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Molecular interrogation of hypothalamic organization reveals distinct dopamine neuronal subtypes

Nature Neuroscience volume 20, pages 176–188 (2017)Cite this article

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Abstract

The hypothalamus contains the highest diversity of neurons in the brain. Many of these neurons can co-release neurotransmitters and neuropeptides in a use-dependent manner. Investigators have hitherto relied on candidate protein-based tools to correlate behavioral, endocrine and gender traits with hypothalamic neuron identity. Here we map neuronal identities in the hypothalamus by single-cell RNA sequencing. We distinguished 62 neuronal subtypes producing glutamatergic, dopaminergic or GABAergic markers for synaptic neurotransmission and harboring the ability to engage in task-dependent neurotransmitter switching. We identified dopamine neurons that uniquely coexpress the Onecut3 and Nmur2 genes, and placed these in the periventricular nucleus with many synaptic afferents arising from neuromedin S+ neurons of the suprachiasmatic nucleus. These neuroendocrine dopamine cells may contribute to the dopaminergic inhibition of prolactin secretion diurnally, as their neuromedin S+ inputs originate from neurons expressing Per2 and Per3 and their tyrosine hydroxylase phosphorylation is regulated in a circadian fashion. Overall, our catalog of neuronal subclasses provides new understanding of hypothalamic organization and function.

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Figure 1: Cell-type diversity in the mouse hypothalamus.
Figure 2: Hierarchical clustering of hypothalamic neuron subtypes.
Figure 3: Neurotransmitter phenotypes in hypothalamic neurons.
Figure 4: Neuropeptide associations to individual hypothalamic neuronal subtypes.
Figure 5: Molecular interrogation of dopamine neurons defines a onecut-3-expressing periventricular subtype.
Figure 6: Efferent projections of periventricular onecut-3+ dopamine neurons.
Figure 7: Suprachiasmatic origin for neuromedin S inputs to onecut-3+ Nmur2+ A14 dopamine neurons.
Figure 8: Periventricular onecut-3+ dopamine neurons respond to neuromedin S produced during light periods.

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Acknowledgements

The authors thank N.-G. Larsson and L. Olson for providing Dat1-Cre mice for the generation of reporter mice, H. Wong and M. Watanabe for antibodies and K. Meletis for his supervision of viral injections in Dat1-Cre mice. This work was supported by the Swedish Research Council (T. Harkany, T. Hökfelt, S.L., C. Broberger), Hjärnfonden (T. Harkany), the Petrus and Augusta Hedlunds Foundation (T. Harkany), the Novo Nordisk Foundation (T. Harkany, T. Hökfelt, C. Broberger), the National Brain Research Program of Hungary (MTA-SE NAP B, KTIA_NAP_13-2014-0013; A.A.), the European Commission (PAINCAGE grant, T. Harkany, T. Hökfelt), the European Research Council (BRAINCELL; S.L., ENDOSWITCH; C. Broberger and SECRET-CELLS; T. Harkany), intramural funds of the Medical University of Vienna (T. Harkany) and an NIH grant AG051459 (T.L.H.). R.A.R. is an EMBO long-term research fellow (ALTF 596-2014) cofunded by the European Commission FP7 (Marie Curie Actions, EMBOCOFUND2012, GA-2012-600394). A.Z. received support from the Human Frontier Science Program. F.C. is a Research Associate of the Fonds de la Recherche Scientifique-FNRS, Belgium. The single-cell sequencing infrastructure at CeMM was supported by a New Frontiers Research Infrastructure grant from the Austrian Academy of Sciences.

