High-performance calcium sensors for imaging activity in neuronal populations and microcompartments

Abstract

Calcium imaging with genetically encoded calcium indicators (GECIs) is routinely used to measure neural activity in intact nervous systems. GECIs are frequently used in one of two different modes: to track activity in large populations of neuronal cell bodies, or to follow dynamics in subcellular compartments such as axons, dendrites and individual synaptic compartments. Despite major advances, calcium imaging is still limited by the biophysical properties of existing GECIs, including affinity, signal-to-noise ratio, rise and decay kinetics and dynamic range. Using structure-guided mutagenesis and neuron-based screening, we optimized the green fluorescent protein-based GECI GCaMP6 for different modes of in vivo imaging. The resulting jGCaMP7 sensors provide improved detection of individual spikes (jGCaMP7s,f), imaging in neurites and neuropil (jGCaMP7b), and may allow tracking larger populations of neurons using two-photon (jGCaMP7s,f) or wide-field (jGCaMP7c) imaging.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Mutagenesis and screening of jGCaMP7 in dissociated neurons.
Fig. 2: jGCaMP7 performance in dissociated neurons.
Fig. 3: jGCaMP7 performance in the Drosophila larval NMJ.
Fig. 4: jGCaMP7 performance in adult Drosophila ellipsoid body neurons.
Fig. 5: jGCaMP7 performance in the mouse primary visual cortex (V1).
Fig. 6: jGCaMP7b for improved dendritic spine imaging.

Data availability

Most of the datasets generated for characterizing the new sensors are included in the published article (and its Supplementary Information files). Additional data that support the findings of this study are available from the corresponding authors upon reasonable request. Correspondence and requests for flies should be addressed to V.J. and L.L.L. for jGCaMP7 protein structure information and constructs and K.S. for neuronal culture screen information and mice.

DNA constructs and AAV plasmids for the jGCaMP7 variants were deposited for distribution at Addgene (http://www.addgene.org, plasmid numbers 104463, 104483–84, 104487–89, 104491–93, 104495–97, 105321–23). Drosophila stocks were deposited at the Bloomington Drosophila Stock Center (http://flystocks.bio.indiana.edu). Gene sequences were deposited at NCBI GenBank (https://www.ncbi.nlm.nih.gov/nuccore/, accession codes: jGCaMP7s MK749391, jGCaMP7f MK749392, jGCaMP7b MK749393, jGCaMP7c MK749394).

Code availability

AAnalysis codes that support the findings of this study are available from the corresponding authors upon reasonable request.

References

  1. 1.

    Nakai, J., Ohkura, M. & Imoto, K. A high signal-to-noise Ca(2+) probe composed of a single green fluorescent protein. Nat. Biotechnol. 19, 137–141 (2001).

    CAS  Article  Google Scholar 

  2. 2.

    Tian, L. et al. Imaging neural activity in worms, flies and mice with improved GCaMP calcium indicators. Nat. Methods 6, 875–881 (2009).

    CAS  Article  Google Scholar 

  3. 3.

    Akerboom, J. et al. Optimization of a GCaMP calcium indicator for neural activity imaging. J. Neurosci. 32, 13819–13840 (2012).

    CAS  Article  Google Scholar 

  4. 4.

    Chen, T. W. et al. Ultrasensitive fluorescent proteins for imaging neuronal activity. Nature 499, 295–300 (2013).

    CAS  Article  Google Scholar 

  5. 5.

    Peron, S. P., Freeman, J., Iyer, V., Guo, C. & Svoboda, K. A cellular resolution map of barrel cortex activity during tactile behavior. Neuron 86, 783–799 (2015).

    CAS  Article  Google Scholar 

  6. 6.

    Ahrens, M. B., Orger, M. B., Robson, D. N., Li, J. M. & Keller, P. J. Whole-brain functional imaging at cellular resolution using light-sheet microscopy. Nat. Methods 10, 413–420 (2013).

    CAS  Article  Google Scholar 

  7. 7.

    Petreanu, L. et al. Activity in motor-sensory projections reveals distributed coding in somatosensation. Nature 489, 299–303 (2012).

    CAS  Article  Google Scholar 

  8. 8.

    Chen, J. L., Carta, S., Soldado-Magraner, J., Schneider, B. L. & Helmchen, F. Behaviour-dependent recruitment of long-range projection neurons in somatosensory cortex. Nature 499, 336–340 (2013).

    CAS  Article  Google Scholar 

  9. 9.

