PlateDesigner: a web-based application for the design of microplate experiments

Utility of epitope-specific IgE, IgG4, and IgG1 antibodies for the diagnosis of wheat allergy

BACKGROUND

The bead-based epitope assay has been used to identify epitope-specific (es) antibodies and successfully used to diagnose clinical allergy to milk, egg, and peanut.

OBJECTIVE

We sought to identify es-IgE, es-IgG4, and es-IgG1 of wheat proteins and determine the optimal peptides to differentiate wheat-allergic from wheat-tolerant using the bead-based epitope assay.

METHODS

Children and adolescents who underwent an oral food challenge to confirm their wheat allergy status were enrolled. Seventy-nine peptides from α-/β-gliadin, γ-gliadin, ω-5-gliadin, and high- and low-molecular-weight glutenin were commercially synthesized and coupled to LumAvidin beads (Luminex Corporation, Austin, Tex). Machine learning methods were used to identify diagnostic epitopes, and performance was evaluated using the DeLong test.

RESULTS

The analysis included 122 children (83 wheat-allergic and 39 wheat-tolerant; 57.4% male). Machine learning coupled with simulations identified wheat es-IgE, but not es-IgG4 or es-IgG1, to be the most informative for diagnosing wheat allergy. Higher es-IgE binding intensity correlated with the severity of allergy phenotypes, with wheat anaphylaxis exhibiting the highest es-IgE binding intensity. In contrast, wheat-dependent exercise-induced anaphylaxis showed lower es-IgG1 binding intensity than did all the other groups. A set of 4 informative epitopes from ω-5-gliadin and γ-gliadin were the best predictors of wheat allergy, with an area under the curve of 0.908 (sensitivity, 83.4%; specificity, 88.4%), higher than the performance exhibited by wheat-specific IgE (area under the curve = 0.646; P < .001). The predictive ability of our model was confirmed in an external cohort of 71 patients (29 allergic, 42 nonallergic), with an area under the curve of 0.908 (sensitivity, 75.9%; specificity, 90.5%).

CONCLUSIONS

The wheat bead-based epitope assay demonstrated greater diagnostic accuracy compared with existing specific IgE tests for wheat allergy.

Injectiondesign: web service of plate design with optimized stratified block randomization for modern GC/LC-MS-based sample preparation

BACKGROUND

Plate design is a necessary and time-consuming operation for GC/LC-MS-based sample preparation. The implementation of the inter-batch balancing algorithm and the intra-batch randomization algorithm can have a significant impact on the final results. For researchers without programming skills, a stable and efficient online service for plate design is necessary.

RESULTS

Here we describe InjectionDesign, a free online plate design service focused on GC/LC-MS-based multi-omics experiment design. It offers the ability to separate the position design from the sequence design, making the output more compatible with the requirements of a modern mass spectrometer-based laboratory. In addition, it has implemented an optimized block randomization algorithm, which can be better applied to sample stratification with block randomization for an unbalanced distribution. It is easy to use, with built-in support for common instrument models and quick export to a worksheet.

CONCLUSIONS

InjectionDesign is an open-source project based on Java. Researchers can get the source code for the project from Github: https://github.com/CSi-Studio/InjectionDesign . A free web service is also provided: http://www.injection.design .

Predicting probability of tolerating discrete amounts of peanut protein in allergic children using epitope-specific IgE antibody profiling

BACKGROUND

IgE-epitope profiling can accurately diagnose clinical peanut allergy.

OBJECTIVE

We sought to determine whether sequential (linear) epitope-specific IgE (ses-IgE) profiling can provide probabilities of tolerating discrete doses of peanut protein in allergic subjects undergoing double-blind, placebo-controlled food challenges utilizing PRACTALL dosing.

METHODS

Sixty four ses-IgE antibodies were quantified in blood samples using a bead-based epitope assay. A pair of ses-IgEs that predicts Cumulative Tolerated Dose (CTD) was determined using regression in 75 subjects from the discovery cohort. This epitope-based predictor was validated on 331 subjects from five independent cohorts (ages 4-25 years). Subjects were grouped based on their predicted values and probabilities of reactions at each CTD threshold were calculated.

RESULTS

In discovery, an algorithm using two ses-IgE antibodies was correlated with CTDs (rho = 0.61, p < .05); this correlation was 0.51 (p < .05) in validation. Using the ses-IgE-based predictor, subjects were assigned into "high," "moderate," or "low" dose-reactivity groups. On average, subjects in the "high" group were four times more likely to tolerate a specific dose, compared with the "low" group. For example, predicted probabilities of tolerating 4, 14, 44, and 144 or 444 mg in the "low" group were 92%, 77%, 53%, 29%, and 10% compared with 98%, 95%, 94%, 88%, and 73% in the "high" group.

