Chemical Analysis Combined with Multivariate Statistical Methods to Determine the Geographical Origin of Milk from Four Regions in China.

Traceability of milk origin in China is conducive to the implementation of the protection of regional products. In order to distinguish milk from different geographical distances in China, we traced the milk of eight farms in four neighboring provinces of China (Inner Mongolia autonomous region, Hebei, Ningxia Hui autonomous and Shaanxi), and multivariate data analysis was applied to the data including elemental analysis, stable isotope analysis and fatty acid analysis. In addition, orthogonal partial least squares discriminant analysis (OPLS-DA) is used to determine the optimal classification model, and it is explored whether the combination of different technologies is better than a single technical analysis. It was confirmed that in the inter-provincial samples, the combination of the two techniques was better than the analysis using a single technique (fatty acids: R2 = 0.716, Q2 = 0.614; fatty acid-binding isotopes: R2 = 0.760, Q2 = 0.635). At the same time, milk produced by farms with different distances of less than 11 km in each province was discriminated, and the discriminant distance was successfully reduced to 0.7 km (Ningxia Hui Autonomous Region: the distance between the two farms was 0.7 km, R2 = 0.771, Q2 = 0.631). For short-distance samples, the combination multiple technologies are not completely superior to a single technique, and sometimes, it is easy to cause model over-fitting.

Establishing an untargeted-to-MRM liquid chromatography-mass spectrometry method for discriminating reconstituted milk from ultra-high temperature milk.

The counterfeit use of reconstituted milk to simulate fresh milk in some countries is largely driven by profiteering; hence, establishing a robust market-surveillance method is an important objective. In this study, an untargeted metabolomics approach that uses ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) was established to discover biomarkers that can be used to classify UHT and reconstituted milk. Furthermore, 36 positive- and 24 negative-ionization mode features were selected as candidate markers to establish a UPLC-tandem mass spectrometry (UPLC-MS/MS) multiple reaction monitoring (MRM) method. The support vector machine (SVM) method was used to process the responses of the selected potential markers, and 100% classifiability was observed. The marker metabolites could be divided into three categories by hierarchical clustering analysis: peptides, lipids, and nucleic acids. The results suggest that the untargeted-to-MRM metabolomics method is an effective tool for distinguishing between UHT and reconstituted milk.

Endogenous Indole Pyruvate Pathway for Tryptophan Metabolism Mediated by IL4I1.

l-tryptophan (Trp) is widely used in food and feed enforcement to play an important role in biological processes. Various metabolites of Trp perform its potent function. The indole pyruvate pathway is one of the main pathways of Trp metabolism in the gut microbiota, providing numerous indole-derivatives, which can modulate intestinal homeostasis and mucosal immunity by activating the aryl hydrocarbon receptor (AHR) signaling pathway. In this study, we constructed an IL4I1-overexpressed 293T cell line and found that IL4I1 can catalyze Trp to produce indole-3-acetic acid (IAA) and indole-3-carboxaldehyde (IAld). Moreover, both IAA and IAld are accumulated in dendritic cells (DCs) and can stimulate the expression of CYP1A1. Our results demonstrate the existence of the indole pyruvate pathway in host cells with IL4I1 as the key enzyme. The IL4I1-mediated Trp metabolism implies the role of dietary impact on immunity.

Determination of the levels of tryptophan and 12 metabolites in milk by liquid chromatography-tandem mass spectrometry with the QuEChERS method.

Tryptophan and metabolites have important biological functions in humans. Milk is an important source of tryptophan intake. In this study, we developed a method to detect levels of tryptophan and 12 metabolites in milk. The analytes were extracted by using the QuEChERS (quick, easy, cheap, effective, rugged, and safe) procedure and analyzed by liquid chromatography-tandem mass spectrometry with electrospray ionization. The proposed method resulted in suitable accuracy (standard deviation ≤10.31%) and high sensitivity (the limits of quantification were between 0.05 and 5 ng/mL). Recoveries were in the range of 44 to 126%. Finally, the developed method was successfully applied to compare the content of tryptophan and metabolites in 4 milk products produced by different processes: pasteurized milk, UHT milk, milk powder, and yogurt. The results of partial least squares-discriminant analysis (PLS-DA) showed that different types of processed milk could be distinguished clearly according to the method used here. The determined tryptophan and metabolites levels in milk can provide a new reference for evaluation of milk.

The combined use of 1 H and 2D NMR-based metabolomics and chemometrics for non-targeted screening of biomarkers and identification of reconstituted milk.

BACKGROUND: The illegal undeclared addition of reconstituted milk powder to ultra-heat treated (UHT) milk to lower production costs is an example of economically motivated adulteration. This activity not only defrauds consumers but also places honest traders at a disadvantage, which could damage the reputation of milk producers and reduce the integrity of the markets. In this research, a non-targeted analytical strategy that combines proton (1 H) nuclear magnetic resonance (NMR) spectroscopy with a chemometrics data mining tool was developed for the authentication of bovine UHT milk. RESULTS: Unsupervised principal component analysis was used to distinguish UHT and tap-water-reconstituted powdered milk. Partial least squares-discriminant analysis (PLS-DA) with R2 (Y) and Q2 equal to 0.859 and 0.748, respectively, was used to differentiate UHT and reconstituted milk samples. Three compounds were selected as biomarkers to distinguish UHT and reconstituted milk and identified according to the standard NMR-spectra database. Finally, a PLS-DA model was established, according to the characteristic spectral bands, to identify UHT milk and reconstituted milk. CONCLUSION: This procedure demonstrated the feasibility of using non-targeted NMR profiling combined with chemometric analysis to combat mislabeling and fraudulent practices in milk production. © 2019 Society of Chemical Industry.