More dry goods and surprise gifts.
Guo Teng. Food characterization and authenticity identification have become emerging research hotspots and important research contents in the field of food quality and safety, and new technologies and methods applied to food counterfeiting are emerging. Omics technology is a research method widely used in the field of biological sciences, including genomics, transcriptomics, proteomics and metabolomics, which can help scientists conduct a comprehensive analysis of food samples at the molecular level, help determine the composition and changes of food, and thus judge its authenticity and quality.
Proteomics-based meat identification technology.
Proteomics studies the existence and activity of the overall level of protein under specific conditions, which can not only identify protein types, but also quantify proteins, and provide a new idea for analyzing the protein composition and content of food in different species, origins and maturity stages. Proteomics based on high-resolution mass spectrometry technology has developed rapidly in recent years, and thousands of proteins can be identified in a single experiment, which has become a powerful research method in food safety control. At present, proteomics has been applied in many fields such as species identification, origin tracing, quality research, adulteration and counterfeiting.
In recent years, meat adulteration incidents have emerged one after another, driven by interests, illegal businesses use cheap chicken, duck, pork, horse meat and other forged beef and mutton products, which seriously infringes on the rights and interests of consumers and the fair trade of food, and at the same time brings great hidden dangers to food safety. Our Hydromics Applications team uses the Orbitrap Exploris 480 ultra-high-resolution mass spectrometer system for data acquisition based on data-dependent mode (DDA) in combination with Proteome Discoverer 30Software for non-labeled quantitative protein identification and analysis of porcine, cattle and mutton samples, screening the characteristic peptides of different meats and identifying the species of meat according to the characteristic peptides to improve the accuracy of identification, and provide technical support for the detection of meat adulteration. Table 1 shows the data-dependent acquisition mode (DDA) for the identification of 500 ng of porcine, bovine, and mutton samples with sheet matching spectra (PSM), which belonged to peptide groups, and protein groups were identified in porcine, bovine, and sheep samples. Orbitrap high-resolution mass spectrometry was used to identify samples of different species, which greatly enriched the information of proteins and peptides in the analysis results, and provided sufficient data for the subsequent screening of species-specific peptides.
Subsequently, through comparative analysis of the list of proteins and peptides in porcine, cattle and sheep samples, 10 characteristic peptides were identified in pork samples, 10 characteristic peptides in beef samples, and 7 characteristic peptides in mutton samples. These characteristic peptides are mainly derived from the peak proteins in meat, such as myosin, myoglobin, hemoglobin, and heat shock protein, which are species-specific and can be used for the qualitative and quantitative analysis of subsequent meat adulteration. Figure 1 shows the precursor ion chromatography mass spectral extraction peak and its secondary fragment ion mass spectrum of myoglobin characteristic peptide in different species as an example, the measured m z of the fragment ion has a small deviation from the theoretical m z, and the spectral quality is high, which can be used as a reference for subsequent qualitative and quantitative analysis and identification.
Fig.1 Chromatographic mass spectrometry extraction peaks and mass spectra of myoglobin protein characteristic peptides of different species.
In order to simulate the real adulterated samples, the pork samples were mixed into the beef and mutton samples in different proportions, and the pig:cattle:mutton mixed samples were prepared in a 1:1:1 mass ratio, the pig:cattle mixed samples were prepared in a 1:1 ratio, and the pig:sheep mixed samples were prepared in a 1:1 ratio. These samples were collected using label-free quantitative proteomics and then quantified by Proteome Discoverer software to quantify changes in protein abundance in meat samples.
