Strategies for Flow Cytometric Profiling of BCR IgH Isotypes: A Comparative Assessment of FcR Blocking Agents

To the Editor,

Incorporating B cell receptor (BCR) immunoglobulin heavy chain (IgH) isotype‐specific antibodies into flow cytometry panels allows for precise identification of class‐switched B cell populations, such as those expressing IgG1 to IgG4, IgA1 or IgA2, and IgE [1]. This approach supports a detailed analysis of B cell functionality in allergic [2, 3], infectious [4], and autoimmune diseases [5]. When analyzing heterogeneous cell populations, Fc receptor (FcR) blocking reagents are frequently used to minimize non‐specific antibody binding [6]. However, these reagents often contain human immunoglobulins that may act as decoy targets and interfere with BCR IgH detection. To our knowledge, no systematic evaluation has yet been conducted to determine how various FcR blocking reagents affect the accuracy of BCR IgH isotype detection.

In this study, we assessed five FcR blocking reagents for their compatibility with BCR IgH isotype staining in flow cytometry. These included normal mouse serum, human AB serum, and three commercial anti‐human FcR blockers. We also investigated whether including a washing step after blocker incubation could reduce interference and improve staining fidelity.

Cryopreserved peripheral blood mononuclear cells (PBMC) were isolated from six healthy donors (three male and three female) using density gradient centrifugation. After thawing, PBMCs were treated with each of the five FcR blockers: normal mouse serum (Reagent 1), three commercial blockers (Reagents 2 to 4), and human AB serum (Reagent 5) (Table S1). A non‐blocked condition served as the control. Each sample was divided into two conditions, one with a washing step after blocker incubation and one without. An 11‐color immunophenotyping panel including IgM, IgD, IgA1, IgA2, and IgG1 to IgG4 (Table S2) was used to characterize B‐cell subsets. Live B‐cells and subsets were gated based on fluorescence minus one (FMO) controls (Figure 1A, Figure S1A–F). One‐way ANOVA followed by Dunnett's post hoc test was used for statistical analysis. Full methodological details are provided in the Supporting Information.

FIGURE 1.

Frequencies of B cell subsets in PBMCs in the absence and presence of FcR blocking reagents, and their effect on the detection of non‐switched (IgM⁺IgD⁺) and class‐switched (IgM⁻IgD⁻) B cells. (A) Representative gating strategy for identifying IgM⁺IgD⁺, IgM⁻IgD⁻, IgA⁻, IgA1⁺, IgA2⁺, IgG1⁺, IgG2⁺, IgG3⁺, and IgG4⁺ B cell populations, based on CD19⁺ live cells in the non‐blocking condition. IgG subtypes were defined by excluding IgA⁺ cells from the IgM⁻IgD⁻ population. Values indicate percentages of cells from each gate, calculated relative to CD19⁺ cells for IgM⁺IgD⁺ and IgM⁻IgD⁻ populations, and relative to the IgM⁻IgD⁻ population for IgA1⁺, IgA2⁺, and IgG1–4⁺ subsets. (B) Cumulative data from six donors, showing the frequencies of IgM⁺IgD⁺ and IgM⁻IgD⁻ cells within the CD19⁺ population (left), and the frequencies of IgA1⁺, IgA2⁺, IgG1⁺, IgG2⁺, IgG3⁺, and IgG4⁺ cells among IgM⁻IgD⁻ B cells (right). Results are presented as mean ± standard deviation. Each color corresponds to a specific B cell subset shown in panels A and B. Squares represent male donors, and circles represent female donors. (C) Representative plots illustrating the effects of five FcR blocking reagents, with or without a washing step, on IgM⁺IgD⁺ and IgM⁻IgD⁻ B cell detection. Non‐blocked cells served as controls. Frequencies (%) were calculated based on the CD19⁺ population. (D, E) Summary data showing the effects of each FcR blocking reagent on the frequency of IgM⁺IgD⁺ cells, without (D) and with (E) a washing step, compared to non‐blocked controls. Squares represent male donors, and circles represent female donors. Statistical analysis was performed using one‐way ANOVA followed by Dunnett's post hoc test. Reagents: (1) Normal mouse serum, (2) Miltenyi FcR Blocking Reagent (human), (3) BioLegend Human TruStain FcX, (4) Thermo Fisher Anti‐Human Fc Receptor Binding Inhibitor, (5) Human AB serum, and NB = non‐blocked.

