Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Long-term self-renewing stem cells in the adult mouse hippocampus identified by intravital imaging

Abstract

Neural stem cells (NSCs) generate neurons throughout life in the mammalian hippocampus. However, the potential for long-term self-renewal of individual NSCs within the adult brain remains unclear. We used two-photon microscopy and followed NSCs that were genetically labeled through conditional recombination driven by the regulatory elements of the stem cell-expressed genes GLI family zinc finger 1 (Gli1) or achaete-scute homolog 1 (Ascl1). Through intravital imaging of NSCs and their progeny, we identify a population of Gli1-targeted NSCs showing long-term self-renewal in the adult hippocampus. In contrast, once activated, Ascl1-targeted NSCs undergo limited proliferative activity before they become exhausted. Using single-cell RNA sequencing, we show that Gli1- and Ascl1-targeted cells have highly similar yet distinct transcriptional profiles, supporting the existence of heterogeneous NSC populations with diverse behavioral properties. Thus, we here identify long-term self-renewing NSCs that contribute to the generation of new neurons in the adult hippocampus.

This is a preview of subscription content

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: Gli1-targeted R cells contain long-term self-renewing hippocampal stem cells.
Fig. 2: Diverse behavioral features of Gli1- and Ascl1-targeted NSCs.
Fig. 3: scRNA-seq of Gli1- and Ascl1-targeted cells identifies NSCs with self-renewal potential.
Fig. 4: Molecular profiling reveals distinct features of Gli1- versus Ascl1-targeted NSCs.

Data availability

All data are available from the authors on request. scRNA-seq data have been submitted into the Gene Expression Omnibus at GSE138941.

Code availability

Source code for next-generation sequencing data processing and scRNA-seq is available at https://github.com/imallona/stem_cells_hippocampus_jessberger_lab/.

References

  1. 1.

    Gage, F. H. Adult neurogenesis in mammals. Science 364, 827–828 (2019).

  2. 2.

    Sorrells, S. F. et al. Human hippocampal neurogenesis drops sharply in children to undetectable levels in adults. Nature 555, 377–381 (2018).

    CAS  Article  Google Scholar 

  3. 3.

    Goncalves, J. T., Schafer, S. T. & Gage, F. H. Adult neurogenesis in the hippocampus: from stem cells to behavior. Cell 167, 897–914 (2016).

    CAS  Article  Google Scholar 

  4. 4.

    Eriksson, P. S. et al. Neurogenesis in the adult human hippocampus. Nat. Med. 4, 1313–1317 (1998).

    CAS  Article  Google Scholar 

  5. 5.

    Knoth, R. et al. Murine features of neurogenesis in the human hippocampus across the lifespan from 0 to 100 years. PLoS ONE 5, e8809 (2010).

    Article  Google Scholar 

  6. 6.

    Moreno-Jimenez, E. P. et al. Adult hippocampal neurogenesis is abundant in neurologically healthy subjects and drops sharply in patients with Alzheimer’s disease. Nat. Med. 25, 554–560 (2019).

    CAS  Article  Google Scholar 

  7. 7.

    Tobin, M. K. et al. Human hippocampal neurogenesis persists in aged adults and Alzheimer’s disease patients. Cell Stem Cell 24, 974–982 (2019).

    CAS  Article  Google Scholar 

  8. 8.

    Spalding, K. L. et al. Dynamics of hippocampal neurogenesis in adult humans. Cell 153, 1219–1227 (2013).

    CAS  Article  Google Scholar 

  9. 9.

    Shin, J. et al. Single-cell RNA-seq with waterfall reveals molecular cascades underlying adult neurogenesis. Cell Stem Cell 17, 360–372 (2015).

    CAS  Article  Google Scholar 

  10. 10.

    Suh, H. K. et al. In vivo fate analysis reveals the multipotent and self-renewal capacities of Sox2+ neural stem cells in the adult hippocampus. Cell Stem Cell 1, 515–528 (2007).

