Toluene inhalation in adolescent rats reduces flexible behaviour in adulthood and alters glutamatergic and GABAergic signalling.

Toluene is a commonly abused inhalant that is easily accessible to adolescents. Despite the increasing incidence of use, our understanding of its long-term impact remains limited. Here, we used a range of techniques to examine the acute and chronic effects of toluene exposure on glutameteric and GABAergic function, and on indices of psychological function in adult rats after adolescent exposure.

Applications of NMR in dairy research.

NMR is a robust analytical technique that has been employed to investigate the properties of many substances of agricultural relevance. NMR was first used to investigate the properties of milk in the 1950s and has since been employed in a wide range of studies; including properties analysis of specific milk proteins to metabolomics techniques used to monitor the health of dairy cows. In this brief review, we highlight the different uses of NMR in the dairy industry.

Ethanol, not detectably metabolized in brain, significantly reduces brain metabolism, probably via action at specific GABA(A) receptors and has measureable metabolic effects at very low concentrations.

Ethanol is a known neuromodulatory agent with reported actions at a range of neurotransmitter receptors. Here, we measured the effect of alcohol on metabolism of [3-¹³C]pyruvate in the adult Guinea pig brain cortical tissue slice and compared the outcomes to those from a library of ligands active in the GABAergic system as well as studying the metabolic fate of [1,2-¹³C]ethanol. Analyses of metabolic profile clusters suggest that the significant reductions in metabolism induced by ethanol (10, 30 and 60 mM) are via action at neurotransmitter receptors, particularly α4β3δ receptors, whereas very low concentrations of ethanol may produce metabolic responses owing to release of GABA via GABA transporter 1 (GAT1) and the subsequent interaction of this GABA with local α5- or α1-containing GABA(A)R.

Latent biochemical relationships in the blood-milk metabolic axis of dairy cows revealed by statistical integration of 1H NMR spectroscopic data.

A detailed understanding of the relationships between the distinct metabolic compartments of blood and milk would be of potential benefit to our understanding of the physiology of lactation, and potentially for development of biomarkers for health and commercially relevant traits in dairy cattle. NMR methods were used to measure metabolic profiles from blood and milk samples from Holstein cows. Data were analyzed using PLS regression to identify quantitative relationships between metabolic profiles and important traits.

1H NMR spectroscopy of serum reveals unique metabolic fingerprints associated with subtypes of surgically induced osteoarthritis in sheep.

Osteoarthritis (OA) is a highly prevalent joint disease. Its slow progressive nature and the correlation between pathological changes and clinical symptoms mean that OA is often well advanced by the time of diagnosis. In the absence of any specific pharmacological treatments, there is a pressing need to develop robust biomarkers for OA.

Statistical total correlation spectroscopy scaling for enhancement of metabolic information recovery in biological NMR spectra.

The high level of complexity in nuclear magnetic resonance (NMR) metabolic spectroscopic data sets has fueled the development of experimental and mathematical techniques that enhance latent biomarker recovery and improve model interpretability. We previously showed that statistical total correlation spectroscopy (STOCSY) can be used to edit NMR spectra to remove drug metabolite signatures that obscure metabolic variation of diagnostic interest. Here, we extend this "STOCSY editing" concept to a generalized scaling procedure for NMR data that enhances recovery of latent biochemical information and improves biological classification and interpretation.

A genome-wide metabolic QTL analysis in Europeans implicates two loci shaped by recent positive selection.

We have performed a metabolite quantitative trait locus (mQTL) study of the (1)H nuclear magnetic resonance spectroscopy ((1)H NMR) metabolome in humans, building on recent targeted knowledge of genetic drivers of metabolic regulation. Urine and plasma samples were collected from two cohorts of individuals of European descent, with one cohort comprised of female twins donating samples longitudinally. Sample metabolite concentrations were quantified by (1)H NMR and tested for association with genome-wide single-nucleotide polymorphisms (SNPs).

Human metabolic profiles are stably controlled by genetic and environmental variation.

¹H Nuclear Magnetic Resonance spectroscopy (¹H NMR) is increasingly used to measure metabolite concentrations in sets of biological samples for top-down systems biology and molecular epidemiology. For such purposes, knowledge of the sources of human variation in metabolite concentrations is valuable, but currently sparse. We conducted and analysed a study to create such a resource.

Statistical integration of 1H NMR and MRS data from different biofluids and tissues enhances recovery of biological information from individuals with HIV-1 infection.

Nuclear magnetic resonance (NMR) spectroscopy is widely used in metabonomics studies, but optimal recovery of latent biological information requires increasingly sophisticated statistical methods to identify quantitative relationships within these often highly complex data sets. Statistical heterospectroscopy (SHY) extracts latent relationships between NMR and mass spectrometry (MS) data from the same samples. Here we extend this concept to identify novel metabolic correlations between different biofluids and tissues from the same individuals.

γ-Hydroxybutyrate and the GABAergic footprint: a metabolomic approach to unpicking the actions of GHB.

