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Dentate gyrus astrocytes exhibit layer-specific molecular, morphological and physiological features

Nature Neuroscience volume 25, pages 1626–1638 (2022)Cite this article

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Abstract

Neuronal heterogeneity has been established as a pillar of higher central nervous system function, but glial heterogeneity and its implications for neural circuit function are poorly understood. Here we show that the adult mouse dentate gyrus (DG) of the hippocampus is populated by molecularly distinct astrocyte subtypes that are associated with distinct DG layers. Astrocytes localized to different DG compartments also exhibit subtype-specific morphologies. Physiologically, astrocytes in upper DG layers form large syncytia, while those in lower DG compartments form smaller networks. Astrocyte subtypes differentially express glutamate transporters, which is associated with different amplitudes of glutamate transporter-mediated currents. Key molecular and morphological features of astrocyte diversity in the mice DG are conserved in humans. This adds another layer of complexity to our understanding of brain network composition and function, which will be crucial for further studies on astrocytes in health and disease.

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Fig. 1: scRNA-seq reveals molecular diversity among DG astrocytes.
Fig. 2: Morphologically distinct astrocyte subtypes localized to different layers of the adult DG.
Fig. 3: Astrocyte subtypes were embedded in a layer-specific cellular environment and performed subtype-specific gap junction coupling.
Fig. 4: Subtype-specific expression of glutamate transporters was associated with different magnitudes of glutamate transporter currents and prospective isolation of astrocyte subtypes by FACS.
Fig. 5: Astrocyte diversity in the adult human DG.
Fig. 6: Common and divergent transcriptomic signatures of mice and human DG astrocyte subtypes.

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Data availability

The data that support the findings of this study are included in the paper and are available from the corresponding author upon reasonable request. Image source data will be accessible in Figshare (https://figshare.com/s/581158ef2d313e4a027a). The lists of significantly enriched genes in astrocyte subgroups are available as Supplementary Tables 1–5. All data points of all graphs of this study are summarized in Supplementary Table 6.

Code availability

For scRNA-seq/snRNA-seq analysis data were obtained from the GEO repository (GSE95752 (ref. 8) and GSE186538 (ref. 43)). Scripts detailing all aspects of the performed analysis are available as Supplementary Note.

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Acknowledgements

We thank C. Lie, M. Llorens-Martin and V. Piatti for fruitful discussions. We thank J. Winkler as a member of the JK’s TAC committee for constructive comments. This work was supported by grants from the German Research Foundation (DFG; SPP1757 BE5136/2-1, BE5136/1-2 to R.B., INST 410/45-1 FUGG; SFB1089 B03, SPP1757 HE6949/1, FOR2795 and HE6949/3 to C.H., Emmy Noether Program grant 455354162 to A.S.), by the Johannes-and Frieda-Marohn Stiftung to F.B., by the LOEWE CePTER Epilepsy Research Center of the state Hessen to E.F. and S.L. and by the Excellence Cluster Cardio-Pulmonary Institute to S.L., Bavarian State Ministry of Sciences, Research, and the Arts (ForInter; F.2-F2412.30/1/24) and IZKF (P074) to S.F. The DFG research training group 2162 “Neurodevelopment and Vulnerability of the Central Nervous System” supported this work as follows: J.K., M.T.-W. and N.C. as fellows and J.S. as an associated fellow. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. The present work was performed in the fulfillment of the requirements for obtaining the degree, “Dr. med”.

