Behavior of rare earth elements in an aquifer perturbed by CO2 injection: Environmental implications.

Three cubic-meters of CO2-saturated water was injected into a subsurface fractured aquifer in a post-mined area, using a push-pull test protocol. Groundwater samples were collected before and after CO2-injection to quantify geochemical changes. CO2-injection initially reduced the pH of water from 7.3 to 5.7, led to the enrichment of major ions (Ca2+, Mg2+, and alkalinity), and dissolved trace metals (including Fe, Mn, As, and Zn) in the groundwater. Rare earth elements (REE) and yttrium concentrations were also measured in these samples before and after CO2 perturbation, to evaluate their behavior. An enrichment of total Y plus REE (REY) occurred. REY fractionation was observed with higher heavy REE (HREE) enrichment compared to light REE (LREE), and significant variations in La/Yb and Y/Ho ratios were observed following CO2 perturbation. Enrichment by a factor of three was observed for Y, Lu, and Tm, and by nearly one order of magnitude for Dy and Yb. A geochemical model was used to evaluate the amount of REE aqueous ions complexed throughout the experiment. Modeling of the results showed that speciation of dissolved REE with carbonate, along with desorption from iron oxyhydroxide surface were the main factors controlling REE behavior. This study increases an understanding of dissolved REE behavior in the environment, and the potential use for applying iron oxides for REE recovery from mine drainages. Furthermore, the description of REE fractionation patterns may assist in surveying CO2 geological storage sites, surveying underground waste disposal sites, and for understanding the formation of ore deposits and fluid inclusions in geological formations.

Metabolomics analysis uncovers that dietary restriction buffers metabolic changes associated with aging in Caenorhabditis elegans.

Dietary restriction (DR) is one of the most universal means of extending lifespan. Yet, whether and how DR specifically affects the metabolic changes associated with aging is essentially unknown. Here, we present a comprehensive and unbiased picture of the metabolic variations that take place with age at the whole organism level in Caenorhabditis elegans by using (1)H high-resolution magic-angle spinning (HR-MAS) nuclear magnetic resonance (NMR) analysis of intact worms. We investigate metabolic variations potentially important for lifespan regulation by comparing the metabolic fingerprint of two previously described genetic models of DR, the long-lived eat-2(ad465) and slcf-1(tm2258) worms, as single mutants or in combination with a genetic suppressor of their lifespan phenotype. Our analysis shows that significant changes in metabolite profiles precede the major physiological decline that accompanies aging and that DR protects from some of those metabolic changes. More specifically, low phosphocholine (PCho) correlates with high life expectancy. A mutation in the tumor suppressor gene PTEN/DAF-18, which suppresses the beneficial effects of DR in both C. elegans and mammals, increases both PCho level and choline kinase expression. Furthermore, we show that choline kinase function in the intestine can regulate lifespan. This study highlights the relevance of NMR metabolomic approaches for identifying potential biomarkers of aging.

Metabolomics-on-a-chip and predictive systems toxicology in microfluidic bioartificial organs.

The world faces complex challenges for chemical hazard assessment. Microfluidic bioartificial organs enable the spatial and temporal control of cell growth and biochemistry, critical for organ-specific metabolic functions and particularly relevant to testing the metabolic dose-response signatures associated with both pharmaceutical and environmental toxicity. Here we present an approach combining a microfluidic system with (1)H NMR-based metabolomic footprinting, as a high-throughput small-molecule screening approach. We characterized the toxicity of several molecules: ammonia (NH(3)), an environmental pollutant leading to metabolic acidosis and liver and kidney toxicity; dimethylsulfoxide (DMSO), a free radical-scavenging solvent; and N-acetyl-para-aminophenol (APAP, or paracetamol), a hepatotoxic analgesic drug. We report organ-specific NH(3) dose-dependent metabolic responses in several microfluidic bioartificial organs (liver, kidney, and cocultures), as well as predictive (99% accuracy for NH(3) and 94% for APAP) compound-specific signatures. Our integration of microtechnology, cell culture in microfluidic biochips, and metabolic profiling opens the development of so-called "metabolomics-on-a-chip" assays in pharmaceutical and environmental toxicology.