Gamma-hydroxybutyrate is found both naturally in the brain and self-administered as a drug of abuse. It has been reported to act at endogenous γ-hydroxybutyrate (GHB) receptors and GABA(B) receptors [GABA(B)R], and may also be metabolized to GABA. Here, the metabolic fingerprints of a range of concentrations of GHB were measured in brain cortical tissue slices and compared with those of ligands active at GHB and GABA-R using principal components analysis (PCA) to identify sites of GHB activity.

Evaluation of full-resolution J-resolved 1H NMR projections of biofluids for metabonomics information retrieval and biomarker identification.

Spectroscopic profiling of biological samples is an integral part of metabolically driven top-down systems biology and can be used for identifying biomarkers of toxicity and disease. However, optimal biomarker information recovery and resonance assignment still pose significant challenges in NMR-based complex mixture analysis. The reduced signal overlap as achieved when projecting two-dimensional (2D) J-resolved (JRES) NMR spectra can be exploited to mitigate this problem and, here, full-resolution (1)H JRES projections have been evaluated as a tool for metabolic screening and biomarker identification.

Statistical total correlation spectroscopy editing of 1H NMR spectra of biofluids: application to drug metabolite profile identification and enhanced information recovery.

Here we present a novel method for enhanced NMR spectral information recovery, utilizing a statistical total correlation spectroscopy editing (STOCSY-E) procedure for the identification of drug metabolite peaks in biofluids and for deconvolution of drug and endogenous metabolite signals. Structurally correlated peaks from drug metabolites and those from closely related drug metabolite pathways are first identified using STOCSY. Subsequently, this correlation information is utilized to scale the biofluid (1)H NMR spectra across these identified regions, producing a modified set of spectra in which drug metabolite contributions are reduced and, thus, facilitating analysis by pattern recognition methods without drug metabolite interferences.

¹H NMR-based metabonomics for investigating diabetes.

Diabetes is characterized by hyperglycemia due to dysfunction of insulin secretion or action. The two most common forms are Type 1 diabetes, in which pancreatic β-cells are destroyed, and Type 2 diabetes, in which a combination of disordered insulin action and secretion results in abnormal carbohydrate, lipid and protein metabolism. Metabonomics employs analytical technologies to measure 'global' metabolic responses to a disease state.

Large-scale human metabolic phenotyping and molecular epidemiological studies via 1H NMR spectroscopy of urine: investigation of borate preservation.

Borate is an antibacterial preservative widely used in clinical and large-scale epidemiological studies involving urine sample analysis. Since it readily forms covalent adducts and reversible complexes with hydroxyl and carboxylate groups, the effects of borate preservation in (1)H NMR-spectroscopy-based metabolic profiling of human urine samples have been assessed. Effects of various concentrations of borate (range 0-30 mM) on (1)H NMR spectra of urine were observed at sequential time points over a 12 month period.

Dynamic biochemical information recovery in spontaneous human seminal fluid reactions via 1H NMR kinetic statistical total correlation spectroscopy.

Human seminal fluid (HSF) is a complex mixture of reacting glandular metabolite and protein secretions that provides critical support functions in fertilization. We have employed 600-MHz (1)H NMR spectroscopy to compare and contrast the temporal biochemical and biophysical changes in HSF from infertile men with spinal cord injury compared to age-matched controls. We have developed new approaches to data analysis and visualization to facilitate the interpretation of the results, including the first application of the recently published K-STOCSY concept to a biofluid, enhancing the extraction of information on biochemically related metabolites and assignment of resonances from the major seminal protein, semenogelin.

Seminal oligouridinosis: low uridine secretion as a biomarker for infertility in spinal neurotrauma.

Background: Compromised sexual health is a major rehabilitative barrier for men with lower-spinal cord injury (SCI). Although studies have revealed decreased sperm motility, the quantitative biochemical changes that underlie the infertility mechanism remain poorly understood.

Methods: We employed a nontargeted approach combining 800 MHz hydrogen nuclear magnetic resonance ((1)H NMR) spectroscopy and ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) with pattern recognition methods to analyze seminal fluid metabolite profiles in 10 men with and 8 without SCI above thoracic vertebra 10 (T10).

Optimization of human plasma 1H NMR spectroscopic data processing for high-throughput metabolic phenotyping studies and detection of insulin resistance related to type 2 diabetes.

Optimizing NMR experimental parameters for high-throughput metabolic phenotyping requires careful examination of the total biochemical information obtainable from (1)H NMR data, which includes concentration and molecular dynamics information. Here we have applied two different types of mathematical transformation (calculation of the first derivative of the NMR spectrum and Gaussian shaping of the free-induction decay) to attenuate broad spectral features from macromolecules and enhance the signals of small molecules. By application of chemometric methods such as principal component analysis (PCA), orthogonal projections to latent structures discriminant analysis (O-PLS-DA) and statistical spectroscopic tools such as statistical total correlation spectroscopy (STOCSY), we show that these methods successfully identify the same potential biomarkers as spin-echo (1)H NMR spectra in which broad lines are suppressed via T2 relaxation editing.

