PROTSENS Rethinking Alternative PROTein Extraction: Decoding SENsory-Protein Extraction Relationships

PROTSENS 重新思考替代性蛋白质提取：解码感觉-蛋白质提取关系

• 批准号: EP/Z000785/1
• 负责人: Anwesha Sarkar
• 金额: $ 26.26万
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FZ000785%2F1
• 关键词: PROTSENS; Rethinking; Alternative; PROTein; Extraction

The global food system emits about 18% Green House Gas (GHGs), due to its reliance on animal-sourced ingredients such as proteins.Therefore, to reduce the environmental impact of the food system and improve sustainability, plant, insect, and microalgae-basedprotein sources are being investigated. However, these proteins suffer from poor sensory perception of bitterness and astringency,leading to poor adoption by society. Previous research projects have failed to provide mechanistic insight and strategies to minimizethese negative sensory perceptions at an ingredient level. Therefore, the question remains, whether these proteins are inherentlybitter and astringent or does the protein extraction process leads to protein modifications that cause these sensory perceptions.PROTSENS aims to understand and minimize these negative perceptions using green extraction methods that preserve proteinstructure. Protein extracts resulting from these novel processes will be thoroughly characterized. The mechanism of astringency andbitterness will be studied from macro to nanoscale using physical methods, while bitterness will be investigated using sensory cells invitro in a simulated oral environment. The in vitro, ex vivo and physical tools will serve as a novel toolbox to investigate astringencyand bitterness perception. The link between protein properties, extraction methods, and their sensory perception will be captured ina Machine Learning (ML) model. The model will provide a guide on protein extraction routes, based on protein source to preserveprotein structure and improve sensory perception. Overall, PROTSENS, through its novel experimental toolkit and ML model,improves the sensory perception of novel proteins and adoption. PROTSENS will open new horizons in European academic researchon food proteins. The success of PROTSENS will help drive the adoption of novel proteins, decrease GHGs in the food system, and helpmitigate climate change.

由于依赖蛋白质等动物来源成分，全球食品系统排放了约 18% 的温室气体 (GHG)。因此，为了减少食品系统对环境的影响并提高可持续性，植物、昆虫和微藻-正在研究基于蛋白质的来源。然而，这些蛋白质对苦味和涩味的感官感知较差，导致社会采用率较低。以前的研究项目未能提供机制见解和策略来最大限度地减少成分水平上的这些负面感官知觉。因此，问题仍然存在，这些蛋白质是否本质上是苦味和涩味的，或者蛋白质提取过程是否会导致蛋白质修饰，从而导致这些感官知觉。PROTSENS 旨在使用保留蛋白质结构的绿色提取方法来理解并最大程度地减少这些负面知觉。这些新工艺产生的蛋白质提取物将被彻底表征。将使用物理方法从宏观到纳米尺度研究涩味和苦味的机制，同时将在模拟口腔环境中使用体外感觉细胞研究苦味。体外、离体和物理工具将作为研究涩味和苦味感知的新工具箱。机器学习 (ML) 模型将捕获蛋白质特性、提取方法及其感官知觉之间的联系。该模型将根据蛋白质来源提供蛋白质提取路线指南，以保留蛋白质结构并改善感官知觉。总体而言，PROTSENS 通过其新颖的实验工具包和 ML 模型，改善了新型蛋白质的感官知觉和采用。 PROTSENS 将为欧洲食品蛋白质学术研究开辟新视野。 PROTSENS 的成功将有助于推动新型蛋白质的采用，减少食品系统中的温室气体排放，并帮助缓解气候变化。