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Programmable RNA editing with compact CRISPR–Cas13 systems from uncultivated microbes

Nature Methods volume 18, pages 499–506 (2021)Cite this article

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An Author Correction to this article was published on 02 January 2022

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Abstract

Competitive coevolution between microbes and viruses has led to the diversification of CRISPR–Cas defense systems against infectious agents. By analyzing metagenomic terabase datasets, we identified two compact families (775 to 803 amino acids (aa)) of CRISPR–Cas ribonucleases from hypersaline samples, named Cas13X and Cas13Y. We engineered Cas13X.1 (775 aa) for RNA interference experiments in mammalian cell lines. We found Cas13X.1 could tolerate single-nucleotide mismatches in RNA recognition, facilitating prophylactic RNA virus inhibition. Moreover, a minimal RNA base editor, composed of engineered deaminase (385 aa) and truncated Cas13X.1 (445 aa), exhibited robust editing efficiency and high specificity to induce RNA base conversions. Our results suggest that there exist untapped bacterial defense systems in natural microbes that can function efficiently in mammalian cells, and thus potentially are useful for RNA-editing-based research.

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Fig. 1: Identification and characterization of type VI-X and VI-Y CRISPR systems.
Fig. 2: Efficient and specific interference activity of Cas13X.1 against transcripts in HEK293 cells.
Fig. 3: Antiviral activity of Cas13X.1 in mammalian cells and mismatch tolerance features of Cas13X.1, RfxCas13d and LwaCas13a.
Fig. 4: Truncated dCas13X.1 with ADAR2dd variants for efficient RNA base editing.

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Data availability

All the sequencing data have been deposited in the NCBI SRA under project accession number PRJNA680488. Meta-information on all raw NGS datasets is provided in Supplementary Table 16. Source data are provided with this paper.

Code availability

Bioinformatics codes were deposited in the GitHub repository (https://github.com/yszhou2016/Cas13).

Change history

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Acknowledgements

We thank M. Poo for discussions and comments on this manuscript; and the FACS facility, H. Wu and L. Quan at ION. This work was supported by the Basic Frontier Scientific Research Program of Chinese Academy of Sciences From 0 to 1 original innovation project (grant no. ZDBS-LY-SM001), the R&D Program of China (grant nos. 2017YFC1001300 and 2018YFC2000100), the CAS Strategic Priority Research Program (grant no. XDB32060000), the National Natural Science Foundation of China (grant nos. 31871502, 31925016, 91957122, 31901047, 82021001), the Shanghai Municipal Science and Technology Major Project (grant no. 2018SHZDZX05), the Shanghai City Committee of Science and Technology Project (grant nos. 18411953700, 18JC1410100, 19XD1424400, 19YF1455100) and the International Partnership Program of Chinese Academy of Sciences (grant no. 153D31KYSB20170059).

Author information

Author notes

  1. These authors contributed equally: Chunlong Xu, Yingsi Zhou, Qingquan Xiao, Bingbing He, Guannan Geng.

Authors and Affiliations

  1. Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China

    Chunlong Xu, Yingsi Zhou, Qingquan Xiao, Bingbing He, Guannan Geng, Zikang Wang, Xue Dong, Yifan Wang, Xiaona Huo & Hui Yang

  2. College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China

    Qingquan Xiao, Bingbing He & Birong Cao

  3. CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China

    Birong Cao

  4. Huigene Therapeutics Inc., Shanghai, China

    Weiya Bai

  5. Shanghai Public Health Clinical Center, Fudan University, Shanghai, China

    Xiang Wang & Dongming Zhou

  6. Department of Pathogen Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China

    Dongming Zhou

  7. Center for Animal Genomics, Agricultural Genome Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China

    Tanglong Yuan

  8. State Key Laboratory of Agrobiotechnology and National Maize Improvement Center, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, China

    Jinsheng Lai

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Contributions

C.X., Y.Z. and H.Y. conceived the project. C.X., Y.Z., Q.X., B.H. and G.G. designed and conducted experiments. Y.Z. and J.L. performed bioinformatics analysis. Z.W. and B.C. assisted with plasmids construction and RNA analysis. T.Y. assisted with cell experiments. X.W., D.Z. and X.H. assisted with virus experiments. H.Y. designed experiments and supervised the whole project. C.X., Y.Z. and H.Y. wrote the paper.

Corresponding authors

Correspondence to Yingsi Zhou, Jinsheng Lai or Hui Yang.