    CAS  Article  Google Scholar 

  11. 11.

    Seri, B., Garcia-Verdugo, J. M., McEwen, B. S. & Alvarez-Buylla, A. Astrocytes give rise to new neurons in the adult mammalian hippocampus. J. Neurosci. 21, 7153–7160 (2001).

    CAS  Article  Google Scholar 

  12. 12.

    Urban, N. et al. Return to quiescence of mouse neural stem cells by degradation of a pro-activation protein. Science 353, 292–295 (2016).

  13. 13.

    Bonaguidi, M. A. et al. In vivo clonal analysis reveals self-renewing and multipotent adult neural stem cell characteristics. Cell 145, 1142–1155 (2011).

    CAS  Article  Google Scholar 

  14. 14.

    Encinas, J. M. et al. Division-coupled astrocytic differentiation and age-related depletion of neural stem cells in the adult hippocampus. Cell Stem Cell 8, 566–579 (2011).

    CAS  Article  Google Scholar 

  15. 15.

    Kempermann, G. The pessimist’s and optimist’s views of adult neurogenesis. Cell 145, 1009–1011 (2011).

    CAS  Article  Google Scholar 

  16. 16.

    Pilz, G. A. et al. Live imaging of neurogenesis in the adult mouse hippocampus. Science 359, 658–662 (2018).

  17. 17.

    Katsimpardi, L. & Lledo, P. M. Regulation of neurogenesis in the adult and aging brain. Curr. Opin. Neurobiol. 53, 131–138 (2018).

    CAS  Article  Google Scholar 

  18. 18.

    Ben Abdallah, N. M., Slomianka, L., Vyssotski, A. L. & Lipp, H. P. Early age-related changes in adult hippocampal neurogenesis in C57 mice. Neurobiol. Aging 31, 151–161 (2010).

    Article  Google Scholar 

  19. 19.

    Kuhn, H. G., Dickinson-Anson, H. & Gage, F. H. Neurogenesis in the dentate gyrus of the adult rat: age-related decrease of neuronal progenitor proliferation. J. Neurosci. 16, 2027–2033 (1996).

    CAS  Article  Google Scholar 

  20. 20.

    Kalamakis, G. et al. Quiescence modulates stem cell maintenance and regenerative capacity in the aging brain. Cell 176, 1407–1419 (2019).

    CAS  Article  Google Scholar 

  21. 21.

    Ziebell, F., Dehler, S., Martin-Villalba, A. & Marciniak-Czochra, A. Revealing age-related changes of adult hippocampal neurogenesis using mathematical models. Development 145, dev153544 (2018).

    Article  Google Scholar 

  22. 22.

    Ahn, S. & Joyner, A. L. In vivo analysis of quiescent adult neural stem cells responding to Sonic hedgehog. Nature 437, 894–897 (2005).

    CAS  Article  Google Scholar 

  23. 23.

    Blomfield, I. M. et al. Id4 promotes the elimination of the pro-activation factor Ascl1 to maintain quiescence of adult hippocampal stem cells. Elife 8, e48561 (2019).

    CAS  Article  Google Scholar 

  24. 24.

    Street, K. et al. Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics. BMC Genomics 19, 477 (2018).

    Article  Google Scholar 

  25. 25.

    Dumitru, I., Neitz, A., Alfonso, J. & Monyer, H. Diazepam binding inhibitor promotes stem cell expansion controlling environment-dependent neurogenesis. Neuron 94, 125–137 (2017).

    CAS  Article  Google Scholar 

  26. 26.

    Berg, D. A. et al. A common embryonic origin of stem cells drives developmental and adult neurogenesis. Cell 177, 654–668 (2019).

    CAS  Article  Google Scholar 

  27. 27.

    Yuzwa, S. A. et al. Developmental emergence of adult neural stem cells as revealed by single-cell transcriptional profiling. Cell Rep. 21, 3970–3986 (2017).

    CAS  Article  Google Scholar 

  28. 28.

