RESUMO
Peanut is a major cause of severe IgE-mediated food allergic reactions, which can be exacerbated by factors, such as exercise, that may increase allergen uptake into the circulation. Enzyme-linked immunosorbent assays (ELISAs) have been used to determine allergen uptake into serum, but there are concerns over their specificity and a confirmatory method is required. Mass spectrometry (MS) methods have the potential to provide rigorous alternatives for allergen determination. A suite of peptide targets representing the major clinically relevant peanut allergens previously applied in food analysis were used to develop a targeted multiple reaction monitoring (MRM) method for determination of peanut in serum. Depletion of serum using affinity chromatography was found to be essential to allow detection of the peptide targets. A comparison of triple quadrupole and Q-TOF methods showed that one Ara h 2 peptide was only detected by the Q-TOF, the other peptide targets giving similar assay sensitivities with both MS platforms, although transitions for all the peptides were detected more consistently with the Q-TOF. The Q-TOF MRM assay detected peanut from spiked serum more effectively than the triple quadrupole assay, with Ara h 3 being detected down to 3 mg total peanut protein/L of serum, comparable with an Ara h 3-specific ELISA. The poor recoveries observed for both methods are likely due to loss of peanut immune complexes during the serum depletion process. Nevertheless, the Q-TOF MRM method has much promise to confirm the uptake of peanut proteins in serum samples providing immune complexes can be disrupted effectively prior to depletion. Graphical abstract.
Assuntos
Alérgenos/sangue , Antígenos de Plantas/sangue , Arachis/química , Análise de Alimentos/métodos , Hipersensibilidade a Amendoim/diagnóstico , Espectrometria de Massas por Ionização e Dessorção a Laser Assistida por Matriz/métodos , Humanos , Hipersensibilidade a Amendoim/sangueRESUMO
Peanut is an important food allergen, but it cannot currently be reliably detected and quantified in processed foods at low levels. A level of 3 mg protein/kg is increasingly being used as a reference dose above which precautionary allergen labeling is applied to food products. Two exemplar matrices (chocolate dessert and chocolate bar) were prepared and incurred with 0, 3, 10, or 50 mg/kg peanut protein using a commercially available lightly roasted peanut flour ingredient. After simple buffer extraction employing an acid-labile detergent, multiple reaction monitoring (MRM) experiments were used to assess matrix effects on the detection of a set of seven peptide targets derived from peanut allergens using either conventional or microfluidic chromatographic separation prior to mass spectrometry. Microfluidic separation provided greater sensitivity and increased ionization efficiency at low levels. Individual monitored transitions were detected in consistent ratios across the dilution series, independent of matrix. The peanut protein content of each sample was then determined using ELISA and the optimized MRM method. Although other peptide targets were detected with three transitions at the 50 mg/kg peanut protein level in both matrices, only Arah2(Q6PSU2)147-155 could be quantified reliably and only in the chocolate dessert at 10 mg/kg peanut protein. Recoveries were consistent with ELISA analysis returning around 30-50% of the incurred dose. MS coupled with microfluidic separation shows great promise as a complementary analytical tool for allergen detection and quantification in complex foods using a simple extraction methodology.
