A distinct metabolic signature predicts development of fasting plasma glucose.

Background: High blood glucose and diabetes are amongst the conditions causing the greatest losses in years of healthy life worldwide. Therefore, numerous studies aim to identify reliable risk markers for development of impaired glucose metabolism and type 2 diabetes. However, the molecular basis of impaired glucose metabolism is so far insufficiently understood.

Comparison of metabolite profiles in U87 glioma cells and mesenchymal stem cells.

Gas chromatography-mass spectrometry (GC-MS) profiles were generated from U87 glioma cells and human mesenchymal stem cells (hMSC). 37 metabolites representing glycolysis intermediates, TCA cycle metabolites, amino acids and lipids were selected for a detailed analysis. The concentrations of these metabolites were compared and Pearson correlation coefficients were used to calculate the relationship between pairs of metabolites.

Rapid metabolic evolution in human prefrontal cortex.

Human evolution is characterized by the rapid expansion of brain size and drastic increase in cognitive capabilities. It has long been suggested that these changes were accompanied by modifications of brain metabolism. Indeed, human-specific changes on gene expression or amino acid sequence were reported for a number of metabolic genes, but actual metabolite measurements in humans and apes have remained scarce.

Metabolomic and transcriptomic stress response of Escherichia coli.

Environmental fluctuations lead to a rapid adjustment of the physiology of Escherichia coli, necessitating changes on every level of the underlying cellular and molecular network. Thus far, the majority of global analyses of E. coli stress responses have been limited to just one level, gene expression.

Metabolic profiling reveals key metabolic features of renal cell carcinoma.

Recent evidence suggests that metabolic changes play a pivotal role in the biology of cancer and in particular renal cell carcinoma (RCC). Here, a global metabolite profiling approach was applied to characterize the metabolite pool of RCC and normal renal tissue. Advanced decision tree models were applied to characterize the metabolic signature of RCC and to explore features of metastasized tumours.

Stability of metabolic correlations under changing environmental conditions in Escherichia coli--a systems approach.

Background: Biological systems adapt to changing environments by reorganizing their cellular and physiological program with metabolites representing one important response level. Different stresses lead to both conserved and specific responses on the metabolite level which should be reflected in the underlying metabolic network.

Methodology/principal Findings: Starting from experimental data obtained by a GC-MS based high-throughput metabolic profiling technology we here develop an approach that: (1) extracts network representations from metabolic condition-dependent data by using pairwise correlations, (2) determines the sets of stable and condition-dependent correlations based on a combination of statistical significance and homogeneity tests, and (3) can identify metabolites related to the stress response, which goes beyond simple observations about the changes of metabolic concentrations.

Assessment of sampling strategies for gas chromatography-mass spectrometry (GC-MS) based metabolomics of cyanobacteria.

Metabolomics is the comprehensive analysis of the small molecules that compose an organism's metabolism. The main limiting step in microbial metabolomics is the requirement for fast and efficient separation of microbes from the culture medium under conditions in which metabolism is rapidly halted. In this article we compare three different sampling strategies, quenching, filtering, and centrifugation, for arresting the metabolic activities of two morphologically diverse cyanobacteria, the unicellular Synechocystis sp.

High-resolution direct infusion-based mass spectrometry in combination with whole 13C metabolome isotope labeling allows unambiguous assignment of chemical sum formulas.

A new strategy for direct infusion-based metabolite analysis employing a combination of high-resolution mass spectrometry and (13)C-isotope labeling of entire metabolomes is described. Differentially isotope labeled metabolite extracts from otherwise identically grown reference plants were prepared and infused into a Fourier transform ion cyclotron resonance mass spectrometer. The derived accurate mass lists from each extract were searched, using an in-house-developed database search tool, against a number of comprehensive metabolite databases.

Hierarchical metabolomics demonstrates substantial compositional similarity between genetically modified and conventional potato crops.

There is current debate whether genetically modified (GM) plants might contain unexpected, potentially undesirable changes in overall metabolite composition. However, appropriate analytical technology and acceptable metrics of compositional similarity require development. We describe a comprehensive comparison of total metabolites in field-grown GM and conventional potato tubers using a hierarchical approach initiating with rapid metabolome "fingerprinting" to guide more detailed profiling of metabolites where significant differences are suspected.

Comparison of rapid liquid chromatography-electrospray ionization-tandem mass spectrometry methods for determination of glycoalkaloids in transgenic field-grown potatoes.

Two rapid methods for highly selective detection and quantification of the two major glycoalkaloids in potatoes, alpha-chaconine and alpha-solanine, were compared for robustness in high-throughput operations for over 1000 analytical runs using potato tuber samples from field trials. Glycoalkaloids were analyzed using liquid chromatography coupled to tandem mass spectrometry in multiple reaction monitoring mode. An electrospray interface was used in the detection of glycoalkaloids in positive ion mode.