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Authors and Affiliations

  1. Institute of Biochemistry, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany

    Julian Karpf, Nicholas Chalmers, Felix Beyer, Julia Schneider, Sven Falk, Andreas Sagner & Ruth Beckervordersandforth

  2. Institute of Cellular Neurosciences, Medical Faculty, Universität Bonn, Bonn, Germany

    Petr Unichenko & Christian Henneberger

  3. Institute of Human Genetics, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany

    Marie-Theres Wittmann & Andre Reis

  4. Institute of Neurology (Edinger Institute), University Hospital, Goethe Universität Frankfurt, Frankfurt, Germany

    Elif Fidan & Stefan Liebner

  5. Department of Pathology, GROW—School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, Netherlands

    Jan Beckervordersandforth

  6. Department of Neurosurgery, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany

    Sebastian Brandner

  7. Excellence Cluster Cardio-Pulmonary Institute (CPI), Partner site Frankfurt, Frankfurt, Germany

    Stefan Liebner

  8. German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany

    Christian Henneberger

  9. Institute of Neurology, University College London, London, UK

    Christian Henneberger

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Contributions

J.K., C.H. and R.B. were responsible for conceptualization; J.K., P.U., N.C., F.B., M.-T. W., J.S., E.F., S.F., A.S. and R.B. were responsible for investigation; J.K., P.U., N.C., F.B., M.-T. W., J.S., E.F., S.F., A.S. and R.B. were responsible for formal analysis; A.R., J.B., S.B., S.L., S.F., A.S., C.H. and R.B. were responsible for resources and funding acquisition; R.B. was responsible for writing the original draft; A.R., S.L., C.H. and R.B were responsible for supervision. All authors read and approved the manuscript.

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Correspondence to Ruth Beckervordersandforth.

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Extended data

Extended Data Fig. 1 scRNA-seq revealed molecularly diverse astrocyte subtypes associated to distinct DG layers.

(a) Heatmap showing differentially regulated genes in the five clusters. Differential gene analysis was performed by using the Wilcoxon Rank sum test as implemented in Seurat. (b) Examples of genes expressed by all DG astrocytes as represented by tSNE plots and immunostaining against the transcription factors ID4 and SOX2 (in white) and GFAP (magenta). (c) tSNE plots of DEGs upregulated in cluster 4 (circle) revealed many known markers for radial glia-like NSCs. Immunostaining against NESTIN (white) and GFAP (magenta) confirmed the expression in radial glia-like NSCs. (d) scRNA seq analysis revealed that S100ß, Aldh1L1 and Aqp4 are expressed in all DG astrocytes except radial glia-like NSCs (circle), which was confirmed by immunostaining against the markers (white) and GFAP (magenta). For AQP4, hGFAPeGFP animals were used to delineate whole astrocytes based on the cytoplasmic GFP signal. In the left panel, the arrows indicate expression of AQP4 in a GZ astrocyte surrounding a blood vessel. The right panel depicts a GFP+ radial glial-like NSCs that lack AQP4 expression at its end feet (arrows). (e) tSNE plots depicting the expression of genes associated to gliogenesis (Id3), cell cycle (Ccnd2, Pcna), and BMP signaling (Bmp1, Jun) in cluster 2 (circle) indicating that cluster 2 represents proliferating astrocytes. (f) Confocal images of dividing astrocytes in the adult mouse DG expressing cell cycle marker MCM2 (white) and astrocyte markers GFAP (magenta) and SOX2 (blue) in hGFAPeGFP animals. (g) tSNE blots of DEG upregulated in cluster 3 (circle) in comparison to cluster 0 and 1. Cluster 3 represented SGZ astrocytes as verified by spatial expression (Fig. 1i-k; Fig. 4b, d) and functional analysis of Glutamate transporter currents (Fig. 4e–g). (h) tSNEs of DEGs upregulated in cluster 0 in comparison to cluster 1, including Slc38a3 and Fam107a, for which RNAscope analysis was performed (Fig. 1l, n). All immunostainings were performed in 4–7 experimental animals in at least 3 independent experiments; all scale bars = 20 µm.

Extended Data Fig. 2 Morphologically distinct astrocyte subtypes localized to different layers of the adult DG.

