The Analysis of Allergens in Raw and Roasted Peanuts Using nanoACQUITY UPLC and Xevo Q-Tof MS

Significance of the Topic

The prevalence of food allergies has risen sharply in recent decades, creating significant public health concerns. Peanut allergy, in particular, is widespread and can trigger life-threatening anaphylaxis. Reliable detection and quantification of peanut allergenic proteins, such as Ara h1, are essential to ensure consumer safety and to support regulatory compliance.

Objectives and Study Overview

This study evaluates a bottom-up proteomics workflow combining nanoACQUITY UPLC with Xevo Q-Tof MS and ProteinLynx Global SERVER (PLGS). The goals are:

• To identify and characterize unmodified and modified peptides of the major peanut allergen Ara h1 in raw and roasted samples.
• To assess the reproducibility and sequence coverage achievable with data-independent MS^E acquisition.
• To establish candidate marker peptides for routine allergen monitoring.
• To demonstrate label-free quantification of Ara h1 in a complex food matrix using an internal ADH standard.

Methodology and Instrumentation

A three-part sample preparation was employed:

1. Protein extraction of Ara h1 from raw and roasted peanut flours using Tris buffer and ammonium sulfate precipitation.
2. Tryptic digestion facilitated by RapiGest SF, reduction/alkylation, and overnight digestion at 37 °C.
3. Spike-in of yeast alcohol dehydrogenase (ADH) as internal standard for quantification and preparation of peanut-in-matrix at 1:200 (v/v).

Chromatography and mass spectrometry details:

• LC: nanoACQUITY UPLC system with BEH C18 column (75 µm×150 mm), 35 °C, 300 nL/min gradient from 95% A (0.1% FA/water) to 20% A over 54 min.
• MS: Xevo Q-Tof in ESI+ mode, alternating low (6 V) and high (15–40 V) collision energy (MS^E), scan range 50–2000 m/z, lock mass at 785.8426.
• Data processing: PLGS with Swiss-Prot database, fixed carbamidomethyl (C), variable acetyl (N-term), deamidation (N/Q), Met-oxidation, hydroxy (P), plus N-linked glycosylation.

Used Instrumentation

• nanoACQUITY UPLC System (Waters Corporation)
• Xevo Q-Tof MS (Waters Corporation)
• ProteinLynx Global SERVER Software (Waters Corporation)

Key Results and Discussion

Reproducible chromatographic profiles were obtained across replicate injections of raw peanut digest. MS^E acquisition enabled synchronous collection of precursor and fragment ion data, enhancing peptide identification confidence.

• Sequence coverage: 64.0% (49 peptides) in raw and 60.3% (55 peptides) in roasted Ara h1.
• High-confidence assignment of both unmodified and modified peptides supported by retention time alignment and fragment matching.
• Relative intensity profiling highlighted three robust marker peptides present in raw and roasted samples: NNPFYFPSR, DLAFPGSGEQVEK, and VLLEENAGGEQEER.
• Quantification in complex matrix: Ara h1 detected at 10 fmol with 26% coverage in the presence of E. coli digest, using ADH top-three peptides for label-free calibration.

Benefits and Practical Applications

• Single-platform detection of multiple allergenic markers with high specificity and minimal false positives.
• Capability to identify natural and processing-induced peptide modifications.
• Label-free quantification without the need for isotopically labeled standards.
• Applicability to raw and processed food matrices for quality control and regulatory testing.

Future Trends and Opportunities

Integration of high-resolution MS and data-independent acquisition will expand multiplexed allergen screening. Advances in bioinformatics will refine peptide marker selection and improve throughput. Emerging workflows may enable simultaneous quantification of multiple allergens at trace levels, supporting real-time monitoring in food production.

Conclusion

The described nanoACQUITY UPLC–Xevo Q-Tof MS^E workflow, combined with PLGS informatics, delivers sensitive, reproducible, and comprehensive analysis of peanut allergen Ara h1. It identifies key peptide markers in raw and roasted samples and enables accurate label-free quantification in complex matrices, making it well-suited for food allergy testing and compliance.

Reference

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