    La Manno, G. et al. RNA velocity of single cells. Nature 560, 494–498 (2018).

    Article  Google Scholar 

  29. 29.

    Bergen, V. & et al. Generalizing RNA velocity to transient cell states through dynamical modeling. Nat. Biotechnol. https://doi.org/10.1038/s41587-020-0591-3 (2020).

  30. 30.

    Hochgerner, H., Zeisel, A., Lonnerberg, P. & Linnarsson, S. Conserved properties of dentate gyrus neurogenesis across postnatal development revealed by single-cell RNA sequencing. Nat. Neurosci. 21, 290–299 (2018).

    CAS  Article  Google Scholar 

  31. 31.

    Yang, C. P., Gilley, J. A., Zhang, G. & Kernie, S. G. ApoE is required for maintenance of the dentate gyrus neural progenitor pool. Development 138, 4351–4362 (2011).

    CAS  Article  Google Scholar 

  32. 32.

    Knobloch, M. et al. Metabolic control of adult neural stem cell activity by Fasn-dependent lipogenesis. Nature 493, 226–230 (2013).

    CAS  Article  Google Scholar 

  33. 33.

    Gut, G., Herrmann, M. D. & Pelkmans, L. Multiplexed protein maps link subcellular organization to cellular states. Science 361, eaar7042 (2018).

  34. 34.

    Zweifel, S. et al. HOPX defines heterogeneity of postnatal subventricular zone neural stem cells. Stem Cell Rep. 11, 770–783 (2018).

    CAS  Article  Google Scholar 

  35. 35.

    Bonaguidi, M. A., Song, J., Ming, G. L. & Song, H. A unifying hypothesis on mammalian neural stem cell properties in the adult hippocampus. Curr. Opin. Neurobiol. 22, 754–761 (2012).

    CAS  Article  Google Scholar 

  36. 36.

    Pilz, G. A. et al. Functional imaging of dentate granule cells in the adult mouse hippocampus. J. Neurosci. 36, 7407–7414 (2016).

    CAS  Article  Google Scholar 

  37. 37.

    R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. https://igraph.org/ (2017).

  38. 38.

    Picardo, M. A. et al. Pioneer GABA cells comprise a subpopulation of hub neurons in the developing hippocampus. Neuron 71, 695–709 (2011).

    CAS  Article  Google Scholar 

  39. 39.

    Csardi, G. & Nepusz, T. The igraph software package for complex network research. Int. J. Complex Syst. 1695, 38 (2006).

  40. 40.

    Kolde, R. pheatmap: Pretty Heatmaps. R package, version 1.0.8. https://CRAN.R-project.org/package=pheatmap (2015).

  41. 41.

    Jaeger, B. N. et al. Miniaturization of Smart-seq2 for single-cell and single-nucleus RNA sequencing. STAR Protoc. 1, 100081 (2020).

    Article  Google Scholar 

  42. 42.

    Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

    CAS  Article  Google Scholar 

  43. 43.

    McCarthy, D. J., Campbell, K. R., Lun, A. T. & Wills, Q. F. Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R. Bioinformatics 33, 1179–1186 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. 44.

    Stuart, T. et al. Comprehensive integration of single-cell data. Cell 177, 1888–1902 (2019).

    CAS  Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the European Research Council (STEMBAR to S.J. and BRAINCOMPATH to F.H.), the Swiss National Science Foundation (BSCGI0_157859 and 310030_196869 to S.J.), the Zurich Neuroscience Center, the University of Zurich (UZH) Forschungskredit fellowship (B.N.J.) and the Wellcome Trust (098357/Z/12/Z to B.D.S.). L.H. was supported by a fellowship from the Francis Crick Institute. Work in the laboratory of F.G. is supported by the Francis Crick Institute, which receives its funding from Cancer Research UK (FC0010089), the UK Medical Research Council (FC0010089) and the Wellcome Trust (FC0010089; also, investigator award 106187/Z/14/Z to F.G.). We thank P. Bethge for experimental help and D. Chichung Lie for comments on the manuscript. We thank E. Yángüez López-Cano from the Functional Genomics Center Zurich (UZH and ETHZ) and the Cytometry Facility of UZH. J. Sarabia del Castillo, G. Gut, and L. Pelkmans contributed to 4i experiments.