1H NMR and UPLC-MS(E) statistical heterospectroscopy: characterization of drug metabolites (xenometabolome) in epidemiological studies.

Statistical HeterospectroscopY (SHY) is a statistical strategy for the coanalysis of multiple spectroscopic data sets acquired in parallel on the same samples. This method operates through the analysis of the intrinsic covariance between signal intensities in the same and related molecular fingerprints measured by multiple spectroscopic techniques across cohorts of samples. Here, the method is applied to 600-MHz (1)H NMR and UPLC-TOF-MS (E) data obtained from human urine samples ( n = 86) from a subset of an epidemiological population unselected for any relevant phenotype or disease factor.

Application of the FLIPSY pulse sequence for increased sensitivity in 1H NMR-based metabolic profiling studies.

Metabolite profiling relies on optimal precision of the acquired data, which requires, among others, a high signal-to-noise ratio (S/N). In addition, increased S/N will increase the likelihood of identification of new biomarkers. Here we introduce, for the first time in metabolite profiling studies by 1H NMR, an approach to enhance the precision of multivariate regression models by use of the FLIPSY (flip angle adjustable one-dimensional NOESY) pulse sequence, augmented by a homospoil pulse after the presaturation period to provide superior baseline quality.

Metabonomics in diabetes research.

Metabonomics has been defined as "quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification" and can provide information on disease processes, drug toxicity, and gene function. In this approach many samples of biological origin (biofluids such as urine or plasma) are analyzed using techniques that produce simultaneous detection. A variety of analytical metabolic profiling tools are used routinely, are also currently under development, and include proton nuclear magnetic resonance spectroscopy and mass spectrometry with a prior online separation step such as high-performance liquid chromatography, ultra-performance liquid chromatography, or gas chromatography.

Statistical correlation and projection methods for improved information recovery from diffusion-edited NMR spectra of biological samples.

Although NMR spectroscopic techniques coupled with multivariate statistics can yield much useful information for classifying biological samples based on metabolic profiles, biomarker identification remains a time-consuming and complex procedure involving separation methods, two-dimensional NMR, and other spectroscopic tools. We present a new approach to aid complex biomixture analysis that combines diffusion ordered (DO) NMR spectroscopy with statistical total correlation spectroscopy (STOCSY) and demonstrate its application in the characterization of urinary biomarkers and enhanced information recovery from plasma NMR spectra. This method relies on calculation and display of the covariance of signal intensities from the various nuclei on the same molecule across a series of spectra collected under different pulsed field gradient conditions that differentially attenuate the signal intensities according to translational molecular diffusion rates.

Experimental and analytical variation in human urine in 1H NMR spectroscopy-based metabolic phenotyping studies.

1H NMR spectroscopy potentially provides a robust approach for high-throughput metabolic screening of biofluids such as urine and plasma, but sample handling and preparation need careful optimization to ensure that spectra accurately report biological status or disease state. We have investigated the effects of storage temperature and time on the 1H NMR spectral profiles of human urine from two participants, collected three times a day on four different days. These were analyzed using modern chemometric methods.

Combined proteomic and metabonomic studies in three genetic forms of the renal Fanconi syndrome.

The renal Fanconi syndrome is a defect of proximal tubular function causing aminoaciduria and low-molecular-weight proteinuria. Dent's disease and Lowe syndrome are defined X-linked forms of Fanconi syndrome; there is also an autosomal dominant idiopathic form (ADIF), phenotypically similar to Dent's disease though its gene defect is still unknown. To assess whether their respective gene products are ultimately involved in a common reabsorptive pathway for proteins and low-molecular-mass endogenous metabolites, we compared renal Fanconi urinary proteomes and metabonomes with normal (control) urine using mass spectrometry and (1)H-NMR spectroscopy, respectively.

(39)K nuclear magnetic resonance and a mathematical model of K(+) transport in human erythrocytes.

(39)K nuclear magnetic resonance was used to measure the efflux of K(+) from suspensions of human erythrocytes [red blood cells (RBCs)], that occurred in response to the calcium ionophore, A23187 and calcium ions; the latter activate the Gárdos channel. Signals from the intra- and extracellular populations of (39)K(+) were selected on the basis of their longitudinal relaxation times, T (1), by using an inversion- recovery pulse sequence with the mixing time, tau(1), chosen to null one or other of the signals. Changes in RBC volume consequent upon efflux of the ions also changed the T (1) values so a new theory was implemented to obviate a potential artefact in the data analysis.

Mathematical modelling of the urea cycle. A numerical investigation into substrate channelling.

Metabolite channelling, the process in which consecutive enzymes have confined substrate transfer in metabolic pathways, has been proposed as a biochemical mechanism that has evolved because it enhances catalytic rates and protects unstable intermediates. Results from experiments on the synthesis of radioactive urea [Cheung, C., Cohen, N.