Author information

Author notes

  1. Roman A Romanov and Amit Zeisel: These authors contributed equally to this work.

  2. Tamas L Horvath and Tibor Harkany: These authors jointly directed this work.

Authors and Affiliations

  1. Department of Molecular Neurosciences, Center for Brain Research, Medical University of Vienna, Vienna, Austria

    Roman A Romanov, Fatima Girach, Erik Keimpema, Daniela Calvigioni & Tibor Harkany

  2. Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden

    Amit Zeisel & Sten Linnarsson

  3. Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden

    Joanne Bakker, Arash Hellysaz, Daniela Calvigioni, Ming-Dong Zhang, Christian Broberger, Tomas Hökfelt & Tibor Harkany

  4. Department of Bioengineering & CNC Program, Stanford University, Stanford, California, USA

    Raju Tomer, Brian Hsueh, Ailey K Crow & Karl Deisseroth

  5. MTA-SE NAP Research Group of Experimental Neuroanatomy and Developmental Biology, Hungarian Academy of Sciences, Budapest, Hungary

    Alán Alpár

  6. Department of Anatomy, Semmelweis University, Budapest, Hungary

    Alán Alpár

  7. Department of Neuroscience, Science for Life Laboratories, Karolinska Institutet, Stockholm, Sweden

    Jan Mulder

  8. Laboratory of Neural Differentiation, Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium

    Frédéric Clotman

  9. Synaptic Systems GmbH, Göttingen, Germany

    Henrik Martens

  10. Microscopy Labs Munich, Global Sales Support-Life Sciences, Carl Zeiss Microscopy GmbH, Munich, Germany

    Christian Schwindling

  11. The Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada

    Jaideep S Bains

  12. Institute of Experimental Medicine, Hungarian Academy of Sciences, Budapest, Hungary

    Zoltán Máté & Gábor Szabó

  13. Department of Genetic and Behavioral Neuroscience, Gunma University Graduate School of Medicine, Maebashi, Japan

    Yuchio Yanagawa

  14. CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria

    Andre Rendeiro, Matthias Farlik & Christoph Bock

  15. Science for Life Laboratory, Albanova University Center, Royal Institute of Technology, Stockholm, Sweden

    Mathias Uhlén

  16. Institute of Physiology, Christian Albrechts University, Kiel, Germany

    Peer Wulff

  17. Program in Integrative Cell Signaling and Neurobiology of Metabolism, Section of Comparative Medicine, Yale University School of Medicine, New Haven, Connecticut, USA

    Tamas L Horvath

Authors
  1. Roman A Romanov
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  2. Amit Zeisel
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  20. Ming-Dong Zhang
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  26. Christian Broberger
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  28. Tomas Hökfelt
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  30. Tamas L Horvath
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  31. Tibor Harkany
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Contributions

T. Harkany and R.A.R. conceived the general framework of this study. T. Harkany, T.L.H., S.L., R.A.R., A.Z., T. Hökfelt, C. Broberger, K.D. designed experiments, T. Harkany, T.L.H., S.L., T. Hökfelt, C. Broberger, K.D., A.A., J.M. and C. Bock senior authors, sponsored research. R.A.R., A.Z., A.H., J.B., F.G., A.A., E.K., R.T., B.H., A.K.C., D.C., M.-D.Z., A.R. and M.F. performed research and analyzed data. H.M., C.S., D.C., Z.M., G.S., F.C., Y.Y., M.U., J.S.B. and P.W. provided unique reagents. R.A.R., A.Z., T.L.H. and T. Harkany wrote the paper. All authors reviewed the manuscript and approved its submission.

Corresponding authors

Correspondence to Tamas L Horvath or Tibor Harkany.

Ethics declarations

Competing interests

T. Harkany declares support from GW Pharmaceuticals on projects unrelated to the focus of this report.

Integrated supplementary information

Supplementary Figure 1 Methodological considerations for and quality control of single-cell RNA-seq

(a) Neuron numbers per cluster in our analysis (blue boxes), and comparison of actual numbers in repeat experiments with statistical probing of random distribution (solid red circles). Note that this comparison excluded sampling or processing-related bias due either to false positive observations or undersampling. (b) Bar plots show the total number of genes detected in individual neuronal subtypes. (c) Likewise, the total number of mRNA molecules passing our filtering criteria (see Online Methods ) were plotted. Grey circles and error bars represent means ± s.e.m. per group in (b,c).