Author information

Affiliations

Authors

Contributions

S.B. performed imaging, analyzed data and cowrote the manuscript. B.N.J. performed scRNA-seq, analyzed data and cowrote the manuscript. G.A.P. performed imaging, analyzed data and cowrote the manuscript. J.D.C. performed 4i analyses. M.K. performed scRNA-seq. L.H. performed the RNAscope experiments. I.M. performed computational analyses of scRNA-seq data. V.I.K. performed computational analyses of scRNA-seq data. D.J.J. and B.D.S. contributed to the concept, performed data analyses and cowrote the manuscript. F.G. and F.H. revised the manuscript. S.J. developed the concept and wrote the manuscript.

Corresponding author

Correspondence to Sebastian Jessberger.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Neuroscience thanks Yukiko Gotoh, Hongjun Song and Juan Song for their contribution to the peer review of this work.

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

Extended data

Extended Data Fig. 1 Characterization of Gli1 and Ascl1-targeted cells.

a, Number of tdTom+ cells in the SGZ 2d after recombination in Gli1 (n = 4 mice) and Ascl1 (n = 3 mice). b, Percentage of the distance of tdTom+ R cells from the anchor/max distance in Gli1 and Ascl1 at 2dpi. Horizontal sections, first 300 μm of DG are considered (Gli1: 53.93 ± 2.27, n = 106 cells; Ascl1: 54.35 ± 1.83, n = 199 cells; Mann Whitney test: Mann–Whitney U = 10407; p = 0.849, two-tailed). c, Percentage of the distance of imaged clones from the anchor/max distance in Gli1 and Ascl1 at 2mpi. Horizontal sections (Gli1: 51.6 ± 2.31, n = 40 clones; Ascl1: 45.6 ± 5.63, n = 18 clones; Mann Whitney test: Mann-Whitney U = 337; p = 0.708, two-tailed). d, Representation of the method used to quantify the distances between R cells and the anchor. Horizontal view of the DG. e, Quantification of the distance between pairs of tdTom+ R cells in Gli1 and Ascl1 at 2dpi. Horizontal sections, first 300 μm of DG are considered (Gli1: 523.5 ± 14.86, n = 608 pair of cells; Ascl1: 546.1 ± 9.25, n = 1696 pair of cells; Mann Whitney test: Mann-Whitney U = 505390; p = 0.469, two-tailed). f, Representation of the method used to quantify the distances between pair of R cells (only the pairings of 3R cells with all the other R cells in the section are shown as examples). Horizontal view of the DG. g, Quantification of tdTom+ cell types in the SGZ 2d after recombination in Gli1 (n = 4 mice) and Ascl1 (n = 3 mice). h, Representative pictures of RNA-Scope with Ki67 probe (green) and Ascl1 probe (grey) and immunostaining for tdTomato (red) and GFAP (cyan) of Gli1 and Ascl1-targeted cells at 5dpi. Filled arrowheads point to R cells; empty arrowheads point to NR cells. i, Quantification of the Ascl1 mRNA dots of: R ki67- cells (Gli1: 4.136 ± 0.366, n = 88 cells; Ascl1: 5.617 ± 0.851, n = 47 cells; Unpaired ttest: t = 1.855; df = 133; p = 0.065, two-tailed), R ki67+ cells (Gli1: 10.83 ± 2.676, n = 6; Ascl1: 8.250 ± 2.089, n = 12; Unpaired ttest: t = 0.734; df = 16; p = 0.473, two-tailed), NR ki67+ cells (Gli1: 8.000 ± 1.741, n = 12; Ascl1: 4.978 ± 0.7160, n = 45; Unpaired t-test: t = 1.834; df = 55; p = 0.0721, two-tailed). j, Quantification of the Ascl1 mRNA levels (fluorescence intensity of the cell/background) of: R ki67- cells (Gli1: 1.739 ± 0.083, n = 77 cells; Ascl1: 1.933 ± 0.198, n = 40 cells; Unpaired t-test: t = 1.055; df = 115; p = 0.293, two-tailed), R ki67+ cells (Gli1: 4.528 ± 1.919, n = 5; Ascl1: 2.502 ± 0.369, n = 12; Unpaired t-test: t = 1.54; df = 15; p = 0.144, two-tailed), NR ki67+ cells (Gli1: 4.157 ± 0.566, n = 10; Ascl1: 2.510 ± 0.258, n = 39; Unpaired t-test: t = 2.815; df = 47; **p = 0.007, two-tailed). k, Quantification of the Ascl1 mRNA dots of: ki67- cells (Gli1: 4.067 ± 0.295, n = 149 cells; Ascl1: 3.516 ± 0.405, n = 124 cells; Unpaired t-test: t = 1.121; df = 271; p = 0.263, two-tailed), ki67+ cells (Gli1: 8.944 ± 1.454, n = 18; Ascl1: 5.667 ± 0.728, n = 57; Unpaired t-test: t = 2.141; df = 73; *p = 0.035, two-tailed). Values are shown as mean ± s.e.m. Bars in violin plots represent median and quartiles. Scale bars represent 100 μm (d,f) and 10 μm (h). For detailed statistics, see Supplementary Table 5.1.

