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Candelabrum cells are ubiquitous cerebellar cortex interneurons with specialized circuit properties

Nature Neuroscience volume 25, pages 702–713 (2022)Cite this article

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Abstract

To understand how the cerebellar cortex transforms mossy fiber (MF) inputs into Purkinje cell (PC) outputs, it is vital to delineate the elements of this circuit. Candelabrum cells (CCs) are enigmatic interneurons of the cerebellar cortex that have been identified based on their morphology, but their electrophysiological properties, synaptic connections and function remain unknown. Here, we clarify these properties using electrophysiology, single-nucleus RNA sequencing, in situ hybridization and serial electron microscopy in mice. We find that CCs are the most abundant PC layer interneuron. They are GABAergic, molecularly distinct and present in all cerebellar lobules. Their high resistance renders CC firing highly sensitive to synaptic inputs. CCs are excited by MFs and granule cells and are strongly inhibited by PCs. CCs in turn primarily inhibit molecular layer interneurons, which leads to PC disinhibition. Thus, inputs, outputs and local signals converge onto CCs to allow them to assume a unique role in controlling cerebellar output.

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Fig. 1: Determining the morphological and electrophysiological properties of CCs using OxtrCre × Ai14 (tdTomato) mice.
Fig. 2: Molecular characterization of cerebellar inhibitory interneurons with snRNAseq.
Fig. 3: Identification of different types of interneurons in the cerebellar cortex with FISH.
Fig. 4: Synaptic excitation of CCs.
Fig. 5: Synaptic Inhibition of CCs.
Fig. 6: CC-mediated inhibition of target neurons.
Fig. 7: CCs disinhibit PCs.

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Data availability

snRNAseq data were published in Kozareva et al.10 and are accessible at https://singlecell.broadinstitute.org/single_cell/study/SCP795/ and at the NeMo archive (https://nemoarchive.org/). Serial EM data are accessible at https://github.com/htem/cb2_data_availability. Data will also be publicly available in the BossDB (https://bossdb.org/) repository upon publication of (ref. 33), which describes the EM dataset. All other data have been added to the Harvard Dataverse, CC Dataset (https://doi.org/10.7910/DVN/APCCSN). Source data are provided with this paper.

Code availability

Analyses used in this study are largely standard approaches for these types of data. The code that supports these findings is available at the Harvard Dataverse at https://doi.org/10.7910/DVN/APCCSN and at https://github.com/MacoskoLab/cerebellum-atlas-analysis.

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Acknowledgements

We thank members of the Regehr lab and G. Fishell for comments on the manuscript. This work was supported by grants from the NIH (R01NS032405 and R35NS097284 to W.G.R., NIH/NIMH Brain Grant 1U19MH114821 to E.Z.M.), the Stanley Center for Psychiatric Research and the Vision Core and NINDS P30 Core Center (NS072030) to the Neurobiology Imaging Center at Harvard Medical School. The EM work was supported by NIH (R21NS085320 and RF1MH114047); the Bertarelli Program in Translational Neuroscience and Neuroengineering, Stanley and Theodora Feldberg Fund, and the Edward R. and Anne G. Lefler Center. Portions of this research were conducted on the O2 High Performance Compute Cluster at Harvard Medical School partially provided through NIH NCRR (1S10RR028832-01) and a Foundry Award for the HMS Connectomics Core. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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  1. Stephanie Rudolph

    Present address: Albert Einstein College of Medicine, New York, NY, USA

  2. These authors contributed equally: Tomas Osorno, Stephanie Rudolph.

Authors and Affiliations

  1. Department of Neurobiology, Harvard Medical School, Boston, MA, USA

    Tomas Osorno, Stephanie Rudolph, Tri Nguyen, Aliya Norton & Wade G. Regehr

  2. Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA

    Velina Kozareva, Naeem M. Nadaf & Evan Z. Macosko

  3. F.M. Kirby Neurobiology Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA

    Wei-Chung Allen Lee

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Contributions

T.O., S.R. and W.G.R. designed experiments. T.O. and S.R. performed electrophysiology experiments. T.N. generated the automated segmentations in the serial EM dataset. N.N. performed smFISH experiments. T.O. analyzed electrophysiology, smFISH and serial EM data. A.N. analyzed serial EM data. V.K. and E.Z.M. analyzed snRNAseq data. T.O., S.R. and W.G.R. wrote the paper with input from all authors. T.M.N. developed and applied the distributed cell segmentation pipeline and reconstruction platform. W.C.A.L. designed EM experiments and provided resources and infrastructure for cell reconstruction.

Corresponding author

Correspondence to Wade G. Regehr.