    O’Connor, D. H. et al. Neural coding during active somatosensation revealed using illusory touch. Nat. Neurosci. 16, 958–965 (2013).

    Article  Google Scholar 

  10. 10.

    Seelig, J. D. & Jayaraman, V. Neural dynamics for landmark orientation and angular path integration. Nature 521, 186–191 (2015).

    CAS  Article  Google Scholar 

  11. 11.

    Huber, D. et al. Multiple dynamic representations in the motor cortex during sensorimotor learning. Nature 484, 473–478 (2012).

    CAS  Article  Google Scholar 

  12. 12.

    Margolis, D. J. et al. Reorganization of cortical population activity imaged throughout long-term sensory deprivation. Nat. Neurosci. 15, 1539–1546 (2012).

    CAS  Article  Google Scholar 

  13. 13.

    Jenett, A. et al. A GAL4-driver line resource for Drosophila neurobiology. Cell Rep. 2, 991–1001 (2012).

    CAS  Article  Google Scholar 

  14. 14.

    Luo, L., Callaway, E. M. & Svoboda, K. Genetic dissection of neural circuits: a decade of progress. Neuron 98, 256–281 (2018).

    CAS  Article  Google Scholar 

  15. 15.

    Akerboom, J. et al. Crystal structures of the GCaMP calcium sensor reveal the mechanism of fluorescence signal change and aid rational design. J. Biol. Chem. 284, 6455–6464 (2009).

    CAS  Article  Google Scholar 

  16. 16.

    Ding, J., Luo, A. F., Hu, L., Wang, D. & Shao, F. Structural basis of the ultrasensitive calcium indicator GCaMP6. Sci. China Life Sci. 57, 269–274 (2014).

    CAS  Article  Google Scholar 

  17. 17.

    Badura, A., Sun, X. R., Giovannucci, A., Lynch, L. A. & Wang, S. S. H. Fast calcium sensor proteins for monitoring neural activity. Neurophotonics 1, 025008 (2014).

    Article  Google Scholar 

  18. 18.

    Barnett, L. M., Hughes, T. E. & Drobizhev, M. Deciphering the molecular mechanism responsible for GCaMP6m’s Ca2+-dependent change in fluorescence. PloS ONE 12, e0170934 (2017).

    Article  Google Scholar 

  19. 19.

    Dana, H. et al. Sensitive red protein calcium indicators for imaging neural activity. eLife 5, e12727 (2016).

    Article  Google Scholar 

  20. 20.

    Wardill, T. J. et al. A neuron-based screening platform for optimizing genetically-encoded calcium Indicators. PLoS ONE 8, e77728 (2013).

    CAS  Article  Google Scholar 

  21. 21.

    Ohkura, M. et al. Genetically encoded green fluorescent Ca2+ iIndicators with improved detectability for neuronal Ca2+ sSignals. PLoS ONE 7, e51286 (2012).

    CAS  Article  Google Scholar 

  22. 22.

    Wolff, T., Iyer, N. A. & Rubin, G. M. Neuroarchitecture and neuroanatomy of the Drosophila central complex: a GAL4-based dissection of protocerebral bridge neurons and circuits. J. Comp. Neurol. 523, 997–1037 (2015).

    Article  Google Scholar 

  23. 23.

    Turner-Evans, D. et al. Angular velocity integration in a fly heading circuit. eLife 6, e23496 (2017).

    Article  Google Scholar 

  24. 24.

    Green, J. et al. A neural circuit architecture for angular integration in Drosophila. Nature 546, 101–106 (2017).

    CAS  Article  Google Scholar 

  25. 25.

    Dana, H. et al. Thy1-GCaMP6 transgenic mice for neuronal population imaging in vivo. PloS ONE 9, e108697 (2014).

    Article  Google Scholar 

  26. 26.

    Mrsic-Flogel, T. D. et al. Homeostatic regulation of eye-specific responses in visual cortex during ocular dominance plasticity. Neuron 54, 961–972 (2007).

    CAS  Article  Google Scholar 

  27. 27.

    Niell, C. M. & Stryker, M. P. Highly selective receptive fields in mouse visual cortex. J. Neurosci. 28, 7520–7536 (2008).

    CAS  Article  Google Scholar 

  28. 28.

    Kerlin, A. et al. Functional clustering of dendritic activity during decision-making. Preprint at https://www.biorxiv.org/content/10.1101/440396v1 (2018).

  29. 29.

