Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Brief Communication
  • Published:

Inducible and multiplex gene regulation using CRISPR–Cpf1-based transcription factors

Abstract

Targeted and inducible regulation of mammalian gene expression is a broadly important capability. We engineered drug-inducible catalytically inactive Cpf1 nuclease fused to transcriptional activation domains to tune the expression of endogenous genes in human cells. Leveraging the multiplex capability of the Cpf1 platform, we demonstrate both synergistic and combinatorial gene expression in human cells. Our work should enable the development of multiplex gene perturbation library screens for understanding complex cellular phenotypes.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Targeted human endogenous gene regulation using individual crRNAs with dLbCpf1-based activators.
Figure 2: Multiplex and synergistic regulation of endogenous human genes by dLbCpf1-based activators.

Similar content being viewed by others

References

  1. Komor, A.C., Badran, A.H. & Liu, D.R. Cell 168, 20–36 (2017).

    Article  CAS  Google Scholar 

  2. Wright, A.V., Nuñez, J.K. & Doudna, J.A. Cell 164, 29–44 (2016).

    Article  CAS  Google Scholar 

  3. Dominguez, A.A., Lim, W.A. & Qi, L.S. Nat. Rev. Mol. Cell Biol. 17, 5–15 (2016).

    Article  CAS  Google Scholar 

  4. Zetsche, B., Volz, S.E. & Zhang, F. Nat. Biotechnol. 33, 139–142 (2015).

    Article  CAS  Google Scholar 

  5. Bao, Z., Jain, S., Jaroenpuntaruk, V. & Zhao, H. ACS Synth. Biol. 6, 686–693 (2017).

    Article  CAS  Google Scholar 

  6. Polstein, L.R. & Gersbach, C.A. Nat. Chem. Biol. 11, 198–200 (2015).

    Article  CAS  Google Scholar 

  7. Zetsche, B. et al. Cell 163, 759–771 (2015).

    Article  CAS  Google Scholar 

  8. Gao, L. et al. Nat. Biotechnol. 35, 789–792 (2017).

    Article  CAS  Google Scholar 

  9. Fonfara, I., Richter, H., Bratovič, M., Le Rhun, A. & Charpentier, E. Nature 532, 517–521 (2016).

    Article  CAS  Google Scholar 

  10. Zetsche, B. et al. Nat. Biotechnol. 35, 31–34 (2017).

    Article  CAS  Google Scholar 

  11. Kim, S.K. et al. ACS Synth. Biol. 6, 1273–1282 (2017).

    Article  CAS  Google Scholar 

  12. Zhang, X. et al. Cell Discov. 3, 17018 (2017).

    Article  CAS  Google Scholar 

  13. Tang, X. et al. Nat. Plants 3, 17018 (2017).

    Article  CAS  Google Scholar 

  14. Chavez, A. et al. Nat. Methods 12, 326–328 (2015).

    Article  CAS  Google Scholar 

  15. Gilbert, L.A. et al. Cell 159, 647–661 (2014).

    Article  CAS  Google Scholar 

  16. Chavez, A. et al. Nat. Methods 13, 563–567 (2016).

    Article  CAS  Google Scholar 

  17. Rivera, V.M., Berk, L. & Clackson, T. Cold Spring Harb. Protoc. 2012, 821–824 (2012).

    PubMed  Google Scholar 

  18. Hilton, I.B. et al. Nat. Biotechnol. 33, 510–517 (2015).

    Article  CAS  Google Scholar 

  19. Liu, X.S. et al. Cell 167, 233–247.e17 (2016).

    Article  CAS  Google Scholar 

  20. Amabile, A. et al. Cell 167, 219–232.e14 (2016).

    Article  CAS  Google Scholar 

  21. Kleinstiver, B.P. et al. Nat. Biotechnol. 34, 869–874 (2016).

    Article  CAS  Google Scholar 

  22. Maeder, M.L. et al. Nat. Methods 10, 977–979 (2013).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank M. Welch and A. Sousa for technical assistance with constructing certain plasmids. B.P.K. acknowledges support from Banting (Natural Sciences and Engineering Research Council of Canada) and Charles A. King Trust Postdoctoral Fellowships. This work was supported by the National Institutes of Health R35 GM118158 (J.K.J.), NIH R01 GM107427 (J.K.J.), R01 DA036858 (J.S.W.) and U01 CA168370 (J.S.W.), the Howard Hughes Medical Institute (J.S.W.), and the Desmond and Ann Heathwood Massachusetts General Hospital Research Scholar Award (J.K.J.).