(a) Confocal images of a hGFAPeGFP brain slice stained only with DAPI (blue) representing an overview of astrocytes subtypes localized to different DG layers; more than 10 experimental animals were analyzed. (b) Heatmap of 3D-reconstructed astrocytes from all DG layers; subtypes are depicted on the right side and marked by color code (as depicted in Fig. 2q, r); morphological parameters depicted below revealed clustering of astrocytes populating the same DG layer. (c-l) Graphs representing the individual morphological parameters used to conduct the PCA. Astrocyte subtypes are indicated below the graphs; red dots represent analysed cells; 8 experimental animals were analysed for morphological analysis. Data are represented as mean ± SEM; one-way ANOVA with Tukey post hoc tests were performed to determine significance; no adjustments were made for multiple comparison; in case of significance, p-values are indicated in the graphs. Scale bars = 20 µm.

Extended Data Fig. 3 Astrocyte subtypes were embedded in a layer-specific cellular environment and displayed subtype-specific gap junction-coupling.

(a) Quantification of astrocytes associated to different DG layers. (b, c) Immunostaining and quantification of IBA+ microglia (red) per DG compartment; DAPI (blue) (d, e) Immunostaining and quantification of PDGFRα+ (red) per DG compartment. 3–6 experimental animals were analyzed and are indicated as red dots representing biological replicates. (f) Schematic representation of Alexa Fluor 594 dye-injections into astrocytes in acute hippocampal slices. (g-j) Two-photon excitation images of astrocyte subtypes from hGFAPeGFP mice. Brightfield images in the upper row show localisation of dye-injected astrocyte subtypes within the adult DG; lower row depicts Alexa Fluor 594 diffusion to gap junction-coupled cells; astrocyte subtypes as indicated. (j) Cellular layers were identified using infrared image channel using DIC (left panel), and astrocytes were classified according to their location to an identified layer. Dye-coupled astrocytes were identified using two-photon excitation imaging of AlexaFluor 594 diffusing from the patched cell (right panel; green line represents SGZ). (k) Representative analysis of a single experiment. A set of dye-coupled cells (dots) and a monoexponential fit (I(d) = 100 % * exp(−d/Cλ), where I is the somatic fluorescence intensity, d is the three-dimensional distance to the patched cell, and Cλ the coupling length constant34. (I) Residuals of this representative example (k) of a monoexponential fit of dye-coupled cells. (m) Residual values of all monoexponential fits for dye-loaded hilus astrocytes (n = 7 patched astrocytes); total of 61 coupled cells (58 hilus astrocytes in red and 3 SGZ astrocytes in blue). Boxed area: same residuals to visualize their spread around zero. (n) Residual values of monoexponential fits for dye-loaded SGZ astrocytes (n = 8 patched astrocytes); total of 46 coupled cell (17 hilus astrocytes in red and 29 SGZ astrocytes in blue). Boxed area: same residuals to visualize their spread around zero. (o) Residual values of monoexponential fits for dialysed ML astrocytes (n = 5 patched astrocytes); total of 50 coupled cells (40 ML astrocytes in green and 10 SGZ/hilar astrocyte in red). Boxed area: same residuals to visualize their spread around zero. Data are represented as mean ± SEM. One-way ANOVA plus Tukey post-hoc tests were performed to determine statistical significance; no adjustments were made for multiple comparison; p-values are indicated in the graphs. Scale bares = 20 µm (b, d), and 50 µm (g-j).

Extended Data Fig. 4 Isolation of distinct astrocytes subtypes by FACS and astrocyte diversity in the adult human DG.

(a) Dot blots depicting FACS gating strategy of adult DG cells according to living (left) and single cells (middle); isotype-matched controls conjugated to PE (a) and APC (b) were used to set the gates for sorting of ACSA1 (SLC1A3)-APC and ACSA2 (ATP1B2)-PE (right). (c) Graph depicting diameter of primary neurospheres generated by SLC1A3+/ATP1B2+ cells, ATP1B2+ cells, SLC1A31+ cells, and the all negative-sorted cell fractions; no significant differences were detected between the population. Neurosphere assay was carried out from 4 independent FACS experiments (3–6 wildtype mice per experiment). One-way ANOVA with Tukey post hoc tests were performed to determine significance; no adjustments were made for multiple comparisons. (d-i) High magnification images of hippocampal sections from three human subjects between 43 and 52 years of age (represent patient 1–3 in average intensity blots Fig. 4h, j, l) were stained against GFAP (magenta), EAATs (white) and DAPI (blue). Immunostaining against SLC1A3 (d-f) and SLC1A2 (g-i). Immunostainings against each marker were performed in 3 patients in 3 independent experiments. Scale bars = 20 µm.

