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2023-01-01

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cc-by (c) Galindo-Luján, Rocío et al., 2023
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/199375

A Proteomics Data Mining Strategy for the Identification of Quinoa Grain Proteins with Potential Immunonutritional Bioactivities

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https://doi.org/10.3390/foods12020390

Abstract

Quinoa proteins are attracting global interest for their wide amino acid profile and as a promising source for the development of biomedical treatments, including those against immunemediated diseases. However, information about the bioactivity of quinoa proteins is scarce. In this study, a quinoa grain proteome map obtained by label-free mass spectrometry-based shotgun proteomics was investigated for the identification of quinoa grain proteins with potential immunonutritional bioactivities, including those related to cancer. After carefully examining the sequence similarities of the 1211 identified quinoa grain proteins against already described bioactive proteins from other plant organisms, 71, 48, and 3 of them were classified as antimicrobial peptides (AMPs), oxidative stress induced peptides (OSIPs), and serine-type protease inhibitors (STPIs), respectively, suggesting their potential as immunomodulatory, anti-inflammatory, and anticancer agents. In addition, data interpretation using Venn diagrams, heat maps, and scatterplots revealed proteome similarities and differences with respect to the AMPs, OSIPs, and STPIs, and the most relevant bioactive proteins in the predominant commercial quinoa grains (i.e., black, red, white (from Peru), and royal (white from Bolivia)). The presented proteomics data mining strategy allows easy screening for potentially relevant quinoa grain proteins and commercial classes for immunonutrition, as a basis for future bioactivity testing.

Subject

Proteòmica, Pèptids, Cereals (Aliment)

Subject (English)

Proteomics, Peptides, Grain (feed)

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Articles publicats en revistes (Enginyeria Química i Química Analítica)
Articles publicats en revistes (Institut de Recerca en Nutrició i Seguretat Alimentària (INSA·UB))

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GALINDO-LUJÁN, Rocío, et al. A Proteomics Data Mining Strategy for the Identification of Quinoa Grain Proteins with Potential Immunonutritional Bioactivities. Foods. 2023. Vol. 12, num. 2. ISSN 2304-8158. [consulted: 15 of August of 2026]. Available at: https://hdl.handle.net/2445/199375

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