Abstract
Brain–immune cross-talk and neuroinflammation critically shape brain physiology in health and disease. A detailed understanding of the brain immune landscape is essential for developing new treatments for neurological disorders. Single-cell technologies offer an unbiased assessment of the heterogeneity, dynamics and functions of immune cells. Here we provide a protocol that outlines all the steps involved in performing single-cell multi-omic analysis of the brain immune compartment. This includes a step-by-step description on how to microdissect the border regions of the mouse brain, together with dissociation protocols tailored to each of these tissues. These combine a high yield with minimal dissociation-induced gene expression changes. Next, we outline the steps involved for high-dimensional flow cytometry and droplet-based single-cell RNA sequencing via the 10x Genomics platform, which can be combined with cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) and offers a higher throughput than plate-based methods. Importantly, we detail how to implement CITE-seq with large antibody panels to obtain unbiased protein-expression screening coupled to transcriptome analysis. Finally, we describe the main steps involved in the analysis and interpretation of the data. This optimized workflow allows for a detailed assessment of immune cell heterogeneity and activation in the whole brain or specific border regions, at RNA and protein level. The wet lab workflow can be completed by properly trained researchers (with basic proficiency in cell and molecular biology) and takes between 6 and 11 h, depending on the chosen procedures. The computational analysis requires a background in bioinformatics and programming in R.
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Data availability
The scRNA-seq data shown in Fig. 4a,b,e are deposited at GEO under GSE128855; Fig. 4f under GSE157480. The CITE-seq data shown in Fig. 5 are deposited at GEO under GSE163120. The gene–cell count matrices of all these datasets can also be downloaded at www.brainimmuneatlas.org. The CITE-seq data shown in Fig. 6 are deposited at GEO under GSE191075.
Code availability
The R codes that were used for scRNA-seq and CITE-seq analyses can be found at Github: https://github.com/Movahedilab/Mouse_brain_borders_NatureProtocols.
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Acknowledgements
This work was supported by Innoviris (Attract grant BB2B 2015−2), Fonds Wetenschappelijk Onderzoek (grant no. 1506316 N) to K.M., a VLAIO grant (no. ImmCyte HBC.2016.0889) to K.M. and JAVG. K.M. is a Collen-Franqui research professor. I.S. is supported by an FWO postdoctoral fellowship. H.V.H. is supported by an FWO predoctoral fellowship. We thank Y. Elkrim, G. van Isterdael, the VIB Flow Core and the VIB Nucleomics Core for technical assistance, VIB Tech Watch and the single-cell accelerator program for support regarding single-cell technologies.
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I.S., H.V.H., K.D.V. and K.M. developed and optimized the protocol with input and help from C.L.S., J.A.V.G., Y.S., M.G., N.V. I.S., H.V.H., K.D.V., J.B., M.V.P., A.R.P.A. and N.V. performed wet-lab work and acquired scRNA-seq and/or CITE-seq data. I.S., D.K., L.M. and Y.S. analyzed the data and/or generated analysis pipelines. I.S., H.V.H., D.K. and K.M. wrote the manuscript. K.M. conceptualized and directed the study.
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Key references using this protocol
Van Hove, H. et al. Nat. Neurosci. 22, 1021–1035 (2019): https://doi.org/10.1038/s41593-019-0393-4
Shemer, A. et al. Immunity 54, 1033–1049.E7 (2020): https://doi.org/10.1016/j.immuni.2020.09.018
Pombo Antunes, A. R. et al. Nat. Neurosci. 24, 595–610 (2021): https://doi.org/10.1038/s41593-020-00789-y
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Scheyltjens, I., Van Hove, H., De Vlaminck, K. et al. Single-cell RNA and protein profiling of immune cells from the mouse brain and its border tissues. Nat Protoc 17, 2354–2388 (2022). https://doi.org/10.1038/s41596-022-00716-4
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DOI: https://doi.org/10.1038/s41596-022-00716-4
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