AI Article Synopsis
- Food fraud is a significant global issue that compromises food authenticity through various factors like biological identity and geographical origin.
- Metabolic markers, discovered using untargeted metabolomics with liquid chromatography-mass spectrometry (LC-MS), are emerging as an effective method for food authentication, although there are still challenges in developing robust procedures for routine checks.
- The review outlines the process of using LC-MS for identifying metabolic markers, highlighting its effectiveness for assessing food authenticity in areas like production and freshness, while also noting the need for further evaluation and application of these markers in real food sample analyses.
Article Abstract
Food fraud is currently a growing global concern with far-reaching consequences. Food authenticity attributes, including biological identity, geographical origin, agricultural production, and processing technology, are susceptible to food fraud. Metabolic markers and their corresponding authentication methods are considered as a promising choice for food authentication. However, few metabolic markers were available to develop robust analytical methods for food authentication in routine control. Untargeted metabolomics by liquid chromatography-mass spectrometry (LC-MS) is increasingly used to discover metabolic markers. This review summarizes the general workflow, recent applications, advantages, advances, limitations, and future needs of untargeted metabolomics by LC-MS for identifying metabolic markers in food authentication. In conclusion, untargeted metabolomics by LC-MS shows great efficiency to discover the metabolic markers for the authenticity assessment of biological identity, geographical origin, agricultural production, processing technology, freshness, cause of animals' death, and so on, through three main steps, namely, data acquisition, biomarker discovery, and biomarker validation. The application prospects of the selected markers by untargeted metabolomics require to be valued, and the selected markers need to be eventually applicable at targeted analysis assessing the authenticity of unknown food samples.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1111/1541-4337.12938 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Background: There is growing interest in the role of environmental factors (i.e., exposome) in the pathogenesis of Alzheimer's diseases.
View Article and Find Full Text PDFBackground: Diet has been associated with memory, emotion/stress regulation, structure and function of the hippocampus and amygdala and attenuation of cognitive aging. There is a well-recognized lack of reliability in self-reported dietary intake and great interest in objective metabolic readout of dietary patterns. In this study we constructed dietary profiles from untargeted metabolomics data using a novel metadata-based source annotation method developed at the Dorrestein Lab, also referred to as "foodomics".
View Article and Find Full Text PDFBackground: It is now widely acknowledged that diet, lifestyle, and environmental exposures largely affect an individual's metabolic state in health and disease, including the brain. Metabolomics has demonstrated its potential to enable exciting discoveries in brain health, facilitated by advances in analytical and informatics techniques. Here, we highlighted the use of MS/MS-based untargeted metabolomics to study the diet and medication exposure of cognitively declined cohorts through the newly developed FoodMASST and DrugMASST tools.
View Article and Find Full Text PDFBackground: Alzheimer's disease (AD) is associated with impaired lipid metabolism in the brain. To identify the specific regions where pathological change to cell functionality occurs, a spatial investigation of regional lipid dysregulation is needed.
Method: We measured untargeted spatial lipidomics using Desorption Electrospray Ionization (DESI) mass spectrometry in the brains of mice from two genotypes, wild type (WT) and APPsw, an AD mouse model overexpression amyloid precursor protein (APP).
Biomarkers.
Alzheimers Dement
December 2024
Alzheimer Center Amsterdam, Amsterdam UMC, Amsterdam, Netherlands; Alzheimer Center, Department of Neurology, Amsterdam university medical center, Amsterdam, Netherlands.
Background: Disease mechanisms underlying Alzheimer's disease (AD) are heterogenous amongst patients. We recently identified five distinct AD subtypes in cerebrospinal fluid (CSF) proteomic data with data-driven techniques (Figure 1). Two of these subtypes were characterised by brain barrier dysfunction: one with choroid plexus dysfunction, and another with blood-brain barrier dysfunction.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!