Ara h 2-specific IgE epitope-like peptides inhibit the binding of IgE to Ara h 2 and suppress lgE-dependent effector cell activation.

BACKGROUND: Clinical and experimental analyses indicate a pathognomonic role for allergen IgE crosslinking through epitope-paratope interactions as a major initial step in the cascade leading to effector cell activation and clinical manifestations of lgE-mediated food allergies. We aimed to undertake the initial development and assessment of Ara h 2-specific IgE epitope-like peptides that can bind to allergen-specific IgE paratopes and suppress effector cell activation. METHODS: We performed biopanning, screening, IgE binding, selection and mapping of peptides. We generated synthetic peptides for use in all functional experiments. ImmunoCAP inhibition, basophil and mast cell activation tests, with LAD2 cells, a human mast cell line were performed. Twenty-six children or young adults who had peanut allergy were studied. RESULTS: We identified and selected three linear peptides (DHPRFNRDNDVA, DHPRYGP and DHPRFST), and immunoblot analyses revealed binding to lgE from peanut-allergic individuals. The peptide sequences were aligned to the disordered region corresponding to the loop between helices 2 and 3 of Ara h 2, and conformational mapping showed that the peptides match the surface of Ara h 2 and h 6 but not other peanut allergens. In ImmunoCAP inhibition experiments, the peptides significantly inhibit the binding of IgE to Ara h 2 (p < .001). In basophil and mast cell activation tests, the peptides significantly suppressed Ara h 2-induced effector cell activation (p < .05) and increased the half-maximal Ara h 2 effective concentration (p < .05). Binding of the peptides to specific IgEs did not induce activation of basophils or mast cells. CONCLUSIONS: These studies show that the indicated peptides reduce the allergenic activity of Ara h 2 and suppress lgE-dependent basophil and mast cell activation. These observations may suggest a novel therapeutic strategy for food allergy based on epitope-paratop blocking.

Solid cancer patients achieve adequate immunogenicity and low rate of severe adverse events after SARS-CoV-2 vaccination.

Background: SARS-CoV-2 vaccination in cancer patients is crucial to prevent severe COVID-19 disease course. Methods: This study assessed immunogenicity of cancer patients on active treatment receiving mRNA-based SARS-CoV-2 vaccine by detection of anti-SARS-CoV-2 S1 IgG antibodies in serum, before, after the first and second doses and 3 months after a complete primary course of vaccination. Results were compared with healthy controls. Results: Of 112 patients, the seroconversion rate was 96%. A significant reduction in antibody levels was observed 3 months after vaccination in patients receiving immune checkpoint inhibitors versus control participants (p < 0.001). Adverse events were mostly mild. Conclusion: Immunogenicity after mRNA-based vaccine in cancer patients is adequate but influenced by the type of anticancer therapy. Antibody levels decline after 3 months, and thus a third vaccination is warranted.

Because cancer patients are especially endangered by SARS-CoV-2 infection and have worse disease course and outcomes, it is crucial to protect them from this infection. This study was aimed at assessing protective antibodies after patients received mRNA-based SARS-CoV-2 vaccines. Protective antibodies (e.g., anti-SARS-CoV-2 S1 IgG antibodies) were assessed in patients' blood before vaccination, after the first and second doses and 3 months after a complete primary course vaccination. Patients' oncological treatment was unaffected by the vaccination received. The results of protective antibodies were also compared with healthy control subjects who were vaccinated in the same manner. More than 110 cancer patients participated and agreed to have their blood samples analyzed. The rate of antibody production was 96% after a complete primary course of vaccination and was similar with that of healthy control subjects. However, there were some differences noted regarding the oncological treatment that the patients were receiving, with patients who were treated with targeted therapy achieving the highest levels of protective antibodies. Adverse events after vaccination were mostly mild and did not interfere with patients' general performance. The rate of antibody production for cancer patients after SARS-CoV-2 vaccination is high and similar to that in healthy control subjects but varies with regard to the oncological treatment that patients are receiving. However, antibodies decline substantially after 3 months, and thus a third vaccination is desirable. There were no new safety concerns after vaccination, and most adverse events were mild and short-lived.

