Absolute quantitation of serum antibody reactivity using the Richards growth model for antigen microspot titration

In spite of its pivotal role in the characterization of humoral immunity, there is no accepted method for the absolute quantitation of antigen specific serum antibodies. We devised a novel method to quantify polyclonal antibody reactivity, which exploits protein microspot assays and employs a novel analytical approach. Microarrays with a density series of disease specific antigen were treated with different serum dilutions and developed for IgG and IgA binding. By fitting binding data of both dilution series to a product of two generalized logistic functions, we obtained estimates of antibody reactivity of two immunoglobulin classes simultaneously. These estimates are the antigen concentrations required for reaching the inflection point of thermodynamic activity coefficient of antibodies and the limiting activity coefficient of antigen. By providing universal chemical units, this method may improve standardization of serological testing, the quality control of antibodies and the quantitative mapping of antibody-antigen interaction space.

Flow Cytometric Evaluation of Yeast-Bacterial Cell-Cell Interactions

Synthetic cell-cell interaction systems can be useful for understanding multicellular communities or for screening binding molecules. We adapt a previously characterized set of synthetic cognate nanobody-antigen pairs to a yeast-bacteria coincubation format and use flow cytometry to evaluate cell-cell interactions mediated by binding between surface-displayed molecules. We further use fluorescence-activated cell sorting (FACS) to enrich for a specific yeast-displayed nanobody within a mixed yeast-display population. Finally, we demonstrate that this system supports characterization of a therapeutically relevant nanobody-antigen interaction: a previously discovered nanobody that binds to the intimin protein expressed on the surface of enterohemorrhagic E. coli. Overall, our findings indicate that the yeast-bacteria format supports efficient evaluation of ligand-target interactions. With further development, this format may facilitate systematic characterization and high throughput discovery of bacterial surface-binding molecules.

Aptasensor for the Detection of Mycobacterium Tuberculosis in Sputum Utilising CFP10-ESAT6 Protein as a Selective Biomarker

A portable electrochemical aptamer-antibody based sandwich biosensor has been designed and successfully developed using an aptamer bioreceptor immobilized onto a screen-printed electrode surface for Mycobacterium tuberculosis (M. tuberculosis) detection in clinical sputum samples. In the sensing strategy, a CFP10-ESAT6 binding aptamer was immobilized onto a graphene/polyaniline (GP/PANI)-modified gold working electrode by covalent binding via glutaraldehyde linkage. Upon interaction with the CFP10-ESAT6 antigen target, the aptamer will capture the target where the nano-labelled Fe3O4/Au MNPs conjugated antibody is used to complete the sandwich format and enhance the signal produced from the aptamer–antigen interaction. Using this strategy, the detection of CFP10-ESAT6 antigen was conducted in the concentration range of 5 to 500 ng/mL. From the analysis, the detection limit was found to be 1.5 ng/mL, thereby demonstrating the efficiency of the aptamer as a bioreceptor. The specificity study was carried out using bovine serum albumin (BSA), MPT64, and human serum, and the result demonstrated good specificity that is 7% higher than the antibody–antigen interaction reported in a previous study. The fabricated aptasensor for M. tuberculosis analysis shows good reproducibility with an relative standard deviation (RSD) of 2.5%. Further analysis of M. tuberculosis in sputum samples have shown good correlation with the culture method with 100% specificity and sensitivity, thus making the aptasensor a promising candidate for M. tuberculosis detection considering its high specificity and sensitivity with clinical samples.

Electrochemical Immunosensor for the Simultaneous Determination of Two Main Peanut Allergenic Proteins (Ara h 1 and Ara h 6) in Food Matrices

Efficiently detecting peanut traces in food products can prevent severe allergic reactions and serious health implications. This work presents the development of an electrochemical dual immunosensor for the simultaneous analysis of two major peanut allergens, Ara h 1 and Ara h 6, in food matrices. A sandwich immunoassay was performed on a dual working screen-printed carbon electrode using monoclonal antibodies. The antibody–antigen interaction was detected by linear sweep voltammetry through the oxidation of enzymatically deposited silver, which was formed by using detection antibodies labeled with alkaline phosphatase and a 3-indoxyl phosphate/silver nitrate mixture as the enzymatic substrate. The assay time was 2 h 20 min, with a hands-on time of 30 min, and precise results and low limits of detection were obtained (Ara h 1: 5.2 ng·mL−1; Ara h 6: 0.017 ng·mL−1). The selectivity of the method was confirmed through the analysis of other food allergens and ingredients (e.g., hazelnut, soybean and lupin). The dual sensor was successfully applied to the analysis of several food products and was able to quantify the presence of peanuts down to 0.05% (w/w). The accuracy of the results was confirmed through recovery studies and by comparison with an enzyme-linked immunosorbent assay. Tracking food allergens is of utmost importance and can be performed using the present biosensor in a suitable and practical way.