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W.C.A.L. declares the following competing interest: Harvard University filed a patent application regarding GridTape (WO2017184621A1) on behalf of the inventors, including W.C.A.L. and negotiated licensing agreements with interested partners. The other authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Examples of candelabrum cell morphologies.

a tdTomato-positive CCs filled with an Alexa-594-containing patch pipette and imaged using 2-photon microscopy. Images show LS-DIC in gray indicating the cell location in the slice, and Alexa-594 fluorescence in black as a maximum intensity Z-projection. b Example of a CC (from Fig. 1b) with the axon shown in yellow, the dendrites in white, and the cell body in cyan. A corresponding sideview is shown, along with quantification of dendritic branching in the cortical layers and distribution of boutons relative to the cell body (example cell, black. n = 305 boutons, average of n = 7 cells, light blue. n = 1125 boutons). c Summary of the dendritic arbor morphology in CCs. In box plots, box outlines and center line indicate median and interquartile range, and the whiskers indicate data points up to 1.5x interquartile range. n = 7 cells. d Images of the CCs shown in a colored as in b. Side views are also shown for each cell.

Source data

Extended Data Fig. 2 Methods used to analyze FISH data.

a. Raw fluorescence image for one channel → image with background fluorescence subtracted→individual puncta are then detected in each slice→ the results from all slices in a Z-stack are combined. b. Top) a mask is created for each channel. Bottom) Channels masks are combined to create cell type masks. Examples for the same field of view are shown for all cell types. Color scales are the same as in Fig. 3. c. Scatter plots of FISH fluorescence are shown for all cells of each cell type. d. Cumulative histograms are shown for Nxph1, Slc6a5, Aldh1a3 for the different cell classes.

Extended Data Fig. 3 Summaries of locations of five classes of cells in different slices, as in Fig. 3.

PLI1: light blue Nxph1+ Slc6a5- Aldh1a3+ PLI2: green Nxph1+ Slc6a5 + Aldh1a3 + Golgi1: grey Nxph1- Slc6a5+ Aldh1a3- Golgi2 + PLI3: purple Nxph1+ Slc6a5 + Aldh1a3- MLI2: orange Nxph1+ Slc6a5- Aldh1a3- a. Four slices each from a female (top) and a male (bottom) are shown. b. The locations of cell types from all slices are overlayed. The symbol sizes have been reduced to allow better visualization of the locations of individual cells. Each type of interneuron displayed a characteristic distribution. The distribution of PLI2s was most similar to that of PLI1s (Fig. 3c-e, Extended Data Fig. 3, green). PLI2s were clustered around the PCL, although unlike PLI1s they were not present in the molecular layer but extended into the upper part of the granular layer (Fig. 3e, green). Golgi1 cells were found in all lobules, and were restricted to the granule cell layer (Fig. 3c-e, Extended Data Fig. 3, grey). Although our labelling strategy was focused on identifying PLI1s, rather than discriminating between PLI3s and Golgi2 cells, the combined labelling of these two cell types is informative (Fig. 3c-e, Extended Data Fig. 3, light purple). The density of cells shows a gradient in the different lobules, peaks in lobule IX, and is extremely low in lobule X. The small peak in cells near the PCL likely reflects PLI3s, which are more rare than other PLIs. As expected, MLI2s are present at higher densities than the other cell types and are restricted to the molecular layer (Fig. 3c-e, Extended Data Fig. 3, orange).

Source data

Extended Data Fig. 4 snRNAseq regional nuclei counts.

snRNAseq nuclei counts for PLI1, PLI2, PLI3, Golgi1, Golgi2 and MLI2 cells from different regions of the cerebellum. Nuclei counts are normalized to the number of PC nuclei in each region. CUL = Culmen, SIM = lobule simplex, AN1 = Crus I of ansiform lobule, AN2 = Crus II of ansiform lobule, PRM = paramedian lobule, PF = paraflocculus, F = flocculus. Data are from Kozareva et al. 10.

Source data

Extended Data Fig. 5 Properties of labelled cells in OxtrCre x Ai14 mice.

a. Slice location of tdTomato labeled cell types for different cerebellar slices. Small PCL cells (top, n = 1206 cells), PCs (middle, n = 1862 cells) and some MLIs (bottom, n = 272 cells) were labeled. b. i) Scatter plot of Slc6a5 signal for individual PLIs as a function of tdTomato fluorescence. ii) Scatter plot of Aldh1a3 signal for individual PLIs as a function of tdTomato fluorescence. iii) Histogram showing distribution of tdTomato fluorescence intensities in PLIs. iv) Median HCR signal for PLIs as a function of tdTomato fluorescence. v) Cumulative plots showing distribution of HCR mean values in all tdTomato expressing PLIs (top) and in PLIs with high tdTomato fluorescence (bottom). c. Summary showing sparse tdTomato labelling of MLIs in OxtrCre x Ai14 mice. MLIs do not express Slc6a5 or Aldh1a3. These cells exist in low density in the most frequent recording regions (lobule VI-VIII). Lobule IX and X were avoided for electrophysiology recordings because they showed the highest density of MLI labeling. n = 4 slices.

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Extended Data Fig. 6 Latency of excitatory inputs elicited by electrical stimulation of the white matter.

a) Example cells aligned to the same timescale as the cumulative plot in B. individual trials shown in gray and averages in light blue (CC) and black (MLI). b) Cumulative distributions of the latency of the first EPSC after electrical stimulation of the white matter for CCs (light blue) and MLIs (black). Each cell is plotted separately. CC n = 7 cells, MLI n = 13 cells. c) Summary of the median latency of EPSCs evoked by white matter stimulation. Each point represents a cell. n = 7 CCs and 13 MLIs. p = 3.6 e-4, two-sided Wilcoxon rank test. In box plots, box outlines and center line indicate median and interquartile range, and the whiskers indicate data points up to 1.5x interquartile range.

