Development of a Mass Spectrometry-Based Method for Quantification of Total Cashew Protein in Roasting Oil

BACKGROUND

Food allergen cross-contact during food preparation and production is one of the causes of unintentional allergen presence in packaged foods. However, little is known about allergen cross-contact in shared frying or roasting oil, which prevents the establishment of effective allergen controls and may put allergic individuals at risk. To better understand the quantity of allergen transferred to frying oil and subsequent products, an analytical method is needed for quantifying protein in oil that has been exposed to frying/roasting conditions.

OBJECTIVE

The goal of this study was to develop a parallel reaction monitoring LC-MS/MS method to quantify the amount of cashew protein in shared roasting oil.

METHODS

The sample preparation method was evaluated to improve protein extractability and peptide performance. Four quantitative peptides representing cashew 2S and 11S proteins were selected as targets based on their sensitivity, heat stability, and specificity. A calibration strategy was developed to quantify the amount of total cashew protein in oil. Method performance was evaluated using a heated cashew-in-oil model system.

RESULTS

The method showed high recovery in oil samples spiked with 100 or 10 parts per million (ppm) total cashew protein heated at 138 or 166°C for 2-30 min. Samples (100 ppm total cashew protein) heated for 30 min had more than 90% recovery when treated at 138°C and more than 50% when heated at 166°C.

CONCLUSION

The method is fit-for-purpose for the analysis of cashew allergen cross-contact in oil.

HIGHLIGHTS

A novel MS-based method was developed that can accurately quantify the amount of cashew protein present in heated oil.

Tree Nuts and Peanuts as a Source of Beneficial Compounds and a Threat for Allergic Consumers: Overview on Methods for Their Detection in Complex Food Products

Consumption of tree nuts and peanuts has considerably increased over the last decades due to their nutritional composition and the content of beneficial compounds. On the other hand, such widespread consumption worldwide has also generated a growing incidence of allergy in the sensitive population. Allergy to nuts and peanuts represents a global relevant problem, especially due to the risk of the ingestion of hidden allergens as a result of cross-contamination between production lines at industrial level occurring during food manufacturing. The present review provides insights on peanuts, almonds, and four nut allergens—namely hazelnuts, walnuts, cashew, and pistachios—that are likely to cross-contaminate different food commodities. The paper aims at covering both the biochemical aspect linked to the identified allergenic proteins for each allergen category and the different methodological approaches developed for allergens detection and identification. Attention has been also paid to mass spectrometry methods and to current efforts of the scientific community to identify a harmonized approach for allergens quantification through the detection of allergen markers.

Are current analytical methods suitable to verify VITAL® 2.0/3.0 allergen reference doses for EU allergens in foods?

Food allergy affects up to 6% of Europeans. Allergen identification is important for the risk assessment and management of the inadvertent presence of allergens in foods. The VITAL® initiative for voluntary incidental trace allergen labeling suggests protein reference doses, based on clinical reactivity in food challenge studies, at or below which voluntary labelling is unnecessary. Here, we investigated if current analytical methodology could verify the published VITAL® 2.0 doses, that were available during this analysis, in serving sizes between 5 and 500 g. Available data on published and commercial ELISA, PCR and mass spectrometry methods, especially for the detection of peanuts, soy, hazelnut, wheat, cow's milk and hen's egg were reviewed in detail. Limit of detection, quantitative capability, matrix compatibility, and specificity were assessed. Implications by the recently published VITAL® 3.0 doses were also considered. We conclude that available analytical methods are capable of reasonably robust detection of peanut, soy, hazelnut and wheat allergens for levels at or below the VITAL® 2.0 and also 3.0 doses, with some methods even capable of achieving this in a large 500 g serving size. Cow's milk and hen's egg are more problematic, largely due to matrix/processing incompatibility. An unmet need remains for harmonized reporting units, available reference materials, and method ring-trials to enable validation and the provision of comparable measurement results.

Detection of Six Commercially Processed Soy Ingredients in an Incurred Food Matrix Using Parallel Reaction Monitoring

Soybeans are one of the major allergenic foods in many countries. Soybeans are commonly processed into different types of soy ingredients to achieve the desired properties. The processing, however, may affect the protein profiles and protein structure, thus affecting the detection of soy proteins. Mass spectrometry (MS) is a potential alternative to the traditional immunoassays for the detection of soy-derived ingredients in foods. This study aims to develop a liquid chromatography-tandem MS method that uniformly detects different types of soy-derived ingredients. Target peptides applicable to the detection of six commercial soy ingredients were identified based on the results of MS label-free quantification and a set of selection criteria. The results indicated that soy ingredient processing can result in different protein profiles. A total of six soy ingredients were then individually incurred into cookie matrices at different levels. Sample preparation methods were optimized, and a distinct improvement in peptide performance was observed after optimization. Cookies and dough incurred with different soy ingredients at 100 ppm total soy protein showed a similar level of peptide recovery (90% mean signal relative to unroasted soy flour), demonstrating the ability of the MS method to detect processed soy ingredients in a uniform manner.