CONCLUSIONS

Accurate predictions of food challenge thresholds are complex due to factors including limited responder sample sizes at each dose and variations in study-specific challenge protocols. Despite these limitations, an epitope-based predictor was able to accurately identify CTDs and may provide a useful surrogate for peanut challenges.

Accurate and reproducible diagnosis of peanut allergy using epitope mapping

BACKGROUND

Accurate diagnosis of peanut allergy is a significant clinical challenge. Here, a novel diagnostic blood test using the peanut bead-based epitope assay ("peanut BBEA") was developed utilizing the LEAP cohort and then validated using two independent cohorts.

METHODS

The development of the peanut BBEA diagnostic test followed the National Academy of Medicine's established guidelines with discovery performed on 133 subjects from the non-interventional arm of the LEAP trial and an independent validation performed on 82 subjects from the CoFAR2 and 84 subjects from the POISED study. All samples were analyzed using the peanut BBEA methodology, which measures levels of IgE to two Ara h 2 sequential (linear) epitopes and compares their combination to a threshold pre-specified in the model development phase. When a patient has an inconclusive outcome by skin prick testing (or sIgE), IgE antibody levels to this combination of two epitopes can distinguish whether the patient is "Allergic" or "Not Allergic." Diagnoses of peanut allergy in all subjects were confirmed by double-blind placebo-controlled food challenge and subjects' ages were 7-55 years.

RESULTS

In the validation using CoFAR2 and POISED cohorts, the peanut BBEA diagnostic test correctly diagnosed 93% of the subjects, with a sensitivity of 92%, specificity of 94%, a positive predictive value of 91%, and negative predictive value of 95%.

CONCLUSIONS

In validation of the peanut BBEA diagnostic test, the overall accuracy was found to be superior to existing diagnostic tests for peanut allergy including skin prick testing, peanut sIgE, and peanut component sIgE testing.

bbeaR: an R package and framework for epitope-specific antibody profiling

SUMMARY

Analysis of epitope-specific antibody repertoires has provided novel insights into the pathogenesis of inflammatory disorders, especially allergies. A novel multiplex immunoassay, termed Bead-Based Epitope Assay (BBEA), was developed to quantify levels of epitope-specific immunoglobulins, including IgE, IgG, IgA and IgD isotypes. bbeaR is an open-source R package, developed for the BBEA, provides a framework to import, process and normalize .csv data files exported from the Luminex reader, evaluate various quality control metrics, analyze differential epitope-binding antibodies with linear modelling, visualize results, and map epitopes' amino acid sequences to their respective primary protein structures. bbeaR enables streamlined and reproducible analysis of epitope-specific antibody profiles.

AVAILABILITY AND IMPLEMENTATION

bbeaR is open-source and freely available from GitHub as an R package: https://github.com/msuprun/bbeaR; vignettes included.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Early epitope-specific IgE antibodies are predictive of childhood peanut allergy

BACKGROUND

Peanut allergy is characterized by the development of IgE against peanut antigen.

OBJECTIVE

We sought to evaluate the evolution of epitope-specific (es)IgE and esIgG4 in a prospective cohort of high-risk infants to determine whether antibody profiles can predict peanut allergy after age 4 years.

METHODS

The end point was allergy status at age 4+ years; samples from 293 children were collected at age 3 to 15 months and 2 to 3 and 4+ years. Levels of specific (s)IgE and sIgG4 to peanut and component proteins, and 50 esIgE and esIgG4 were quantified. Changes were analyzed with mixed-effects models. Machine learning algorithms were developed to identify a combination of antigen- and epitope-specific antibodies that using 3- to 15-month or 2- to 3-year samples can predict allergy status at age 4+ years.

RESULTS

At age 4+ years, 38% of children were Tolerant or 14% had Possible, 8% Convincing, 24% Serologic, and 16% Confirmed allergy. At age 3 to 15 months, esIgE profiles were similar among groups, whereas marked increases were evident at age 2 and 4+ years only in Confirmed and Serologic groups. In contrast, peanut sIgE level was significantly lower in the Tolerant group at age 3 to 15 months, increased in Confirmed and Serologic groups but decreased in Convincing and Possibly Allergic groups over time. An algorithm combining esIgEs with peanut sIgE outperformed different clinically relevant IgE cutoffs, predicting allergy status on an "unseen" set of patients with area under the curves of 0.84 at age 3 to 15 months and 0.87 at age 2 to 3 years.

