We designed an experimental platform, utilizing single-cell transcriptomic and epigenomic profiling. We employed this system to interrogate single-cell data for subset- specific signatures.

Myeloid cells (MC) of the central nervous system (CNS) constitute a heterogeneous population that includes A) yolk sac-derived CNS microglia, B) bone marrow-derived resident MC and C) infiltrating bone marrow-derived MC. While bone marrow and yolk sac progenies differ in origin, their protein expression exhibit significant overlap. Current canonical myeloid markers, lack the specificity required for use as disease biomarkers or therapeutic targets.

We created chimeras in congenic animals by transplantation of bone marrow from CD45.1⁺ donors into sub-lethally irradiated CD45.2⁺ recipients. Following active EAE, CD11b⁺ MC were collected from CNS at the peak of the disease. Fluorescent-activated cell sorting (FACS) separated CD45.1⁺ MC from CD45.2⁺ MC. Each sample was analyzed simultaneously for single-cell gene expression (scRNA-seq) and epigenetic signatures (scATAC-seq) via the 10X Genomics Multiomic assay. We employed bioinformatics software (Seurat v4.0) for analysis and visualization of data profiling over 20,000 cells.

Bone marrow derived (CD45.1+) or microglial and CNS-resident (CD45.2+) MC were both present in the CNS tissue during acute EAE. Analyses of single-cell transcriptomic and ATAC-seq data, independently distinguished common clusters of MC derived entirely from the CD45.2+ cells. Unsupervised annotation, recognized these cells as microglia. CD45.1+ MC and microglia exhibited extensive gene expression overlap; however, differential gene expression analysis and logistic regression modeling yielded a signature set of genes within the microglia accurately distinguished microglia from bone-marrow- derived MC in independent datasets.

Single-cell data recapitulates the subtle differences in the otherwise comparable gene expression patterns among microglia and bone marrow-derived MC. These patterns shed light on the subset-specific biological roles and may present as superior substitutes for the suboptimal canonical myeloid markers.