Under non‐blocking conditions, class‐switched (IgM⁻IgD⁻) and non‐switched (IgM⁺IgD⁺) B cells accounted for 20.4% ± 6.0% and 56.9% ± 12.0% of CD19⁺ cells, respectively. Among the class‐switched cells, IgG1⁺ cells (37.0% ± 6.9%) were the most abundant, followed by IgG2 (17.0% ± 7.5%), IgG3 (4.5% ± 1.8%), and IgG4 (1.5% ± 1.1%). IgA1⁺ B cells (24.4% ± 7.4%) were more frequent than IgA2⁺ B cells (7.0% ± 3.5%) (Figure 1B).

Reagents 1 through 4 did not significantly alter the detection of non‐switched B cells in both washed and unwashed conditions (Figure 1C–E). In contrast, Reagent 5, applied without washing, impaired the detection of these populations (Figure 1D). Reagent 1, with or without a wash step, had no significant effect on the detection of class‐switched B cells compared to the non‐blocking condition (Figure 2A–D). Reagents 2 to 4 had no observable impact on IgA1 or IgA2 detection, while Reagent 5 significantly reduced IgA1⁺ and IgA2⁺ B cell frequencies when applied without washing (Figure 2C,D). All blocking reagents except Reagent 1 reduced the detection of IgG1⁺ and IgG4⁺ cells (Figure 2B,C). Reagents 2, 4, and 5 also decreased IgG2 and IgG3 detection. Interestingly, Reagent 3 slightly increased IgG2⁺ cell frequency but did not affect IgG3 detection (Figure 2C). Washing the cells after using Reagents 2, 4, or 5 partially restored IgG subclass detection, while Reagent 3 fully restored detection. However, IgG3⁺ cells showed a shift into the IgG1⁺ gate in some conditions (Figure 2D). We compared the cell populations based on the sex factor and found no notable differences, except for the IgG2⁺ B cell subset. The frequency of IgG2⁺ B cells was consistently higher in female donors compared to male donors (Figure 2C,D), a finding that aligns with previously reported sex‐related differences in immunoglobulin isotype expression [7].

FIGURE 2.

Effect of FcR blocking reagents on the detection of class‐switched B cell subsets. (A, B) Representative plots showing IgA⁻, IgA1⁺, IgA2⁺ subsets (A) and IgG1⁺, IgG2⁺, IgG3⁺, and IgG4⁺ subsets (B) across five FcR blocking reagents, with and without washing. Non‐blocked samples were used as controls. Frequencies (%) indicate the proportions of these populations among IgM⁻IgD⁻ B cells. (C, D) Cumulative data illustrating the impact of the FcR blocking reagents on the detection of IgA and IgG subclasses, without (C) and with (D) a washing step, compared to the non‐blocking condition. Squares represent male donors, and circles represent female donors. Statistical comparisons were performed using one‐way ANOVA followed by Dunnett's test. Significance levels: *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Reagents: (1) Normal mouse serum, (2) Miltenyi FcR Blocking Reagent (human), (3) BioLegend Human TruStain FcX, (4) Thermo Fisher Anti‐Human Fc Receptor Binding Inhibitor, (5) Human AB serum, and NB = non‐blocked.

We also assessed the capacity of the FcR blocking reagents to prevent off‐target binding of PE‐conjugated isotype controls (mIgG1κ, mIgG2aκ, mIgG2bκ) to CD14⁺ monocytes (Figure S2). Only mIgG2aκ showed strong non‐specific binding in the absence of any blocker (Figure S2B–D). All tested FcR blocking reagents significantly reduced this non‐specific binding. However, introducing a wash step after blocker treatment (Figure S2E,F) increased background staining, suggesting that surface FcRs may have become re‐exposed after washing (Figure S2F).

FcR blocking reagents that use human serum IgG compromise the detection of BCR IgH isotypes, particularly IgG subclasses. This interference persists even when cells are washed prior to staining. Human AB serum showed the most pronounced negative effect, reducing IgH isotype signals regardless of washing. We recommend avoiding human‐derived FcR blocking reagents in experiments that include BCR IgH staining. When blocking is necessary, non‐human serum alternatives such as normal mouse serum may be preferable.