Assuntos
Alérgenos/análise , Arachis/imunologia , Espectrometria de Massas/métodos , Microfluídica/métodos , Arachis/química , Análise de Alimentos/métodos , Hipersensibilidade a Amendoim/etiologia , Proteínas de Plantas/análise , Proteínas de Plantas/imunologiaRESUMO
Profiling allergens in complex food ingredients used in oral food challenges and immunotherapy is crucial for regulatory acceptance. Mass spectrometry based analysis employing data-independent acquisition coupled with ion mobility mass spectrometry-mass spectrometry (DIA-IM-MS) was used to investigate the allergen composition of raw peanuts and roasted peanut flour ingredients used in challenge meals. This comprehensive qualitative and quantitative analysis using label-free approaches identified and quantified 123 unique protein accessions. Semiquantitative analysis indicated that allergens Ara h 1 and Ara h 3 were the most abundant proteins and present in approximately equal amounts and were extracted in reduced amounts from roasted peanut flours. The clinically significant allergens Ara h 2 and 6 were less abundant, but relative quantification was unaffected by roasting. Ara h 5 was undetectable in any peanut sample, while the Bet v 1 homologue Ara h 8 and the lipid transfer protein allergen, Ara h 9, were detected in low abundance. The oleosin allergens, Ara h 10 and 11, were moderately abundant in the raw peanuts but were 100-fold less abundant in the defatted roasted peanut flour than the major allergens Ara h 1, 3, 2, and 6. Certain isoforms of the major allergens dominated the profile. The relative quantitation of the major peanut allergens showed little variation between different batches of roasted peanut flour. These data will support future development of targeted approaches for absolute quantification of peanut allergens which can be applied to both food ingredients used in clinical studies and extracts used for skin testing and to identify trace levels of allergens in foods.
Assuntos
Antígenos de Plantas/análise , Arachis/química , Ingredientes de Alimentos/análise , Hipersensibilidade a Amendoim , Proteômica , Administração Oral , Antígenos de Plantas/administração & dosagem , Cromatografia Líquida , Humanos , Espectrometria de MassasRESUMO
Background: Global healthcare systems continue to be challenged by the COVID-19 pandemic, and there is a need for clinical assays that can help optimise resource allocation, support treatment decisions, and accelerate the development and evaluation of new therapies. Methods: We developed a multiplexed proteomics assay for determining disease severity and prognosis in COVID-19. The assay quantifies up to 50 peptides, derived from 30 known and newly introduced COVID-19-related protein markers, in a single measurement using routine-lab compatible analytical flow rate liquid chromatography and multiple reaction monitoring (LC-MRM). We conducted two observational studies in patients with COVID-19 hospitalised at Charité - Universitätsmedizin Berlin, Germany before (from March 1 to 26, 2020, n=30) and after (from April 4 to November 19, 2020, n=164) dexamethasone became standard of care. The study is registered in the German and the WHO International Clinical Trials Registry (DRKS00021688). Findings: The assay produces reproducible (median inter-batch CV of 10.9%) absolute quantification of 47 peptides with high sensitivity (median LLOQ of 143 ng/ml) and accuracy (median 96.8%). In both studies, the assay reproducibly captured hallmarks of COVID-19 infection and severity, as it distinguished healthy individuals, mild, moderate, and severe COVID-19. In the post-dexamethasone cohort, the assay predicted survival with an accuracy of 0.83 (108/130), and death with an accuracy of 0.76 (26/34) in the median 2.5 weeks before the outcome, thereby outperforming compound clinical risk assessments such as SOFA, APACHE II, and ABCS scores. Interpretation: Disease severity and clinical outcomes of patients with COVID-19 can be stratified and predicted by the routine-applicable panel assay that combines known and novel COVID-19 biomarkers. The prognostic value of this assay should be prospectively assessed in larger patient cohorts for future support of clinical decisions, including evaluation of sample flow in routine setting. The possibility to objectively classify COVID-19 severity can be helpful for monitoring of novel therapies, especially in early clinical trials. Funding: This research was funded in part by the European Research Council (ERC) under grant agreement ERC-SyG-2020 951475 (to M.R) and by the Wellcome Trust (IA 200829/Z/16/Z to M.R.). The work was further supported by the Ministry of Education and Research (BMBF) as part of the National Research Node 'Mass Spectrometry in Systems Medicine (MSCoresys)', under grant agreements 031L0220 and 161L0221. J.H. was supported by a Swiss National Science Foundation (SNSF) Postdoc Mobility fellowship (project number 191052). This study was further supported by the BMBF grant NaFoUniMedCOVID-19 - NUM-NAPKON, FKZ: 01KX2021. The study was co-funded by the UK's innovation agency, Innovate UK, under project numbers 75594 and 56328.