Proteomics and Food Analysis: Principles, Techniques, and Applications

Quality assessment of variable collagen tissues of sea cucumber (Stichopus japonicus) body wall under different heat treatment durations by label-Free proteomics analysis

The microstructure of the body wall, body wall composition, and collagen fibers of sea cucumber (Stichopus japonicus) under different heating times (1 h, 4 h, 12 h, and 24 h) was investigated based on heat treatment at 80 °C. A Label-Free proteomics technique was applied to study the proteomic changes in the body wall of sea cucumbers under 4 and 12 h of heat treatment. Compared with the fresh group, 981 proteins were found to be differentially expressed proteins (DEPs) after heat treatment at 80 °C (4 h), and 1110 DEPs were observed after heat treatment at the same temperature for 12 h. There were 69 DEPs associated with mutable collagenous tissues (MCTs) structures. The results of correlation analysis showed that 55 DEPs were correlated with sensory properties, among which A0A2G8KRV2 was significantly correlated with hardness and SEM image texture features (SEM_Energy, SEM_Correlation, SEM_Homogeneity, and SEM_Contrast). These findings could be conducive to further comprehension of the structural changes and mechanisms of quality loss in the body wall of sea cucumbers at different heat treatment times.

A Coding Basis and Three-in-One Integrated Data Visualization Method 'Ana' for the Rapid Analysis of Multidimensional Omics Dataset

With innovations and advancements in analytical instruments and computer technology, omics studies based on statistical analysis, such as phytochemical omics, oilomics/lipidomics, proteomics, metabolomics, and glycomics, are increasingly popular in the areas of food chemistry and nutrition science. However, a remaining hurdle is the labor-intensive data process because learning coding skills and software operations are usually time-consuming for researchers without coding backgrounds. A MATLAB^® coding basis and three-in-one integrated method, 'Ana', was created for data visualizations and statistical analysis in this work. The program loaded and analyzed an omics dataset from an Excel^® file with 7 samples * 22 compounds as an example, and output six figures for three types of data visualization, including a 3D heatmap, heatmap hierarchical clustering analysis, and principal component analysis (PCA), in 18 s on a personal computer (PC) with a Windows 10 system and in 20 s on a Mac with a MacOS Monterey system. The code is rapid and efficient to print out high-quality figures up to 150 or 300 dpi. The output figures provide enough contrast to differentiate the omics dataset by both color code and bar size adjustments per their higher or lower values, allowing the figures to be qualified for publication and presentation purposes. It provides a rapid analysis method that would liberate researchers from labor-intensive and time-consuming manual or coding basis data analysis. A coding example with proper code annotations and completed user guidance is provided for undergraduate and postgraduate students to learn coding basis statistical data analysis and to help them utilize such techniques for their future research.

Paleoproteomics

Paleoproteomics, the study of ancient proteins, is a rapidly growing field at the intersection of molecular biology, paleontology, archaeology, paleoecology, and history. Paleoproteomics research leverages the longevity and diversity of proteins to explore fundamental questions about the past. While its origins predate the characterization of DNA, it was only with the advent of soft ionization mass spectrometry that the study of ancient proteins became truly feasible. Technological gains over the past 20 years have allowed increasing opportunities to better understand preservation, degradation, and recovery of the rich bioarchive of ancient proteins found in the archaeological and paleontological records. Growing from a handful of studies in the 1990s on individual highly abundant ancient proteins, paleoproteomics today is an expanding field with diverse applications ranging from the taxonomic identification of highly fragmented bones and shells and the phylogenetic resolution of extinct species to the exploration of past cuisines from dental calculus and pottery food crusts and the characterization of past diseases. More broadly, these studies have opened new doors in understanding past human-animal interactions, the reconstruction of past environments and environmental changes, the expansion of the hominin fossil record through large scale screening of nondiagnostic bone fragments, and the phylogenetic resolution of the vertebrate fossil record. Even with these advances, much of the ancient proteomic record still remains unexplored. Here we provide an overview of the history of the field, a summary of the major methods and applications currently in use, and a critical evaluation of current challenges. We conclude by looking to the future, for which innovative solutions and emerging technology will play an important role in enabling us to access the still unexplored "dark" proteome, allowing for a fuller understanding of the role ancient proteins can play in the interpretation of the past.