Examinando por Autor "Pont, Laura"

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Comprehensive characterization of raw and processed quinoa from conventional and organic farming by label-free shotgun proteomics
(SSRN, 2024-03-27) Galindo Luján, Rocío; Pont, Laura; Minic, Zoran; Berezovski, Maxim V.; Quispe Jacobo, Fredy Enrique; Sanz Nebot, Victoria
Quinoa, a dicotyledonous plant native to the Andes, is recognized as a high-quality food due to its outstanding nutritional properties, including complete proteins. However, there is a lack of information on how the proteomic profile of raw quinoa is influenced by processing methods such as boiling and extrusion, as well as by conventional and organic farming conditions. Here, proteins from both raw (seeds and grains) and processed (boiled and extruded) white quinoa cultivated under conventional and organic farming were extracted, trypsinized, and analyzed by nanoliquid chromatography-tandem mass spectrometry (nanoLC-MS/MS). The mass spectra data were then scrutinized against a dedicated quinoa database from The National Center for Biotechnology Information via MaxQuant/Andromeda, leading to the identification and quantification of 1,796 proteins. Finally, qualitative and quantitative data interpretation tools were employed for data inspection and visualization, unveiling for the first time, similarities and differences at the proteomic level among the studied samples.
Matrix-assisted laser desorption ionization time-of-flight mass spectrometry combined with chemometrics for protein profiling and classification of boiled and extruded quinoa from conventional and organic crops
(MDPI, 2024-06-17) Galindo Luján, Rocío; Pont, Laura; Quispe Jacobo, Fredy Enrique; Sanz Nebot, Victoria; Benavente, Fernando
Quinoa is an Andean crop that stands out as a high-quality protein-rich and gluten-free food. However, its increasing popularity exposes quinoa products to the potential risk of adulteration with cheaper cereals. Consequently, there is a need for novel methodologies to accurately characterize the composition of quinoa, which is influenced not only by the variety type but also by the farming and processing conditions. In this study, we present a rapid and straightforward method based on matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) to generate global fingerprints of quinoa proteins from white quinoa varieties, which were cultivated under conventional and organic farming and processed through boiling and extrusion. The mass spectra of the different protein extracts were processed using the MALDIquant software (version 1.19.3), detecting 49 proteins (with 31 tentatively identified). Intensity values from these proteins were then considered protein fingerprints for multivariate data analysis. Our results revealed reliable partial least squares-discriminant analysis (PLS-DA) classification models for distinguishing between farming and processing conditions, and the detected proteins that were critical for differentiation. They confirm the effectiveness of tracing the agricultural origins and technological treatments of quinoa grains through protein fingerprinting by MALDI-TOF-MS and chemometrics. This untargeted approach offers promising applications in food control and the food-processing industry.