Metabolómica: acceso abierto

Schistosomiasis is the second most widespread human parasitic disease. It is principally treated with one drug, praziquantel, which is administered to 100 million people each year; less sensitive strains of schistosomes are emerging. One of the most appealing drug targets against schistosomiasis is thioredoxin glutathione reductase (TGR). This natural chimeric enzyme is a peculiar fusion of a glutaredoxin domain with a thioredoxin selenocysteine (U)-containing reductase domain. Selenocysteine is located on a flexible C-terminal arm that is usually disordered in the available structures of the protein and is essential for the full catalytic activity of TGR. MHC molecules are cell surface proteins, which take active part in host immune reactions and involvement of MHC class in response to almost all antigens and it give effects on specific sites. Predicted MHC binding regions acts like red flags for antigen specific and generate immune response against the parent antigen. So a small fragment of antigen can induce immune response against whole antigen. This theme is implemented in designing subunit and synthetic peptide vaccines. In this study,
we analyzed thioredoxin glutathione reductase of Schistosoma mansoni and is allows potential drug targets to identify active sites, which form antibodies against or infection. The method integrates prediction of peptide MHC class binding; proteosomal C terminal cleavage and TAP transport efficiency. Antigenic epitopes of thioredoxin glutathione reductase are important antigenic determinants against the various toxic reactions and infections.

Mass spectrometry based metabolomics experiments generate copious amounts of signal data which in turn is processed to ultimately convert the signal data into identified metabolites so that biological interpretation and pathway analysis can be performed. The actual number of biochemicals detected in global biochemical profiling studies utilizing liquid chromatography coupled to mass spectrometry (LC/MS) is much lower than the total number of mass spectral ion-features detected, particularly when using positive electrospray ionization (ESI+). Given the conflicting numbers of detected metabolites reported in literature, a detailed analysis of the ion-feature composition is warranted. Ultrahigh pressure liquid chromatography (UHPLC)/Ion-trap MS and fragmentation (MS2) nominal mass data from 10 human plasma samples were analyzed in triplicate. The resulting detected ion-features were analyzed for ion-feature reproducibility, type and source. It was found that nearly 70% of all ion-features detected were non-reproducible, that 22% were from chemicals contributed to the samples due to storage and processing and that only 25% of the reproducible and annotatable ion-features could be determined to be protonated molecular ions. In addition, a previously undocumented ion-feature type; amalgam adducts, and ion-feature source; ions arising from chemistry of compounds occurring within extracted samples is reported. Ultimately, this analysis demonstrated that from an average of 10,000 ion-features detected in a human plasma sample ultimately only 220 compounds of biological origin were detected and identified from a positive ion analysis only.

Each year about 1.4 million people die from lung cancer worldwide. Despite efforts in prevention, diagnosis and treatment, survival rate remains poor for this disease. This unfortunate situation is largely due to the fact that a high proportion of cases are diagnosed at advanced stages, highlighting the great need for identifying new biomarkers in order to improve early diagnosis and treatment. Recent studies on microRNAs have not only shed light on their involvement in tumor development and progression, but also suggested their potential utility as biomarkers for subtype diagnostics, staging and prediction of treatment response. This review article summarizes the impact of microRNAs on lung cancer biology, and highlights their role in the detection and classification of lung cancer as well as direct targets for drug development.

Background: Alzheimer’s disease (AD) is the most common neurodegenerative disorder, manifesting clinical symptoms of cognitive impairment and dementia. The vast majority of cases are late onset AD (LOAD), which are genetically heterogeneous and occur sporadically. The neuropathological changes of LOAD can be reproduced by supplementing a rabbit’s diet with 2% cholesterol for 12 weeks. Methods: In the present study, a non-targeted Fourier transform ion cyclotron resonance mass spectrometry based metabolomics approach and multivariate statistics were used to survey the effect of cholesterol on cerebrospinal fluid metabolites over a 12 week time-course. Results: Of the 6515 accurate masses detected in the rabbit CSF, 375 showed significant differences in intensity (p < 0.05) between samples collected at different time points. Further analysis of top 95 (p < 0.01) revealed four clusters of metabolites with different expression patterns throughout the course of the cholesterol treatment. The majority of effects were observed in 12 weeks of cholesterol treated samples, while certain masses showed transient changes at 8 weeks but returned back to near the levels of the controls at 12 weeks. The masses that started to change 8 weeks into the treatment may represent early metabolic changes linked to certain defects in the brain related to AD development. Putative metabolite identifications revealed certain phosphorylated glycerolipids and peptide fragments decreased after 8 weeks of cholesterol treatment. Conclusion: This study showed that there are specific metabolic perturbations which occur in the CSF as a result of high cholesterol loading. Given the changes of short peptide fragments in particular, the effects are likely the consequence of brain degeneration caused by high cholesterol levels. Further investigations of these masses will lead to a greater understanding of the metabolic mechanisms associated with cholesterol-related AD development. Some of these masses may be used as candidates for the development of diagnostic, prognostic or theranostic markers.

Background & methods: Evidence indicates that there are significant differences in how glucose and fructose affect host metabolism although the details remain unclear. We determined how liver cells adopt intermediary metabolism to fructose administration. Cultured HepG2 cells were incubated with 5 mM glucose or fructose, above the 5 mM glucose concentration in control cultures. [1,2-13C2]-D-glucose was used as the single metabolic tracer.

Results: Addition of 5 mM glucose maintained the ratio of complete glucose oxidation to that of other acetateyielding substrates, while addition of 5 mM added fructose significantly decreased 13CO2 Delta by its contribution to citrate and glutamate in the TCA cycle. Fructose maintained a high rate of direct glucose oxidation via G6PDH which was also seen with glucose-treatment. New palmitate production via fatty acid synthase was significantly increased by both sugars. In contrast to glucose-treatment which resulted in increased intracellular palmitate and oleate content, fructose increased the co-release of newly formed palmitate and oleate into the culture media.
Conclusion: These findings demonstrate that fructose rearranges TCA cycle metabolism by providing acetyl-
CoA for oxidation, increasing citrate shuttling and strongly promoting triglyceride efflux of altered de novo synthesis
pathways.