Supplementary Figure 2 Sex and acute stress do not bias neuronal clustering

(a) Numbers of cells from female animals in each cluster (‘observed’) with respect to the range expected by random sampling (‘expected by random ± s.d.’). Clusters on the ordinate follow their listing in Figure 2. The overall frequency of cells of female origin was 30% in the neuronal dataset. The expected means ± s.d. were calculated from the binomial distribution (Bin(N,p) where p = 0.3 and N = the number of cells in each cluster). Clusters show no significant bias for sampling. Clusters #6 and #55 lean towards female and male dominance, respectively. Note that cluster #7 only contains neurons from males. Upper panel: p values calculated using binomial distribution for enrichment of males/females in each cluster. (b) Cluster distribution of cells isolated from animals 6h after acute formalin stress. Solid red circles denote neurons from stress-exposed animals (‘observed’). Blue bars represent the binomial distribution as calculated if distribution was random (‘expected by random ± s.d.’). Upper panel: p values calculated using binomial distribution for enrichment of cells from stress-exposed animals in each cluster. None of the clusters showed stress-related bias.

Supplementary Figure 3 Visualization of hypothalamic neuron subtypes on two-dimensional maps using tSNE

1,194 genes, perplexity = 5, 10 or 20 with 200 principle components. Neurons were color-coded by highest expression of well-known, cluster-defining hypothalamic markers. (a) Distribution of neurons expressing select neuropeptide and neurotransmission-related genes. (b) Distribution of 62 neuronal clusters determined by the BackSpinV2 algorithm. For abbreviations we refer to Figures 1 and 2 of the manuscript.

Supplementary Figure 4 Distribution of 62 neuronal clusters determined by the BackSpinV2 algorithm

Data for each cluster is shown separately on a cumulative tSNE background. Please note that most of the 62 groups are clustered in terms of tSNE plot coordinates while some show lower stringency: 46 of 62 clusters as relatively well separated in the tSNE plot with forming visual clusters with or without outliers; 10 neuronal groups as “satisfactory” clustered with more than one separation core or by forming segregated groups with a relatively large distance between individual neurons. Several clusters do not form segregated groups in tSNE plots: Vglut2 1, Vglut2 3, Vglut2 16, Hmit+/−, GABA 4, GABA 5 because of several possible reasons: a deeper inner heterogeneity of the clusters Vglut2 (all), Hmit+/− and GABA 5, their mixed phenotypes and/or a low number of genes segregating those cells. One needs to remember fundamental algorithmic differences between BackSpin and tSNE: BackSpin can “ignore” genes (which are enriched in other clusters) when splitting the current group. In contrast, tSNE always considers all genes. Thus, tSNE will be more sensitive to carryover of mRNA and contamination by doublets than BackSpin. Individual data points correspond to single cells.

Supplementary Figure 5 Heterogeneity of corticotropin-releasing hormone systems in the mouse hypothalamus

