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Proteomic profiling of fava bean tissues: Optimization of extraction method and comparative analysis using LC-MS

ABSTRACT: Fava beans (Vicia faba) have demonstrated potential to replace traditional animal-based protein sources. The quantity and quality of protein found in fava beans makes them a potential candidate for sustainable protein alternative. However, the understanding of their proteomic profile remains limited. In this study, we present an optimized proteomic workflow for fava beans, comparing the extraction efficiency of detergent-based vs chaotrope-based extraction methods. We conducted liquid chromatography-mass spectrometry (LC-MS) using data-independent acquisition (DIA) to improve coverage and analysed the protein profiles of different fava bean tissues, including dried mature beans, freeze dried fresh whole beans, outer coat, and cotyledon (core). Our results reveal significant differences in protein composition between extraction methods and bean tissues, providing insights into the most effective approach for studying fava bean proteomes. Future studies can utilize this optimized workflow for the functional characterization of fava bean proteins, advancing the exploration of sustainable plant-based protein sources. This study provides a valuable resource for advancing proteomic research of legume species, contributing to more efficient proteomic profiling in plant research.

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ORGANISM(S): Vicia Faba

TISSUE(S): Seed

SUBMITTER: Richard Wilson

LAB HEAD: Dr Richard Wilson

PROVIDER: PXD063207 | Pride | 2026-06-29

REPOSITORIES: Pride

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Project description:Some studies have shown that acute intake of high-phenol virgin olive oil reduces pro-inflammatory, pro-oxidant and pro-thrombotic states, but nowadays still remains unclear if those effects attributed to its phenolic fraction could be exerted at transcriptional level in vivo. Two virgin olive oil-based breakfasts with high (398 ppm) and low (70 ppm) content of phenolic compounds were administered to twenty patients (9 men and 11 women) with metabolic syndrome following a double-blinded random crossover design. Prior to the first breakfast intervention, participants followed a 6-week washout period in which they were instructed to not take vitamins, soy supplements, or any drug. To eliminate the potential effect that might exist in their usual dietary habits, all subjects followed a low-fat, carbohydrate rich (CHO) diet during this period and untill the end of the study. In the 24 h before each breakfast intervention, participants were instructed to avoid consuming phenol-rich foods such as fruit or juices, wine, grape juice, chocolate, coffee, tea, olive oil, or soya, and to refrain from intense physical exercise during that period. After a 12 h fasting and following a randomized sequential crossover design with one-week washout period, participants reported to the hospital and received two fat meals consisting of 60 g of white bread, 40 mL of VOO (CANOLIVA®, Antonio Cano e Hijos™, Córdoba, Spain) with high (398 ppm) or low (70 ppm) content in phenolic compounds, and 60,000 IU of vitamin A per m2 of body surface. Olive oil with low content in phenolic compounds was obtained as a result of extraction by physical procedures of most of the phenolic compounds in the high-phenol olive oil, so that both oils kept a similar composition of the remaining macro- and micronutrients. Throughout the 4-h duration of the study, the subjects performed no physical activity, nor did they consume anything but water. Gene expression was performed on peripheral blood mononuclear cells (PBMCs) at postprandial period (4 hours after breakfast) by microarray analysis and verified by qRT-PCR. Two sets of dye-swaped experiments were performed making a total of four technical replicates per subject. Each of the hybridizations compared total RNA from PBMCs obtained 4h after the intake of virgin olive oil with high phenolic content vs. total RNA from PBMCs obtained 4h after low-phenol virgin olive oil consumption.

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Proteomic profiling of fava bean tissues: Optimization of extraction method and comparative analysis using LC-MS

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