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Live single-cell transcriptional dynamics via RNA labelling during the phosphate response in plants

Nature Plants volume 7, pages 1050–1064 (2021)Cite this article

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Abstract

Plants are constantly adapting to ambient fluctuations through spatial and temporal transcriptional responses. Here, we implemented the latest-generation RNA imaging system and combined it with microfluidics to visualize transcriptional regulation in living Arabidopsis plants. This enabled quantitative measurements of the transcriptional activity of single loci in single cells, in real time and under changing environmental conditions. Using phosphate-responsive genes as a model, we found that active genes displayed high transcription initiation rates (one initiation event every ~3 s) and frequently clustered together in endoreplicated cells. We observed gene bursting and large allelic differences in single cells, revealing that at steady state, intrinsic noise dominated extrinsic variations. Moreover, we established that transcriptional repression triggered in roots by phosphate, a crucial macronutrient limiting plant development, occurred with unexpectedly fast kinetics (on the order of minutes) and striking heterogeneity between neighbouring cells. Access to single-cell RNA polymerase II dynamics in live plants will benefit future studies of signalling processes.

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Fig. 1: Identification of fast responsive transcripts regulated at the transcriptional level by phosphate resupply.
Fig. 2: Validation of pSPX1::MS2×128 transgenic plants.
Fig. 3: Imaging of SPX1 transcription in fixed plant tissues reveals allelic differences in the root cap and polyploid expression in mature tissue.
Fig. 4: Quantitation of SPX1 transcription in fixed cells gives insights into transcription dynamics, ploidy and intrinsic versus extrinsic noise.
Fig. 5: Combining microfluidic and MS2 technology reveals fast transcriptional repression triggered by Pi supply in pSPX1::MS2×128 transgenic plants.
Fig. 6: The SPX1 promoter generates bursts of activity in root cap cells grown at steady state in the absence of phosphate.
Fig. 7: Analysis of transcription site activity following Pi supply in pSPX1::MS2×128 S line transgenic plants.

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Data availability

The genetic constructs, lines and datasets generated in the current study are available from the corresponding author upon request.

References

  1. Lopez-Maury, L., Marguerat, S. & Bahler, J. Tuning gene expression to changing environments: from rapid responses to evolutionary adaptation. Nat. Rev. Genet. 9, 583–593 (2008).

    Article  CAS  PubMed  Google Scholar 

  2. Birnbaum, K. et al. A gene expression map of the Arabidopsis root. Science 302, 1956–1960 (2003).

    Article  CAS  PubMed  Google Scholar 

  3. Balleza, E., Kim, J. M. & Cluzel, P. Systematic characterization of maturation time of fluorescent proteins in living cells. Nat. Methods 15, 47–51 (2018).

    Article  CAS  PubMed  Google Scholar 

  4. Sorenson, R. S., Deshotel, M. J., Johnson, K., Adler, F. R. & Sieburth, L. E. Arabidopsis mRNA decay landscape arises from specialized RNA decay substrates, decapping-mediated feedback, and redundancy. Proc. Natl Acad. Sci. USA 115, E1485–E1494 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Narsai, R. et al. Genome-wide analysis of mRNA decay rates and their determinants in Arabidopsis thaliana. Plant Cell 19, 3418–3436 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Kollist, H. et al. Rapid responses to abiotic stress: priming the landscape for the signal transduction network. Trends Plant Sci. 24, 25–37 (2019).

    Article  CAS  PubMed  Google Scholar 

  7. Bertrand, E. et al. Localization of ASH1 mRNA particles in living yeast. Mol. Cell 2, 437–445 (1998).

    Article  CAS  PubMed  Google Scholar 

  8. Fusco, D. et al. Single mRNA molecules demonstrate probabilistic movement in living mammalian cells. Curr. Biol. 13, 161–167 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Boireau, S. et al. The transcriptional cycle of HIV-1 in real-time and live cells. J. Cell Biol. 179, 291–304 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Lucas, T. et al. Live imaging of bicoid-dependent transcription in Drosophila embryos. Curr. Biol. 23, 2135–2139 (2013).