Extended Data Fig. 5 Common and divergent transcriptomic signatures of mouse and human DG astrocyte subtypes.

(a) Top 30 DEGs for each human DG astrocyte cluster. (b) Heatmap depicting pseudobulk gene expression levels for the same genes as in (a). Color bar for each row depicts if the gene was identified as differentially expressed in the pseudobulk differential gene expression analysis. (c) Percentage of DEGs detected by Seurat that were also detected in the pseudobulk differential gene expression analysis either for all detected genes (red bars) or the top 30 DEGs (cyan bars). Differential gene analysis was performed by using the Wilcoxon Rank sum test as implemented in Seurat. Pseudobulk differential gene expression analysis was performed using glmQLFTest function implemented in edgeR.

Extended Data Fig. 6 Common and divergent transcriptomic signatures of mouse and human DG astrocyte subtypes.

(a–f) Examples of genes differentially expressed in mouse niche astrocytes (a, b), radial glia-like NSCs (c) and proliferating astrocytes (d–f) as represented by tSNE plots (upper row) and UMAP plots representing their expression pattern in human DG astrocytes (lower row). (g-j) ISH images from the Allen Mouse Brain Atlas (g-i; mouse.brain-map.org) and Allen Human Brain Atlas (j; human.brain-map.org) for Glul (mouse.brain-map.org/ish/experiment/show/14421), Grm3 (mouse.brain-map.org/ish/experiment/show/72231), Slc1a3 (mouse.brain-map.org/ish/experiment/show/20274), SLC1A3 (human.brain-map.org/ish/experiment/show/159113739). (k-p) Analysis of the integrated mouse and human data sets revealed candidates showing a corresponding expression in mouse (dark blue, upper row) and human (red, lower row) astrocytes belonging to the same clusters. (q) CTNNA2 was predominantly expressed only in human astrocytes and (r) LDHB in mouse astrocytes. (s-u) Immunostaining against HOPX (white), GFAP (magenta), and DAPI in human sections. (s, t) HOPX is not expressed in adult hippocampal and cortical astrocytes in postmortem slices (s; arrow) and in freshly fixed adult DG tissue (t). (u) However, almost all cortical astrocytes expressed HOPX in the fetal brain (arrowheads). HOPX expression was determined in 3 independent experiments in 5 human individuals. All scale bares = 20 µm, except (g-i) = 50 µm, and (j) = 100 µm; UMAP = Uniform Manifold Approximation and Projection; gw = gestational week.

Supplementary information

Supplementary Information

Supplementary Note—Workflow of human to mice scRNA-seq/snRNA-seq data comparison.

Reporting Summary

Supplementary Table 1

Differentially expressed genes of clusters 0–4 compared to all others.

Supplementary Table 2

Differentially expressed genes upregulated in cluster 3 in comparison to clusters 0 and 1.

Supplementary Table 3

Differentially expressed genes of clusters 0 and 1 compared to each other.

Supplementary Table 4

Differentially expressed genes of human DG astrocyte clusters identified by Seurat.

Supplementary Table 5

Differentially expressed genes of human DG astrocyte clusters identified by pseudobulk differential gene expression analysis using EdgeR.

Supplementary Table 6

Summary table containing statistical source data.

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Karpf, J., Unichenko, P., Chalmers, N. et al. Dentate gyrus astrocytes exhibit layer-specific molecular, morphological and physiological features. Nat Neurosci 25, 1626–1638 (2022). https://doi.org/10.1038/s41593-022-01192-5

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