Skip to main content

Thank you for visiting 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.

Optogenetic control of gene expression in plants in the presence of ambient white light


Optogenetics is the genetic approach for controlling cellular processes with light. It provides spatiotemporal, quantitative and reversible control over biological signaling and metabolic processes, overcoming limitations of chemically inducible systems. However, optogenetics lags in plant research because ambient light required for growth leads to undesired system activation. We solved this issue by developing plant usable light-switch elements (PULSE), an optogenetic tool for reversibly controlling gene expression in plants under ambient light. PULSE combines a blue-light-regulated repressor with a red-light-inducible switch. Gene expression is only activated under red light and remains inactive under white light or in darkness. Supported by a quantitative mathematical model, we characterized PULSE in protoplasts and achieved high induction rates, and we combined it with CRISPR–Cas9-based technologies to target synthetic signaling and developmental pathways. We applied PULSE to control immune responses in plant leaves and generated Arabidopsis transgenic plants. PULSE opens broad experimental avenues in plant research and biotechnology.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: PULSE is an optogenetic system for the control of gene expression in plants grown under standard light–dark cycles.
Fig. 2: Characterization of BOff in Arabidopsis protoplasts.
Fig. 3: Characterization of PULSE in Arabidopsis protoplasts.
Fig. 4: PULSE-controlled expression of a Cas9-derived gene activator (dCas9–TV) and an Arabidopsis transcription factor (LFY) in Arabidopsis protoplasts.
Fig. 5: Implementation and characterization of PULSE in N. benthamiana leaves.
Fig. 6: In planta optogenetic heterologous induction of immunity and conditional subcellular targeting of receptors, and PULSE functionality in Arabidopsis transgenic lines.

Data availability

Raw and associated data generated with plate-reader-, RT-qPCR- and microscope-specific software that support the findings of this study are available from the corresponding author upon request. The plasmids used in all experiments are available at AddGene, and the plasmid maps at the public repository JBEI-ICE ( Source data are provided with this paper.

Code availability

The numerical integration, fitting process and identifiability analysis with the profile likelihood method were performed in MATLAB using the freely available Data2Dynamics software. Details relative to the equations used can be found in the Supplementary Note. Source data are provided with this paper.


  1. 1.

    Deisseroth, K. & Hegemann, P. The form and function of channelrhodopsin. Science 357, eaan5544 (2017).

    PubMed  PubMed Central  Google Scholar 

  2. 2.

    Alberio, L. et al. A light-gated potassium channel for sustained neuronal inhibition. Nat. Methods 15, 969–976 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. 3.

    Ye, H., Baba, M. D.-E., Peng, R.-W. & Fussenegger, M. A synthetic optogenetic transcription device enhances blood-glucose homeostasis in mice. Science 332, 1565 (2011).

    CAS  PubMed  Google Scholar 

  4. 4.

    Strickland, D. et al. TULIPs: tunable, light-controlled interacting protein tags for cell biology. Nat. Methods 9, 379–384 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. 5.

    Shin, Y. et al. Spatiotemporal control of intracellular phase transitions using light-activated optoDroplets. Cell 168, 159–171.e14 (2017).

    CAS  PubMed  Google Scholar 

  6. 6.

    van Bergeijk, P., Adrian, M., Hoogenraad, C. C. & Kapitein, L. C. Optogenetic control of organelle transport and positioning. Nature 518, 111–114 (2015).

    PubMed  PubMed Central  Google Scholar 

  7. 7.

    Kolar, K., Knobloch, C., Stork, H., Žnidarič, M. & Weber, W. OptoBase: a web platform for molecular optogenetics. ACS Synth. Biol. 7, 1825–1828 (2018).

    CAS  PubMed  Google Scholar 

  8. 8.

    Müller, K. et al. A red light-controlled synthetic gene expression switch for plant systems. Mol. Biosyst. 10, 1679–1688 (2014).

    PubMed  Google Scholar 

  9. 9.

    Chatelle, C. et al. A green-light-responsive system for the control of transgene expression in mammalian and plant cells. ACS Synth. Biol. 7, 1349–1358 (2018).

    CAS  PubMed  Google Scholar 

  10. 10.

    Ochoa-Fernandez, R. et al. in Optogenetics: Methods and Protocols (ed. Kianianmomeni, A.) 125–139 (Humana Press, 2016).

  11. 11.

    Nash, A. I. et al. Structural basis of photosensitivity in a bacterial light-oxygen-voltage/helix-turn-helix (LOV-HTH) DNA-binding protein. Comput. Biol. 108, 9449–9945 (2011).

    CAS  Google Scholar 

  12. 12.

