Chemometrics models for overcoming high between subject variability: applications in clinical metabolic profiling studies

In human metabolic profiling studies, between-subject variability is often the dominant feature and can mask the potential classifications of clinical interest. Conventional models such as principal component analysis (PCA) are usually not effective in such situations and it is therefore highly desirable to find a suitable model which is able to discover the underlying pattern hidden behind the high between-subject variability. In this study we employed two clinical metabolomics data sets as the testing grounds, in which such variability had been observed, and we demonstrate that a proper choice of chemometrics model can help to overcome this issue of high between-subject variability. Two data sets were used to represent two different types of experiment designs. The first data set was obtained from a small-scale study investigating volatile organic compounds (VOCs) collected from chronic wounds using a skin patch device and analysed by thermal desorption-gas chromatography-mass spectrometry. Five patients were recruited and for each patient three sites sampled in triplicate: healthy skin, boundary of the lesion and top of the lesion, the aim was to discriminate these three types of samples based on their VOC profile. The second data set was from a much larger study involving 35 healthy subjects, 47 patients with chronic obstructive pulmonary disease and 33 with asthma. The VOCs in the breath of each subject were collected using a mask device and analysed again by GC–MS with the aim of discriminating the three types of subjects based on breath VOC profiles. Multilevel simultaneous component analysis, multilevel partial least squares for discriminant analysis, ANOVA-PCA, and a novel simplified ANOVA-PCA model—which we have named ANOVA-Mean Centre (ANOVA-MC)—were applied on these two data sets. Significantly improved results were obtained by using these models. We also present a novel validation procedure to verify statistically the results obtained from those models.     

A systematic analysis of TCA Escherichia coli mutants reveals suitable genetic backgrounds for enhanced hydrogen and ethanol production using glycerol as main carbon source

Biodiesel has emerged as an environmentally friendly alternative to fossil fuels; however, the low price of glycerol feed‐stocks generated from the biodiesel industry has become a burden to this industry. A feasible alternative is the microbial biotransformation of waste glycerol to hydrogen and ethanol. Escherichia coli, a microorganism commonly used for metabolic engineering, is able to biotransform glycerol into these products. Nevertheless, the wild type strain yields can be improved by rewiring the carbon flux to the desired products by genetic engineering. Due to the importance of the central carbon metabolism in hydrogen and ethanol synthesis, E. coli single null mutant strains for enzymes of the TCA cycle and other related reactions were studied in this work. These strains were grown anaerobically in a glycerol‐based medium and the concentrations of ethanol, glycerol, succinate and hydrogen were analysed by HPLC and GC. It was found that the reductive branch is the more relevant pathway for the aim of this work, with malate playing a central role. It was also found that the putative C4‐transporter dcuD mutant improved the target product yields. These results will contribute to reveal novel metabolic engineering strategies for improving hydrogen and ethanol production by E. coli.     

A Dimer Interface Mutation in Glyceraldehyde-3-Phosphate Dehydrogenase Regulates Its Binding to AU-rich RNA

Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is an enzyme best known for its role in glycolysis. However, extra-glycolytic functions of GAPDH have been described, including regulation of protein expression via RNA binding. GAPDH binds to numerous adenine-uridine rich elements (AREs) from various mRNA 3′-untranslated regions in vitro and in vivo despite its lack of a canonical RNA binding motif. How GAPDH binds to these AREs is still unknown. Here we discovered that GAPDH binds with high affinity to the core ARE from tumor necrosis factor-α mRNA via a two-step binding mechanism. We demonstrate that a mutation at the GAPDH dimer interface impairs formation of the second RNA-GAPDH complex and leads to changes in the RNA structure. We investigated the effect of this interfacial mutation on GAPDH oligomerization by crystallography, small-angle x-ray scattering, nano-electrospray ionization native mass spectrometry, and hydrogen-deuterium exchange mass spectrometry. We show that the mutation does not significantly affect GAPDH tetramerization as previously proposed. Instead, the mutation promotes short-range and long-range dynamic changes in regions located at the dimer and tetramer interface and in the NAD⁺ binding site. These dynamic changes are localized along the P axis of the GAPDH tetramer, suggesting that this region is important for RNA binding. Based on our results, we propose a model for sequential GAPDH binding to RNA via residues located at the dimer and tetramer interfaces.     

