RESULTS: Targeted and non-targeted metabolomics for both polar and semi-polar metabolites of Phialemonium curvatum AWO2 (DSM 23903) cultivated in MSM with palm oil (MSM-P) or glucose (MSM-G) as carbon sources were obtained. Targeted metabolomics on central carbon metabolism of tricarboxylic acid (TCA) cycle and glyoxylate cycle were analysed using LC-MS/MS-TripleQ and GC-MS, while untargeted metabolite profiling was performed using LC-MS/MS-QTOF followed by multivariate analysis. Targeted metabolomics analysis showed that glyoxylate pathway and TCA cycle were recruited at central carbon metabolism for triglyceride and glucose catabolism, respectively. Significant differences in organic acids concentration of about 4- to 8-fold were observed for citric acid, succinic acid, malic acid, and oxaloacetic acid. Correlation of organic acids concentration and key enzymes involved in the central carbon metabolism was further determined by enzymatic assays. On the other hand, the untargeted profiling revealed seven metabolites undergoing significant changes between MSM-P and MSM-G cultures.
CONCLUSIONS: Overall, this study has provided insights on the understanding on the effect of triglycerides and sugar as carbon source in fungi global metabolic pathway, which might become important for future optimization of carbon flux engineering in fungi to improve organic acids production when vegetable oil is applied as the sole carbon source.
METHODS: The case-control portion of the study was conducted in nine UK centers with men ages 50-69 years who underwent prostate-specific antigen screening for prostate cancer within the Prostate Testing for Cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.
RESULTS: Thirty-five metabolites were strongly associated with prostate cancer (P < 0.0014, multiple-testing threshold). These fell into four classes: (i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); (ii) fatty acids and ratios; (iii) amino acids; (iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal.
CONCLUSIONS: We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk.
IMPACT: The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.
METHODS: The internalization of type II FIPV WSU 79-1146 in Crandell-Rees Feline Kidney (CrFK) cells was visualized using a fluorescence microscope, and optimization prior to phenotype microarray (PM) study was performed. Then, four types of Biolog Phenotype MicroArray™ plates (PM-M1 to PM-M4) precoated with different carbon and nitrogen sources were used to determine the metabolic profiles in FIPV-infected cells.
RESULTS: The utilization of palatinose was significantly low in FIPV-infected cells; however, there were significant increases in utilizing melibionic acid, L-glutamine, L-glutamic acid and alanyl-glutamine (Ala-Gln) compared to non-infected cells.
CONCLUSION: This study has provided the first insights into the metabolic profiling of a feline coronavirus infection in vitro using PMs and deduced that glutamine metabolism is one of the essential metabolic pathways for FIPV infection and replication. Further studies are necessary to develop strategies to target the glutamine metabolic pathway in FIPV infection.