Extended Data Fig. 2 Intravital 2-photon imaging does not affect proliferation or lineage commitment of Gli1-targeted NSCs.

a, Explanatory scheme of the different parameters extracted from lineage data of the imaged clones. b, Comparison of cell proliferation in contralateral and ipsilateral side in Gli1 mice after 2 months of 2-photon imaging (dorsal DG, horizontal sections). c, Quantification of Ki67+ cells and Ki67+ tdTom+ cells in contra- and ipsilateral side. Horizontal sections, first 360 μm of DG are considered (Ki67+ ipsilateral: 1345 ± 235.7, n = 3 mice; Ki67+ contralateral: 1278 ± 252.2, n = 3 mice; Paired t-test: t = 0.2631; df = 2; p = 0.817, two-tailed. Ki67 + /tdTom+ ipsilateral: 28 ± 11.06, n = 3 mice; Ki67 + /tdTom+ contralateral: 68.33 ± 26.1, n = 3 mice; Paired t-test: t = 2.678; df = 2; p = 0.116, two-tailed). d, Percentage of Ki67+ tdTom + /tdTom+ cells in contra- and ipsilateral side (ipsilateral: 7.26 ± 1.84, n = 4 mice; contralateral: 8.58 ± 0.63, n = 4 mice; Paired t-test: t = 0.895; df = 3; p = 0.436, two-tailed). e, Percentage of tdTom+ Hopx+ Ki67 + /tdTom+ Hopx+ cells in contra- and ipsilateral side (ipsilateral: 9.0 ± 1.83, n = 3 mice; contralateral: 9.63 ± 1.91, n = 3 mice; Paired t-test: t = 0.392; df = 2; p = 0.733, two-tailed). f, Comparison of the number and identity of tdTom+ cells in contralateral and ipsilateral side in Gli1 mice after 2 months of 2-photon imaging (dorsal DG, horizontal sections). g, Quantification of tdTom+ neurons and Sox2+ tdTom+ glial cells in contra- and ipsilateral side. Horizontal sections, first 360 μm of DG are considered (tdTom+ ipsilateral: 475.3 ± 45.16, n = 3 mice; tdTom+ contralateral: 424.7 ± 128.2, n = 3 mice; Paired t-test: t = 0.475; df = 2; p = 0.681, two-tailed. tdTom+ SOX2 + ipsilateral: 279.3 ± 36.5, n = 3 mice; tdTom+ Sox2+ contralateral: 293 ± 75.5, n = 3 mice; Paired t-test: t = 0.345; df = 2; p = 0.762, two-tailed). h, Percentage of Sox2+ tdTom + /tdTom+ in contra- and ipsilateral side (ipsilateral: 36.93 ± 3.78, n = 3 mice; contralateral: 41.49 ± 2.49, n = 3 mice; Paired t-test: t = 1.347; df = 2; p = 0.31, two-tailed). i, Quantification of the DG area covered by GFAP + cells/area tot in Gli1 contra- and ipsilateral side at 2 weeks after surgery (ipsilateral: 0.77 ± 0.03, n = 3 mice; contralateral: 0.73 ± 0.01, n = 3 mice; Paired t -test: t = 2.004; df = 2; p = 0.183, two-tailed). j, Quantification of the DG area covered by Iba1+ cells/area tot in Gli1 contra- and ipsilateral side at 2 weeks after surgery (ipsilateral: 0.51 ± 0.05, n = 3 mice; contralateral: 0.5 ± 0.04, n = 3 mice; Paired t-test: t = 0.677; df = 2; p = 0.568, two-tailed). k, Quantification of the DG area covered by GFAP + cells/area tot in Gli1 contra- and ipsilateral side at 2.5 months after surgery (ipsilateral: 0.79 ± 0.03, n = 3 mice; contralateral: 0.83 ± 0.02, n = 3 mice; Paired t-test: t = 1.654; df = 2; p = 0.24, two-tailed). Values are shown as mean ± s.e.m. Scale bars represent 100 μm (b, f). For detailed statistics, see Supplementary Table 5.1.