    Article  CAS  PubMed  Google Scholar 

  11. Chao, J. A., Patskovsky, Y., Almo, S. C. & Singer, R. H. Structural basis for the coevolution of a viral RNA–protein complex. Nat. Struct. Mol. Biol. 15, 103–105 (2008).

    Article  CAS  PubMed  Google Scholar 

  12. Pichon, X., Lagha, M., Mueller, F. & Bertrand, E. A growing toolbox to image gene expression in single cells: sensitive approaches for demanding challenges. Mol. Cell 71, 468–480 (2018).

    Article  CAS  PubMed  Google Scholar 

  13. Tantale, K. et al. A single-molecule view of transcription reveals convoys of RNA polymerases and multi-scale bursting. Nat. Commun. 7, 12248 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Misson, J. et al. A genome-wide transcriptional analysis using Arabidopsis thaliana Affymetrix gene chips determined plant responses to phosphate deprivation. Proc. Natl Acad. Sci. USA 102, 11934–11939 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Thibaud, M. C. et al. Dissection of local and systemic transcriptional responses to phosphate starvation in Arabidopsis. Plant J. 64, 775–789 (2010).

    Article  CAS  PubMed  Google Scholar 

  16. Rubio, V. et al. A conserved MYB transcription factor involved in phosphate starvation signaling both in vascular plants and in unicellular algae. Genes Dev. 15, 2122–2133 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Bustos, R. et al. A central regulatory system largely controls transcriptional activation and repression responses to phosphate starvation in Arabidopsis. PLoS Genet. 6, e1001102 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Puga, M. I. et al. SPX1 is a phosphate-dependent inhibitor of PHOSPHATE STARVATION RESPONSE 1 in Arabidopsis. Proc. Natl Acad. Sci. USA 111, 14947–14952 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Wang, Z. et al. Rice SPX1 and SPX2 inhibit phosphate starvation responses through interacting with PHR2 in a phosphate-dependent manner. Proc. Natl Acad. Sci. USA 111, 14953–14958 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Zhu, J. et al. Two bifunctional inositol pyrophosphate kinases/phosphatases control plant phosphate homeostasis. eLife https://doi.org/10.7554/eLife.43582 (2019).

  21. Wild, R. et al. Control of eukaryotic phosphate homeostasis by inositol polyphosphate sensor domains. Science 352, 986–990 (2016).

    Article  CAS  PubMed  Google Scholar 

  22. Grossmann, G. et al. The RootChip: an integrated microfluidic chip for plant science. Plant Cell 12, 4234–4240 (2011).

    Article  Google Scholar 

  23. Misson, J., Thibaud, M. C., Bechtold, N., Raghothama, K. & Nussaume, L. Transcriptional regulation and functional properties of Arabidopsis Pht1;4, a high affinity transporter contributing greatly to phosphate uptake in phosphate deprived plants. Plant Mol. Biol. 55, 727–741 (2004).

    Article  CAS  PubMed  Google Scholar 

  24. Tutucci, E. et al. An improved MS2 system for accurate reporting of the mRNA life cycle. Nat. Methods 15, 81–89 (2018).

    Article  CAS  PubMed  Google Scholar 

  25. Engler, C., Gruetzner, R., Kandzia, R. & Marillonnet, S. Golden gate shuffling: a one-pot DNA shuffling method based on type IIs restriction enzymes. PLoS ONE 4, e5553 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Grefen, C. et al. A ubiquitin-10 promoter-based vector set for fluorescent protein tagging facilitates temporal stability and native protein distribution in transient and stable expression studies. Plant J. 64, 355–365 (2010).

    Article  CAS  PubMed  Google Scholar 

  27. Duncan, S., Olsson, T. S. G., Hartley, M., Dean, C. & Rosa, S. A method for detecting single mRNA molecules in Arabidopsis thaliana. Plant Methods 12, 13 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Duan, K. et al. Characterization of a sub-family of Arabidopsis genes with the SPX domain reveals their diverse functions in plant tolerance to phosphorus starvation. Plant J. 54, 965–975 (2008).

