Immunophenotyping of putative human B1 B cells in healthy controls and common variable immunodeficiency (CVID) patients.

B1 B cells represent a unique subset of B lymphocytes distinct from conventional B2 B cells, and are important in the production of natural antibodies. A potential human homologue of murine B1 cells was defined recently as a CD20(+) CD27(+) CD43(+) cell. Common variable immunodeficiency (CVID) is a group of heterogeneous conditions linked by symptomatic primary antibody failure. In this preliminary report, we examined the potential clinical utility of introducing CD20(+) CD27(+) CD43(+) B1 cell immunophenotyping as a routine assay in a diagnostic clinical laboratory. Using a whole blood assay, putative B1 B cells in healthy controls and in CVID patients were measured. Peripheral blood from 33 healthy donors and 16 CVID patients were stained with relevant monoclonal antibodies and underwent flow cytometric evaluation. We established a rapid, whole blood flow cytometric assay to investigate putative human B1 B cells. Examination of CD20(+) CD27(+) CD43(+) cells is complicated by CD3(+) CD27(+) CD43(hi) T cell contamination, even when using stringent CD20 gating. These can be excluded by gating on CD27(+) CD43(lo-int) B cells. Although proportions of CD20(+)CD27(+)CD43(lo­int) cells within B cells in CVID patients were decreased by 50% compared to controls (P < 0·01), this was not significant when measured as a percentage of all CD27(+) B cells (P = 0·78) [corrected]. Immunophenotypic overlap of this subset with other innate-like B cells described recently in humans is limited. We have shown that putative B1 B cell immunophenotyping can be performed rapidly and reliably using whole blood. CD20(+) CD27(+) CD43(lo-int) cells may represent a distinct B1 cell subset within CD27(+) B cells. CVID patients were not significantly different from healthy controls when existing CD27(+) B cell deficiencies were taken into account.

Cross-tissue immune cell analysis reveals tissue-specific features in humans.

Despite their crucial role in health and disease, our knowledge of immune cells within human tissues remains limited. We surveyed the immune compartment of 16 tissues from 12 adult donors by single-cell RNA sequencing and VDJ sequencing generating a dataset of ~360,000 cells. To systematically resolve immune cell heterogeneity across tissues, we developed CellTypist, a machine learning tool for rapid and precise cell type annotation. Using this approach, combined with detailed curation, we determined the tissue distribution of finely phenotyped immune cell types, revealing hitherto unappreciated tissue-specific features and clonal architecture of T and B cells. Our multitissue approach lays the foundation for identifying highly resolved immune cell types by leveraging a common reference dataset, tissue-integrated expression analysis, and antigen receptor sequencing.