The peptide abundance intensity information was counted for 3 technical replicates for each sample described above, and Figure 2a shows that the peptide signal intensity distribution of each group of samples fluctuates slightly, and the results have good stability and reproducibilityThe protein marker module in the Proteome Discoverer software was used to display the different species of proteins identified, taking the porcine:bovine:mutton mixed sample as an example (Fig. 2b), and the results showed that the proportion of peptides belonging to the porcine, bovine, and sheep species in the mixed sample was respectively. 36% and 3583%, which is consistent with the actual incorporation ratio. The mass spectrometry data of porcine, cattle, and mutton samples analyzed separately and mixed samples in equal proportions were preprocessed by PD software, and principal component analysis (PCA cluster analysis) was performed based on peptide abundance values. As shown in Figure 2c, the results of the three technical replicates of each group of samples were tightly aggregated, and the pure pig, beef and mutton samples were in the quadrant, indicating that there were obvious differences in peptide abundance between the three samples, and the discrimination effect was good. At the same time, we also found that samples mixed in equal proportions were also effectively distinguished from each other in PCA analysis, as well as from pure porcine, bovine, and sheep samples.
Summary:The label-free quantitative analysis scheme based on ultra-high-resolution orbitrap can identify a variety of meats at the same time, providing a powerful detection platform for meat adulteration identification, and has broad application prospects in the field of food authenticity identification.
Metabolomics-based food quality analysis and counterfeit detection technology.
The metabolome is an extension and terminal of the genome, which studies the metabolic end products of organisms that are most closely related to phenotype. Changes in the genome and proteome are not necessarily expressed and may not affect the system, but the production and metabolism of small molecules are the end result of a series of events, which can more directly and accurately reflect the changes in the sample (organism) and the differences between them. Metabolomics can be regarded as a research paradigm that characterizes the small molecule groups of substances in a sample by chemical fingerprinting with high information, so as to find differences and characterize their structuresIt is a research idea and tool strategy。In the field of food science, omics ideas have been widely used in food safety and quality research.
This is a study from National Cheng Kung University in Taiwan, which examines the changes in small molecule metabolites in fresh fish during storage based on Orbitrap high-resolution mass spectrometry QE Plus, and attempts to identify potential markers that can indicate the freshness of the fish. The experiment was carried out in three stages: the first step was to store the fish meat for 72 h at 4, and then the MS1 information of all samples at M z 70 1000 was collected in Full Scan mode, and the data were aligned, normalized and filtered to obtain 487,924,375 valid characteristic peaksIn the second step, 115 characteristic peaks common to the three batches of samples were obtained by data-dependent scanning mode (top n=10), and then identified by searching the high-resolution library, among which 8 metabolites could be regarded as potential fish freshness markersIn the third step, fresh fish meat was stored at 4 for 0h, 24h, 48h, and 72h, respectively, and the change trend of 8 markers over time was studied, and their indicative effect on fish freshness was verified. The results of the study showed that the enzymatic hydrolysis of fish lipids during storage led to the accumulation of free fatty acids linoleic acid (ALA), docosahexaenoic acid (DHA), arachidonic acid (AA) and linoleic acid (LA). With the cessation of aerobic respiration, the oxidation of fatty acids is rapidly redirected from the mitochondria to the peroxisomes, resulting in a decrease in decanoylcarnitine. Subsequently, the production of ATP stops, and a large number of degradable compounds (uracil, hypoxanthine, and inosinosine) are produced, resulting in spoilage of the fish.
In addition, many scholars have studied the origin traceability of high value-added crops, the differences of different brands of liquor or wine, the changes of small molecule groups in the process of food fermentation, the quality and adulteration of dairy products, etc., based on Orbitrap high-resolution mass spectrometry, combined with the professional metabolomics software Compound Discoverer and lipidomics software LiPidSearch, etc., and have achieved very good results and results. In summary, the basic analysis process and ideas are as follows:
Summary:Foodomics is one of the most concerned research contents in the field of food research in recent years, emphasizing the treatment of food as a whole, and the use of emerging, comprehensive and high-throughput detection technologies to present the contribution of food to human health regulation and nutritional balance as a whole, so as to break through the limitations of the traditional sense of conducting separate research on individual components in food, resulting in a large difference between the research results and the real situation. The Future of Foodomics: Multi-omics Workflow Integration. We can provide panoramic multi-dimensional omics technology to help customers achieve data discovery, multi-level data processing, and then multi-layer information mining.
If you need to cooperate** This article, please leave a message at the end of the article.
Foodomics