SARS-CoV-2 mRNA vaccination induces an intranasal mucosal response characterized by neutralizing antibodies.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mRNA vaccine-induced systemic antibody profiles are well characterized; however, little is known about whether intranasal mucosal antibodies are induced or can neutralize virus in response to mRNA vaccination. Objective: We sought to evaluate intranasal mucosal antibody production with SARS-CoV-2 mRNA vaccination. Methods: SARS-CoV-2-specific IgG and IgA concentrations and neutralization activity from sera and nasal mucosa via nasal epithelial lining fluid (NELF) collection were measured in SARS-CoV-2 mRNA-vaccinated healthy volunteers (N = 29) by using multiplex immunoassays. Data were compared before and after vaccination, between mRNA vaccine brands, and by sex. Results: SARS-CoV-2 mRNA vaccination induced an intranasal immune response characterized by neutralizing mucosal antibodies. IgG antibodies displayed greater Spike 1 (S1) binding specificity than did IgA in serum and nasal mucosa. Nasal antibodies displayed greater neutralization activity against the receptor-binding domain than serum. Spikevax (Moderna)-vaccinated individuals displayed greater SARS-CoV-2-specific IgG and IgA antibody concentrations than did Comirnaty (BioNTech/Pfizer)-vaccinated individuals in their serum and nasal epithelial lining fluid. Sex-dependent differences in antibody response were not observed. Conclusion: SARS-CoV-2 mRNA vaccination induces a robust systemic and intranasal antibody production with neutralizing capacity. Spikevax vaccinations elicit a greater antibody response than does Comirnaty vaccination systemically and intranasally.

Comparison of multiplexed protein analysis platforms for the detection of biomarkers in the nasal epithelial lining fluid of healthy subjects.

BACKGROUND: Multiplexed protein analysis platforms are a novel and efficient way to characterize biomarkers in a variety of biological samples. Few studies have compared protein quantitation and reproducibility of results across platforms. We utilize a novel nasosorption technique to collect nasal epithelial lining fluid (NELF) from healthy subjects, and compare the detection of proteins in NELF across three commonly used platforms. METHODS: NELF was collected from both nares of twenty healthy subjects using an absorbent fibrous matrix and analyzed using three different protein analysis platforms: Luminex, Meso Scale Discovery (MSD), and Olink. Twenty-three protein analytes were shared across two or more platforms, and correlations across platforms were assessed using Spearman correlations. RESULTS: Among the twelve proteins represented on all three platforms, IL1⍺ and IL6 were very highly correlated (Spearman correlation coefficient [r] ≥ 0.9); CCL3, CCL4, and MCP1 were highly correlated (r ≥ 0.7); and IFNÉ£, IL8, and TNF⍺ were moderately correlated (r ≥ 0.5). Four proteins (IL2, IL4, IL10, IL13) were poorly correlated across at least two platform comparisons (r < 0.5); for two of these proteins (IL10 and IL13), the majority of observations were below the limits of detection for Olink and Luminex. DISCUSSION: Multiplexed protein analysis platforms are a promising method for analyzing nasal samples for biomarkers of interest in respiratory health research. For most proteins evaluated, there was good correlation across platforms, although results were less consistent for low abundance proteins. Of the three platforms tested, MSD had the highest sensitivity for analyte detection.

Development of LC-HRMS untargeted analysis methods for nasal epithelial lining fluid exposomics.

BACKGROUND: The nasal mucosa, as a primary site of entry for inhaled substances, contains both inhaled xenobiotic and endogenous biomarkers. Nasal mucosa can be non-invasively sampled (nasal epithelial lining fluid "NELF") and analyzed for biological mediators. However, methods for untargeted analysis of compounds inhaled and/or retained in the nasal mucosa are needed. OBJECTIVES: This study aimed to develop a high resolution LC-MS untargeted method to analyze collected NELF. Profiling of compounds in NELF samples will also provide baseline data for future comparative studies to reference. METHODS: Extracted NELF analytes were injected to LC-ESI-MS. After spectrum processing, an in-house library provided annotations with high confidence, while more tentative annotation proposals were obtained via ChemSpider database matching. RESULTS: The established method successfully detected unique molecular signatures within NELF. Baseline profiling of 27 samples detected 2002 unknown molecules, with 77 and 463 proposed structures by our in-house library and Chemspider matching. High confidence annotations revealed common metabolites and tentative annotations implied various environmental exposure biomarkers are also present in NELF. SIGNIFICANCE: The experimental pipeline for analyzing NELF samples serves as simple and robust method applicable for future studies to characterize identities/effects of inhaled substances and metabolites retained in the nasal mucosa. IMPACT STATEMENT: The nasal mucosa contains exogenous and endogenous compounds. The development of an untargeted analysis is necessary to characterize the nasal exposome by deciphering the identity and influence of inhaled compounds on nasal mucosal biology. This study established a high resolution LC-MS based untargeted analysis of non-invasively collected nasal epithelial lining fluid. Baseline profiling of the nasal mucosa (n = 27) suggests the presence of environmental pollutants, along with detection of endogenous metabolites. Our results show high potential for the analytical pipeline to facilitate future respiratory health studies involving inhaled pollutants or pharmaceutical compounds and their effects on respiratory biology.