Abstract
Alzheimer’s disease (AD) is a complex neurodegenerative disease, perturbing neuronal and non-neuronal cell populations. In this study, using single-cell transcriptomics, we mapped all non-immune, non-neuronal cell populations in wild-type and AD model (5xFAD) mouse brains. We identified an oligodendrocyte state that increased in association with brain pathology, which we termed disease-associated oligodendrocytes (DOLs). In a murine model of amyloidosis, DOLs appear long after plaque accumulation, and amyloid-beta (Aβ) alone was not sufficient to induce the DOL signature in vitro. DOLs could be identified in a mouse model of tauopathy and in other murine neurodegenerative and autoimmune inflammatory conditions, suggesting a common response to severe pathological conditions. Using quantitative spatial analysis of mouse and postmortem human brain tissues, we found that oligodendrocytes expressing a key DOL marker (SERPINA3N/SERPINA3 accordingly) are present in the cortex in areas of brain damage and are enriched near Aβ plaques. In postmortem human brain tissue, the expression level of this marker correlated with cognitive decline. Altogether, this study uncovers a shared signature of oligodendrocytes in central nervous system pathologies.
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Data availability
Raw and processed mouse sequencing data that support the findings of this study have been deposited in the Gene Expression Omnibus database under accession number GSE202297.
Code availability
All the code is available on GitHub at: https://github.com/PierreBSC/DOL_project
Change history
31 January 2023
A Correction to this paper has been published: https://doi.org/10.1038/s41593-023-01266-y
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Acknowledgements
The research of I.A. is supported by the Seed Networks for the Human Cell Atlas of the Chan Zuckerberg Initiative, the Thompson Family Foundation Alzheimer’s Research Fund and the Adelis Foundation. I.A. is an Eden and Steven Romick Professorial Chair, supported by the HHMI International Scholar Award, a European Research Council Consolidator Grant (724471-HemTree2.0), an MRA Established Investigator Award (509044), the DFG (SFB/TRR167), the Ernest and Bonnie Beutler Research Program for Excellence in Genomic Medicine, the Helen and Martin Kimmel awards for innovative investigation and the SCA award of the Wolfson Foundation and Family Charitable Trust. Research in the M.S. laboratory is supported by Advanced European Research Council grants (741744); Israel Science Foundation (ISF) research grant 991/16; and ISF-Legacy Heritage Bio-Medical Science Partnership research grant 1354/15. We would like to thank the Adelis and Thompson Foundations for their generous support of our AD research. This work is also supported by awards K01-AG056673 and R56-066782–01 from the National Institute on Aging of the National Institutes of Health, R01-GM131399 (Q.M.) from the National Institute of General Medical Sciences, AARF-17–505009 (H.F.) from the Alzheimer’s Association and W81XWH1910309 (H.F.) from the US Department of Defense.
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Contributions
M.S., I.A. and M.K. conceived the study. M.K and P.B. designed the experiments. M.K. conducted the animal work, isolated cells and generated single-cell sequencing libraries. M.K. and S.H. conducted the imaging experiments. M.K. and S.H. conducted the in vitro experiments, with assistance from R.H. P.B. conducted the data analysis for the sequencing, re-analysis of the published datasets and spatial analysis of the mouse LPS treatment Visium data. P.B. developed a new algorithmic approach for image analysis and analyzed imaging experiments. Y.C., S.C, Q.M. and H.F. conducted the Visium spatial transcriptomics on human brain samples and the data analysis. B.S. and B.B. provided the computational resources for analysis. M.K., M.S., P.B. and I.A. wrote the paper, with input from all the other authors.
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M.S. serves as a consultant of Immunobrain Checkpoint Ltd.
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Extended data
Extended Data Fig. 1 Quality control of CD45− libraries described in Fig. 1.
Extended data Fig. 1 associated to Fig. 1. (a) Distribution of total cellular unique molecular identifiers (UMI). Dashed line marks the threshold for analysis. (b) Distribution of total gene UMIs. Dashed line marks the threshold for analysis. (c) Distribution of the proportion of mitochondrial genes. Dashed line marks the threshold for analysis. (d) Comparison of the total cellular UMI distribution in cells from 5xFAD and WT mice (left panel) and the proportion of mitochondrial genes in cells from 5xAD and WT mice (right panel). P values were computed using a Kruskal-Wallis test. The box bounds the IQR. Line, median. Whiskers extend to a maximum of 1.5*IQR beyond the box. n = 18 independent mice (9 5xFAD, 9 WT) (e) Violin plot of known marker genes expression across the different cell clusters. (f) Comparison of the main cell-type proportions between 5xAD and WT mice.
Extended Data Fig. 2 Quality control of GalC+ libraries described in Fig. 2.