Combination of Experimental and Bioinformatic Approaches for Identification of Immunologically Relevant Protein-Peptide Interactions.

Protein-peptide interactions are an essential player in cellular processes and, thus, of great interest as potential therapeutic agents. However, identifying the protein's interacting surface has been shown to be a challenging task. Here, we present a methodology for protein-peptide interaction identification, implementing phage panning, next-generation sequencing and bioinformatic analysis. One of the uses of this methodology is identification of allergen epitopes, especially suitable for globular inhaled and venom allergens, where their binding capability is determined by the allergen's conformation, meaning their interaction cannot be properly studied when denatured. A Ph.D. commercial system based on the M13 phage vector was used for the panning process. Utilization of various bioinformatic tools, such as PuLSE, SAROTUP, MEME, Hammock and Pepitope, allowed us to evaluate a large amount of obtained data. Using the described methodology, we identified three peptide clusters representing potential epitopes on the major wasp venom allergen Ves v 5.

Immunophenotypes of anti-SARS-CoV-2 responses associated with fatal COVID-19.

Background: The relationship between anti-SARS-CoV-2 humoral immune response, pathogenic inflammation, lymphocytes and fatal COVID-19 is poorly understood. Methods: A longitudinal prospective cohort of hospitalised patients with COVID-19 (n=254) was followed up to 35 days after admission (median, 8 days). We measured early anti-SARS-CoV-2 S1 antibody IgG levels and dynamic (698 samples) of quantitative circulating T-, B- and natural killer lymphocyte subsets and serum interleukin-6 (IL-6) response. We used machine learning to identify patterns of the immune response and related these patterns to the primary outcome of 28-day mortality in analyses adjusted for clinical severity factors. Results: Overall, 45 (18%) patients died within 28 days after hospitalisation. We identified six clusters representing discrete anti-SARS-CoV-2 immunophenotypes. Clusters differed considerably in COVID-19 survival. Two clusters, the anti-S1-IgGlowestTlowestBlowestNKmodIL-6mod, and the anti-S1-IgGhighTlowBmodNKmodIL-6highest had a high risk of fatal COVID-19 (HR 3.36-21.69; 95% CI 1.51-163.61 and HR 8.39-10.79; 95% CI 1.20-82.67; p≤0.03, respectively). The anti-S1-IgGhighestTlowestBmodNKmodIL-6mod and anti-S1-IgGlowThighestBhighestNKhighestIL-6low cluster were associated with moderate risk of mortality. In contrast, two clusters the anti-S1-IgGhighThighBmodNKmodIL-6low and anti-S1-IgGhighestThighestBhighNKhighIL-6lowest clusters were characterised by a very low risk of mortality. Conclusions: By employing unsupervised machine learning we identified multiple anti-SARS-CoV-2 immune response clusters and observed major differences in COVID-19 mortality between these clusters. Two discrete immune pathways may lead to fatal COVID-19. One is driven by impaired or delayed antiviral humoral immunity, independently of hyper-inflammation, and the other may arise through excessive IL-6-mediated host inflammation response, independently of the protective humoral response. Those observations could be explored further for application in clinical practice.

Split-BioID a conditional proteomics approach to monitor the composition of spatiotemporally defined protein complexes.

Understanding the function of the thousands of cellular proteins is a central question in molecular cell biology. As proteins are typically part of multiple dynamic and often overlapping macromolecular complexes exerting distinct functions, the identification of protein-protein interactions (PPI) and their assignment to specific complexes is a crucial but challenging task. We present a protein fragments complementation assay integrated with the proximity-dependent biotinylation technique BioID. Activated on the interaction of two proteins, split-BioID is a conditional proteomics approach that allows in a single and simple assay to both experimentally validate binary PPI and to unbiasedly identify additional interacting factors. Applying our method to the miRNA-mediated silencing pathway, we can probe the proteomes of two distinct functional complexes containing the Ago2 protein and uncover the protein GIGYF2 as a regulator of miRNA-mediated translation repression. Hence, we provide a novel tool to study dynamic spatiotemporally defined protein complexes in their native cellular environment.