(a,a1) Genetic tracing reveals the distribution of Crh+ neurons concentrated in the bed nucleus of stria terminalis (BST, a)1-3 and paraventricular hypothalamic nucleus (PVH, a1), as well as shows scattered neurons with a history of Crh expression4,5. (b) Taxonomy of Crh+ neurons in the mouse hypothalamus. Note that dual GABA/glutamate phenotypes exist. Cluster numbers are as per Figure 2. (c) Crh, CRH receptors 1,2 (encoded by Crhr1/2 genes) and CRH-binding protein (Crhbp gene) mRNA expression in hypothalamic neuronal subtypes (vertical axes). Expression levels (horizontal axis) were plotted as means of log ± s.e.m. Red and green colors identify GABAergic and glutamatergic clusters (#44 and #45), which express Crh mRNA at levels exceeding 2x s.e.m. Note that significant levels of gene expression in clusters were found only for Crhr2 and Crhbp but not for Crhr1 (*q < 0.05). Crhr1 and Crhr2 were mostly present at low copy numbers in sparse hypothalamic neurons amongst different subtypes. (d) Heat-map representation of genes differentially expressed between GABAergic and glutamatergic Crh+ neurons. Increasing color intensity towards red is proportionate to higher mRNA content. Only p values (Wilcoxon rank-sum test) are shown yet all q values were also < 0.05; n = 10 (GABA) and n = 11 (glutamate) neurons in discrete branches of taxonomy. In GABA+/Crh+ neurons, we observed a predominance of Prkacb (encoding c-AMP-dependent protein kinase subunit B), Amd2 (coding for S-adenosylmethionine decarboxylase 2), Psma7 (encoding proteasome subunit α7), Syt1 (encoding synaptotagmin 1), Crim1 (producing cysteine rich transmembrane BMP regulator 1), Chn1 (coding for chimerin 1), Rgs17 (encoding regulator of G protein signaling 17), Syn2 (producing synapsin 2), Celf2 (coding for Elav-like family member 2) and Sec61a2 (encoding translocon α2 subunit). Glutamatergic neurons were found to express higher levels of Tmem50b (that is, transmembrane protein 50B protein), Tmem176b (encoding transmembrane protein 176B), Pdcl3 (coding for phosducin-like protein 3), Usp31 (encoding ubiquitin-specific peptidase 31), Frg1 (encoding FSHD region geme 1) and Cyb5r1 (producing cytochrome b5 reductase 1). Scale bars = 250 μm (a,a1). Abbreviation: 3V, third ventricle.

References:

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2. Lee, Y. & Davis, M. Role of the hippocampus, the bed nucleus of the stria terminalis, and the amygdala in the excitatory effect of corticotropin-releasing hormone on the acoustic startle reflex. J Neurosci. 17, 6434-6446 (1997).

3. McNally, G.P. & Akil, H. Role of corticotropin-releasing hormone in the amygdala and bed nucleus of the stria terminalis in the behavioral, pain modulatory, and endocrine consequences of opiate withdrawal. Neuroscience 112, 605-617 (2002).

4. Palkovits, M. Stress-induced expression of co-localized neuropeptides in hypothalamic and amygdaloid neurons. European journal of pharmacology 405, 161-166 (2000).

5. Watts, A.G., Sanchez-Watts, G. & Kelly, A.B. Distinct patterns of neuropeptide gene expression in the lateral hypothalamic area and arcuate nucleus are associated with dehydration-induced anorexia. J Neurosci. 19, 6111-6121 (1999).

Supplementary Figure 6 Representative markers for hypothalamic neuronal subtypes and their localization

(a) For each neuronal cluster, the most specific markers were calculated (gene names are on top). To identify the most unique markers for each neuronal cluster, we used power = 0 analysis to identify topmost-expressed unique genes. To force uniqueness, we excluded genes that appear in the list of top 5 markers in other clusters. Since we often observed clusters that are characterized by gene combinations rather than unique global markers, some of the top 5 markers showed low specificity. All genes were found to be statistically significant by the Wilcoxon rank-sum test (q < 0.05) with the exception of L3hypdh (p = 0.04), Prkd1 (p = 0.007) and Ing2 (p = 0.01). The color scale to the right presents values after log transform, which were centered and normalized to mean = 0 and s.d. = 1 for each gene. Saturated colors represent the upper and lower 1% (range 1-99%). (b-c1) Novel neuropeptide identities in the hypothalamus. Hypocretin (Hcrt, b) and galanin (Gal, c)-containing neuronal clusters (#35 and #37, respectively) uniquely co-express mRNAs for pyroglutamylated RFamide peptide (Qrfp; b1) and neuropeptide VF precursor (Npvf, c1). Note that Hcrt+ cluster #36 lacks Qfrp expression. In situ hybridization identifies Qrfp+ or Nvpf+ neurons in the arcuate nucleus (Arc)-lateral hypothalamic area (LHA) and dorsomedial hypothalamus (DMH), respectively. Histochemical data are from the Allen Brain Atlas (www.brain-map.org). Scale bars = 150 μm. mRNA copy numbers were expressed as means ± s.e.m. (log2(mRNA copies + 1); power = 1). *q < 0.05 (Wilcoxon rank-sum test corrected for multiple testing).