    Article  CAS  PubMed  Google Scholar 

  29. Bhosale, R. et al. A spatiotemporal DNA endoploidy map of the Arabidopsis root reveals roles for the endocycle in root development and stress adaptation. Plant Cell 30, 2330–2351 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Levsky, J. M., Shenoy, S. M., Pezo, R. C. & Singer, R. H. Single-cell gene expression profiling. Science 297, 836–840 (2002).

    Article  CAS  PubMed  Google Scholar 

  31. Femino, A. M., Fay, F. S., Fogarty, K. & Singer, R. H. Visualization of single RNA transcripts in situ. Science 280, 585–590 (1998).

    Article  CAS  PubMed  Google Scholar 

  32. Zhu, J., Liu, M., Liu, X. & Dong, Z. RNA polymerase II activity revealed by GRO-seq and pNET-seq in Arabidopsis. Nat. Plants 4, 1112–1123 (2018).

    Article  CAS  PubMed  Google Scholar 

  33. Hetzel, J., Duttke, S. H., Benner, C. & Chory, J. Nascent RNA sequencing reveals distinct features in plant transcription. Proc. Natl Acad. Sci. USA 113, 12316–12321 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Furlong, E. E. M. & Levine, M. Developmental enhancers and chromosome topology. Science 361, 1341–1345 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Garcia, H. G., Tikhonov, M., Lin, A. & Gregor, T. Quantitative imaging of transcription in living Drosophila embryos links polymerase activity to patterning. Curr. Biol. 23, 2140–2145 (2013).

    Article  CAS  PubMed  Google Scholar 

  36. Alamos, S., Reimer, A., Niyogi, K. K. & Garcia, H. G. Quantitative imaging of RNA polymerase II activity in plants reveals the single-cell basis of tissue-wide transcriptional dynamics. Nat. Plants https://doi.org/10.1038/s41477-021-00976-0 (2021).

  37. Elowitz, M. B., Levine, A. J., Siggia, E. D. & Swain, P. S. Stochastic gene expression in a single cell. Science 297, 1183–1186 (2002).

    Article  CAS  PubMed  Google Scholar 

  38. Guichard, M., Bertran Garcia de Olalla, E., Stanley, C. E. & Grossmann, G. Microfluidic systems for plant root imaging. Methods Cell. Biol. 160, 381–404 (2020).

    Article  CAS  PubMed  Google Scholar 

  39. Bayle, V. et al. Arabidopsis thaliana high-affinity phosphate transporters exhibit multiple levels of posttranslational regulation. Plant Cell 23, 1523–1535 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Pichon, X. et al. Visualization of single endogenous polysomes reveals the dynamics of translation in live human cells. J. Cell Biol. 214, 769–781 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Pena, E. J. & Heinlein, M. RNA transport during TMV cell-to-cell movement. Front. Plant Sci. 3, 193 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Kanno, S. et al. Development of real-time radioisotope imaging systems for plant nutrient uptake studies. Phil. Trans. R. Soc. B 367, 1501–1508 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Kanno, S. et al. A novel role for the root cap in phosphate uptake and homeostasis. eLife 5, e14577 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Schubert, V., Berr, A. & Meister, A. Interphase chromatin organisation in Arabidopsis nuclei: constraints versus randomness. Chromosoma 121, 369–387 (2012).

    Article  CAS  PubMed  Google Scholar 

  45. Hanchi, M. et al. The phosphate fast-responsive genes PECP1 and PPsPase1 affect phosphocholine and phosphoethanolamine content. Plant Physiol. 176, 2943–2962 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Gutierrez, R. A., Ewing, R. M., Cherry, J. M. & Green, P. J. Identification of unstable transcripts in Arabidopsis by cDNA microarray analysis: rapid decay is associated with a group of touch- and specific clock-controlled genes. Proc. Natl Acad. Sci. USA 99, 11513–11518 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Sarrobert, C. et al. Identification of an Arabidopsis thaliana mutant accumulating threonine resulting from mutation in a new dihydrodipicolinate synthase gene. Plant J. 24, 357–367 (2000).

    Article  CAS  PubMed  Google Scholar 

  48. Secco, D. et al. Stress induced gene expression drives transient DNA methylation changes at adjacent repetitive elements. eLife https://doi.org/10.7554/eLife.09343 (2015).