    Yang, Y. et al. Improved calcium sensor GCaMP-X overcomes the calcium channel perturbations induced by the calmodulin in GCaMP. Nat. Commun. 9, 1504 (2018).

    Article  Google Scholar 

  30. 30.

    Mank, M. et al. A genetically encoded calcium indicator for chronic in vivo two-photon imaging. Nat. Methods 5, 805–811 (2008).

    CAS  Article  Google Scholar 

  31. 31.

    Steinmetz, N. A. et al. Aberrant cortical activity in multiple GCaMP6-expressing transgenic mouse lines. eneuro 4, ENEURO.0207-17.2017 (2017).

    Article  Google Scholar 

  32. 32.

    Zariwala, H. A. et al. A Cre-dependent GCaMP3 reporter mouse for neuronal imaging in vivo. J. Neurosci. 32, 3131–3141 (2012).

    CAS  Article  Google Scholar 

  33. 33.

    Wekselblatt, J. B., Flister, E. D., Piscopo, D. M. & Niell, C. M. Large-scale imaging of cortical dynamics during sensory perception and behavior. J. Neurophysiol. 115, 2852–2866 (2016).

    CAS  Article  Google Scholar 

  34. 34.

    Dana, H. et al. Thy1 transgenic mice expressing the red fluorescent calcium indicator jRGECO1a for neuronal population imaging in vivo. PLoS ONE 13, e0205444 (2018).

    Article  Google Scholar 

  35. 35.

    Scott, B. B. et al. Imaging cortical dynamics in GCaMP transgenic rats with a head-mounted widefield macroscope. Neuron 100, e1045 (2018).

    Article  Google Scholar 

  36. 36.

    Sadakane, O. et al. Long-term two-photon calcium imaging of neuronal populations with subcellular resolution in adult non-human primates. Cell Rep. 13, 1989–1999 (2015).

    CAS  Article  Google Scholar 

  37. 37.

    Mutze, J. et al. Excitation spectra and brightness optimization of two-photon excited probes. Biophys. J. 102, 934–944 (2012).

    CAS  Article  Google Scholar 

  38. 38.

    Xu, C. & Webb, W. W. Measurement of two-photon excitation cross sections of molecular fluorophores with data from 690 to 1050nm. J. Opt. Soc. Am. B 13, 481–491 (1996).

    CAS  Article  Google Scholar 

  39. 39.

    Makarov, N. S., Drobizhev, M. & Rebane, A. Two-photon absorption standards in the 550-1600 nmexcitation wavelength range. Opt. Express 16, 4029–4047 (2008).

    CAS  Article  Google Scholar 

  40. 40.

    Villalobos, A., Ness, J. E., Gustafsson, C., Minshull, J. & Govindarajan, S. Gene Designer: a synthetic biology tool for constructing artificial DNA segments. BMC Bioinforma. 7, 285 (2006).

    Article  Google Scholar 

  41. 41.

    Wolff, T. & Rubin, G. M. Neuroarchitecture of the Drosophila central complex: a catalog of nodulus and asymmetrical body neurons and a revision of the protocerebral bridge catalog. J. Comp. Neurol. 526, 2585–2611 (2018).

    CAS  Article  Google Scholar 

  42. 42.

    Seelig, J. D. et al. Two-photon calcium imaging from head-fixed Drosophila during optomotor walking behavior. Nat. Methods 7, 535–540 (2010).

    CAS  Article  Google Scholar 

  43. 43.

    Pologruto, T. A., Sabatini, B. L. & Svoboda, K. ScanImage: flexible software for operating laser scanning microscopes. Biomed. Eng. Online 2, 13 (2003).

    Article  Google Scholar 

  44. 44.

    Reiser, M. B. & Dickinson, M. H. A modular display system for insect behavioral neuroscience. J. Neurosci. Methods 167, 127–139 (2008).

    Article  Google Scholar 

  45. 45.

    Berens, P. CircStat: a MATLAB toolbox for circular statistics. J. Stat. Softw. 31, 1–21 (2009).

    Article  Google Scholar 

  46. 46.

    Pologruto, T. A., Sabatini, B. L. & Svoboda, K. ScanImage: flexible software for operating laser-scanning microscopes. Biomed. Eng. OnLine 2, 13 (2003).

    Article  Google Scholar 

  47. 47.

    Brainard, D. H. The Psychophysics Toolbox. Spat. Vis. 10, 433–436 (1997).

    CAS  Article  Google Scholar 

  48. 48.