Supplementary Figure 7 Histochemical analysis of novel neuronal markers and A14 neurons in the mouse hypothalamus

(a) Novel markers for hierarchical junctions in the hypothalamic diagram (Figure 2). From left to right: oxytocin and Arg-vasopressin (Avp) in the magnocellular paraventricular nucleus of the hypothalamus (PVN), ubiquitin-specific peptidase 48 (USP48), ADP-ribosylation factor guanine nucleotide-exchange factor 1 (AARFGEF1), kinesin family member 5A (KIF5A), as well as dopamine transporter (DAT) expression at the median eminence. (b) Morphology of A14 periventricular dopamine neurons across the mouse hypothalamus. Phosphorylated-TH and onecut-3 co-existence was taken as positive cell identification (arrowheads). Numbers denote anterior-posterior coordinates relative to Bregma. (c) Quantitative immunofluorescence microscopy reveals an inverse relationship between the intensities of GFP and phospho-Ser40-TH (p-Ser40-TH) immunoreactivities for periventricular dopamine neurons in Th-GFP reporter mice. ***p < 0.001 between the groups indicated. Bracketed numbers denote group sizes. Data in box plots represent medians and 10th, 25th, 70th and 90th percentiles. (d,d1) Representative confocal micrographs of coronal single optical sections from the periventricular region of Dat1-tdTomato mice at select anterior-posterior subdivisions stained for onecut-3 and TH. Endogenous tdTomato signal was not amplified. Venn diagrams show the average number of Dat1-tdTomato (red), onecut-3 (green) and TH (blue) immunoreactive (ir) neurons ± s.e.m. per optical slice (n = 6 animals). The relative number of immunoreactive somata compared to the total number of cells is denoted as percentages. Overlap represents co-localization. Note the high degree of co-localization for the tdTomato signal with TH and onecut-3 immunoreactivities. Also note a cluster of tdTomato cells at the retrochiasmatic region that are onecut-3+ but likely lack appreciable TH expression. All encircled cells in the photomicrographs were color-coded according to the cell’s fluorescence labeling. Bregma levels were indicated at the bottom-left. (e) Single-plane views of CLARITY-reconstructed mouse hypothalami stained for TH and focusing on the A14 cell group (semi-transparent overlay). Images were taken at a semi-horizontal plane, with the lower focusing on A14 neurons (see also Supplementary Movie 3). Abbreviations: 3V, third ventricle; A13, zona incerta; Arc, arcuate nucleus; PeVN, periventricular nucleus; SCN, suprachiasmatic nucleus. Scale bars = 150 μm (a [junctions 61/49, 23 inset, 28, 27]), 250 μm (a [junction 23, 42],e), 50 μm (d,d1), 45 μm (a [junction 42 inset],b).

Supplementary Figure 8 Neuronal heterogeneity in the suprachiasmatic nucleus

(a) In situ hybridization histochemistry showing the expression of vasoactive intestinal polypeptide (Vip) mRNA in the suprachiasmatic nucleus (SCN). (b) Likewise, gastrin-releasing peptide (Grp) mRNA was selectively detected in cluster #40 and histochemically localized to the SCN. (c) VIP/GRP co-existence in boutons within the SCN and terminals in the periventricular nucleus (PeVN). (c1) GABAergic neuronal components (green), including a subset of neurons and axonal pathways co-expressing (arrowheads) a DsRed construct under the control of the Cck promoter (blue) are shown in a dual-reporter mouse, highlighting the abundance of GABA neurons in the SCN. (d) Top: Neurotransmitter heterogeneity in the SCN. Overlapping parts of the Venn diagram denote dual GABA/glutamate neurons. ND: non-defined. Bottom: Molecular heterogeneity of neuromedin S-containing neurons. Note the abundance of clock genes, Vip and Cck. (e) Differential Per3 mRNA expression in neuronal subclasses of the hypothalamus. Note highest levels of Per3 mRNA assignment to clusters #40 and #41. Red color denotes expression levels of > 2x s.e.m. from zero. Clusters were ordered according to Figure 2. mRNA copy numbers were expressed as means ± s.e.m. (log2(mRNA copies + 1)), power = 0. (f) Period gene 2 (Per2) mRNA localization by in situ hybridization in the SCN. (g) Neuromedin S (NMS) immunoreactivity around the third ventricle (3V) including synaptic boutons co-stained for the presynaptic protein VAMP2. The existence of particular neuronal subclasses was confirmed by in situ hybridization data from the open source Allen Brain Atlas database (www.brain-map.org). Abbreviations: 3V, third ventricle. Scale bars = 150 μm (a,b,c left,c1), 70 μm (f left), 20 μm (c right,f right).