Ethics declarations

Competing interests

H.Y. is a founder of Hui-Gene Therapeutics. H.Y., C.X., Y.Z., and Q.X. are co-inventors on US patent application 16/864,982 relating to the Cas proteins described in this manuscript. The remaining authors declare no competing interests.

Additional information

Peer review information Nature Methods thanks the anonymous reviewers for their contribution to the peer review of this work. Lei Tang was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Computational pipeline for the identification of new CRISPR RNA-Targeting System Cas13 and protein schematics for Cas13 effectors.

a, Schematic describing a fast and classical computational pipeline for CRISPR system identification. In fast pipeline, a minimal definition for a putative class 2 CRISPR locus was used, requiring only a CRISPR repeat array and a nearby protein of 400 to 900 aa in length. b, Distribution of RNxxxH, RHxxxH, RQxxxH motifs among Cas13 proteins. All values are presented as percentage of motif occurrence (n = 180). c, Schematics describing protein-size and HEPN motif position of previously identified Cas13a/b/c/d and Cas13X/f proteins used in this study. The RxxxxH HEPN motif is highlighted. d, Similarity analysis between type E and F effectors by position-specific iterated BLAST. E value of >1e-10 defined as cutoff for non-significant similarity. e, HEPN domain alignment between type VI-X/Y and previously reported Cas13 effectors. Conserved residuals for Cas13X and Cas13Y were highlighted in pink and previously reported Cas13 in green.

Source data

Extended Data Fig. 2 Pre-crRNA processing mechanism of Cas13X.1 and effect of crRNA length and PFS on Cas13X.1 activity.

a, Procedure diagram of mCherry reporter inhibition assay for testing Cas13 activity in HEK293T. b, Schematics describing HEPN-active and -inactive Cas13X.1. The wild-type and inactivated mutant RxxxxH HEPN motifs are highlighted. c, Schematic diagram of potential mechanisms for pre-crRNA to mature crRNA processing by Cas13X.1. d, Reporter inhibition assay revealed ribonuclease-activity dependence on HEPN domains and crRNAs with 3’DR. e, Top, Schematic diagram showing the mCherry specific crRNAs with different spacer lengths. Bottom, Changes of mCherry fluorescence intensity for mCherry specific crRNAs of different lengths relative to non-targeting (NT) crRNA, as measured by flow cytometry. f, PFS analysis with crRNA targeting sequences flanked by different PFS. All values are presented as mean ± s.e.m (n = 3). P values are by two-sided unpaired t-test.

Source data

Extended Data Fig. 3 Comparison of knockdown activity between previously reported Cas13 and Cas13X.1/Cas13Y.1.

a, Relative target RNA knockdown by individual position-matched Cas13X.1 and RfxCasRx crRNAs. b, Cas13X.1 targeting efficiency of 12 endogenous transcripts, each with 3 guides and a non-targeting (NT) crRNA in HEK293T cells. c, Comparison of mCherry knockdown activity among Cas13X.1, Cas13Y.1, LwaCas13a, PspCas13b and RfxCas13d (n = 3 for each protein). d, Comparison of endogenous genes knockdown activity among Cas13X.1, Cas13Y.1, LwaCas13a, PspCas13b and RfxCas13d (n = 12 for each protein). *P < 0.05, ***P < 0.001, two-sided unpaired t-test. All values are presented as mean ± s.e.m (n = 3). P values are by two-sided unpaired t-test.

Source data

Extended Data Fig. 4 Genome-wide search for similar sequences with crRNA target from both B4GALNT1 and EZH2 gene predicted several potential off-target genes and volcano plot showed their differential expression significance.

Red and blue dot indicate significantly upregulated and downregulated off-target genes. Grey dot depicts non-significantly regulated off-target genes. Large blue dot indicates target gene, B4GALNT1 and EZH2.

Source data

Extended Data Fig. 5 Collateral activity comparison between Cas13X.1, RfxCas13d and LwaCas13a in HEK293T cells.

a, Schematics describing collateral activity detection system based on EGFP-transgenic HEK293T cells. b-e, Target knockdown and collateral activity for Cas13X.1, RfxCas13d and LwaCas13a with mCherry, endogenous ANXA4, B4GALNT1 and EZH2-targeting crRNAs. All values are presented as mean ± s.e.m (n = 3). P values are by two-sided unpaired t-test.

