Advances in human B cell phenotypic profiling

Denise A Kaminski, Chungwen Wei, Yu Qian, Alexander F Rosenberg, Ignacio Sanz, Denise A Kaminski, Chungwen Wei, Yu Qian, Alexander F Rosenberg, Ignacio Sanz

Abstract

To advance our understanding and treatment of disease, research immunologists have been called-upon to place more centralized emphasis on impactful human studies. Such endeavors will inevitably require large-scale study execution and data management regulation ("Big Biology"), necessitating standardized and reliable metrics of immune status and function. A well-known example setting this large-scale effort in-motion is identifying correlations between eventual disease outcome and T lymphocyte phenotype in large HIV-patient cohorts using multiparameter flow cytometry. However, infection, immunodeficiency, and autoimmunity are also characterized by correlative and functional contributions of B lymphocytes, which to-date have received much less attention in the human Big Biology enterprise. Here, we review progress in human B cell phenotyping, analysis, and bioinformatics tools that constitute valuable resources for the B cell research community to effectively join in this effort.

Keywords: B lymphocyte; autoimmunity; data clustering; data management; flow cytometry; human.

Figures

Figure 1
Figure 1
Human B cell subsets identified with an established memory B cell fluorescent reagent panel (see Wei et al., 2011). Schematized flow cytometry plot (gated on viable PBMC CD19+ B cells) indicates four core B cell subsets (gray ovals) defined by CD27 and IgD expression. SwMe, switched memory; DN, double-negative; NSM, non-switched memory. The naïve core subset can be further subdivided into transitional and mature-naïve B cells. Distinguishing T3 from mature-naïve requires a mitochondrial dye extrusion step not included in the memory B cell panel. The switched memory and CD27+/int memory-phenotype core subsets can be further evaluated for changes (thick red and green arrows) in the indicated markers known to be associated with B cell activation.
Figure 2
Figure 2
Event clusters identified by FLOCK analysis. FLOCK (Qian et al., 2010) version 1.0 was run unsupervised on human PBMC stained with the 12-color memory B cell reagent panel described in OMIP-003 (Wei et al., 2011) pre-gated on single, viable CD19+ lymphoid events. (A) Overlay of 25 populations, indicated in unique colors, identified in the sample displayed as two-dimensional plots. (B) Representative event clusters of the indicated Patterns based on CD27 versus IgD signals. Numbers below the plots indicate IDs of populations (see Table 3) with similar event distributions as displayed in the corresponding plot. (C) Population 19 displayed as all parameters analyzed by FLOCK. In (B,C), whiteevents on the gray background are the total CD19+ population, for reference. Characteristics of all 25 populations can be found in Table 3.

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