    Motta-Mena, L. B. et al. An optogenetic gene expression system with rapid activation and deactivation kinetics. Nat. Chem. Biol. 10, 196–202 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Moosmann, P., Georgiev, O., Thiesen, H., Hagmann, M. & Schaffner, W. Silencing of RNA polymerases II and III-dependent transcription by the KRAB protein domain of KOX1, a Krüppel-type zinc finger factor. Biol. Chem. 378, 669–677 (1997).

    CAS  PubMed  Google Scholar 

  14. 14.

    Baaske, J. et al. Dual-controlled optogenetic system for the rapid down-regulation of protein levels in mammalian cells. Sci. Rep. 8, 15024 (2018).

    PubMed  PubMed Central  Google Scholar 

  15. 15.

    Ikeda, M. & Ohme-Takagi, M. A novel group of transcriptional repressors in Arabidopsis. Plant Cell Physiol. 50, 970–975 (2009).

    CAS  PubMed  Google Scholar 

  16. 16.

    Kelly, J. M. & Lagarias, J. C. Photochemistry of 124-kilodalton Avena phytochrome under constant illumination in vitro. Biochemistry 24, 6003–6010 (1985).

    CAS  Google Scholar 

  17. 17.

    Müller, K. et al. Multi-chromatic control of mammalian gene expression and signaling. Nucleic Acids Res. 41, e124 (2013).

    PubMed  PubMed Central  Google Scholar 

  18. 18.

    Li, Z. et al. A potent Cas9-derived gene activator for plant and mammalian cells. Nat. Plants 3, 930–936 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. 19.

    Selma, S. et al. Strong gene activation in plants with genome-wide specificity using a new orthogonal CRISPR/Cas9-based programmable transcriptional activator. Plant Biotechnol. J. 17, 1703–1705 (2019).

    PubMed  PubMed Central  Google Scholar 

  20. 20.

    Simon, R., Igeño, M. I. & Coupland, G. Activation of floral meristem identity genes in Arabidopsis. Nature 384, 59–62 (1996).

    CAS  PubMed  Google Scholar 

  21. 21.

    de Felipe, P. et al. E unum pluribus: multiple proteins from a self-processing polyprotein. Trends Biotechnol. 24, 68–75 (2006).

    PubMed  Google Scholar 

  22. 22.

    Zipfel, C. et al. Perception of the Bacterial PAMP EF-Tu by the receptor EFR restricts Agrobacterium-mediated transformation. Cell 125, 749–760 (2006).

    CAS  PubMed  Google Scholar 

  23. 23.

    Kunze, G. et al. The N terminus of bacterial elongation factor Tu elicits innate immunity in Arabidopsis plants. Plant Cell 16, 3496–3507 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Lacombe, S. et al. Interfamily transfer of a plant pattern-recognition receptor confers broad-spectrum bacterial resistance. Nat. Biotechnol. 28, 365 (2010).

    CAS  PubMed  Google Scholar 

  25. 25.

    Suzuki, N. et al. Respiratory burst oxidases: the engines of ROS signaling. Curr. Opin. Plant Biol. 14, 691–699 (2011).

    CAS  PubMed  Google Scholar 

  26. 26.

    Gaupels, F., Durner, J. & Kogel, K.-H. Production, amplification and systemic propagation of redox messengers in plants? The phloem can do it all! N. Phytol. 214, 554–560 (2017).

    CAS  Google Scholar 

  27. 27.

    Kirchhofer, A. et al. Modulation of protein properties in living cells using nanobodies. Nat. Struct. Mol. Biol. 17, 133 (2009).

    PubMed  Google Scholar 

  28. 28.

    Gulati, S. et al. Targeting G protein-coupled receptor signaling at the G protein level with a selective nanobody inhibitor. Nat. Commun. 9, 1996 (2018).

    PubMed  PubMed Central  Google Scholar 

  29. 29.

    Schornack, S. et al. Protein mislocalization in plant cells using a GFP-binding chromobody. Plant J. 60, 744–754 (2009).

    CAS  PubMed  Google Scholar 

  30. 30.

    Yu, D. et al. Optogenetic activation of intracellular antibodies for direct modulation of endogenous proteins. Nat. Methods 16, 1095–1100 (2019).

    CAS  PubMed  Google Scholar 

  31. 31.

    Moore, I., Samalova, M., Kurup, S., For, T. & Analysis, M. Transactivated and chemically inducible gene expression in plants. Plant J. 45, 651–683 (2006).

    CAS  PubMed  Google Scholar 

  32. 32.

    Zuo, J. & Chua, N. H. Chemical-inducible systems for regulated expression of plant genes. Curr. Opin. Biotechnol. 11, 146–151 (2000).

    CAS  PubMed  Google Scholar 

  33. 33.