Extensive metabolic cross-talk in melon fruit revealed by spatial and developmental combinatorial metabolomics

? Variations in tissue development and spatial composition have a major impact on the nutritional and organoleptic qualities of ripe fleshy fruit, including melon (Cucumis melo). To gain a deeper insight into the mechanisms involved in these changes, we identified key metabolites for rational food quality design. ? The metabolome, volatiles and mineral elements were profiled employing an unprecedented range of complementary analytical technologies. Fruits were followed at a number of time points during the final ripening process and tissues were collected across the fruit flesh from rind to seed cavity. Approximately 2000 metabolite signatures and 15 mineral elements were determined in an assessment of temporal and spatial melon fruit development. ? This study design enabled the identification of: coregulated hubs (including aspartic acid, 2-isopropylmalic acid, β-carotene, phytoene and dihydropseudoionone) in metabolic association networks; global patterns of coordinated compositional changes; and links of primary and secondary metabolism to key mineral and volatile fruit complements. ? The results reveal the extent of metabolic interactions relevant to ripe fruit quality and thus have enabled the identification of essential candidate metabolites for the high-throughput screening of melon breeding populations for targeted breeding programmes aimed at nutrition and flavour improvement.     

Comparison of five xylan synthesis mutants reveals new insight into the mechanisms of xylan synthesis

Previous studies using co-expression analysis have identified a large number of genes likely to be involved in secondary cell-wall formation. However, the function of very few of these genes is known. We have studied the cell-wall phenotype of irx7, irx8 and irx9, three previously described irregular xylem (irx) mutants, and irx14 and parvus-3, which we now show also to be secondary cell-wall mutants. All five mutants, which have mutations in genes encoding putative glycosyltransferases, exhibited large decreases in xylan. In addition, all five mutants were found to have the same specific defect in xylan structure, retaining MeGlcUA but lacking GlcUA side branches. Polysaccharide analysis by carbohydrate gel electrophoresis (PACE) was used to determine the xylan structure in Arabidopsis, and revealed that side branches are added to approximately one in every eight xylose residues. Interestingly, this ratio is constant in all the lines analysed despite the wide variation in xylan content and the absence of GlcUA branches. Xylanase digestion of xylan from wild-type plants released a short oligosaccharide sequence at the reducing end of the xylan chain. MALDI-TOF MS analysis indicated that this sequence of sugars was absent in xylan from irx7, irx8 and parvus-3 mutants, but was present in irx9 and irx14. This is consistent with previous NMR analysis of xylan from irx7, irx8 and irx9, and suggests that PARVUS may be involved in the synthesis of a xylan primer whereas IRX14 may be required to synthesize the xylan backbone. This hypothesis is supported by assays showing that irx9 and irx14 are both defective in incorporation of radiolabel from UDP (14)C-xylose. This study has important implications for both our understanding of xylan biosynthesis and the functional analysis of cell-wall biosynthesis genes.     

Inter-laboratory reproducibility of fast gas chromatography–electron impact–time of flight mass spectrometry (GC–EI–TOF/MS) based plant metabolomics

The application of gas chromatography–mass spectrometry (GC–MS) to the ‘global’ analysis of metabolites in complex samples (i.e. metabolomics) has now become routine. The generation of these data-rich profiles demands new strategies in data mining and standardisation of experimental and reporting aspects across laboratories. As part of the META-PHOR project’s (METAbolomics for Plants Health and OutReach: ) priorities towards robust technology development, a GC–MS ring experiment based upon three complex matrices (melon, broccoli and rice) was launched. All sample preparation, data processing, multivariate analyses and comparisons of major metabolite features followed standardised protocols, identical models of GC (Agilent 6890N) and TOF/MS (Leco Pegasus III) were also employed. In addition comprehensive GC×GC–TOF/MS was compared with 1 dimensional GC–TOF/MS. Comparisons of the paired data from the various laboratories were made with a single data processing and analysis method providing an unbiased assessment of analytical method variants and inter-laboratory reproducibility. A range of processing and statistical methods were also assessed with a single exemplary dataset revealing near equal performance between them. Further investigations of long-term reproducibility are required, though the future generation of global and valid metabolomics databases offers much promise.