Orthogonal filtered recoupled-STOCSY to extract metabolic networks associated with minor perturbations from NMR spectroscopy.

Supervised multivariate statistical analyses of NMR spectroscopic data sets are often required to identify metabolic differences between sample classes, and the use of orthogonal filters has proven to be highly efficient even when dealing with weak perturbations. In this note, we associate orthogonal filters to the recently reported recoupled-statistical total correlation spectroscopy (RSTOCSY). An initial supervised deflation of the spectral matrix is applied to remove all information orthogonal to the effect of interest and is followed by an RSTOCSY analysis to extract a list of pairs of metabolites that experience correlated perturbations. This list can then be used to find possibilities for the perturbed metabolic network. This supervised RSTOCSY approach, dubbed OR-STOCSY, yields metabolites related to perturbations of biological interest, even if they make a minor contribution to the global variance of a complex data set compared to other (possibly confounding) effects under study. The method is demonstrated with the application to genetic phenotypes in Caenorhabditis elegans.

Broad-ranging natural metabotype variation drives physiological plasticity in healthy control inbred rat strains.

Maintaining homeostasis in higher organisms involves a complex interplay of multiple ubiquitous and organ-specific molecular mechanisms that can be characterized using functional genomics technologies such as transcriptomics, proteomics, and metabonomics and dissected out through genetic investigations in healthy and diseased individuals. We characterized the genomic, metabolic, and physiological divergence of several inbred rat strains--Brown Norway, Lewis, Wistar Kyoto, Fisher (F344)--frequently used as healthy controls in genetic studies of the cardiometabolic syndrome. Hierarchical clustering of (1)H NMR-based metabolic profiles (n = 20 for urine, n = 16 for plasma) identified metabolic phenotype (metabotype) divergence patterns similar to the phylogenetic variability based on single nucleotide polymorphisms. However, the observed urinary metabotype variation exceeded that explainable by genetic polymorphisms. To understand further this natural variation, we used an integrative, knowledge-based network biology metabolic pathway analysis approach, coined Metabolite-Set Enrichment Analysis (MSEA). MSEA reveals that homeostasis and physiological plasticity can be achieved despite widespread divergences in glucose, lipid, amino acid, and energy metabolism in the host, together with different gut microbiota contributions suggestive of strain-specific transgenomic interactions. This work illustrates the concept of natural metabolomic variation, leading to physiologically stable albeit diverse strategies within the range of normality, all of which are highly relevant to animal model physiology, genetical genomics, and patient stratification in personalized healthcare.

Targeted projection NMR spectroscopy for unambiguous metabolic profiling of complex mixtures.

Unambiguous identification of individual metabolites present in complex mixtures such as biofluids constitutes a crucial prerequisite for quantitative metabolomics, toward better understanding of biochemical processes in living systems. Increasing the dimensionality of a given NMR correlation experiment is the natural solution for resolving spectral overlap. However, in the context of metabolites, natural abundance acquisition of (1)H and (13)C NMR data virtually excludes the use of higher dimensional NMR experiments (3D, 4D, etc.) that would require unrealistically long acquisition times. Here, we introduce projection NMR techniques for studies of complex mixtures, and we show how discrete sets of projection spectra from higher dimensional NMR experiments are obtained in a reasonable time frame, in order to capture essential information necessary to resolve assignment ambiguities caused by signal overlap in conventional 2D NMR spectra. We determine optimal projection angles where given metabolite resonances will have the least overlap, to obtain distinct metabolite assignment in complex mixtures. The method is demonstrated for a model mixture composition made of ornithine, putrescine and arginine for which acquisition of a single 2D projection of a 3D (1)H-(13)C TOCSY-HSQC spectrum allows to disentangle the metabolite signals and to access to complete profiling of this model mixture in the targeted 2D projection plane.