    Pelli, D. G. The VideoToolbox software for visual psychophysics: transforming numbers into movies. Spat. Vis. 10, 437–442 (1997).

    CAS  Article  Google Scholar 

  49. 49.

    Peirce, J. W. Generating stimuli for neuroscience using PsychoPy. Front Neuroinform 2, 10 (2009).

    PubMed  Google Scholar 

  50. 50.

    Myatt, D., Hadlington, T., Ascoli, G. & Nasuto, S. Neuromantic–from semi-manual to semi-automatic reconstruction of neuron morphology. Front Neuroinform 6, 4 (2012).

    Article  Google Scholar 

  51. 51.

    Kitamura, K., Judkewitz, B., Kano, M., Denk, W. & Hausser, M. Targeted patch-clamp recordings and single-cell electroporation of unlabeled neurons in vivo. Nat. Methods 5, 61–67 (2008).

    CAS  Article  Google Scholar 

Download references

Acknowledgements

We thank D. Flickinger for design of the microscope used for spine imaging, M. Reiser, M. Isaacson, J. Chen, J. Liu and A. Chiu for the G4.0 panel display system used in the fly-on-ball imaging experiments and D. Walpita and J. Hagemeier for neuronal culture (all from Janelia). This work is part of the GENIE Project at the Howard Hughes Medical Institute, Janelia Research Campus. A.K. is supported by the Hertie Foundation.

Author information

Affiliations

Authors

Contributions

V.J., L.L.L., E.R.S., D.S.K. and K.S. initiated the project. H.D. and D.S.K. conducted neuronal culture screening. H.D. performed mouse visual cortical experiments. B.M., A.M.K. and Y.C. performed experiments on mouse dendrites. Y.S. carried out fly larval neuromuscular junction studies. B.H. carried out adult fly experiments. J.P.H., G.T., A.T. and A.W. performed protein assays. J.J.M. and R.P performed biophysical characterization of all constructs. All authors analyzed data. H.D., Y.S., B.M., B.H., A.W., A.K., E.R.S., V.J., L.L.L., K.S. and D.S.K. wrote the paper with comments from all authors.

Corresponding authors

Correspondence to Vivek Jayaraman or Loren L. Looger or Karel Svoboda.

Ethics declarations

Competing interests

All authors declare no competing interests.

Additional information

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

Integrated supplementary information

Supplementary Figure 1 One-photon excitation and emission spectra of jGCaMP7 sensors.

Measurement of excitation and emission spectra for GCaMP6 and jGCaMP7 sensors. Emission spectra were calculated with 495 nm excitation light, excitation spectra were calculated with 515 nm emission light (data from a single measurement per sensor).

Supplementary Figure 2 Two-photon excitation spectra of jGCaMP7 sensors.

Measurement of the two-photon excitation spectra for GCaMP6 and jGCaMP7 sensors (averaged data from n = 2 independent measurements per sensor).

Supplementary Figure 3 Biophysical properties of purified GCaMP sensors.

Measurement of jGCaMP7 properties in purified protein solutions: a. Molecular brightness (average of n = 2 independent measurements). b. Two-photon excitation cross-section (average of n = 2 independent measurements). c. Bleaching time constant in calcium-saturated solution (n = 3 independent measurements, blue dots). d. Bleaching time constant in calcium-free solution (bleaching was measured with 6.5 mW of 488 nm illumination, light intensity was 4.5 W/cm2, protein concentration was 4 μM, n=3 independent measurements, blue dots, errorbars show mean ± s.d.).

Supplementary Figure 4 Reproducible jGCaMP7s V1 responses across trials.

The response amplitude was averaged and normalized over 980 neurons expressing jGCaMP7s and plotted vs. trial number. No stimulus adaptation was evident (mean ± s.e.m.).

Supplementary Figure 5 Comparison of orientation tuning in V1 neurons measured with different sensors.

a. Distribution of orientation selectivity index (OSI) for visually responsive cells measured using different sensors (n = 625 cells, jGCaMP7s; 614, jGCaMP7f; 844, jGCaMP7b; 345, jGCaMP7c; 337, GCaMP6s; 221, GCaMP6f). The left-shifted distributions of jGCaMP7s and GCaMP6s are probably due to high sensitivity and affinity compared to the other sensors, which enables detection of the weaker responses to non-preferred grating directions and reduces the OSI value. b. Distribution of OSI values across sensors (same data as in a). Red lines correspond to medians, each box shows the 25th to 75th percentile range, whisker length is the shorter of 1.5 times the 25th to 75th range or until the extreme data point. c. Averaged ΔF/F0 traces of all cells detected as responsive from a single mouse (gray traces, left: n = 2 mice, 384 neurons, for jGCaMP7s; right: n = 3 mice, 321 neurons, for jGCaMP7f) and their mean (red and green lines), shifted that the preferred response for each cell appears first. jGCaMP7s shows a small increase in its response to the drifting grating moving to the orthogonal direction to the preferred stimulus, compared to jGCaMP7f, which is likely to contribute to the left shift of its OSI distribution shown in a.

