A method to unravel complexity in human peripheral blood B-cell subsets through multiomic cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) analyses.

Classifying heterogeneous human B cells into discrete subsets based on surface phenotype alone remains a major challenge. We discovered a mouse splenic IgM+IgDlow/- B-cell subset (BDL) that induces proliferation of CD4+Foxp3+ T regulatory cells, making them a therapeutic target for autoimmunity. Because they are rare and lack sufficient cell surface markers, a multiomics strategy is required to identify and track them in humans. The lack of correlation between mRNA expression levels and cell surface expression is a drawback to a transcriptome-only single-cell RNA sequencing (scRNA-seq) approach because "novel" cell populations identified by surface protein transcripts may prove impossible to validate. To that end, a method was developed using human peripheral blood (PB) IgM+IgDlow/- B cells as a surrogate. A flow cytometry gating scheme (CD27 vs IgD and CD24 vs CD38) capturing all major human PB B-cell subsets was utilized. CD19+IgM+IgDlow/- PB B cells were tagged with the 4 markers using cellular indexing of transcriptomes and epitopes by sequencing. Biaxial plots similar to flow cytometry were used to identify naïve, immature, and memory B cells, and then confirmed with scRNA-seq. These studies using a multiomic workflow allowed the identification of IgM+IgDlow/- B-cell subsets by cell surface expression that could subsequently be analyzed for unique transcriptional profiles.