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.
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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).
AAnalysis codes that support the findings of this study are available from the corresponding authors upon reasonable request.
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).
Tian, L. et al. Imaging neural activity in worms, flies and mice with improved GCaMP calcium indicators. Nat. Methods 6, 875–881 (2009).
Akerboom, J. et al. Optimization of a GCaMP calcium indicator for neural activity imaging. J. Neurosci. 32, 13819–13840 (2012).
Chen, T. W. et al. Ultrasensitive fluorescent proteins for imaging neuronal activity. Nature 499, 295–300 (2013).
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).
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).
Petreanu, L. et al. Activity in motor-sensory projections reveals distributed coding in somatosensation. Nature 489, 299–303 (2012).
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).
O’Connor, D. H. et al. Neural coding during active somatosensation revealed using illusory touch. Nat. Neurosci. 16, 958–965 (2013).
Seelig, J. D. & Jayaraman, V. Neural dynamics for landmark orientation and angular path integration. Nature 521, 186–191 (2015).
Huber, D. et al. Multiple dynamic representations in the motor cortex during sensorimotor learning. Nature 484, 473–478 (2012).
Margolis, D. J. et al. Reorganization of cortical population activity imaged throughout long-term sensory deprivation. Nat. Neurosci. 15, 1539–1546 (2012).
Jenett, A. et al. A GAL4-driver line resource for Drosophila neurobiology. Cell Rep. 2, 991–1001 (2012).
Luo, L., Callaway, E. M. & Svoboda, K. Genetic dissection of neural circuits: a decade of progress. Neuron 98, 256–281 (2018).
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).
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).
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).
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).
Dana, H. et al. Sensitive red protein calcium indicators for imaging neural activity. eLife 5, e12727 (2016).
Wardill, T. J. et al. A neuron-based screening platform for optimizing genetically-encoded calcium Indicators. PLoS ONE 8, e77728 (2013).
Ohkura, M. et al. Genetically encoded green fluorescent Ca2+ iIndicators with improved detectability for neuronal Ca2+ sSignals. PLoS ONE 7, e51286 (2012).
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).
Turner-Evans, D. et al. Angular velocity integration in a fly heading circuit. eLife 6, e23496 (2017).
Green, J. et al. A neural circuit architecture for angular integration in Drosophila. Nature 546, 101–106 (2017).
Dana, H. et al. Thy1-GCaMP6 transgenic mice for neuronal population imaging in vivo. PloS ONE 9, e108697 (2014).
Mrsic-Flogel, T. D. et al. Homeostatic regulation of eye-specific responses in visual cortex during ocular dominance plasticity. Neuron 54, 961–972 (2007).
Niell, C. M. & Stryker, M. P. Highly selective receptive fields in mouse visual cortex. J. Neurosci. 28, 7520–7536 (2008).
Kerlin, A. et al. Functional clustering of dendritic activity during decision-making. Preprint at https://www.biorxiv.org/content/10.1101/440396v1 (2018).
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).
Mank, M. et al. A genetically encoded calcium indicator for chronic in vivo two-photon imaging. Nat. Methods 5, 805–811 (2008).
Steinmetz, N. A. et al. Aberrant cortical activity in multiple GCaMP6-expressing transgenic mouse lines. eneuro 4, ENEURO.0207-17.2017 (2017).
Zariwala, H. A. et al. A Cre-dependent GCaMP3 reporter mouse for neuronal imaging in vivo. J. Neurosci. 32, 3131–3141 (2012).
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).
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).
Scott, B. B. et al. Imaging cortical dynamics in GCaMP transgenic rats with a head-mounted widefield macroscope. Neuron 100, e1045 (2018).
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).
Mutze, J. et al. Excitation spectra and brightness optimization of two-photon excited probes. Biophys. J. 102, 934–944 (2012).
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).
Makarov, N. S., Drobizhev, M. & Rebane, A. Two-photon absorption standards in the 550-1600 nmexcitation wavelength range. Opt. Express 16, 4029–4047 (2008).
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).
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).
Seelig, J. D. et al. Two-photon calcium imaging from head-fixed Drosophila during optomotor walking behavior. Nat. Methods 7, 535–540 (2010).
Pologruto, T. A., Sabatini, B. L. & Svoboda, K. ScanImage: flexible software for operating laser scanning microscopes. Biomed. Eng. Online 2, 13 (2003).
Reiser, M. B. & Dickinson, M. H. A modular display system for insect behavioral neuroscience. J. Neurosci. Methods 167, 127–139 (2008).
Berens, P. CircStat: a MATLAB toolbox for circular statistics. J. Stat. Softw. 31, 1–21 (2009).
Pologruto, T. A., Sabatini, B. L. & Svoboda, K. ScanImage: flexible software for operating laser-scanning microscopes. Biomed. Eng. OnLine 2, 13 (2003).
Brainard, D. H. The Psychophysics Toolbox. Spat. Vis. 10, 433–436 (1997).
Pelli, D. G. The VideoToolbox software for visual psychophysics: transforming numbers into movies. Spat. Vis. 10, 437–442 (1997).
Peirce, J. W. Generating stimuli for neuroscience using PsychoPy. Front Neuroinform 2, 10 (2009).
Myatt, D., Hadlington, T., Ascoli, G. & Nasuto, S. Neuromantic–from semi-manual to semi-automatic reconstruction of neuron morphology. Front Neuroinform 6, 4 (2012).
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).
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.
All authors declare no competing interests.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Integrated supplementary information
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).
Measurement of the two-photon excitation spectra for GCaMP6 and jGCaMP7 sensors (averaged data from n = 2 independent measurements per sensor).
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.).
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.
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 Figs. 1–6 and Supplementary Tables 1–3
Comprehensive neuronal culture screening results for variants of GCaMP6s
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.
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.
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.
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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
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