    Andres, J., Blomeier, T. & Zurbriggen, M. D. Synthetic switches and regulatory circuits in plants. Plant Physiol. 179, 862–884 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Cosentino, C. et al. Engineering of a light-gated potassium channel. Science 348, 707–710 (2015).

    CAS  PubMed  Google Scholar 

  35. 35.

    Papanatsiou, M. et al. Optogenetic manipulation of stomatal kinetics improves carbon assimilation, water use, and growth. Science 363, 1456–1459 (2019).

    CAS  PubMed  Google Scholar 

  36. 36.

    Martin-Arevalillo, R. & Vernoux, T. Shining light on plant hormones with genetically encoded biosensors. Biol. Chem. 400, 477–486 (2018).

    Google Scholar 

  37. 37.

    Kolar, K. & Weber, W. Synthetic biological approaches to optogenetically control cell signaling. Curr. Opin. Biotechnol. 47, 112–119 (2017).

    CAS  PubMed  Google Scholar 

  38. 38.

    Levskaya, A., Weiner, O. D., Lim, W. A. & Voigt, C. A. Spatiotemporal control of cell signalling using a light-switchable protein interaction. Nature 461, 997–1001 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. 39.

    Toettcher, J. E., Weiner, O. D. & Lim, W. A. Using optogenetics to interrogate the dynamic control of signal transmission by the Ras/Erk module. Cell 155, 1422–1434 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Renicke, C., Schuster, D., Usherenko, S., Essen, L. O. & Taxis, C. A LOV2 domain-based optogenetic tool to control protein degradation and cellular function. Chem. Biol. 20, 619–626 (2013).

    CAS  PubMed  Google Scholar 

  41. 41.

    Bonger, K. M., Rakhit, R., Payumo, A. Y., Chen, J. K. & Wandless, T. J. General method for regulating protein stability with light. ACS Chem. Biol. 9, 111–115 (2014).

    CAS  PubMed  Google Scholar 

  42. 42.

    Niopek, D. et al. Engineering light-inducible nuclear localization signals for precise spatiotemporal control of protein dynamics in living cells. Nat. Commun. 5, 4404 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Yumerefendi, H. et al. Control of protein activity and cell fate specification via light-mediated nuclear translocation. PLoS One 10, e0128443 (2015).

    PubMed  PubMed Central  Google Scholar 

  44. 44.

    Gibson, D. G. et al. Enzymatic assembly of DNA molecules up to several hundred kilobases. Nat. Methods 6, 343 (2009).

    CAS  PubMed  Google Scholar 

  45. 45.

    Beyer, H. M. et al. AQUA Cloning: a versatile and simple enzyme-free cloning approach. PLoS One 10, e0137652 (2015).

    PubMed  PubMed Central  Google Scholar 

  46. 46.

    Sarrion-Perdigones, A. et al. GoldenBraid 2.0: a comprehensive DNA assembly framework for plant synthetic biology. Plant Physiol. 162, 1618 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. 47.

    Binder, A. et al. A modular plasmid assembly kit for multigene expression, gene silencing and silencing rescue in plants. PLoS One 9, e88218 (2014).

    PubMed  PubMed Central  Google Scholar 

  48. 48.

    Weber, E., Engler, C., Gruetzner, R., Werner, S. & Marillonnet, S. A modular cloning system for standardized assembly of multigene constructs. PLoS One 6, e16765 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. 49.

    Müller, K., Zurbriggen, M. D. & Weber, W. Control of gene expression using a red- and far-red light–responsive bi-stable toggle switch. Nat. Protoc. 9, 622 (2014).

    PubMed  Google Scholar 

  50. 50.

    Sellaro, R. et al. Cryptochrome as a sensor of the blue/green ratio of natural radiation in Arabidopsis. Plant Physiol. 154, 401 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. 51.

    Bauer, P. Regulation of iron acquisition responses in plant roots by a transcription factor: regulation of iron acquisition responses. Biochem. Mol. Biol. Educ. 44, 438–449 (2016).

    CAS  PubMed  Google Scholar 

  52. 52.

    Vazquez-Vilar, M. et al. GB3.0: a platform for plant bio-design that connects functional DNA elements with associated biological data. Nucleic Acids Res. 45, 2196–2209 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. 53.

    Naranjo-Arcos, M. A. et al. Dissection of iron signaling and iron accumulation by overexpression of subgroup Ib bHLH039 protein. Sci. Rep. 7, 10911 (2017).

    PubMed  PubMed Central  Google Scholar 

  54. 54.

    Trujillo, M. in Environmental Responses in Plants: Methods and Protcools (ed. Duque, P.) 323–329 (Humana Press, 2016).

  55. 55.

    Clough, S. J. & Bent, A. F. Floral dip: a simplified method for Agrobacterium-mediated transformation of Arabidopsis thaliana. Plant J. 16, 735–743 (1998).