Author information

Authors and Affiliations

Authors

Contributions

Y.E.T., B.P.K., J.K.N., J.Y.H., J.S.W., and J.K.J. conceived of and designed experiments. Y.E.T., B.P.K., J.K.N., J.Y.H., J.E.H., and J.G. performed experiments. Y.E.T., B.P.K., J.K.N., J.Y.H., J.S.W., and J.K.J. wrote the manuscript.

Corresponding author

Correspondence to J Keith Joung.

Ethics declarations

Competing interests

B.P.K. is a consultant for Avectas. J.S.W. is a founder and scientific advisory board member of KSQ Therapeutics. J.K.J. has financial interests in Beam Therapeutics, Editas Medicine, Monitor Biotechnologies, Pairwise Plants, Poseida Therapeutics, and Transposagen Biopharmaceuticals. J.K.J.'s interests were reviewed and are managed by Massachusetts General Hospital and Partners HealthCare in accordance with their conflict of interest policies.

Integrated supplementary information

Supplementary Figure 1 Characterization of dCpf1 for gene activation.

(a) Schematic of doxycycline-inducible GFP reporter stably integrated into HEK293T cells used to assess CRISPRa activity. Promoter shown contains seven repeated activator target sites.

(b) Maps for expression constructs encoding dCas9, dLbCpf1, and dAsCpf1 fusions to the VP64-p65-Rta (VPR) activator.

(c) Quantification of GFP activation measured 3 days post-transfection with vectors expressing the protein fusions and guide RNAs. The rTTA+Dox serves as a positive control for GFP activation. Fluorescence values were normalized to HEK293-GFP reporter cells without plasmids transfected (column 1). Each bar is the mean of two replicates.

(d) Western blot analysis of HA-tagged dCas9, dLbCpf1, and dAsCpf1 fusions to VPR. The top band is the P2A-BFP attached to the fusion (P2A uncleaved) and the bottom band is the mature fusion without the P2A-BFP attached (P2A cleaved). The anti-GAPDH panel serves as a loading control.

Supplementary Figure 2 Analysis of various crRNAs targeted to the human CD5 and CD22 promoters.

32 crRNAs (16 for each gene) were designed to target sites located within promoter sequences 1 kb upstream or 500 bps downstream of the TSS of each gene. Repetitive sequences were not targeted. After 72 hours post-transfection, cells were stained with fluorescently labeled antibody for (a) CD5 or (b) CD22 protein and fluorescent-positive cells were quantified by flow cytometry. Error bars represent s.e.m. for three biological independent replicates. Red circles indicate samples that are significantly different (Student t-test, two-tailed test assuming equal variance, p <0.05) compared to controls in which no crRNA was expressed. (c) and (d) are examples of experimental flow cytometry plots stained for CD5 and CD22 activation, respectively. (e) and (f) are examples of flow cytometry plots for negative controls stained for CD5 and CD22, respectively.

Supplementary Figure 3 Synergistic regulation of endogenous human genes by dLbCpf1-based activators.

Activities of direct dLbCpf1-p65 or dLbCpf1-VPR fusions with three single crRNAs, pooled sets of single crRNAs, and a MST encoding all three crRNAs on the HBB, AR, or NPY1R endogenous gene promoters. Transcripts were measured in HEK293 cells using RT-qPCR with relative mRNA expression calculated by comparison to the control sample in which no crRNA is expressed. Synergistic effects of dLbCpf1-VPR fusions with MST crRNAs or individual pooled crRNAs are all statistically significant (Student t-test, two-tailed test assuming equal variance, p<0.05) except for cases where n.s. (not significant) is indicated.

Supplementary Figure 4 Experiments to optimize activities of MST crRNAs with dLbCpf1-VPR.

Results of experiments designed to test the transfection of various amounts and ratios of expression plasmids encoding dLbCpf1-VPR and crRNAs targeted to the promoters of three endogenous human genes (HBB, AR, and NPY1R) in HEK293 cells. crRNAs were encoded as a single crRNA in one transcript (Single crRNA) or as multiple crRNAs in one transcript (MST crRNA)). Transfected cells were harvested and assayed for gene expression by RT-qPCR at three different time points post-transfection (48 hours, 72 hours, and 96 hours). Representative data shown are of three biological independent replicates with error bars representing standard deviation (SD) of three technical replicates. n.s., not significantly different as determined by Student t-test (p > 0.05); *, significantly different as determined by Student t-test (two-tailed test assuming equal variance, p< 0.05)

Supplementary Figure 5 Activities of MST crRNA with different dLbCpf1-based activators in human U2OS cells.