  49. Godon, C. et al. Under phosphate starvation conditions, Fe and Al trigger accumulation of the transcription factor STOP1 in the nucleus of Arabidopsis root cells. Plant J. 99, 937–949 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Pandolfini, L. et al. METTL1 promotes let-7 microRNA processing via m7G methylation. Mol. Cell 74, 1278–1290 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Harrison, S. J. et al. A rapid and robust method of identifying transformed Arabidopsis thaliana seedlings following floral dip transformation. Plant Methods 2, 19 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  52. Tsanov, N. et al. smiFISH and FISH-quant—a flexible single RNA detection approach with super-resolution capability. Nucleic Acids Res. 44, e165 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Ouyang, W., Mueller, F., Hjelmare, M., Lundberg, E. & Zimmer, C. ImJoy: an open-source computational platform for the deep learning era. Nat. Methods 16, 1199–1200 (2019).

    Article  CAS  PubMed  Google Scholar 

  54. Mueller, F. et al. FISH-quant: automatic counting of transcripts in 3D FISH images. Nat. Methods 10, 277–278 (2013).

    Article  CAS  PubMed  Google Scholar 

  55. Dufrene, Y. F., Martinez-Martin, D., Medalsy, I., Alsteens, D. & Muller, D. J. Multiparametric imaging of biological systems by force-distance curve-based AFM. Nat. Methods 10, 847–854 (2013).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

S.H. was supported by a PhD fellowship from the CEA and PACA region, the ANR Reglisse 13-ADAP-008 fellowship and the CEA DRF impulsion programme, and the FOSSI project supported E.M., L.C., L.N., M.-C.T. and P.D. Additional grant support was received by H.J. from CEA-Enhanced Eurotalent and ANR PhlowZ 19-CE-13-0007. We thank the Heliobiotech platform for access to their RT–qPCR machine. We thank E. Basyuk for her help with the MS2 plasmids, and we thank L. Laplaze and G. Desbrosses for providing access to the growth chambers of IRD and Montpellier University. We thank O. Radulescu for his help with calculating total, extrinsic and intrinsic noise for an undefined number of alleles; T. Desnos and C. Mercier for their assistance on figure drawing; and S. Kanno and H. Garcia for critical reading of the manuscript. We thank J. Escudier for the synthesis of the SPX1 set of fluorescent probes. We acknowledge the MRI imaging facility (belonging to the National Infrastructure France-BioImaging supported by the French National Research Agency, ANR-10-INBS-04) and the ZoOM platform (supported by the Région Provence Alpes Côte d’Azur, the Conseil General of Bouches du Rhône, the French Ministry of Research, the Centre National de la Recherche Scientifique and the Commissariat à l’Energie Atomique et aux Energies Alternatives).

Author information

Author notes

  1. These authors contributed equally: Sahar Hani, Laura Cuyas, Pascale David.

Authors and Affiliations

  1. Aix Marseille Univ, CEA, CNRS, BIAM, UMR7265, SAVE (Signalisation pour l’Adaptation des Végétaux à leur Environnement), Saint-Paul lez Durance, France

    Sahar Hani, Laura Cuyas, Pascale David, Marie-Christine Thibaud, Nathalie Pochon, Hélène Javot & Laurent Nussaume

  2. Agroinnovation International-TIMAC AGRO, Groupe Roullier, Saint-Malo, France

    Laura Cuyas

  3. Department of Animal, Plant and Soil Sciences, Australian Research Council Centre of Excellence in Plant Energy Biology, School of Life Sciences, La Trobe University, Bundoora, Victoria, Australia

    David Secco & James Whelan

  4. UMR5096 CNRS/Université de Perpignan, Laboratoire Génome et Développement des Plantes, Perpignan, France

    Rémy Merret

  5. Unité Imagerie et Modélisation, Institut Pasteur and CNRS UMR 3691, Paris, France

    Florian Mueller

  6. MRI, BioCampus Montpellier, CRBM, Univ. Montpellier, CNRS, Montpellier, France

    Orestis Faklaris

  7. UMR 5168 CNRS-CEA-INRA-Université Grenoble Alpes, Laboratoire de Physiologie Cellulaire et Végétale, iRIG, CEA-Grenoble, Grenoble, France