Source data

Extended Data Fig. 6 Biochemical characterization of on-target and collateral ribonuclease activity.

a, On-target ribonuclease activity comparison among LwaCas13a, RfxCas13d, Cas13X.1 and Cas13Y.1. b, Collateral ribonuclease activity comparison among LwaCas13a, RfxCas13d, Cas13X.1 and Cas13Y.1. AU, arbitrary unit. All Values shown are mean (n = 3).

Extended Data Fig. 7 Bioinformatics analysis for identifying minimal number of coronaviruses-targeting crRNAs.

a, Schematic describing a computational pipeline for identifying the minimal number of crRNAs targeting all coronaviruses by analyzing available coronavirus genomes. b,c, Histograms showing the predicted minimal number of 22-nt and 30-nt crRNAs with zero mismatch to target all sequenced 3,137 coronavirus genomes. d, Seventeen 30-nt crRNAs with single-nt mismatch in the minimal pool that targets all coronaviruses and their similarity with human transcriptome.

Source data

Extended Data Fig. 8 Verification of eABE function with mCherry* reporter system and predicted Cas13X.1 protein structure.

a, Schematic procedure of testing eABE with the mCherry* reporter system. b, Predicted protein structure of Cas13X.1. Yellow denote N terminal; green indicate C terminal; red represent HEPN motif.

Extended Data Fig. 9 Effect of mismatched base position on xABE activity and Sanger sequencing results of editing human endogenous transcripts by xABE.

a, Mismatch positions in different crRNAs targeting the mCherry amber mutation. b, Effect of mismatched base position with 50-nt spacer on A-to-I editing efficiency by both full and mini xABE editors. All values are presented as mean ± s.e.m (n = 3). c, Sanger sequencing results showing representative A-to-I conversion on endogenous transcripts by full and mini xABE editors. Red triangles indicate mutation sites.

Source data

Extended Data Fig. 10 Off-target RNA editing effect for xABE, mxABE, xCBE, mxCBE and REPAIR system.

a, Transcriptome-wide off-target sites numbers for GFP/mCherry (control), xABE, mxABE, xCBE and mxCBE transfection experiments in HEK293T cells. All values are presented as mean ± s.e.m (n = 3). b, Manhattan plots of transcriptome-wide off-target RNA editing analysis for REPAIR transfection experiments in HEK293T cells (A-to-I editor targeting endogenous SMAD4 RNA). The x and y axis are proportionally enlarged with each Manhattan plot to make the axis legend clear. Non-DR, guide RNA without direct repeats. NT, non-targeting crRNA.

Source data

Supplementary information

Supplementary Information

Supplementary gating strategy and experimental protocol.

Reporting Summary

Supplementary Table 1

Genomic positions and habitat information of Cas13X.1-X.2 and Cas13Y.1-Y5

Supplementary Table 2

Cas13X.1-X.2 and Cas13Y.1-Y.5 protein sequences used in the study

Supplementary Table 3

Type VI-X and VI-Y classification criteria

Supplementary Table 4

HEPN domains sequence alignment of type VI-A to VI-Y Cas13 proteins

Supplementary Table 5

Spacer sequences in Cas13X and Cas13Y associated CRISPR arrays

Supplementary Table 6

Natural crRNA targets

Supplementary Table 7

Significant differentially downregulated and upregulated genes by EZH2 knockdown with Cas13X.1

Supplementary Table 8

Significant differentially downregulated and upregulated genes by EZH2 knockdown with RfxCas13d

Supplementary Table 9

Significant differentially downregulated and upregulated genes by B4GALNT1 knockdown with Cas13X.1

Supplementary Table 10

Significant differentially downregulated and upregulated genes by B4GALNT1 knockdown with RfxCas13d

Supplementary Table 11

Primers used in the study

Supplementary Table 12

Predicted off-target sequences from hg38 genome for B4GALNT1 crRNA

Supplementary Table 13

Predicted off-target sequences from hg38 transcriptome for B4GALNT1 crRNA

Supplementary Table 14

Predicted off-target sequences from hg38 genome for EZH2 crRNA

Supplementary Table 15

Predicted off-target sequences from hg38 transcriptome for EZH2 crRNA

Supplementary Table 16

RNA-seq datasets information

Source data

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Xu, C., Zhou, Y., Xiao, Q. et al. Programmable RNA editing with compact CRISPR–Cas13 systems from uncultivated microbes. Nat Methods 18, 499–506 (2021). https://doi.org/10.1038/s41592-021-01124-4

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