Boukid Fatma
ClonBio Group LTD, 6 Fitzwilliam Pl, Dublin D02 XE61, Ireland.
J Proteomics. 2026 Feb 9;327:105624. doi: 10.1016/j.jprot.2026.105624.
Despite rapid market growth, plant-based foods such as meat analogs, plant-based milk, yogurt alternatives, and fermented products still fall short of matching the sensory, structural, and nutritional qualities of animal-based counterparts, primarily due to simple ingredient substitution that fails to reproduce the molecular structure, interactions, and functional properties required for optimal texture, flavor, and nutritional performance. Proteomics, using advanced mass spectrometry (MS) and label-free quantification methods, provides an approach to analyze plant protein composition, structure, interactions, and modifications, enabling targeted functional improvements. This review describes how proteomic workflows inform formulation across three areas. First, protein compositional and structural characterization employs techniques such as liquid chromatography-tandem mass spectrometry (LC-MS/MS) and differential scanning calorimetry (DSC) coupled with MS to map protein composition and structural behavior, supporting decisions on protein sources, fractionation, and purification. Second, indirect proteomic methods coupled with other non-proteomic complementary tools are used to determine structure-function relationships induced by processing to examine processing-induced crosslinking, enzymatic modifications, and lipid-protein interactions that influence texture. Third, targeted MS methods, including selected reaction monitoring (SRM) and parallel reaction monitoring (PRM), are applied to profile off-flavor compounds and identify protein modification sites relevant to sensory and nutritional properties. By integrating proteomic data with processing strategies, this review outlines how proteomics can be used to examine key functional attributes related to texture, flavor, and nutritional quality in plant-based foods. SIGNIFICANCE: This review highlights the pivotal role of proteomics in advancing next-generation plant-based foods. Proteomic analysis enables an in-depth understanding of plant protein structure, composition, interactions, and bioactivity, providing critical insights for the development of functionally enhanced and consumer-acceptable alternatives. By integrating proteomics with AI, machine learning, multi-omics approaches, and cutting-edge analytical tools such as spatial proteomics and mass spectrometry imaging, the review demonstrates how protein functionality, flavor, texture, nutrition, and allergenicity can be optimized. Furthermore, it emphasizes the potential of proteomics to accelerate innovation in personalized nutrition, support sustainable and circular food systems, improve food safety, and reduce waste by valorizing plant-based by-products. This work serves as a roadmap for researchers and industry stakeholders seeking to leverage proteomics to design novel, high-quality, and sustainable plant-based protein products.
尽管市场增长迅速，但诸如肉类替代品、植物基牛奶、酸奶替代品和发酵产品等植物性食品在感官、结构和营养品质方面仍无法与动物性食品相媲美，这主要是由于简单的成分替代未能重现最佳质地、风味和营养性能所需的分子结构、相互作用和功能特性。蛋白质组学利用先进的质谱（MS）和无标记定量方法，提供了一种分析植物蛋白质组成、结构、相互作用和修饰的方法，从而实现有针对性的功能改进。本综述描述了蛋白质组学工作流程如何在三个领域为配方设计提供信息。首先，蛋白质组成和结构表征采用液相色谱-串联质谱（LC-MS/MS）和差示扫描量热法（DSC）等技术，并结合质谱来绘制蛋白质组成和结构行为图谱，为蛋白质来源、分级分离和纯化的决策提供支持。其次，间接蛋白质组学方法与其他非蛋白质组学补充工具相结合，用于确定加工过程诱导的结构-功能关系，以研究影响质地的加工诱导交联、酶促修饰和脂蛋白相互作用。第三，靶向质谱方法，包括选择反应监测（SRM）和平行反应监测（PRM），用于分析异味化合物并识别与感官和营养特性相关的蛋白质修饰位点。通过将蛋白质组学数据与加工策略相结合，本综述概述了蛋白质组学如何用于研究植物性食品中与质地、风味和营养品质相关的关键功能属性。意义：本综述强调了蛋白质组学在推动下一代植物性食品发展中的关键作用。蛋白质组学分析能够深入了解植物蛋白质的结构、组成、相互作用和生物活性，为开发功能增强且消费者可接受的替代品提供关键见解。通过将蛋白质组学与人工智能、机器学习、多组学方法以及空间蛋白质组学和质谱成像等前沿分析工具相结合，本综述展示了如何优化蛋白质功能、风味、质地、营养和致敏性。此外，它强调了蛋白质组学在加速个性化营养创新、支持可持续和循环食品系统、提高食品安全以及通过利用植物性副产品减少浪费方面的潜力。这项工作为寻求利用蛋白质组学设计新型、高质量和可持续植物性蛋白质产品的研究人员和行业利益相关者提供了路线图。
