Background: Proteins are vital for physiological functions in organisms and their accurate quantification in terms of amino acid (AA) profile in food samples is crucial for safety and quality control. Typically, methodologies involve hydrolyzing peptide bonds to release AAs, followed by their separation, detection, and quantification. However, many pretreatment protocols require up to 72 h. Most contemporary methods depend on liquid chromatography for the separation process, which is particularly challenging and time-consuming due to their diverse chemical properties. Results: Hydrolysis was performed in a microwave oven and the conditions were optimized using a full factorial experimental design considering temperature and time as variables. The chromatographic separation of AAs was achieved using a Poroshell 120 HILIC-OH5 column. Our protocol showed limits of detection and quantification below 22 and 75 ng/mL, respectively. The hydrolysis time was reduced to 50 min at 170 °C, and separation of underivatized AAs was accomplished in less than 10 min. The method was validated on a Standard Reference Material® and applied on various commercial products, including soybean, hemp, rice, pea, and chickpea flours, two types of animal feed, infant biscuits, and Parmesan cheese. Additionally, the ability of principal component analysis of the AA profiles to differentiate between distinct classes of materials was tested. Significance: The proposed analytical method for quantifying amino acids in food samples combines the use of a chromatographic column developed for non-derivatized amino acid separation with optimized hydrolysis via a full factorial design. This approach maximizes protein-to-amino acid conversion and reduces digestion time. The method demonstrated performances competitive with the latest and most sensitive protocols, while offering significantly shorter analysis times.

Quantification of amino acids in food samples using microwave-assisted digestion and hydrophilic interaction liquid chromatography (HILIC) coupled with mass spectrometry

Nasa, Jacopo La;Vaselli, Alessio;Degano, Ilaria;Bonaduce, Ilaria
2025-01-01

Abstract

Background: Proteins are vital for physiological functions in organisms and their accurate quantification in terms of amino acid (AA) profile in food samples is crucial for safety and quality control. Typically, methodologies involve hydrolyzing peptide bonds to release AAs, followed by their separation, detection, and quantification. However, many pretreatment protocols require up to 72 h. Most contemporary methods depend on liquid chromatography for the separation process, which is particularly challenging and time-consuming due to their diverse chemical properties. Results: Hydrolysis was performed in a microwave oven and the conditions were optimized using a full factorial experimental design considering temperature and time as variables. The chromatographic separation of AAs was achieved using a Poroshell 120 HILIC-OH5 column. Our protocol showed limits of detection and quantification below 22 and 75 ng/mL, respectively. The hydrolysis time was reduced to 50 min at 170 °C, and separation of underivatized AAs was accomplished in less than 10 min. The method was validated on a Standard Reference Material® and applied on various commercial products, including soybean, hemp, rice, pea, and chickpea flours, two types of animal feed, infant biscuits, and Parmesan cheese. Additionally, the ability of principal component analysis of the AA profiles to differentiate between distinct classes of materials was tested. Significance: The proposed analytical method for quantifying amino acids in food samples combines the use of a chromatographic column developed for non-derivatized amino acid separation with optimized hydrolysis via a full factorial design. This approach maximizes protein-to-amino acid conversion and reduces digestion time. The method demonstrated performances competitive with the latest and most sensitive protocols, while offering significantly shorter analysis times.
2025
Nasa, Jacopo La; Vaselli, Alessio; Caroti, Giulia; Rota, Gianpaolo; Carnaroglio, Diego; Degano, Ilaria; Bonaduce, Ilaria
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1330738
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