Innovative Application of Metabolomics on Bioactive Ingredients of Foods

Abstract

Metabolomics, as a new omics technology, has been widely accepted by researchers and has shown great potential in the field of nutrition and health in recent years. This review briefly introduces the process of metabolomics analysis, including sample preparation and extraction, derivatization, separation and detection, and data processing. This paper focuses on the application of metabolomics in food-derived bioactive ingredients. For example, metabolomics techniques are used to analyze metabolites in food to find bioactive substances or new metabolites in food materials. Moreover, bioactive substances have been tested in vitro and in vivo, as well as in humans, to investigate the changes of metabolites and the underlying metabolic pathways, among which metabolomics is used to find potential biomarkers and targets. Metabolomics provides a new approach for the prevention and regulation of chronic diseases and the study of the underlying mechanisms. It also provides strong support for the development of functional food or drugs. Although metabolomics has some limitations such as low sensitivity, poor repeatability, and limited detection range, it is developing rapidly in general, and also in the field of nutrition and health. At the end of this paper, we put forward our own insights on the development prospects of metabolomics in the application of bioactive ingredients in food.

A Novel Strategy for Mixed Jam Evaluation: Apparent Indicator, Sensory, Metabolomic, and GC-IMS Analysis

“…Sample solutions were ground in a frozen tissue grinder for 6 min (−10 • C, 50 Hz), followed by low-temperature ultrasonic extraction for 30 min (5 • C, 40 kHz). The samples were allowed to stand at −20 • C for 30 min, followed by centrifugation for 15 min (4 • C, 13,000× g) [5]. The supernatant was pipetted into an injection vial with an internal cannula for analysis.…”

“…The stability of the model was assessed using principal component analysis (PCA) and orthogonal least squares discriminant analysis (OPLS-DA) with seven cycles of crossvalidation [5]. The selection of significantly different metabolites was determined based on the variable weight (variable importance in projection [VIP]) values obtained from the OPLS-DA model and the p-value obtained from the student's t-test.…”

“…To reduce the dimensionality and increase the interpretability and validity of the data, multivariate statistical analysis techniques, including principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) modeling, were applied to the processed metabolite lists for further analysis. The projected score values of the samples on the plane formed by the first principal component (PC1) and the second principal component (PC2) are the spatial coordinates, which can intuitively reflect the similarity or difference between the samples [5,37]. Dimensionality reduction analysis revealed relative coordinate points on the principal components p1 and p2.…”

“…The field of metabolomics, which is an integral component of systems biology, focuses on the comprehensive analysis of small molecule metabolites and their dynamic alterations within living organisms, specific tissues, and individual cells [4]. Metabolites include a wide range of compounds such as sugars, amino acids, organic acids, secondary metabolites (e.g., alkaloids and flavonoids), and lipids [5]. In recent years, metabolomics has been widely used for food component analysis.…”

Assessment of the Bioaccessibility of Carotenoids in Goji Berry (Lycium barbarum L.) in Three Forms: In Vitro Digestion Model and Metabolomics Approach

“…Metabolomic methods are fundamental apparatuses in the food sector to identify metabolites and perform subjective and quantitative analyses [ 9 , 10 ]. Detection systems, such as LC−MS, HPLC−ESI/APCI−MS, and UPLC−LTQ−MS, with high detection sensitivity and phenomenal detachment execution, are commonly used to detect small molecule metabolites in fruits [ 11 , 12 ]. Among them, ESI and APCI techniques are relatively more suitable soft ionization techniques for the analysis of protonated molecular ions of the most relevant plant secondary metabolites, and numerous studies have demonstrated their superiority for several identification errands [ 13 ].…”