Source data

Extended Data Fig. 7 Climbing fibers (CFs) excite candelabrum cells via glutamate spillover.

Previous studies have shown that CFs do not synapse directly onto molecular layer interneurons (MLIs), but that CF activation evokes a slow spillover current in MLIs and GCs. We performed similar experiments. We placed a stimulus electrode in the granular layer to activate axons and then assessed the properties of the inputs by stimulating with multiple trials for a range of stimulus intensities and determining the rise time and decay times of EPSCs. Experiments were performed with inhibitory transmission blocked. As in previous studies, we identified putative CF spillover currents based on slow rise and decay times, all or none activation and pronounced depression. If it satisfied these criteria we went on to determine its sensitivity to inhibiting glutamate uptake with TBOA. Many stimulus sites and many EPSCs were tested for each cell and CF inputs to MLIs were observed in 2 of 4 cells, whereas they were observed in 3 of 25 CCs. ai) Example of CF spillover excitation for an MLI. Individual traces shown in gray and average in black. ii) Responses evoked by a stimulation of increasing intensities for the same MLI, with 4 traces overlaid for each intensity. iii) Summary of EPSC amplitudes as a function of stimulus intensity for ai. iv) Slow EPSCs before and after bath application of 50 µM DL-TBOA. Shaded error bars show the average + /- SEM for 10 trials. bi-iv) Same as panel a for a candelabrum cell. c. Summary of amplitude, kinetic parameters, and paired pulse ratio for CF spillover excitation onto CCs. n = 2 cells (MLIslow), 3 cells (CCslow) and 10 cells (CCfast). d. Summary of the effect of TBOA on the amplitudes, rise-times and decay times of synaptic responses. n is the same as in panel c. In all box plots, box outlines and center line indicate median and interquartile range, and the whiskers indicate data points up to 1.5x interquartile range. Whenever n < 5, only the mean value is indicated with a horizontal line.

Source data

Extended Data Fig. 8 Examples of mossy fiber and granule cell excitatory inputs to CCs.

a. EM reconstruction of a candelabrum cell (blue) and examples of connected mossy fibers (red) and granule cell parallel fibers (gold). Dashed boxes denote regions of insets shown to the right and on the bottom of the Fig. (i, ii, iii). a, example of extraglomerular MF synapse onto the basal dendrite of a CC. Left, reconstruction; right, single-plane EM image detailing the synapse. (ii), example of glomerular MF synapse onto the basal dendrite of a CC. Left, reconstruction; right, single-plane EM images. (iii), PF synapses into the apical dendrite of a CC. Left, reconstruction shown in in a horizontal orientation; right, single-plane EM images of PF-CC synapses. b) Same as panel a for a different CC. (i), example of parallel fiber synapses. Left, reconstruction in a horizontal orientation; right, single-plane EM image with synapse details. (ii), example of a glomerular mossy fiber synapse. Left, reconstruction; middle and right, single-plane EM images showing details of the synapse. Inset scalebars: 500 nm. c,d) Examples of granule cell ascending branch (yellow) excitatory inputs to CCs (blue) for two different cells. Horizontal views of the ascending branch showing the location of the synapse (dashed boxes) and the bifurcation into a parallel fiber (arrow). Dashed boxes denote regions also shown in expanded views along with corresponding EM sections. Inset scalebars: 500 nm.

Extended Data Fig. 9 Additional examples of Purkinje cell (a,b. purple) and MLI (c,d. orange) synapses onto candelabrum cells (light blue).

a Purkinje cell (purple) synapse onto a candelabrum cell. b Same as panel a for a different candelabrum cell. c An MLI with stellate cell morphology (orange) synapse onto a candelabrum cell. d An MLI with basket cell morphology (orange) synapse onto a candelabrum cell. Dashed boxes denote regions shown in insets. Insets show an expanded view of the reconstruction along with single-plane EM sections showing the details of the synapse. Inset scalebars: 500 nm.

Extended Data Fig. 10 The importance of serial EM in identifying synaptic contacts.

The same field of view from Extended Data Fig. 9b is shown, with a CC axon (light blue), a synaptically-connected MLI (orange) and a PC (purple). The axon of the CC ascends very close to the PC, but does not form any synapses onto the PC. Two synapses onto an MLI are shown in the dashed boxes (a,b), along with their respective single-plane EM sections. Inset scalebars: 500 nm. This figure illustrates the importance of EM in identifying synaptic contacts, and how reconstructed cells, and likely fluorescence images, have limitations.

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Osorno, T., Rudolph, S., Nguyen, T. et al. Candelabrum cells are ubiquitous cerebellar cortex interneurons with specialized circuit properties. Nat Neurosci 25, 702–713 (2022). https://doi.org/10.1038/s41593-022-01057-x

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