Characterization of chemoresistant human non-small cell lung cancer cells by metabolic and lipidomic profiling.

INTRODUCTION: Lung cancer is one of the most malignant cancers and the leading cause of cancer-related deaths worldwide, while acquired chemoresistance would represent a major problem in the treatment of non-small cell lung cancer (NSCLC) because of the reduced treatment effect and increased rates of recurrence. METHODS: To establish the chemoresistant NSCLC cells, doxorubicin was treated to A549 cells over 3 months at gradually increasing concentrations from 0.03 to 0.5 µM. Real-time PCR and Western blotting were employed for investigating mRNA and protein expression of the glutathione peroxidase (GPX) protein family and multidrug resistance protein 1 (MRP1) in A549 and A549/CR cells. We also employed gas chromatography mass-spectrometry and nano electrospray ionization mass-spectrometry coupled with multivariate statistical analysis to characterize the unique metabolic and lipidomic profiles of chemoresistant NSCLC cells in order to identify potential therapeutic targets. RESULTS: Reactive oxygen species levels were decreased, and mRNA and protein levels of GPX2 and multidrug resistance protein 1 (MRP1) were increased in A549/CR. We identified 87 metabolites and intact lipid species in A549 and A549/CR. Among these metabolites, lactic acid, glutamic acid, glycine, proline, aspartic acid, succinic acid, and ceramide, alongside the PC to PE ratio, and arachidonic acid-containing phospholipids were suggested as characteristic features of chemoresistant NSCLC cells (A549/CR). CONCLUSIONS: This study reveals characteristic feature differences between drug-resistance NSCLC cells and their parental cells. We suggest potential therapeutic targets in chemoresistant NSCLC. Our results provide new insight into metabolic and lipidomic alterations in chemoresistant NSCLC. This could be used as fundamental information to develop therapeutic strategies for the treatment of chemoresistant NSCLC patients.

Mycobiome analysis for distinguishing the geographical origins of sesame seeds.

Sesame (Sesamum indicum) is one of the most widely cultivated crops in Asia and Africa. The identification of the geographical origins of sesame seeds is important for the detection of fraudulent samples. This study was conducted to build a prediction model and suggest potential biomarkers for distinguishing the geographical origins of sesame seeds using mycobiome (fungal microbiome) analysis coupled with multivariate statistical analysis. Sesame seeds were collected from 25 cities in Korea, six cities in China, and five sites in other countries (Ethiopia, India, Nigeria, and Pakistan). According to the expression of fungal internal transcribed spacer (ITS) sequences in sesame seeds, 21 fungal genera were identified in sesame seeds from various countries. The optimal partial least squares-discriminant analysis model was established by applying two components with unit variance scaling. Based on seven-fold cross validation, the predictive model had 94.4% (Korea vs. China/other countries), 91.7% (China vs. Korea/other countries), and 88.9% (other countries vs. Korea/China) accuracy in determining the geographical origins of sesame seeds. Alternaria, Aspergillus, and Macrophomina were suggested as the potential fungal genera to differentiate the geographical origins of sesame seeds. This study demonstrated that mycobiome analysis could be used as a complementary method for distinguishing the geographical origins of raw sesame seeds.

Characteristics of fecal metabolic profiles in patients with irritable bowel syndrome with predominant diarrhea investigated using 1 H-NMR coupled with multivariate statistical analysis.

BACKGROUND: Gut microbiota are known to be closely related to irritable bowel syndrome (IBS). However, not much is known about characteristic fecal metabolic profiles of IBS. We aimed to characterize fecal metabolites in patients with IBS with predominant diarrhea (IBS-D) using 1 H-nuclear magnetic resonance (1 H-NMR) spectroscopy. METHODS: In this study, we enrolled 29 patients diagnosed with IBS-D according to the Rome IV criteria, 22 healthy controls (HC) and 11 HC administered laxatives (HC-L) in the age group of 20-69 year. The usual diet of the patients and HC was maintained, their fecal samples were collected and investigated by NMR-based global metabolic profiling coupled with multivariate statistical analysis. RESULTS: We detected 55 metabolites in 1 H-NMR spectra of fecal samples: four amines, 16 amino acids, six fatty acids, eight organic acids, three sugars, and 18 other compounds. Orthogonal partial least square-discriminant analysis derived score plots showed clear separation between the IBS-D group and the HC and HC-L groups. Among the 55 metabolites identified, we found five disease-relevant potential biomarkers distinguishing the IBS-D from the HC, namely, cadaverine, putrescine, threonine, tryptophan, and phenylalanine. CONCLUSIONS: The patients with IBS-D were clearly differentiated from the HC and HC-L by fecal metabolite analysis using 1 H-NMR spectroscopy, and five fecal metabolites characteristic of IBS-D were found. The findings of this study could be used to develop alternative and complementary diagnostic methods and as a source of fundamental information for developing novel therapies for IBS-D.