    Eric Maréchal

  8. Institut de Génétique Moléculaire de Montpellier, Univ. Montpellier, CNRS, Montpellier, France

    Edouard Bertrand

  9. Institut de Génétique Humaine, Univ. Montpellier, CNRS, Montpellier, France

    Edouard Bertrand

  10. Equipe labélisée Ligue Nationale Contre le Cancer, Montpellier, France

    Edouard Bertrand

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  1. Sahar Hani
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Contributions

E.B. provided the MS2 and MCP original constructs, and L.N. conceived the experiments. L.C., S.H. and P.D. performed all the experiments under the supervision of L.N. for the physiological part and E.B. for cell biology. The RNA-seq data were produced by D.S. and J.W. and analysed by L.N., L.C. M.-C.T. and E.M. The luminescence experiments were performed by N.P. under the supervision of H.J. H.J. also implemented the microfluidic technique in the SAVE team. R.M. performed the experiments for cap and polyA tail detection, F.M. provided assistance for image analysis and computation and O.F. took part in the spinning disk and mosaic acquisition experiments. The manuscript was written by L.N. and E.B. with help from S.H., P.D. and L.C.

Corresponding authors

Correspondence to Edouard Bertrand or Laurent Nussaume.

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The authors declare no competing interests.

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Peer review information Nature Plants thanks Zhicheng Dong and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–12 with legends and Tables 1–3 with legends.

Reporting Summary

Supplementary Video 1

Bursting activity of the pSPX1::MS2×128 reporter. Video of root cap cells of the Arabidopsis S line expressing pSPX1::MS2×128 and MCP–GFP and continuously grown without Pi. MIPs (xy and xz) are from a time-lapse video recorded in 3D (44 z planes). Time (in min) is indicated.

Supplementary Video 2

Putative release of single RNAs in the nucleoplasm when promoter activity stochastically turns off when a burst ends. Video of root cap cells of the Arabidopsis S line expressing pSPX1::MS2×128 and MCP–GFP and continuously grown without Pi. MIPs (xy and xz) are from a time-lapse video recorded in 3D (44 z planes). Time (in min) is indicated.

Supplementary Video 3

Transcriptional repression of the pSPX1::MS2×128 reporter triggered by Pi resupply. Video of root cells of the Arabidopsis S line transformed with pSPX1::MS2×128 and MCP–GFP, after receiving a Pi-rich solution at time t = 0 min. MIP from a time-lapse video recorded in 3D (200 z planes). Acquisitions lasted 39 min.

Supplementary Video 4

Transcriptional repression of the pSPX1::MS2×128 reporter triggered by Pi resupply. Zoom on a few cells cropped from Supplementary Video 3.

Supplementary Video 5

Transcriptional repression of the pSPX1::MS2×128 reporter triggered by Pi resupply. Another video of root cells of the Arabidopsis S line transformed with pSPX1::MS2×128 and MCP–GFP, after receiving a Pi-rich solution at time t = 0 min. MIP from a time-lapse video recorded in 3D (200 z planes). Acquisitions lasted 54 min.

Supplementary Video 6

Transcriptional repression of the pSPX1::MS2×128 reporter triggered by Pi resupply. Magnification deriving from Supplementary Video 5.

Supplementary Video 7

Transcriptional repression of the pSPX1::MS2×128 reporter triggered by Pi resupply. Magnification deriving from Supplementary Video 5.

Supplementary Video 8

Transcriptional repression of the pSPX1::MS2×128 reporter triggered by Pi resupply. Video of root cells of the Arabidopsis J line transformed with pSPX1::MS2×128 and MCP–GFP, after receiving a Pi-rich solution at time t = 0 min. MIP from a time-lapse video recorded in 3D (200 z planes). Acquisitions lasted 54 min.

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Hani, S., Cuyas, L., David, P. et al. Live single-cell transcriptional dynamics via RNA labelling during the phosphate response in plants. Nat. Plants 7, 1050–1064 (2021). https://doi.org/10.1038/s41477-021-00981-3

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