Class Lisa-Carina, Kuhnen Gesine, Schmid Jasmin, Rohn Sascha, Kuballa Jürgen
GALAB Laboratories GmbH, Am Schleusengraben 7, 21029 Hamburg, Germany.
Hamburg School of Food Science, Institute of Food Chemistry, University of Hamburg, Grindelallee 117, 20146 Hamburg, Germany.
Foods. 2024 Oct 18;13(20):3315. doi: 10.3390/foods13203315.
The diminishing of food waste is gaining increasing importance, especially in context with a growing population and a need for the sustainable use of food resources. A more precise determination of the best-before date can contribute to this general aim. As proteoforms can be regarded as indicators for ecophysiological influences, their suitability for determining the spoilage and, consequently, the shelf-life of food is suggested. Proteoforms reflect the spoilage of food more accurately. The aim of the present study was to develop an efficient proteomics workflow to determine the shelf-life of milk as a prominent target. In this case, raw milk was chosen as model, as it degrades much faster. The integration of different multivariate analysis techniques was used to analyze the spoilage of raw milk with regard to aspects of its proteome. As the feasibility of such an approach has already been demonstrated in previous studies, it is further necessary to enable a robust and reproducible workflow, primarily gaining appropriate numbers and amounts of peptides when the research question differs and other dairy products are evaluated. In the present study, two approaches for gaining peptides were considered: In addition to a direct hydrolysis of a protein-rich sample solution, in-gel hydrolysis is another common approach in proteomics. By separating the proteins in a traditional gel electrophoresis before hydrolysis, the change in the individual proteins and, consequently, potential peptides can be monitored more specifically during storage. However, the traditional approach offers not only possibilities but also limitations that must be considered. The study showed that it is beneficial to apply a combination of different application strategies, as they complement each other and can thus increase the information content of a sample or confirm a theory. Mass spectrometric features, which represent a chemical-structural change of all kinds of compounds during storage, were selected, and three of them were identified as peptides, originating from α-s1-casein.
减少食物浪费变得越来越重要，特别是在人口不断增长以及需要可持续利用食物资源的背景下。更精确地确定保质期有助于实现这一总体目标。由于蛋白质变体可被视为生态生理影响的指标，因此建议其适用于确定食物的变质情况以及保质期。蛋白质变体能更准确地反映食物的变质情况。本研究的目的是开发一种高效的蛋白质组学工作流程，以确定作为主要目标的牛奶的保质期。在这种情况下，选择生牛奶作为模型，因为它变质更快。整合不同的多变量分析技术，从蛋白质组方面分析生牛奶的变质情况。由于此前的研究已经证明了这种方法的可行性，因此进一步需要建立一个稳健且可重复的工作流程，特别是当研究问题不同且评估其他乳制品时，要获得合适数量和量的肽段。在本研究中，考虑了两种获取肽段的方法：除了直接水解富含蛋白质的样品溶液外，胶内水解是蛋白质组学中的另一种常用方法。通过在水解前在传统凝胶电泳中分离蛋白质，可以在储存过程中更具体地监测单个蛋白质以及潜在肽段的变化。然而，传统方法不仅有优势，也有必须考虑的局限性。研究表明，应用不同的应用策略组合是有益的，因为它们相互补充，从而可以增加样品的信息含量或证实一种理论。选择了代表储存过程中各种化合物化学结构变化的质谱特征，其中三个被鉴定为源自α-s1-酪蛋白的肽段。