Extended Data Fig. 3 NR cells behavior is similar between Gli1- and Ascl1- derived lineages.

a, Relationship between time to first division and R cell self-renewal duration. Gli1 and Ascl1-targeted R cells are shown as dots in the XY correlation graph (correlation analysis: Spearman r = −0.03, n = 113 XY pairs; p (two-tailed) = 0.744). b, Time until division of R cells (in days) in successive divisions. Div1: first division after the first neurogenic division in the clone. Comparison among consecutive divisions in each mouse line (Gli1 Div1: 8.49 ± 1.29, n = 36 divisions; Gli1 Div2: 6.89 ± 1.95, n = 14 divisions; Gli1 Div3: 7.75 ± 1.49, n = 4 divisions; p = 0.511. Ascl1 Div1: 3.12 ± 0.49, n = 37 divisions; Ascl1 Div2: 3.2 ± 1.28, n = 10 divisions; Ascl1 Div3: 20, n = 1 divisions; p = 0.225. Statistical test used: Kruskal Wallis) and comparison between Gli1 and Ascl1 (Div1: Mann Whitney test: Mann-Whitney U = 302; ***p < 0.0001, two-tailed; Div2: Mann Whitney test: Mann-Whitney U = 34.5; *p = 0.034, two-tailed). c, Heat maps representing the frequencies of division modes of Gli1- and Ascl1- targeted NR cells (division rounds (Div) 1, 3 and 5 counting from the first NR division. Gli1 Div1 n = 91 divisions; Gli1 Div3 n = 65 divisions; Gli1 Div5 n = 11 divisions. Ascl1 Div1 n = 85 divisions; Ascl1 Div3 n = 71 divisions; Ascl1 Div5 n = 18 divisions). R, radial glia-like cell; NR, proliferating progenitor cell; N, neuron; A, astrocyte. Division events contain only certain lineage relations. d, Time (in days) between NR cell divisions (Gli1: 1.38 ± 0.08, n = 460 cells; Ascl1: 1.24 ± 0.08, n = 461 cells; Mann Whitney test: Mann-Whitney U = 100475; p = 0.1207, two-tailed). e, Relative frequency of the NR cells cell fate distribution. The lineage trees are shifted to the first R cell division and NR divisions are pooled according to the time windows in which they take place (Gli1 n in 0–20 days interval: 410, Gli1 n in 20–40 days interval: 78, Gli1 n in 40–70 days interval: 12; Ascl1 n in 0- 20 days interval: 424, Ascl1 n in 20–40 days interval: 74, Ascl1 n in 40–70 days interval: 0). Error bars represent the standard error of the proportion. Division events contain all binary lineage relations (certain and uncertain). Values are shown as mean ± s.e.m. For detailed statistics, see Supplementary Table 5.2.

