Cutting-edge assessment techniques for B cell immune memory: an overview

Figures & data

Figure 1. Development of human B cells.

Table 1. B cells subpopulations based on their CD markers expression.

B cell subpopulation	CD markers	Location
B-1 cells	CD5, CD11b	Mostly in peripheral blood
B-2 cells	CD19, CD20, CD21, CD22, CD23, CD24	Peripheral blood
Naive B cells	CD19, CD20, CD21, CD22, CD24, IgD, IgM	Peripheral blood, bone marrow
Transitional B cells	CD19, CD20, CD21, CD24, CD38, IgD	Bone marrow, spleen, lymph nodes
Memory B cells
(A) NCSMB cells	CD19, CD20, CD21, CD27, CD24, IgM	Peripheral blood, bone marrow
(B) CSMB cells	CD19, CD20, CD21, CD27, CD24, IgG	Peripheral blood, bone marrow
Marginal zone B cells	CD19, CD21, CD23, CD35	Peripheral blood, spleen
Follicular B cells	CD19, CD20, CD21, CD23, CD35	Peripheral blood, lymph nodes
Germinal center B cells	CD19, CD20, CD23, CD38, CD77	Germinal centers (secondary lymphoid organs)
Plasmablasts	CD19, CD20, CD27, CD38	Peripheral Blood
Plasma cells	CD19, CD38	Bone marrow
Regulatory B cells (Bregs)	CD19, CD24, CD38, CD1d, IL-10, TGF-β	Peripheral blood, lymph nodes, spleen

Table 2. Summary of advantages and disadvantages of techniques for analysis of B-cell subpopulations.

Method	Advantages	Disadvantages
ELISpot	- Highly sensitive - Single-cell resolution - Quantitative data	- Limited multiplexing - Subjectivity in spot counting - Limited spatial information - Cell viability requirement
FluoroSpot	- Multiplexing capability - Sensitivity and specificity - Single-cell resolution - Quantitative data	- Cost - Complex data analysis - Spot overlapping - Subjectivity in spot counting - Limited spatial information
Flow cytometry for B cell subpopulations	- High throughput - Multi-parameter analysis - Cell phenotype and function - Identification of rare cell subsets - Sorting capabilities—dynamic analysis - Biomarker discovery	- Complexity of instrumentation - Cost and maintenance - Data analysis complexity
MFC with tetramers for specific B cells	- High specificity - Quantitative analysis - Multiparametric analysis - Identification of rare specific B cell populations - Dynamic analysis - Sorting capabilities—compatibility with functional assays	- Tetramer availability - Specificity and affinity of tetramers - Complexity of instrumentation and analysis - Cost and resource intensiveness - Cell viability requirement - Data analysis complexity
Single-cell sequencing	- Provides transcriptomic information at single-cell level - Allows for unbiased discovery of cell populations and states - Enables the study of cellular heterogeneity - Provides information on cell–cell interactions and signaling pathways	- Technically complex and resource-intensive - Requires specialized bioinformatics expertise - Limited sensitivity for low-abundance transcripts - May require a large number of cells for certain protocols