CONCLUSIONS

Early epitope-specific plus peanut-specific IgE is predictive of allergy status at age 4+ years.

Ovomucoid epitope-specific repertoire of IgE, IgG4 , IgG1 , IgA1 , and IgD antibodies in egg-allergic children

BACKGROUND

Egg-white ovomucoid, that is, Gal d 1, is associated with IgE-mediated allergic reactions in most egg-allergic children. Epitope-specific IgE levels have been correlated with the severity of egg allergy, while emerging evidence suggests that other antibody isotypes (IgG₁ , IgG₄ , IgA, and IgD) may have a protective function; yet, their epitope-specific repertoires and associations with atopic comorbidities have not been studied.

METHODS

Bead-based epitope assay (BBEA) was used to quantitate the levels of epitope-specific (es)IgA, esIgE, esIgD, esIgG₁ , and esIgG₄ antibodies directed at 58 (15-mer) overlapping peptides, covering the entire sequence of ovomucoid, in plasma of 38 egg-allergic and 6 atopic children. Intraclass correlation (ICC) and coefficient of variation (CV) were used for the reliability assessment. The relationships across esIgs were evaluated using network analysis; linear and logistic regressions were used to compare groups based on egg allergy status and comorbidities.

RESULTS

BBEA had high reliability (ICC >0.75) and low variability (CV <20%) and could detect known IgE-binding epitopes. Egg-allergic children had lower esIgA₁ (P = .010) and esIgG₁ (P = .016) and higher esIgE (P < .001) and esIgD (P = .015) levels compared to the atopic controls. Interestingly, within the allergic group, children with higher esIgD had decreased odds of anaphylactic reactions (OR =0.48, P = .038). Network analysis identified most associations between esIgE with either esIgG₄ or esIgD; indicating that IgE-secreting plasma cells could originate from either sequential isotype switch from antigen-experienced intermediate isotypes or directly from the IgD⁺ B cells.

CONCLUSIONS

Collectively, these data point toward a contribution of epitope-specific antibody repertoires to the pathogenesis of egg allergy.

Comprehensive Immunoprofiling of Pediatric Zika Reveals Key Role for Monocytes in the Acute Phase and No Effect of Prior Dengue Virus Infection

Zika virus (ZIKV) is an emerging, mosquito-borne flavivirus responsible for recent epidemics across the Americas, and it is closely related to dengue virus (DENV). Here, we study samples from 46 DENV-naive and 43 DENV-immune patients with RT-PCR-confirmed ZIKV infection at early-acute, late-acute, and convalescent time points from our pediatric cohort study in Nicaragua. We analyze the samples via RNA sequencing (RNA-seq), CyTOF, and multiplex cytokine/chemokine Luminex to generate a comprehensive, innate immune profile during ZIKV infection. Immunophenotyping and analysis of cytokines/chemokines reveal that CD14+ monocytes play a key role during ZIKV infection. Further, we identify CD169 (Siglec-1) on CD14+ monocytes as a potential biomarker of acute ZIKV infection. Strikingly distinct transcriptomic and immunophenotypic signatures are observed at all three time points. Interestingly, pre-existing dengue immunity has minimal impact on the innate immune response to Zika. Finally, this comprehensive immune profiling and network analysis of ZIKV infection in children serves as a valuable resource.

Novel Bead-Based Epitope Assay is a sensitive and reliable tool for profiling epitope-specific antibody repertoire in food allergy

Identification of allergenic IgE epitopes is instrumental for the development of novel diagnostic and prognostic methods in food allergy. In this work, we present the quantification and validation of a Bead-Based Epitope Assay (BBEA) that through multiplexing of epitopes and multiple sample processing enables completion of large experiments in a short period of time, using minimal quantities of patients’ blood. Peptides that are uniquely coupled to beads are incubated with serum or plasma samples, and after a secondary fluorophore-labeled antibody is added, the level of fluorescence is quantified with a Luminex reader. The signal is then normalized and converted to epitope-specific antibody binding values. We show that the effect of technical artifacts, i.e. well position or reading order, is minimal; and batch effects - different individual microplate runs - can be easily estimated and eliminated from the data. Epitope-specific antibody binding quantified with BBEA is highly reliable, reproducible and has greater sensitivity of epitope detection compared to peptide microarrays. IgE directed at allergenic epitopes is a sensitive biomarker of food allergy and can be used to predict allergy severity and phenotypes; and quantification of the relationship between epitope-specific IgE and IgG4 can further improve our understanding of the immune mechanisms behind allergic sensitization.