In house validation of a high resolution mass spectrometry Orbitrap-based method for multiple allergen detection in a processed model food

In recent years, mass spectrometry (MS) has been establishing its role in the development of analytical methods for multiple allergen detection, but most analyses are being carried out on low-resolution mass spectrometers such as triple quadrupole or ion traps. In this investigation, performance provided by a high resolution (HR) hybrid quadrupole-Orbitrap™ MS platform for the multiple allergens detection in processed food matrix is presented. In particular, three different acquisition modes were compared: full-MS, targeted-selected ion monitoring with data-dependent fragmentation (t-SIM/dd2), and parallel reaction monitoring. In order to challenge the HR-MS platform, the sample preparation was kept as simple as possible, limited to a 30-min ultrasound-aided protein extraction followed by clean-up with disposable size exclusion cartridges. Selected peptide markers tracing for five allergenic ingredients namely skim milk, whole egg, soy flour, ground hazelnut, and ground peanut were monitored in home-made cookies chosen as model processed matrix. Timed t-SIM/dd2 was found the best choice as a good compromise between sensitivity and accuracy, accomplishing the detection of 17 peptides originating from the five allergens in the same run. The optimized method was validated in-house through the evaluation of matrix and processing effects, recoveries, and precision. The selected quantitative markers for each allergenic ingredient provided quantification of 60-100 μg_ingred/g allergenic ingredient/matrix in incurred cookies.

A harmonized immunoassay with liquid chromatography-mass spectrometry analysis in egg allergen determination

Food allergy is a serious health issue worldwide. Implementing allergen labeling regulations is extremely challenging for regulators, food manufacturers, and analytical kit manufacturers. Here we have developed an "amino acid sequence immunoassay" approach to ELISA. The new ELISA comprises of a monoclonal antibody generated via an analyte specific peptide antigen and sodium lauryl sulfate/sulfite solution. This combination enables the antibody to access the epitope site in unfolded analyte protein. The newly developed ELISA recovered 87.1%-106.4% ovalbumin from ovalbumin-incurred model processed foods, thereby demonstrating its applicability as practical egg allergen determination. Furthermore, the comparison of LC-MS/MS and the new ELISA, which targets the amino acid sequence conforming to the LC-MS/MS detection peptide, showed a good agreement. Consequently the harmonization of two methods was demonstrated. The complementary use of the new ELISA and LC-MS analysis can offer a wide range of practical benefits in terms of easiness, cost, accuracy, and efficiency in food allergen analysis. In addition, the new assay is attractive in respect to its easy antigen preparation and predetermined specificity. Graphical abstract The ELISA composing of the monoclonal antibody targeting the amino acid sequence conformed to LC-MS detection peptide, and the protein conformation unfolding reagent was developed. In ovalbumin determination, the developed ELISA showed a good agreement with LC-MS analysis. Consequently the harmonization of immunoassay with LC-MS analysis by using common target amino acid sequence was demonstrated.

Advances in ultra-high performance liquid chromatography coupled to tandem mass spectrometry for sensitive detection of several food allergens in complex and processed foodstuffs

Sensitive detection of food allergens is affected by food processing and foodstuff complexity. It is therefore a challenge to detect cross-contamination in food production that could endanger an allergic customer's life. Here we used ultra-high performance liquid chromatography coupled to tandem mass spectrometry for simultaneous detection of traces of milk (casein, whey protein), egg (yolk, white), soybean, and peanut allergens in different complex and/or heat-processed foodstuffs. The method is based on a single protocol (extraction, trypsin digestion, and purification) applicable to the different tested foodstuffs: chocolate, ice cream, tomato sauce, and processed cookies. The determined limits of quantitation, expressed in total milk, egg, peanut, or soy proteins (and not soluble proteins) per kilogram of food, are: 0.5mg/kg for milk (detection of caseins), 5mg/kg for milk (detection of whey), 2.5mg/kg for peanut, 5mg/kg for soy, 3.4mg/kg for egg (detection of egg white), and 30.8mg/kg for egg (detection of egg yolk). The main advantage is the ability of the method to detect four major food allergens simultaneously in processed and complex matrices with very high sensitivity and specificity.

An SPR based sensor for allergens detection

A simple, sensitive and label-free optical sensor method was developed for allergens analysis using α-casein as the biomarker for cow's milk detection, to be used directly in final rinse samples of cleaning in place systems (CIP) of food manufacturers. A Surface Plasmon Resonance (SPR) sensor chip consisting of four sensing arrays enabling the measurement of samples and control binding events simultaneously on the sensor surface was employed in this work. SPR offers several advantages in terms of label free detection, real time measurements and superior sensitivity when compared to ELISA based techniques. The gold sensor chip was used to immobilise α-casein-polyclonal antibody using EDC/NHS coupling procedure. The performance of the assay and the sensor was first optimised and characterised in pure buffer conditions giving a detection limit of 58ngmL^-1 as a direct binding assay. The assay sensitivity can be further improved by using sandwich assay format and amplified with nanoparticles. However, at this stage this is not required as the detection limit achieved exceeded the required allergens detection levels of 2µgmL^-1 for α-S1-casein. The sensor demonstrated good selectivity towards the α-casein as the target analyte and adequate recoveries from CIP final rinse wash samples. The sensor would be useful tool for monitoring allergen levels after cleaning procedures, providing additional data that may better inform upon wider food allergen risk management decision(s) that are made by food manufacturer. In particular, this sensor could potentially help validate or optimise cleaning practices for a given food manufacturing process.