Author Contributions

Ozge Ardicli: conceptualization (supporting), formal analysis (supporting), methodology (supporting), resources (equal), visualization (equal), writing – original draft preparation (equal). Juan Felipe Lopez: conceptualization (supporting), formal analysis (supporting), methodology (supporting), resources (equal), visualization (equal), writing – review and editing (equal). Margot E. Starrenburg: conceptualization (supporting), methodology (supporting), writing – review and editing (equal). Laura Buergi: formal analysis (supporting), methodology (supporting), resources (equal). Tayfun K. Carli: supervision (supporting), methodology (supporting), writing – review and editing (equal). Cezmi A. Akdis: supervision (supporting), methodology (supporting), writing – review and editing (equal). Mübeccel Akdis: supervision (supporting), methodology (supporting), writing – review and editing (equal). Willem van de Veen: conceptualization (lead), formal analysis (lead), funding acquisition (lead), methodology (lead), resources (equal), supervision (lead), visualization (equal), writing – original draft preparation (equal), writing – review and editing (equal).

Conflicts of Interest

C.A.A. has received research grants from the Swiss National Science Foundation, European Union (EU CURE, EU Syn‐Air‐G), Novartis Research Institutes (Basel, Switzerland), Stanford University (Redwood City, Calif), Seed Health (Boston, USA) and SciBase (Stockholm, Sweden); is the Co‐Chair for EAACI Guidelines on Environmental Science in Allergic diseases and Asthma; is on the Advisory Boards of Sanofi/Regeneron (Bern, Switzerland, New York, USA), Stanford University Sean Parker Asthma Allergy Center (CA, USA), Novartis (Basel, Switzerland), Glaxo Smith Kline (Zurich, Switzerland), Bristol‐Myers Squibb (New York, USA), Seed Health (Boston, USA), and SciBase (Stockholm, Sweden); and is the Editor‐in‐Chief of Allergy. M.A. has received research grants from the Swiss National Science Foundation, Bern; research grant from Stanford University; Leading House for the Latin American Region, Seed Money Grant. She is the Scientific Advisory Board member of Stanford University Sean Parker Asthma Allergy Center, CA; Advisory Board member of LEO Foundation Skin Immunology Research Center, Copenhagen; and Scientific Co‐Chair of World Allergy Congress (WAC) Istanbul, 2022, Scientific Programme Committee Chair, EAACI. The other authors declare no conflicts of interest.

Supporting information

Data S1.

Figure S1. Gating strategy for CD19⁺ B cells and comparison of full panel staining with fluorescence‐minus‐one (FMO) controls. (A) Lymphocytes were identified based on forward scatter area (FSC‐A) and side scatter area (SSC‐A). Doublets were excluded using FSC and SSC height versus width parameters. Live CD3⁻CD14⁻CD16⁻CD19⁺ cells were gated. Frequencies were calculated relative to the preceding population. (B–F) Each panel compares full panel staining with corresponding FMO controls to establish gate boundaries. (B) CD19, CD3, CD14, CD16, and viability dye (Zombie Yellow); (C) IgD and IgM; (D) IgA and IgA2; (E) IgG1 (AF488 and Dylight 550), IgG2, and IgG3; (F) IgG4.

Figure S2. Non‐specific binding of mouse IgG2aκ to monocytes is blocked by all FcR blocking reagents. (A) Representative dot plots showing gating strategy for live, single CD14⁺ monocytes. (B–G) Histograms and mean fluorescence intensity (MFI) data for PE‐conjugated isotype controls, including mIgG1κ (B, E), mIgG2aκ (C, F), and mIgG2bκ (D, G), assessed in the presence of five FcR blocking reagents, without (B–D) and with (E–G) a washing step. Non‐blocked samples served as controls. The blue curve represents cells stained only with CD14 and viability dye, without isotype control. Other colors represent conditions for each FcR blocker. NB = non‐blocked.

Table S1. FcR blocking reagents.

Table S2. B cell immunophenotyping panel.

Table S3. Panel for isotype control staining on monocytes.

Ardicli O., Lopez J. F., Starrenburg M. E., et al., “Strategies for Flow Cytometric Profiling of BCR IgH Isotypes: A Comparative Assessment of FcR Blocking Agents,” Allergy 80, no. 10 (2025): 2898–2901, 10.1111/all.16624.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.