A Sequence-based Antibody Paratope Prediction Model Through Combing Local-Global Information and Partner Features

Antibodies are proteins which play a vital role in the immune system by recognizing and neutralizing antigens. The region on the antibody binds to the antigens, also known as paratope, mediates antibody-antigen interaction with high affinity and specificity. And the accurate prediction of those regions from antibody sequence contributes to the design of therapeutic antibodies and remains challenging. However, the experimental methods are time-consuming and expensive. In this article, we propose a sequence-based method for antibody paratope prediction by combing the local and global features of antibody sequence and global features of partner antigen sequence. For extracting local features, we use Convolution Neural Networks(CNNs) and a sliding window approach on antibody sequence. For extracting global features, we use Attention-based Bidirectional Long Short-Term Memory(Att-BLSTM) networks on antibody sequence. For extracting partner features, we employ Att-BLSTM on the partner antigen sequence as well. And then, all features are combined to predict antibody paratope by fully-connected networks. The experiments show that our proposed method achieves superior performance over the state-of-the-art sequenced-based antibody paratope prediction methods on benchmark datasets.

Modeling of protein complexes in CASP14 with emphasis on the interaction interface prediction

The goal of CASP experiments is to monitor the progress in the protein structure prediction field. During the 14th CASP edition we aimed to test our capabilities of predicting structures of protein complexes. Our protocol for modeling protein assemblies included both template-based modeling and free docking. Structural templates were identified using sensitive sequence-based searches. If sequence-based searches failed, we performed structure-based template searches using selected CASP server models. In the absence of reliable templates we applied free docking starting from monomers generated by CASP servers. We evaluated and ranked models of protein complexes using an improved version of protein structure quality assessment method, VoroMQA, taking into account both interaction interface and global structure scores. If reliable templates could be identified, generally accurate models of protein assemblies were generated with the exception of an antibody-antigen interaction. The success of free docking mainly depended on the accuracy of initial subunit models and on the scoring of docking solutions. To put our overall results in perspective, we analyzed our performance in the context of other CASP groups. Although the subunits in our assembly models often were not of the top quality, these models had, overall, the best predicted interfaces according to several protein-protein interface accuracy measures. Since we did not use co-evolution-based prediction of inter-chain contacts, we attribute our relative success in predicting interfaces primarily to the emphasis on the interaction interface when modeling and scoring.

A framework for highly multiplexed dextramer mapping and prediction of T cell receptor sequences to antigen specificity

T cell receptor (TCR) antigen–specific recognition is essential for the adaptive immune system. However, building a TCR-antigen interaction map has been challenging due to the staggering diversity of TCRs and antigens. Accordingly, highly multiplexed dextramer-TCR binding assays have been recently developed, but the utility of the ensuing large datasets is limited by the lack of robust computational methods for normalization and interpretation. Here, we present a computational framework comprising a novel method, ICON (Integrative COntext-specific Normalization), for identifying reliable TCR-pMHC (peptide–major histocompatibility complex) interactions and a neural network–based classifier TCRAI that outperforms other state-of-the-art methods for TCR-antigen specificity prediction. We further demonstrated that by combining ICON and TCRAI, we are able to discover novel subgroups of TCRs that bind to a given pMHC via different mechanisms. Our framework facilitates the identification and understanding of TCR-antigen–specific interactions for basic immunological research and clinical immune monitoring.

TOP-Plus is a Versatile Biosensor Platform for Monitoring SARS-CoV-2 Antibody Durability

Background Low initial SARS-CoV-2 antibody titers dropping to undetectable levels within months after infection have raised concerns over long term immunity. Both the antibody levels and avidity of the antibody-antigen interaction should be examined to understand the quality of the antibody response. Methods A testing-on-a-probe “plus” panel (TOP-Plus) was developed, which included a newly developed avidity assay built into the previously described SARS-CoV-2 TOP assays that measured total antibody (TAb), surrogate neutralizing antibody (SNAb), IgM and IgG on a versatile biosensor platform. TAb and SNAb levels were compared with avidity in previously infected individuals at 1.3 and 6.2 months post-infection in paired samples from 80 COVID-19 patients. Sera from SARS-CoV-2 vaccinated individuals were also evaluated for antibody avidity. Results The newly designed avidity assay in this TOP panel correlated well with a reference Bio-Layer Interferometry avidity assay (r=0.88). The imprecision of the TOP avidity assay was less than 10%. Although TAb and neutralization activity (by SNAb) decreased between 1.3 and 6.2 months post-infection, the antibody avidity increased significantly (P < 0.0001). Antibody avidity in 10 SARS-CoV-2 vaccinated individuals (median 28 days post-vaccination) was comparable to the measured antibody avidity in infected individuals (median 26 days post-infection). Conclusion This highly precise and versatile TOP-Plus panel with the ability to measure SARS-CoV-2 TAb, SNAb, IgG and IgM antibody levels and avidity of individual sera on one sensor can become a valuable asset in monitoring not only SARS-CoV-2-infected patients, but also the status of individuals’ COVID-19 vaccination response.