    CAS  PubMed  Google Scholar 

Download references


This study was supported in part by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy (CEPLAS—EXC-1028 project no. 194465578 to R.S. and M.D.Z., EXC-2048/1—project no. 390686111 to R.S. and M.D.Z., CIBSS – EXC-2189—project no. 390939984 to T.O., J.T. and W.W., and BIOSS – EXC-294 to J.T. and W.W.), the iGRAD Plant (IRTG 1525 to R.O.F., J.S., R.S. and M.D.Z.), and the Collaborative Research Centers SFB1208 (project no. 267205415; project A13 to M.D.Z.) and SFB924 (INST 95/1126-2; project B4 to T.O.), the European Commission – Research Executive Agency (H2020 Future and Emerging Technologies FET-Open project no. 801041 CyGenTig to M.D.Z.). J.B.M. is supported by a fellowship from the Eastern Academic Research Consortium. We thank D. Orzaez (Polytechnic University of Valencia) and K. Gardner (City University of New York) for kindly providing the GoldenBraid and EL222 plasmids, respectively, T. Brumbarova (University of Düsseldorf) for aid with quantitative reverse-transcription PCR experiments, R. Wurm and M. Gerads (University of Düsseldorf) for technical assistance, and J. Schmidt (Technical Workshop Biology, University of Freiburg) for designing and constructing the light boxes used in this work. We are indebted to J. Casal (University of Buenos Aires), D. Nusinow (Danforth Center), S. Romero, H. Beyer and U. Urquiza (University of Düsseldorf) for careful reading and their suggestions to improve the manuscript.

Author information




R.O.F., N.B.A., L.-A.K., J.B.M. and S.M.B. designed and cloned the constructs. S.M.B. performed preliminary tests and R.O.F. conducted all Arabidopsis protoplasts experiments. F.-G.W. and R.E. developed the mathematical model. R.O.F., N.B.A., J.S. and L.-A.K. contributed to the establishment of PULSE in planta. N.B.A. conducted the conditional targeting and immunity induction in planta. R.O.F. and G.G. generated the transgenic Arabidopsis PULSE lines and performed the experiments. R.O.F., N.B.A., T.O., R.S. and M.D.Z. designed the experiments. J.T., W.W., T.O., R.S. and M.D.Z. supervised the research. T.O., R.S. and M.D.Z. analyzed the data and discussed results. M.D.Z. planned and directed the project. R.O.F. and M.D.Z. designed the system and wrote the initial manuscript with input from all authors. All authors contributed to editing and read the final version of the manuscript.

Corresponding author

Correspondence to Matias D. Zurbriggen.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nina Vogt 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 Model-based functional characterization, and prediction and validation of PULSE function.

a,b, Quantitative characterization of On-Off PULSE kinetics and reversibility. PULSE-driven FLuc expression assays in Arabidopsis protoplasts. (a) FLuc/RLuc ratios for protein expression kinetics, n = 6 protoplast samples. (b) Normalized starting quantity (SQ) of FLuc transcript to the SQ geometric mean of EF and TIP41L transcripts (internal normalization controls), n = 2 technical replicates for each transcript (b). Protoplasts were transformed and kept in the dark, 12 h for protein (a) and 16 h for mRNA (b) determination, followed by illumination with either 10 µmol m−2 s−1 of red or blue light, or kept in darkness. Arrows indicate the time point where the samples were split into different illumination conditions, for example, red to dark, red to blue (On-Off), red to blue to red (On-Off-On). The curves are the fits to the ODE-based model. The shaded areas represent the error bands as calculated in 95% confidence intervals with a constant Gaussian error model using the profile likelihood method. c, Model aided prediction of PULSE-controlled protein expression levels as a function of red light intensities and illumination times. The calibrated model yields estimated FLuc/RLuc expression ranges (heatmap). d, Experimental validation of the model predictions of the operating range of PULSE. Selected model simulated expression levels at different red light intensities and illumination times as indicated in (c) were experimentally tested and the resulting FLuc/RLuc ratios (means and 2xSEM are plotted, n = 6 protoplast samples for each condition, black circles) were compared to the predicted values (grey squares). RLU = Relative Luminescence Units. Source data

Supplementary information

Supplementary Information

Supplementary Note, Figs. 1–11 and Tables 1–3.

Reporting Summary

Supplementary Dataset

Statistical Source Data Supplementary Fig. 1.

Source data

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 5

Statistical source data.

Source Data Fig. 6

Statistical source data.

Source Data Extended Data Fig. 1

Statistical source data.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Ochoa-Fernandez, R., Abel, N.B., Wieland, FG. et al. Optogenetic control of gene expression in plants in the presence of ambient white light. Nat Methods 17, 717–725 (2020).

Download citation

Further reading


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing