Effect of High NEFA Concentration on Lipid Metabolism Disorders in Hepatocytes Based on lipidomics

Published: 15 February 2024| Version 1 | DOI: 10.17632/h6snst5hm8.1
欣怡 Fan,


Fatty liver is a common nutritional metabolic disease in periparturient dairy cows, which seriously affects their reproductive performance. During periparturient period, dairy cows are in a state of negative energy balance because they cannot meet the nutritional requirements for maintenance and lactation. As a result, non-esterified fatty acids (NEFA) are mobilized from adipose tissue, leading to an increase in NEFA concentration in the blood. When the rate of NEFA esterification into triglycerides (TAG) exceeds the rate of NEFA processing, fatty liver will form. Existing studies suggest that NEFA is closely associated with lipid metabolism disorders in hepatocytes, but it is not clear through which metabolites or metabolic pathways NEFA affects lipid metabolism disorders in hepatocytes. Therefore, the aim of this study was to investigate the effect of high concentration of NEFA on lipid metabolism in hepatocytes through the lipidomic approach and molecular biology techniques. Here, we found that NEFA (0.6-2.4 mM) significantly reduced the cell viability in a concentration-dependent manner, indicating that high concentrations of NEFA have lipotoxicity on hepatocytes. In addition, NEFA promoted TAG accumulation, increased the mRNA expression of the lipogenic molecules SREBP and FASN, and decreased the mRNA expression of lipolytic molecules CPT1A and HSL in hepatocytes. Mechanistically, the results of lipidomics analysis further showed that NEFA induced lipid metabolism disorders in hepatocytes by regulating metabolic pathways such as glycerol phospholipid metabolism, glycosyl phosphatidylinositol anchored biosynthesis, triglyceride metabolism, sphingolipid metabolism, and inositol phosphate metabolism.


Steps to reproduce

Chemicals and Reagents The mass spectrometry-pure acetonitrile, isopropanol, and chromatography-pure ammonium acetate used in this experiment were purchased from Thermo-Fisher Scientific Ultrapure water for the experiments was obtained from Millipore Reference Ultrapure Water System equipped with a 0.22 μm filter head for liquid-quantity coupling. equipped with a 0.22 μm filter head. Sample Preparation To minimize degradation, samples were thawed under an ice bath. Ten grinding beads were added to each tube of cell samples with 10 µL of deionized water and homogenize for 3 min. 300 µL of lipid extraction solvent was added and homogenized again for 3 min. The samples were vortexed and mixed at 1200 rpm for 20 min at 10°C , and then centrifuged at 4000 g for 20 min at 4°C 20 µL of supernatant was transferred to a 96-well plate and mixed with 80 µL of lipid dilution solvent for LC-MS analysis. Instrumentation This project utilized an Ultra High Performance Liquid Chromatography-Triple Quadrupole Mass Spectrometry (UPLC-TQMS) instrument for targeted lipidomic assays. System optimization and maintenance were performed every 48 hours. Analytical Quality Control Procedures Endogenous small molecule metabolites are susceptible to changes in ambient temperature and environment, and therefore, sample thawing requires that it be performed slowly on an ice bath slowly, thus avoiding changes in metabolite composition and concentration caused by activation of metabolic enzymes after the sample is sharply returned to room temperature. The reagents used for extraction were pre-frozen and stored in an ice bath. The reagents used for extraction were pre-frozen and stored in a -20°C refrigerator to avoid the exothermic addition of organic solvents to the precipitated proteins, which can lead to the degradation of small molecule metabolites in biological samples. The entire sample preparation process should be completed as quickly as possible. The entire sample preparation process should be completed as quickly as possible. There were reagent blanks and mixed QC samples before and after analyzing each batch of samples. These QCs were also added to monitor the analytical process for of possible contamination and data quality. Sample Run Order In order to eliminate errors caused by the order of the analytical process, the samples to be tested were randomized according to the group information, and QC samples, blanks, etc. were interspersed with the overall samples for testing. QC samples, blank samples, etc. were interspersed in the overall sample for testing. Sample Control Procedure Samples for each project were entered into Metabo-Profile's LIMS management system upon receipt. The system assigned a unique identifier, MP ID, that matches the original sample information. This identification was tracked throughout the experiment.


Yunnan Agricultural University