Supplementary Figure 6 jGCaMP7b for improved dendritic spine imaging.

a. Expression schema for targeted single-neuron labeling. b. Experimental setup, V1 imaging. c. Mean images of example dendritic imaging session for GCaMP6s (top, one example cell out of 5 different recorded neurons) and jGCaMP7b (bottom, one example cell out of 5 different recorded neurons). d. GCaMP7b labelled neurons had more detectable spines (medians [95% CI]: 0.23 [0.17–0.32] vs. 0.3 [0.23–0.37] spines/μm for 6s and 7b respectively; n = 35 dendritic segments (5 neurons from 4 animals) and 37 dendritic segments (5 neurons from 4 animals) for 6s and 7b respectively, p = 0.01, Wilcoxon rank-sum test). e. GCaMP7b labelled neurons had a higher number of spontaneously active spines (medians [CI]: 0.17 [0.12–0.24] vs. 0.23 [0.21–0.33] spines/μm for 6s and 7b respectively; n = 35 dendritic segments (5 neurons from 4 animals) and 37 dendritic segments (5 neurons from 4 animals) for 6s and 7b respectively, p = 0.001, two-sided Wilcoxon rank-sum test. Orange lines correspond to medians, each box shows the 25th to 75th percentile range, whisker length is the shorter of 1.5 times the 25th to 75th range or until the extreme data point.

Supplementary information

Supplementary Information

Supplementary Figs. 1–6 and Supplementary Tables 1–3

Reporting Summary

Supplementary Dataset 1

Comprehensive neuronal culture screening results for variants of GCaMP6s

Supplementary Video 1

Recording of jGCaMP7s fluorescence signal of layer 2/3 neurons in the mouse visual cortex in vivo: this video shows 83 s of continuous fluorescence recording from one FOV of jGCaMP7s-expressing neurons (shown also in Fig. 5a) in the mouse visual cortex, in response to drifting grating stimulation (6 s of blank display, followed by 4 s of gratings moving in one of eight directions, 0.05 cycles per degree, 1 Hz temporal frequency). The times when the grating appears and its movement direction are indicated by the arrow in the upper left corner of the respective frames. FOV size 250 μm, 50 FOVs were recorded from n = 4 mice expressing jGCaMP7s with similar results, as summarized in Fig. 5.

Supplementary Video 2

Recording of jGCaMP7f fluorescence signal of layer 2/3 neurons in the mouse visual cortex in vivo: this video shows 83 s of continuous fluorescence recording from one FOV of jGCaMP7f-expressing neurons in the mouse visual cortex, in response to drifting grating stimulation (4 s of blank display, followed by 4 sec of gratings moving in one of eight directions, 0.05 cycles per degree, 1 Hz temporal frequency). The times when the grating appears and its movement direction are indicated by the arrow in the upper left corner of the respective frames. FOV size 250 μm, 55 FOVs were recorded from n = 5 mice expressing jGCaMP7f with similar results, as summarized in Fig. 5.

Supplementary Video 3

Recording of jGCaMP7c fluorescence signal of layer 2/3 neurons in the mouse visual cortex in vivo: this video shows 83 s of continuous fluorescence recording from one FOV of jGCaMP7c-expressing neurons in the mouse visual cortex, in response to drifting grating stimulation (6 s of blank display, followed by 4 s of gratings moving in one of eight directions, 0.05 cycles per degree, 1 Hz temporal frequency). The times when the grating appears and its movement direction are indicated by the arrow in the upper left corner of the respective frames. FOV size 250 μm, 38 FOVs were recorded from n = 4 mice expressing jGCaMP7c with similar results, as summarized in Fig. 5.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Dana, H., Sun, Y., Mohar, B. et al. High-performance calcium sensors for imaging activity in neuronal populations and microcompartments. Nat Methods 16, 649–657 (2019). https://doi.org/10.1038/s41592-019-0435-6

Download citation

Further reading

Search

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