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–8 and Supplementary Table 1 (PDF 2300 kb)

Supplementary Methods Checklist (PDF 434 kb)

Supplementary Table 2

Gene expression in neurons in hypothalamic clusters #1-#62 (XLSX 1165 kb)

Supplementary Table 3: Marker sets used to define junction points during dendrogram construction

This table shows the top markers that separate each junction of the dendrogram in Figure 2a. For each junction, we searched for genes that best separate the two sides of the junction. The average of the log2(x+1) expression (left) and the fraction of positive cells in each group (expression > 0; right) were calculated, and genes were ranked by their difference. The table shows the top 50 genes found to be specific for each side of particular junctions (left and right) as mentioned above each sub-table. In addition to the score, the p value was calculated using binomial distribution against the null hypothesis that the positive cells are distributed randomly between the groups. q values correspond to p values corrected for multiple testing since each gene was tested for all 61 junctions. (XLSX 727 kb)

Supplementary Table 4: Expression of neuropeptide-coding genes in hypothalamic clusters #1-#62

Increasing color depth from white toward red was used to visualize genes expressed by individual clusters at distinct levels of statistical significance (q values are shown). (XLSX 18 kb)

Supplementary Table 5: P values for neuron-specific genes (Wilcoxon rank-sum test) expressed by hypothalamic neuronal clusters #1-#62

Increasing color depth from white toward red was used to visualize genes at distinct levels of statistical significance. (XLSX 5722 kb)

Supplementary Table 6: Q values for neuron-specific genes (Wilcoxon rank-sum test corrected for multiple testing using horizontal correction) expressed by hypothalamic neuronal clusters #1-#62

Increasing color depth from white toward red was used to visualize genes at distinct levels of statistical significance. (XLSX 3151 kb)

Three-dimensional reconstruction of the suprachiasmatic nucleus-paraventricular hypothalamic nucleus region by light-sheet microscopy.

Red and green colors correspond to phospho-Ser40-TH and onecut-3 immunosignals respectively. Data in rendered form are shown in Fig. 5f. Imaging was performed on a Zeiss Lightsheet Z.1 microscope at 5x primary magnification. (AVI 61385 kb)

Three-dimensional reconstruction of the retrochiasmatic-arcuate nucleus rostral-caudal extent by light-sheet microscopy.

Red and green colors correspond to phospho-Ser40-TH and onecut-3 immunosignals respectively. Data in rendered form are shown in Fig. 5f. Imaging was performed on a Zeiss Lightsheet Z.1 microscope at 5x primary magnification. (AVI 15287 kb)

Three-dimensional reconstruction of TH+ neurons of the hypothalamus in the intact adult mouse forebrain by CLARITY.

TH+ cells were visualized using TH immunostaining (see Expanded Methods for details). The size of the bounding box in the movie (i.e. zoomed in volume) is 4.624 mm × 1.910 mm. (WMV 32860 kb)

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Romanov, R., Zeisel, A., Bakker, J. et al. Molecular interrogation of hypothalamic organization reveals distinct dopamine neuronal subtypes. Nat Neurosci 20, 176–188 (2017). https://doi.org/10.1038/nn.4462

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