Metabolomics approach reveals high energy diet improves the quality and enhances the flavor of black Tibetan sheep meat by altering the composition of rumen microbiota

 Front. Nut. 2022

This study aims to determine the impact of dietary energy levels on rumen microbial composition and its relationship to the quality of Black Tibetan sheep meat by applying metabolomics and Pearson's correlation analyses. For this purpose, UHPLC-QTOF-MS was used to identify the metabolome, whereas 16S rDNA sequencing was used to detect the rumen microbiota. Eventually, we observed that the high energy diet group (HS) improved the carcass quality of Black Tibetan sheep and fat deposition in the longissimus lumborum (LL) compared to the medium energy diet group (MS). However, HS considerably increased the texture, water holding capacity (WHC), and volatile flavor of the LL when compared to that of MS and the low energy diet group (LS). Metabolomics and correlation analyses revealed that dietary energy levels mainly affected the metabolism of carbohydrates and lipids of the LL, which consequently influenced the content of volatile flavor compounds (VOCs) and fats. Furthermore, HS increased the abundance of Quinella, Ruminococcus 2, (Eubacterium) coprostanoligenes, and Succinivibrionaceae UCG-001, all of which participate in the carbohydrate metabolism in rumen and thus influence the metabolite levels (stachyose, isomaltose, etc.) in the LL. Overall, a high-energy diet is desirable for the production of Black Tibetan sheep mutton because it improves the mouthfeel and flavor of meat by altering the composition of rumen microbiota, which influences the metabolism in the LL.

Effects of different feeding regimes on muscle metabolism and its association with meat quality of Tibetan sheep

 Food Chem. 374, 131611, 2022

This study aimed to explore the effects of different feeding regimes on muscle metabolism and its association with meat quality of Tibetan sheep through correlation analysis of meat quality and differential metabolites using untargeted and targeted metabolomics. The untargeted metabolome was detected by UHPLC-QTOF-MS, and the targeted metabolome was detected by UHPLC-QQQ-MS (amino acids) and GC–MS (fatty acids). Based on the researched results, the nutritional quality of meat, including the content of protein and fat and the edible quality of meat, including tenderness, water holding capacity (WHC), texture, and flavor of Tibetan sheep were superior in the stall-feeding group (GBZ) than in the traditional grazing group (CBZ). In the GBZ group, the key upregulated metabolites and metabolic pathways were dominated by essential amino acids (EAAs) and amino acid metabolism as well as the key downregulated metabolites and metabolic pathways were dominated by polyunsaturated fatty acids (PUFA) and lipid metabolism. Correlation analysis showed that there was a significant correlation between the results of untargeted metabolomics and some phenotypic data, including shear force, cooking loss, drip loss, chewiness, elasticity, flavor, and the content of protein and fat. Taken together, stall-feeding would be appropriate for the production of Tibetan mutton, offering better mouthfeel and higher nutrition by altering the muscle metabolism and increasing the beneficial compound deposition in the muscle.

A review on the application of chromatographic methods, coupled to chemometrics, for food authentication

Food Control, 93, 165-182, 2018

DOI: 10.1016/j.foodcont.2018.06.015

The increase of food adulteration, inducing losing a large amount of money as well as of the confidence of consumers, has become an urgent issue for producers, researchers, governments and consumers. Chromatographic methods, in combination with chemometrics, are usually developed and applied throughout the food chain to verify the nature or origin of food, with both targeted (metabolomics) and non-targeted (profiling) approaches. Their operation, together with their advantages and drawbacks, will be discussed in this review to show strategies to solve food authentication issues.