Milk lipids are fundamental to the nutritional quality, functional properties, and processing behavior of dairy products. In this study, we employed an untargeted lipidomics approach based on ultra-high-performance liquid chromatography coupled with ultra-high-performance liquid chromatography–high-resolution mass spectrometry (UHPLC-HRMS) to systematically characterize the lipid profiles of ten milk types from eight animal species, including camel, mare, donkey, goat, buffalo, yak, Jersey, and Holstein. A total of 640 lipid species were identified, spanning triglycerides (TGs), phospholipids (PLs), sphingolipids (SPs), ceramides (Cer), wax esters (WEs), and other subclasses. A statistical analysis revealed significant differences in lipid types and abundances among the milk samples. Camel milk exhibited the highest lipid diversity, with notable enrichment in phospholipids and sphingolipids, conferring superior emulsifying properties and stability. Mare milk was rich in polyunsaturated fatty acids (PUFAs), such as linoleic acid and alpha-linolenic acid, making it ideal for developing health-focused dairy products. Despite having the lowest total lipid content, donkey milk was enriched in cholesterol esters and PUFA, suitable for low-fat functional dairy products. Goat milk featured a balanced lipid composition with higher levels of medium-chain fatty acids (MCFAs), promoting digestibility. Buffalo milk was characterized by high TG and wax ester (WE) levels, offering high energy density and suitability for rich dairy products. Yak milk contained higher levels of ceramides (Cer) and saturated fatty acids, reflecting adaptations to high-altitude environments. Jersey milk and Holstein milk displayed similar lipid profiles, with stable compositions suitable for versatile dairy product development. Principal component analysis (PCA), hierarchical clustering, and volcano plot analyses further confirmed species-specific lipidomic signatures and revealed several potential lipid biomarkers, such as LPC (O-16:0) in Hongyuan yak milk, suggesting applications in geographical indication (GI) traceability. This study offers a comprehensive lipidomic landscape across diverse milk sources, providing molecular insights to guide the development of tailored, functional, and regionally branded dairy products.

Lung cancer is the most common primary malignant lung tumor. However, the etiology of lung cancer is still unclear. Fatty acids include short-chain fatty acids (SCFAs) and polyunsaturated fatty acids (PUFAs) as essential components of lipids. SCFAs can enter the nucleus of cancer cells, inhibit histone deacetylase activity, and upregulate histone acetylation and crotonylation. Meanwhile, PUFAs can inhibit lung cancer cells. Moreover, they also play an essential role in inhibiting migration and invasion. However, the mechanisms and different effects of SCFAs and PUFAs on lung cancer remain unclear. Sodium acetate, butyrate, linoleic acid, and linolenic acid were selected to treat H460 lung cancer cells. Through untargeted metabonomics, it was observed that the differential metabolites were concentrated in energy metabolites, phospholipids, and bile acids. Then, targeted metabonomics was conducted for these three target types. Three LC-MS/MS methods were established for 71 compounds, including energy metabolites, phospholipids, and bile acids. The subsequent methodology validation results were used to verify the validity of the method. The targeted metabonomics results show that, in H460 lung cancer cells incubated with linolenic acid and linoleic acid, while the content of PCs increased significantly, the content of Lyso PCs decreased significantly. This demonstrates that there are significant changes in LCAT content before and after administration. Through subsequent WB and RT-PCR experiments, the result was verified. We demonstrated a substantial metabolic disparity between the dosing and control groups, further verifying the reliability of the method.

The important metabolic characteristics of cancer cells include increased fat production and changes in amino acid metabolism. Based on the category of tumor, tumor cells are capable of synthesizing as much as 95% of saturated and monounsaturated fatty acids through de novo synthesis, even in the presence of sufficient dietary lipid intake. This fat transformation starts early when cell cancerization and further spread along with the tumor cells grow more malignant. In addition, local catabolism of tryptophan, a common feature, can weaken anti-tumor immunity in primary tumor lesions and TDLN. Arginine catabolism is likewise related with the inhibition of anti-tumor immunity. Due to the crucial role of amino acids in tumor growth, increasing tryptophan along with arginine catabolism will promote tumor growth. However, immune cells also require amino acids to expand and distinguish into effector cells that can kill tumor cells. Therefore, it is necessary to have a deeper understanding of the metabolism of amino acids and fatty acids within cells. In this study, we established a method for the simultaneous analysis of 64 metabolites consisting of fatty acids and amino acids, covering biosynthesis of unsaturated fatty acids, aminoacyl-tRNA biosynthesis, and fatty acid biosynthesis using the Agilent GC-MS system. We selected linoleic acid, linolenic acid, sodium acetate, and sodium butyrate to treat H460 cells to validate the current method. The differential metabolites observed in the four fatty acid groups in comparison with the control group indicate the metabolic effects of various fatty acids on H460 cells. These differential metabolites could potentially become biomarkers for the early diagnosis of lung cancer.