Two-dimensional statistical recoupling for the identification of perturbed metabolic networks from NMR spectroscopy.

The development of Statistical Total Correlation Spectroscopy (STOCSY), a representation of the autocorrelation matrix of a spectral data set as a 2D pseudospectrum, has allowed more reliable assignment of one- and two-dimensional NMR spectra acquired from the complex mixtures that are usually used in metabolomics/metabonomics studies, thus, improving precise identification of candidate biomarkers contained in metabolic signatures computed by multivariate statistical analysis. However, the correlations obtained cannot always be interpreted in terms of connectivities between metabolites. In this study, we combine statistical recoupling of variables (SRV) and STOCSY to identify perturbed metabolite systems. The resulting Recoupled-STOCSY (R-STOCSY) method provides a 2D correlation landscape based on the SRV clusters representing physical, chemical, and biological entities. This enables the identification of correlations between distant clusters and extends the recoupling scheme of SRV, which was previously limited to the association of neighboring clusters. This allows the recovery of only meaningful correlations between metabolic signals and significantly enhances the interpretation of STOCSY. The method is validated through the measurement of the distances between the metabolites involved in these correlations, within the whole metabolic network, which shows that the average shortest path length is significantly shorter for the correlations detected in this new way compared to metabolite couples randomly selected from within the entire KEGG metabolic network. This enables the identification without any a priori knowledge of the perturbed metabolic network. The R-STOCSY completes the recoupling procedure between distant clusters, further reducing the high dimensionality of metabolomics/metabonomics data set and finally allows the identification of composite biomarkers, highlighting disruption of particular metabolic pathways within a global metabolic network. This allows the perturbed metabolic network to be extracted through NMR based metabolomics/metabonomics in an automated, and statistical manner.

Statistical recoupling prior to significance testing in nuclear magnetic resonance based metabonomics.

Significance testing is a crucial step in metabolic biomarker recovery from the metabolome-wide latent variables computed by multivariate statistical analysis. In this study we propose an algorithm based on the landscape of the covariance/correlation ratio of consecutive variables along the chemical shift axis to restore, prior to significance testing, the spectral dependency and recouple variables in clusters which correspond to physical, chemical, and biological entities: statistical recoupling of variables (SRV). Variables are associated into a series of clusters, which are then considered as individual objects for the control of the false discovery rate. Compared to classical procedures, it is found that SRV allows efficient recovery of statistically significant metabolic variables. The proposed SRV method when associated with the Benjamini-Yekutieli correction retains a low level of significant variables in the noise areas of the nuclear magnetic resonance (NMR) spectrum, close to that observed using the conservative Bonferroni correction (false positive rate), while also allowing successful identification of statistically significant metabolic NMR signals in cases where the classical procedures of Benjamini-Yekutieli and Benjamini-Hochberg (false discovery rate) fail. This procedure improves the interpretability of latent variables for metabolic biomarker recovery.

Metabolic profiling strategy of Caenorhabditis elegans by whole-organism nuclear magnetic resonance.

In this study, we present a methodology for metabotyping of C. elegans using 1H high resolution magic angle spinning (HRMAS) whole-organism nuclear magnetic resonance (NMR). We demonstrate and characterize the robustness of our metabolic phenotyping method, discriminating wild-type N2 from mutant sod-1(tm776) animals, with the latter being an otherwise silent mutation, and we identify and quantify several confounding effects to establish guidelines to ensure optimal quality of the raw data across time and space. We monitor the sample stability under experimental conditions and examine variations arising from effects that can potentially confuse the biological interpretation or prevent the automation of the protocol, including sample culture (breeding of the worms by two biologists), sample preparation (freezing), NMR acquisition (acquisition by different spectroscopists, acquisition in different facilities), and the effect of the age of the animals. When working with intact model organisms, some of these exogenous effects are shown to be significant and therefore require control through experimental design and sample randomization.

