Single-Cell Transcriptomic Analyses Define Distinct Peripheral B Cell Subsets and Discrete Development Pathways

Abstract

Separation of B cells into different subsets has been useful to understand their different functions in various immune scenarios. In some instances, the subsets defined by phenotypic FACS separation are relatively homogeneous and so establishing the functions associated with them is straightforward. Other subsets, such as the “Double negative” (DN, CD19+CD27-IgD-) population, are more complex with reports of differing functionality which could indicate a heterogeneous population. Recent advances in single-cell techniques enable an alternative route to characterize cells based on their transcriptome. To maximize immunological insight, we need to match prior data from phenotype-based studies with the finer granularity of the single-cell transcriptomic signatures. We also need to be able to define meaningful B cell subsets from single cell analyses performed on PBMCs, where the relative paucity of a B cell signature means that defining B cell subsets within the whole is challenging. Here we provide a reference single-cell dataset based on phenotypically sorted B cells and an unbiased procedure to better classify functional B cell subsets in the peripheral blood, particularly useful in establishing a baseline cellular landscape and in extracting significant changes with respect to this baseline from single-cell datasets. We find 10 different clusters of B cells and applied a novel, geometry-inspired, method to RNA velocity estimates in order to evaluate the dynamic transitions between B cell clusters. This indicated the presence of two main developmental branches of memory B cells. A T-independent branch that involves IgM memory cells and two DN subpopulations, culminating in a population thought to be associated with Age related B cells and the extrafollicular response. The other, T-dependent, branch involves a third DN cluster which appears to be a precursor of classical memory cells. In addition, we identify a novel DN4 population, which is IgE rich and closely linked to the classical/precursor memory branch suggesting an IgE specific T-dependent cell population.

Severity of SARS-CoV-2 infection is linked to double-negative (CD27− IgD−) B cell subset numbers

“…In 2007, it was described the expansion of an unknown B cell subset characterized by the absence of both IgD and CD27 (double-negative, DN) in systemic lupus erythematosus (SLE) patients, thus being postulated that they could represent a novel memory population [ 4 ]. Additional heterogeneity within the DN population has been recently established, where these cells comprise four major subsets: DN1 to DN4 B cells, based on their relative expression of CD21 and CD11c [ 3 , 5 , 6 ]. Although not clear yet, it has been suggested that DN1 may represent early activated memory cells, whereas DN2 cells would embody primed antibody-secreting cells (ASC) precursors derived from newly activated naïve cells [ 7 ].…”

Clinical implementation of single-cell RNA sequencing using liver fine needle aspirate tissue sampling and centralized processing captures compartment specific immuno-diversity

“…Furthermore, among the naïve subset, we further identified a subgroup of TCL6 transitional B cells (Cluster 4) by their expression of PCDH9, SOX4, and TCL6 [61][62][63] . Cluster 2, CD69 naïve B cells, were defined by elevated expression of the NR4A nuclear receptors (i.e.…”

“…FCRL5+ atypical memory B cells also overexpressed SIGLEC6, which is considered an exhaustion marker for B cells 69 . The remaining population of memory B cells, cluster 1, were defined as CD27+ classical memory B cells based on their expression of CD27, AHNAK, and IGHG1 (Suppl Fig 5b,c) 61 .…”

SARS-CoV-2 spike-specific memory B cells express markers of durable immunity after non-severe COVID-19 but not after severe disease

“…For example, several subsets of double negative (DN; CD27 -IgD -) B cells have been defined in recent years (21,22). Type 1 double negative cells (DN1 cells), defined as DN cells that express CXCR5 or CD21 and lack CD11c and FcRL5, are transcriptionally similar to class-switched memory B cells and seem to be part of a functional B cell response (21,23). On the other hand, type 2 DN cells (DN2 cells), defined as CD11c + /FcRL5 + and CXCR5 -/CD21 -DN cells, are thought to arise from the activation of naïve B cells outside of the B cell follicle in the lymph node.…”

“…On the other hand, type 2 DN cells (DN2 cells), defined as CD11c + /FcRL5 + and CXCR5 -/CD21 -DN cells, are thought to arise from the activation of naïve B cells outside of the B cell follicle in the lymph node. Type 3 DN cells (DN3 cells), defined as CD11c -/FcRL5and CXCR5 -/CD21 -DN cells, have also been associated with this extrafollicular response and may be DN2 cell precursors (22,23). DN2 cells are more abundant in patients with autoimmune disorders, such as systemic lupus erythematosus, and are thought to differentiate into auto-antibody-secreting cells.…”