The mycoplasma surface proteins MIB and MIP promote the dissociation of the antibody-antigen interaction

Mycoplasma immunoglobulin binding (MIB) and mycoplasma immunoglobulin protease (MIP) are surface proteins found in the majority of mycoplasma species, acting sequentially to capture antibodies and cleave off their VH domains. Cryo–electron microscopy structures show how MIB and MIP bind to a Fab fragment in a “hug of death” mechanism. As a result, the orientation of the VL and VH domains is twisted out of alignment, disrupting the antigen binding site. We also show that MIB-MIP has the ability to promote the dissociation of the antibody-antigen complex. This system is functional in cells and protects mycoplasmas from antibody-mediated agglutination. These results highlight the key role of the MIB-MIP system in immunity evasion by mycoplasmas through an unprecedented mechanism, and open exciting perspectives to use these proteins as potential tools in the antibody field.

A10 FOOD ANTIGEN-STRESS INTERACTION LEADS TO INCREASE PAIN SIGNALING IN ILEUM AND COLON VIA STAT6 IN AN IBS MODEL

Background Abdominal pain can be triggered by food ingestion in IBS patients. Previously we have shown that a food antigen induces local release of immune mediators in the colon that increase dorsal root ganglion (DRG) neuron excitability when there is previous antigen exposure in the presence of psychological stress. However, it is unknown if this effect is limited to the colon. Furthermore, the involvement of histamine in the neuronal hyperexcitability suggests that the stress-food antigen interaction evokes a Th2 immune response. Thus, we sought to investigate the role of STAT6, a transcription factor downstream of Th2 cytokines and important for IgE production. Aims 1) Determine if stress-food antigen interaction leads to release of mediators within the small intestine that increase DRG neuron excitability. 2) Determine the involvement of STAT6 on neuronal hyperexcitability induced by the stress-food antigen interaction. Methods BALB/c mice were exposed to water avoidance stress (WAS) or sham stress (SHAM) for 1 hr daily for 10 days. On day 2–10, mice were exposed to ovalbumin (OVA) or saline (SAL). Seven days later, mice were re-exposed to either OVA or SAL every 2 days for 2 weeks yielding 3 groups: WAS/OVA+OVA, WAS/SAL+OVA, and SHAM/OVA+OVA. STAT6 deficient mice were also exposed to WAS/OVA+OVA protocol. Ileum or colonic supernatants were obtained 4 hours after tissue collection. DRG neurons were incubated overnight with supernatants prior to perforated patch clamp recordings. Neuronal excitability was evaluated by measuring the rheobase (minimum current to elicit an action potential, decreased rheobase indicates increased excitability). Mechanosensitivity of extrinsic afferent nerves innervating distal ileum was examined using ex vivo extracellular afferent nerve recordings. Data was analyzed by one or two-way ANOVA with Bonferroni post-hoc test. Results Ileum supernatants from WAS/OVA+OVA mice increased DRG neuron excitability compared to WAS/SAL+OVA and SHAM/OVA+OVA mice (63.3 ± 6.2 pA vs 83.2 ± 5.4 pA, 86.7 ± 4.5 pA, p<0.05). Ileum afferent nerve response to distention was significantly augmented in WAS/OVA+OVA mice compared to WAS/SAL+OVA and SHAM/OVA+OVA (P<0.05, n=4–7). DRG neurons incubated with WAS/OVA+OVA supernatant from STAT6 deficient mice were less excitable compared to neurons incubated with colonic supernatants from wild type mice (86.5 ± 4.1 pA vs 67.6 ± 4.8 pA, p<0.05). Conclusions Stress-food antigen interaction releases mediators in both the small intestine and colon to increase nociceptive signaling, an important finding as IBS can involve both areas. The release of excitatory mediators within the gut appears to involve STAT6. Thus, a stress-food antigen interaction evoking a Th2 immune response in the gut may be a mechanism underlying food induced symptoms in IBS. Funding Agencies Queen’s University, Department of Medicine