Extended Data Fig. 4 Transcriptional analysis of Gli1- vs Ascl1-targeted cells.

a, Representative FACS plots showing gating for live (Hoechst-) tdTomato+ DG cells sorted for scRNA-seq. b, t-Distributed Stochastic Neighbor Embedding (t-SNE) visualization of the 4 clusters (non-dividing NSCs (ndNSCs), dividing NSCs (dNSCs), Immature Neurons (IN), Mature Neurons (MN)) identified in Gli1- and Ascl1 targeted tdTomato+ neuronal cells. c, Uniform Manifold Approximation and Projection (UMAP) visualization of the seven individual datasets used for analysis. _1 and _2 indicate duplicates for a given data point. d, UMAP visualization of the cell isolated 5 days or 12 weeks after tamoxifen injection. e, Distribution of the cells among the 4 clusters, 5 days or 12 weeks after tamoxifen injection. f, Expression pattern of Ascl1 mRNA. g, Violin plots showing Ascl1 mRNA levels in Gli1- and Ascl1-derived ndNSCs and dNSCs (Wilcoxon text, *p < 0.05). h, Position of Gli1 (red) and Ascl1 (blue) ndNSCs and dNSCs along the pseudotime axis as calculated by Monocle. Cells present along the full pseudotime range (grey rectangle) or sharing the same pseudotime range (green rectangle) are depicted. i-j, Volcano plots showing significantly differentially expressed genes (DEGs) (red, padj < 0.05) between Gli1 or Ascl1-targeted ndNSCs (i) or dNSCs (j) when comparing only cells with shared pseudotime range. Venn diagrams indicate the overlap between DEGs found when comparing Gli1 or Ascl1-targeted ndNSCs (i) or dNSCs (j) using the full pseudotime range (grey circles) or the shared pseudotime range (green circles). Among the top 10 DEGs, bolded gene names highlight the DEGs found in both comparisons. k, UMAP visualization of RNA velocities calculated using scVelo. For detailed statistics, see Supplementary Table 5.3.

Extended Data Fig. 5 Stem cell markers associated with quiescence are differentially expressed between Gli1- and Ascl1-targeted NSCs.

