The Biosynthesis Of Secondary Metabolites.
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EV volumes were calculated using the NTA data i.e., using the EV diameters for calculating the sphere volumes in each size class, which were multiplied by the particle numbers in each size class. Subsequently, the EV volumes of all size classes were summed to yield the total volume of the EVs applied to the metabolomics analysis. Metabolite concentrations inside the EVs were calculated by dividing the mole amount of metabolites with the total volumes of EVs in the metabolomics samples. The metabolite concentrations of platelets were calculated similarly using the average platelet volume of 8 fl (normal range 7.2-11.7 fl in Demirin , 2011 ) and 1 x 107 platelets/sample. The contribution of uEV-derived metabolites to urine was calculated by dividing the mole amount of individual metabolites in the control uEV samples with the urine volume from which the EVs were isolated and comparing this concentration value to the concentration of the same metabolites measured from the urine filtrates. Loss of EVs during isolation was not taken into account in these calculations. Human Metabolome Database (HMDB) and EVpedia (accessed 12.8.2016) were searched for reported EV-resident enzymes and transporters linked to the common EV metabolites. For assigning the subcellular localizations of the common EV metabolites, HMDB and Small Molecule Pathway Database (SMPDB) were used. The statistics module and metabolite set enrichment analysis through over representation analysis in the Metaboanalyst 3.0 software were employed to analyze the metabolomics data. The MS-compound panel of 102 metabolites (Table ) was used as a reference library and pathways with ≥ 2 metabolites present in all control samples of either EV type were included. For comparisons of population means, the input data was log-transformed, normalized to the EV-derived parameters or to concentrations of other metabolites from the same panel as indicated. When comparing two population means, differences between the groups were tested for statistical significance with non-parametric Wilcoxon rank test or student´s t-test with equal variance. For the comparisons of three population means, one-way ANOVA with Fischer's LSD as the post-hoc analysis was used.
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Characterization of the urinary EV samples applied to metabolomics by western blotting and Nanoparticle tracking analysis. A. Western blotting of the urinary EV samples in the metabolomics study with EV-markers demonstrated significant variation in EV quantity from different donors. Two out of three samples from prostate cancer patients of Helsinki Urological Biobank project (HUB.1-3) obtained before prostatectomy (pre) contained more EVs than the samples from the same patients after prostatectomy (post) or from healthy controls. B. The urinary EV concentrations in these samples measured by nanoparticle tracking analysis and by quantification of CD9 band optical density (OD) from the western blot correlated well. C. Size distribution of the urinary EVs applied to metabolomics was obtained by nanoparticle tracking analysis showing that the EV sizes did not vary much between samples (N = 8).