Extended data Fig. 2 associated to Fig. 2. (a) Gating strategy used to enrich for oligodendrocytes. (b) Proportion of oligodendrocytes isolated in each sequenced plate. Large bars correspond to the median and small bars to IQR. n = 48 384-well plates (c) Number of oligodendrocytes sequenced for each 5xAD and WT mice (left panel) and across ages (right panel). Large bars correspond to the median and small bars to IQR. n = 33 independent mice (17 5xFAD, 16 WT) (d) Proportion of cluster 14 in WT and 5xFAD mice across ages. Large bars correspond to the median and small bars to IQR. n = 33 independent mice (across ages: 6–8 m; n = 4 5xFAD, 4 WT, 10–11 m; n = 6 5xFAD, 5 WT, 15 m; n = 3 5xFAD, 3 WT, 24 m; n = 4 5xFAD, 4 WT) (e) Volcano plot corresponding to the differential expression analysis between DOL-like and the rest of oligodendrocytes as identified by Zhou et al.11. DOL genes are colored in orange. (f) Proportion of DOL-like among oligodendrocytes between 5xFAD and WT mice in the data by Zhou et al.11. P-value was computed using the Kruskal-Wallis test.
Extended Data Fig. 3 Cell type annotation of dataset described in Fig. 3 and culture quality control.
Extended data Fig. 3 associated to Fig. 3. (a) Spearman correlation between the mean transcriptomic profiles of the cell clusters identified in the dataset from Lee et al. (b) Violin plot of known marker genes across the different cell clusters. (c) Violin plot of known DAM marker gene expression across the different microglia clusters after refined clustering. (d) Representative bright-field microscopy image of the primary oligodendrocyte culture; scale bar corresponds to 50 μm. Representative results from 12 independent experiments.
Extended Data Fig. 4 GSEA and quality control of datasets described in Fig. 4.
Extended data Fig. 4 associated to Fig. 4. (a) GSEA analysis plot corresponding to the acute EAE dataset. (b) GSEA analysis plot corresponding to the multiphasic EAE dataset. (c) GSEA analysis plot corresponding to the aging SVZ dataset. (d) score of topic number 8, corresponding to DOL-like signature, in LPS-stimulated and control samples. n = 6 independent samples (3 LPS-stimulated, 3 control). Thick line corresponds to the median, the bottom and upper limits of the box to the first and third quartile, respectively. The lower and upper whiskers correspond to the lowest and highest values respectively within the range of the first (third) quartile minus (plus) 1.5 times the Interquartile range. (e) GSEA analysis plot of the DOL signature in topic 8. (f) Serpina3n expression (transcripts per thousand) in LPS-treated and control mice. n = 6 independent samples (3 LPS-stimulated, 3 control). p-value was computed by performing a Gene Set Enrichment Analysis as described by Subramanian et al56. Thick line corresponds to the median, the bottom and upper limits of the box to the first and third quartile, respectively. The lower and upper whiskers correspond to the lowest and highest values respectively within the range of the first (third) quartile minus (plus) 1.5 times the Interquartile range. (g) Intensity of the oligodendrocyte signature across the sections of the three LPS treated mice.
Extended Data Fig. 5 Quality control of image analysis described in Fig. 5.
Extended data Fig. 5 associated to Fig. 5. (a) Separated channels corresponding to the 5xFAD brain sample in Fig. 5a; scale bar corresponds to 20 μm. (b) Distribution of cell size across mice samples. The box bounds the IQR. Line, median. Whiskers extend to a maximum of 1.5*IQR beyond the box. n = 6 independent samples (4 5xFAD, 2 WT). (c) Distribution of OLIG2 intensity across mouse samples. The box bounds the IQR. Line, median. Whiskers extend to a maximum of 1.5*IQR beyond the box. n = 6 independent samples (4 5xFAD, 2 WT). (d) Distribution of OLIG2 intensity and estimated threshold (vertical red line). (e) Proportion of OLIG2+ cells across mouse samples. (f) Number of plaques in 5xFAD (n = 4) and WT (n = 2) mice. (g) Distribution of SERPINA3N intensity and the estimated threshold (vertical red line). (h) The 15 most contributing genes to the macrophage signature. (i) The 15 most contributing genes to the inflammatory signature. (j) Separated channels corresponding to the postmortem AD brain sample in Fig. 5i; scale bar corresponds to 50 μm. (k) Distribution of cell size across human samples. The box bounds the IQR. Line, median. Whiskers extend to a maximum of 1.5*IQR beyond the box. n = 16 independent samples (8 AD, 8 NDC). (l) Distribution of SERPINA3 intensity and the estimated threshold (vertical red line) for the two different batches of samples.
Supplementary information
Supplementary Table 1
Details of mice used in the study
Supplementary table 2
DEGs in 5xFAD compared to WT, according to different cell types. P values were computed using a binomial regression with complementary log–log link function (Methods)
Supplementary table 3
Details of postmortem AD patients brain samples used in the study
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Kenigsbuch, M., Bost, P., Halevi, S. et al. A shared disease-associated oligodendrocyte signature among multiple CNS pathologies. Nat Neurosci 25, 876–886 (2022). https://doi.org/10.1038/s41593-022-01104-7
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DOI: https://doi.org/10.1038/s41593-022-01104-7
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