity

Hui K. Kim, Myungjae Song, Jinu Lee, A. Vipin Menon, Soobin Jung, Young Mook Kang, Jae W. Choi, Euijeon Woo, Hyun C. Koh, Jin Wu Nam, Hyongbum Kim

Research output: Contribution to journalArticlepeer-review

142 Citations (Scopus)

Abstract

CRISPR from Prevotella and Francisella 1 (Cpf1) is an effector endonuclease of the class 2 CRISPR-Cas (clustered regularly interspaced short palindromic repeats-CRISPR-associated proteins) gene editing system. We developed a method for evaluating Cpf1 activity, based on target sequence composition in mammalian cells, in a high-throughput manner. A library of >11,000 target sequence and guide RNA pairs was delivered into human cells using lentiviral vectors. Subsequent delivery of Cpf1 into this cell library induced insertions and deletions (indels) at the integrated synthetic target sequences, which allowed en masse evaluation of Cpf1 activity by using deep sequencing. With this approach, we determined protospacer-adjacent motif sequences of two Cpf1 nucleases, one from Acidaminococcus sp. BV3L6 (hereafter referred to as AsCpf1) and the other from Lachnospiraceae bacterium ND2006 (hereafter referred to as LbCpf1). We also defined target-sequence-dependent activity profiles of AsCpf1, which enabled the development of a web tool that predicts the indel frequencies for given target sequences (http://big.hanyang.ac.kr/cindel). Both the Cpf1 characterization profile and the in vivo high-throughput evaluation method will greatly facilitate Cpf1-based genome editing.

Original languageEnglish
Pages (from-to)153-159
Number of pages7
JournalNature Methods
Volume14
Issue number2
DOIs
Publication statusPublished - 2017 Feb 1

Bibliographical note

Funding Information:
Acknowledgments The authors would like to thank D.-S. Jang (Medical Illustrator, Medical Research Support Section, Yonsei University College of Medicine) for his help with the illustrations, D. Kim for developing Python programs, M. K. Song (Biostatistics Collaboration Unit, Yonsei University College of Medicine) and Y. Kim for the assistance with statistical analysis, E.-S. Lee for proofreading, R. Gopalappa for assistance with sample preparation, Severance Biomedical Science Institute for bioinformatics analysis, and B. Kleinstiver and K. Joung (both at Massachusetts General Hospital) for sharing raw data for Supplementary Figure 9 and Figure 3d. This work was supported in part by the National Research Foundation of Korea (grants 2014R1A1A1A05006189 (H.K.), 2013M3A9B4076544 (H.K.), 2014M3C9A3063541 (J.-W.N.), and 2015R1A2A1A15052668 (H.K.)), the Korean Health Technology R&D Project, Ministry of Health and Welfare, Republic of Korea (grants HI14C2019 (Medistar program) (H.K.), HI16C1012 (H.K.), and HI15C1578 (J.-W.N.)), and a faculty research grant of Yonsei University College of Medicine for 2015 (6-2015-0086 (H.K.)).

Publisher Copyright:
© 2017 Nature America, inc., part of springer Nature. All rights reserved.

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Biochemistry
  • Molecular Biology
  • Cell Biology

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