a, Representative example of a Gli1- tdTom DG section (5 days post tamoxifen injection) stained with multiple antibodies using the 4i protocol. Visualization of 9 different cellular markers in addition to tdTomato. Single channels are shown. b, Representative images of a Gli1 and an Ascl1 DG section stained using 4i protocol, 5 days post tamoxifen injection. Visualization of six different cellular markers plus tdTomato. (Top) Prox1/blue, tdTom/red, SOX2/green, GFAP/light blue, Id4/magenta. (Middle) tdTom/red, Hopx/green, Mt3/magenta. (Bottom) single channels at higher magnification (regions in the white squares). c, Example of a Gli1-targeted R cell stained using the 4i protocol (5 days post tamoxifen injection). Visualization of 5 different R cell markers in addition to tdTomato and DAPI. Displayed are single channels and a merged picture. d, Percentage of cells that express different NSC and proliferation markers in Gli1- and Ascl1-targeted R cells (Gli1 n = 330 cells; Ascl1 n = 316 cells). e, Quantification of Sox2 (Gli1 = 5.24 ± 0.11 n = 330 cells; Ascl1 = 5.22 ± 0.14, n = 316 cells; Mann Whitney test: Mann-Whitney U = 51100; p = 0.661, two-tailed), Id4 (Gli1 = 2.02 ± 0.03, n = 317 cells; Ascl1 = 1.98 ± 0.03, n = 285 cells; Mann Whitney test: Mann-Whitney U = 44567; p = 0.776, two-tailed) and Ki67 (Gli1 = 3.78 ± 0.36, n = 32 cells; Ascl1 = 4.82 ± 0.28, n = 69 cells; Mann Whitney test: Mann-Whitney U = 760; p = *0.011, two-tailed) protein levels (fluorescence intensity of the cell/background) in Gli1- and Ascl1-targeted R cells. f, Quantification of Hopx protein levels (fluorescence intensity of the cell/background) in Gli1- and Ascl1- targeted R cells that are either positive or negative for Mt3 (Gli1 positive: 7.77 ± 0.20, n = 313 cells; Gli1 negative: 5.47 ± 0.5, n = 24 cells; Whitney test: Mann-Whitney U = 2394; **p = 0.003, two-tailed. Ascl1 positive: 6.46 ± 0.18, n = 284 cells; Ascl1 negative: 3.28 ± 0.32, n = 32 cells; Whitney test: Mann-Whitney U = 1651; ****p < 0.0001, two-tailed. Gli1 positive vs Ascl1 positive: Mann Whitney test: Mann-Whitney U = 35578; ****p < 0.0001, two-tailed. Gli1 negative vs Ascl1 negative: Mann Whitney test: Mann-Whitney U = 182; ***p = 0.0006, two-tailed). Values are shown as mean ± s.e.m. Bars in violin plots represent median and quartiles. Scale bars represent 400 μm (a), 100 μm (b) and 20 μm (c, high magnification and b). For detailed statistics, see Supplementary Table 5.4.

Supplementary information

Supplementary Information

Supplementary Fig. 1.

Reporting Summary

Supplementary Tables 1–5

DEGs, antibody specifications and statistics results.

Supplementary Video 1

Distribution of imaged Gli1- and Ascl1-targeted clones. Three-dimensional reconstruction of one DG from Gli1 and one DG from Ascl1 animals that were in vivo imaged for 2 months. Imaged clones are highlighted in green to provide an overview of the localization of imaged clones in the dorsal DG.

Supplementary Video 2

Long-term self-renewing Gli1-targeted R cell. Representative movie (corresponding to the lineage shown in Fig.1d,e) shows the long-term self-renewal capacity of a Gli1-targeted R cell (51 d; measured between first division and last appearance of the R cell). Note the radial morphology of the starting R cell illustrated by the display of a z-stack (each z-step is 5 µm). The first neurogenic wave starts at d7, with the R cell (white arrowhead) returning to a quiescence state until d39 when it reenters cell cycle and the second neurogenic phase is initiated. The neurons generated in the first (d32; dark blue circles) and second neurogenic wave (d61; light blue) are highlighted. Note the presence of the R cell after the first division (d7) until d54. The picture of time point d56 (last appearance of the R cell) is not shown due to motion artifacts (breathing) of the animal. Minor shifts in x and y direction between imaging sessions have been automatically corrected. Scale bar represents 20 µm.

Supplementary Video 3

Long-term self-renewing Gli1-targeted R cell. An example movie depicting the long-term persistence of a Gli1-targeted R cell during the imaging at d102 (corresponding to Fig. 1f). A z-stack at the first time point (d4) illustrates the radial morphology of the starting R cell. The R cell enters the cell cycle at d74 and is still present at the last time point imaged at d102 (white arrowhead; R cell persistence of 102 d). The R cell (red) and its progeny at d102, an NR cell (orange) and two neurons (blue) are highlighted by colored circles. Minor shifts in x and y direction between imaging sessions have been automatically corrected resulting in a cropped picture in some of the time points. Scale bar represents 20 µm.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Bottes, S., Jaeger, B.N., Pilz, GA. et al. Long-term self-renewing stem cells in the adult mouse hippocampus identified by intravital imaging. Nat Neurosci 24, 225–233 (2021). https://doi.org/10.1038/s41593-020-00759-4

Download citation

Further reading

Search

Quick links

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