Multiplexed Fc array for evaluation of antigen-specific antibody effector profiles

Abstract

Antibodies are widely considered to be a frequent primary and often mechanistic correlate of protection of approved vaccines; thus evaluating the antibody response is of critical importance in attempting to understand and predict the efficacy of novel vaccine candidates. Historically, antibody responses have been analyzed by determining the titer of the humoral response using measurements such as an ELISA, neutralization, or agglutination assays. In the simplest case, sufficiently high titers of antibody against vaccine antigen(s) are sufficient to predict protection. However, antibody titer provides only a partial measure of antibody function, which is dependent on both the variable region (Fv) to bind the antigen target, and the constant region (Fc) to elicit an effector response from the innate arm of the immune system. In the case of some diseases, such as HIV, for which an effective vaccine has proven elusive, antibody effector function has been shown to be an important driver of monoclonal antibody therapy outcomes, of viral control in infected patients, and of vaccine-mediated protection in preclinical and clinical studies. We sought to establish a platform for the evaluation of the Fc domain characteristics of antigen-specific antibodies present in polyclonal samples in order to better develop insights into Fc receptor-mediated antibody effector activity, more fully understand how antibody responses may differ in association with disease progression and between subject groups, and differentiate protective from non-protective responses. To this end we have developed a high throughput biophysical platform capable of simultaneously evaluating many dimensions of the antibody effector response.

Keywords: ADCC; Antibody; Effector function; IgG; Phagocytosis; Vaccines.

Fig. 1

Fc Array Assay Schematic. A. HIV (or other) antigens are conjugated to fluorescently-coded magnetic beads, incubated with serum or other polyclonal Ig samples, capturing antibodies specific to each antigen of interest prior to characterization with a panel of Fc-specific detection reagents such as FcγRs. B. Median Fluorescence Intensity (MFI) data is collected on the array reader for each specificity and subject. C. Output data from multiple detection reagents are combined to give a profile of the humoral response across features and subjects. The combined data can be used as the input features for computational analysis including grouping of features (D) and predictions of functional assays (E).

Fig. 2

Comparison with gold standard FcR affinity characterization by SPR. Comparison of previously determined ELISA/SPR binding affinities (Moldt et al., 2011) of a panel of mAb Fc mutants against Fc Array MFI. A) Anti-huIgG-PE detection of Fc variants bound to gp120-conjugated beads. B) FcγRIII detection of Fc variants bound to gp120 beads. C-E) Correlations between ELISA and Fc Array (C), SPR and Fc Array (D), and ELISA and SPR (E) for the panel of Fc mutants.

Fig. 3

Differentiation of IgG subclasses and an aglycosylated mutant via FcγR detection. A) Titration curves of subclass switched and aglycosylated (N297Q, or NQ) VRC01 Abs against HIV envelope beads detected with anti-huIgG-PE to quantify the level of mAb binding to each envelope variant, or detected with FcγRIIA R131 or FcγRIIIA V158 to quantify the ability of bound mAb to interact with these innate immune receptors. B) Calculated half-maximal binding concentration of each VRC01 variant to each antigen-conjugated bead, for each Fc detection reagent shown in (A). Curves that could not be reliably fit were plotted with values at the top of each scale.

Fig. 4

IgG glycosylation state differences captured by lectin detection reagents. A) Signal to noise ratios of lectin detection reagents for antibody samples from HIV + subjects (N = 11) against a technical negative (blank) on anti-huIgG and gp120 YU2 conjugated beads. Shaded region denotes values with a signal:noise ratio of < 2. B) Signal to noise ratios of AAL lectin detection for HIV positive and negative subjects (N = 3) on gp120 CN54 beads with and without prior PNGase treatment. Shaded region denotes values with a signal:noise ratio of < 2. C) Overview of PNGase treatment of conjugated beads. Signal of HIVIG compared to a technical negative (PBS) sample against beads conjugated with the named antigens before and after PNGase treatment and detected with tetramerized lectin detection reagents. D–F) Observed signal intensities (MFI) for a set of twelve subject samples with similar responses against gp120 CN54 when detected with total anti-huIgG-PE (D) but differing response magnitude when assayed with the fucose-specific lectin detection reagent LCA (E), and the sialic acid-sensitive lectin SNA (F). G) Correlation between signals (MFI) from fucose-specific lectin detection reagents (AAL and LCA) on anti-huIgG beads and the prevalence of fucosylated glycoforms from total serum IgG for a set of 10 subject samples.

Fig. 5

Specificity of rhesus antigens (A) and detection reagents (B) for NHP samples. A) Reponses of SIV vaccinated (+, black) and sham (−, red) macaques against a panel of SIV antigens using the anti-rhesus IgG-PE detection reagent. Bar and whiskers denote the median and interquartile ranges for each group. B) Responses of the same SIV vaccinated (+) and sham (−) macaques against a single antigen (SIVmac239 gp120) detected with nine different human (hu) and rhesus (rh) derived Fc-binding detection reagents in addition to the anti-rhesus IgG-PE antibody.

Fig. 6

Similarities and differences among Fv-specificity and Fc characteristics across a cohort of HIV + human donors. A heatmap and dendogram of data centered to the mean and scaled by standard deviation for each feature showing the relationship of each of the Fc Array features (antigen-detection reagent pairs as indicated in color bars) across a cohort of HIV-infected subjects. Hierarchical clustering has grouped features and subjects by similarity. Missing data points are indicated in black.

Fig. 7

Principal Component Analysis identifies shared Fc characteristics as differentiating among HIV infected subjects. A principal component (PC) biplot indicating the magnitude and direction that each Fc Array feature contributed to the two lead PCs. Features are color coded by detection reagents and indicated by dots labeled with “detection reagent.antigen” combinations. Groupings were manually drawn to showcase Fc-dependent feature sets.