Metabotyping of Caenorhabditis elegans reveals latent phenotypes.

Assigning functions to every gene in a living organism is the next challenge for functional genomics. In fact, 85-90% of the 19,000 genes of the nematode Caenorhabditis elegans genome do not produce any visible phenotype when inactivated, which hampers determining their function, especially when they do not belong to previously characterized gene families. We used (1)H high-resolution magic angle spinning NMR spectroscopy ((1)H HRMAS-NMR) to reveal the latent phenotype associated to superoxide dismutase (sod-1) and catalase (ctl-1) C. elegans mutations, both involved in the elimination of radical oxidative species. These two silent mutations are significantly discriminated from the wild-type strain and from each other. We identify a metabotype significantly associated with these mutations involving a general reduction of fatty acyl resonances from triglycerides, unsaturated lipids being known targets of free radicals. This work opens up perspectives for the use of (1)H HRMAS-NMR as a molecular phenotyping device for model organisms. Because it is amenable to high throughput and is shown to be highly informative, this approach may rapidly lead to a functional and integrated metabonomic mapping of the C. elegans genome at the systems biology level.

Effect of aqueous acetic, oxalic, and carbonic acids on the adsorption of europium(III) onto alpha-alumina.

Chemical retention, i.e., partition of the element between aqueous solution and mineral surface, is a key phenomenon for assessing the safety of possible nuclear waste disposal. For this purpose, the sorption of Eu(III) onto a model mineral-alpha-alumina-is studied here, including the effects of groundwater chemistry: pH and concentrations of small organic and inorganic ligands (acetate, oxalate, and carbonate anions). This work presents some experimental evidence for a synergic mechanism of sorption of europium-ligand complexes onto the alumina. Only cationic complexes were necessary to consider to model experimental results. Using the ion-exchange theory (IET) and a corresponding restricted set of parameters-exchange capacities and thermodynamic equilibrium constants-the whole set of sorption experiments of Eu(III) cationic species onto the alpha-alumina was modeled under various chemical conditions.

Sorption of aqueous carbonic, acetic, and oxalic acids onto alpha-alumina.

The presence of organic complexing agents can modify the behavior of a surface. This study aims to better understand the impact of carboxylic acids (acetic, oxalic, and carbonic acids) issued from cellulose degradation and equally naturally present in soils. First, evidence of two different kinds of sites for chloride adsorption onto alpha-alumina and another for sodium sorption was provided. Consequently, no competition between these cation and anion sorptions occurs on alpha-alumina. The associated exchange capacities and ionic exchange constants were measured. Second, the adsorption behavior of the carboxylic acids was studied as a function of aqueous -log[H(+)] and 0.01 to 0.1 M ionic strength (NaCl), and modeled by using mass action law for ideal biphasic systems. The carboxylic acids were found to be adsorbed on the same sites as chloride ions. The competition between organic ligands and chloride ions was satisfactorily accounted for by the model assuming the deprotonated form of the ligands was sorbed on alpha-alumina. The model also allowed us to interpret the adsorption of all species under various conditions without any extra fitting parameters.

On the use of spectroscopic techniques for interaction studies, part I: complexation between europium and small organic ligands.

In the framework of environmental studies, it is important to understand the interaction of humic substances with cations (heavy metals, radionuclides) and to determine their complexation constants in order to evaluate their potential impact on their fate. For this purpose, two techniques have been used: electrospray ionization mass spectrometry, a newly used technique in speciation studies, and time-resolved laser-induced fluorescence spectrometry, a well-known technique for such studies. As a first step, for simplification purposes and to compare both techniques, simple molecules having functional groups present in humic substances have been selected, such as acetic, glycolic, and 4-hydroxyphenylacetic acids. Both techniques have been used to obtain stoichiometries and complexation constants between these simple molecules and europium (III).