Graphs showing activation of three endogenous human genes with dLbCpf1-VPR direct fusions (left panel), dLbCpf1-DmrA(x4) and DmrC-p65 fusions (middle panel), and dLbCpf1-DmrA(x4) and DmrC-VPR fusions (right panel) and crRNAs expressed from a multiplex single transcript (MST) or from transcripts encoding a single crRNA. RNA expression was measured by RT-qPCR and relative expression shown was calculated by comparison to a control sample in which no crRNA is expressed. Representative data are shown for three biological independent replicates and error bars indicate standard deviation (SD) of three technical replicates. n.s., not significantly different as determined by Student t-test (p > 0.05); *, significantly different as determined by Student t-test (two-tailed test assuming equal variance, p< 0.05)

Supplementary Figure 6 Inducibility and reversibility of A/C heterodimerizer drug-regulated dLbCpf1-based activators.

(a) To measure the kinetics of activator induction, HEK293 cells were transfected with plasmids expressing dLbCpf1-DmrA(x4), DmrC-p65, and MST crRNAs targeting the human HBB or AR promoters (same crRNAs used in Fig. 2b). 34 hours after transfection, these cells were split into two cultures: one with media containing A/C heterodimerizer (500uM) (top, blue) and one with media lacking the A/C heterodimerizer (bottom, purple). Cells were collected at various time points and relative mRNA expression levels were measured by RT-qPCR compared to a negative control. (b) To measure the kinetics of reversibility, HEK293 cells were transfected as in (a). 24 hours after transfection, A/C heterodimerzer (500uM) was added to the medium. 10 hours later, these cells were split into two cultures: one with media containing A/C heterodimerizer (500uM) (top, blue) and one with media lacking the A/C heterodimerizer (bottom, purple). Cells were collected at various time points and relative mRNA expression levels were measured by RT-qPCR compared to a negative control. Error bars represent s.e.m. of three biological independent replicates.

Supplementary Figure 7 Optimization of a A/C heterodimerizer drug-inducible dCas9-based activator.

(a) Titrations of A/C heterodimerizer (left panel) and expression plasmids encoding dCas9-DmrA(x4) fusion protein and DmrC-VP64 or DmrC-p65 effectors (right panel) together with plasmids expressing either one or three sgRNAs targeted upstream of the human VEGFA transcription start site. Gene activation assessed by VEGFA ELISA; error bars represent s.e.m. for n = 3.

(b) Relative differences in gene activation between direct dCas9-activation domain fusions compared to drug-dependent dCas9-based activator fusions, using either one or three sgRNAs targeted upstream of the VEGFA transcription start site. Gene activation assessed by VEGFA ELISA; error bars represent s.e.m. for n = 2, otherwise n = 1.

(c) Differences in VEGFA expression observed with variable numbers of DmrA domains fused to either the amino-terminal or carboxy-terminal end of dCas9 (DmrA-dCas9 or dCas9-DmrA, respectively) and with the VP64 activation domain fused to the amino or carboxy-terminal end of DmrC (VP64-DmrC or DmrC-VP64, respectively). These experiments also included an expression vector expressing three sgRNAs targeted upstream of the VEGFA transcription start site. Gene activation assessed by VEGFA ELISA; error bars represent s.e.m. for n = 3.

Supplementary Figure 8 Targeting range of dCpf1-based activators.

Graphs representing the percentage of NGG “desert” regions for 32,696 human TSSs that are targetable by (a) wild-type Cpf1 (TTTV PAM) and (b) wild-type Cpf1 together with two engineered Cpf1 variants (that recognize TYCV and TATV PAMs). TSSs were binned by the their total desert region lengths (in bps) and box plots of percentage coverage were generated for each bin.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–8, Supplementary Tables 1–2 and Supplementary Notes 1–2 (PDF 2381 kb)

Life Sciences Reporting Summary (PDF 175 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tak, Y., Kleinstiver, B., Nuñez, J. et al. Inducible and multiplex gene regulation using CRISPR–Cpf1-based transcription factors. Nat Methods 14, 1163–1166 (2017). https://doi.org/10.1038/nmeth.4483

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nmeth.4483

This article is cited by

Search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research