Environ Pollut. 2018 Dec 01. pii: S0269-7491(18)34134-4. [Epub ahead of print]246
45-52
Exposure to airborne particulate matter (PM) 2.5 induced various adverse health effects, such as metabolic syndrome, systemic inflammation and respiratory infection. However, a global influence of PM2.5-induced metabolic and proteomic disorders remains confusing, and the underlying mechanism is still under-explored. Herein, LC-MS/MS-based metabolomics, lipidomics and isobaric tags for relative and absolute quantification (iTRAQ)-based proteomics were applied to analyze the toxicological characteristics of PM2.5 from Taiyuan City in China (Taiyuan-PM2.5) on human lung carcinoma cells (A549) after the 24-h treatment. Metabolites, lipids and proteins that have distinctive differences were screened by SIEVE, LipidSearch and Proteome Discoverer, respectively. The abundance of 56 metabolites (40 increased and 16 decreased), 22 lipids (19 increased and 3 decreased) and 81 proteins (55 up-regulated and 26 down-regulated) were significantly changed upon the PM2.5 treatment. Among the proteomics analysis, 16 proteins were specifically related to RNA splicing, mainly including up-regulated serine/arginine-rich splicing factor 1 (SRSF1), SRSF2, small nuclear ribonucleoprotein 70 kDa (snRNP70), small nuclear ribonucleoprotein polypeptide B (SNRPB), SNRPC, SNRPE and down-regulated heterogeneous nuclear ribonucleoprotein U-like 2 (hnRNP UL2). At the metabolic level, PM2.5 exposure significantly altered the sphingolipid metabolism, including ceramide, serine, sphingosine and sphingomyelin. It was proposed that excessive accumulation of ceramide and expression of key enzymes (ceramide synthases, phingomyelinase, sphingosine kinase types 2 and protein phosphatase-1) induced the secretion of pro-inflammatory cytokines, generation of lipotoxicity and alterations of RNA splicing in PM2.5-treated A549 cells. In general, our results demonstrated that ceramide accumulation and altered RNA splicing could becritical contributors to PM2.5-induced cytotoxicity at metabolic and proteomic level, which might be considered as potential markers for toxicological evaluation of PM2.5 samples.
Keywords: Human lung carcinoma cells; LC-MS/MS; Lipidomics; Metabolomics; Proteomics