Single-cell RNA-seq analysis of human CSF microglia and myeloid cells in neuroinflammation

Basic information
Sample
3

Technology
10X Genomics
Omics
scRNA-seq
Source
PBMCs

Dataset ID
32371549
Platform
Illumina HiSeq 4000, NovaSeq
Species
Human
Disease
RRMS,anti-MOG disorder
Age range
34 - 56
Update date
2020-05-05
Summary

Objective: To identify and characterize myeloid cell populations within the CSF of patients with MS and anti-myelin oligodendrocyte glycoprotein (MOG) disorder by high-resolution single-cell gene expression analysis. Methods: Single-cell RNA sequencing (scRNA-seq) was used to profile individual cells of CSF and blood from 2 subjects with relapsing-remitting MS (RRMS) and one with anti-MOG disorder. Publicly available scRNA-seq data from the blood and CSF of 2 subjects with HIV were also analyzed. An informatics pipeline was used to cluster cell populations by transcriptomic profiling. Based on gene expression by CSF myeloid cells, a flow cytometry panel was devised to examine myeloid cell populations from the CSF of 11 additional subjects, including individuals with RRMS, anti-MOG disorder, and control subjects without inflammatory demyelination. Results: Common myeloid populations were identified within the CSF of subjects with RRMS, anti-MOG disorder, and HIV. These included monocytes, conventional and plasmacytoid dendritic cells, and cells with a transcriptomic signature matching microglia. Microglia could be discriminated from other myeloid cell populations in the CSF by flow cytometry. Conclusions: High-resolution single-cell gene expression analysis clearly distinguishes distinct myeloid cell types present within the CSF of subjects with neuroinflammation. A population of microglia exists within the human CSF, which is detectable by surface protein expression. The function of these cells during immunity and disease requires further investigation.

Overall design

single cell made for 2 MS patients and 1 MOG patient (PBMC and CSF samples)

Contributors

Ekaterina Esaulova 1, Claudia Cantoni 1, Irina Shchukina 1, Konstantin Zaitsev 1, Robert C Bucelli 1, Gregory F Wu 2, Maxim N Artyomov 1, Anne H Cross 1, Brian T Edelson 2

Contact

bedelson@path.wustl.edu(Brian T Edelson )

snRNA-Seq
Sample nameSample titleDiseaseGenderAgeSourceTreatmentTechnologyPlatformOmicsSample IDDataset IDAction
No data available