Ingenuity pathways analysis of urine metabonomics phenotypes toxicity of gentamicin in multiple organs

We introduce the use of Ingenuity Pathway Analysis to analyzing global metabonomics in order to characterize phenotypically biochemical perturbations and the potential mechanisms of the gentamicin-induced toxicity in multiple organs. A single dose of gentamicin was administered to Sprague Dawley rats (200 mg/kg, n = 6) and urine samples were collected at -24-0 h pre-dosage, 0-24, 24-48, 48-72 and 72-96 h post-dosage of gentamicin. The urine metabonomics analysis was performed by UPLC/MS, and the mass spectra signals of the detected metabolites were systematically deconvoluted and analyzed by pattern recognition analyses (Heatmap, PCA and PLS-DA), revealing a time-dependency of the biochemical perturbations induced by gentamicin toxicity. As result, the holistic metabolome change induced by gentamicin toxicity in the animal's organisms was characterized. Several metabolites involved in amino acid metabolism were identified in urine, and it was confirmed that gentamicin biochemical perturbations can be foreseen from these biomarkers. Notoriously, it was found that gentamicin induced toxicity in multiple organs system in the laboratory rats. The proof-of-knowledge based Ingenuity Pathway Analysis revealed gentamicin induced liver and heart toxicity, along with the previously known toxicity in kidney. The metabolites creatine, nicotinic acid, prostaglandin E2, and cholic acid were identified and validated as phenotypic biomarkers of gentamicin induced toxicity. Altogether, the significance of the use of metabonomics analyses in the assessment of drug toxicity is highlighted once more; furthermore, this work demonstrated the powerful predictive potential of the Ingenuity Pathway Analysis to study of drug toxicity and its valuable complementation for metabonomics based assessment of the drug toxicity.

Spectroscopic correlation analysis of NMR-based metabonomics in exercise science

Spectroscopic studies of complex clinical fluids have led to the application of a more holistic approach to their chemical analysis becoming more popular and widely employed. The efficient and effective interpretation of multidimensional spectroscopic data relies on many chemometric techniques and one such group of tools is represented by so-called correlation analysis methods. Typical of these techniques are two-dimensional correlation analysis and statistical total correlation spectroscopy (STOCSY). Whilst the former has largely been applied to optical spectroscopic analysis, STOCSY was developed and has been applied almost exclusively to NMR metabonomic studies. Using a 1H NMR study of human blood plasma, from subjects recovering from exhaustive exercise trials, the basic concepts and applications of these techniques are examined. Typical information from their application to NMR-based metabonomics is presented and their value in aiding interpretation of NMR data obtained from biological systems is illustrated. Major energy metabolites are identified in the NMR spectra and the dynamics of their appearance and removal from plasma during exercise recovery are illustrated and discussed. The complementary nature of two-dimensional correlation analysis and statistical total correlation spectroscopy are highlighted.

Discrimination of Type 2 diabetic patients from healthy controls by using metabonomics method based on their serum fatty acid profiles

Metabonomics, the study of metabolites and their roles in various disease states, is a novel methodology arising from the post-genomics era. This methodology has been applied in many fields, including work in cardiovascular research and drug toxicology. In this study, metabonomics method was employed to the diagnosis of Type 2 diabetes mellitus (DM2) based on serum lipid metabolites. The results suggested that serum fatty acid profiles determined by capillary gas chromatography combined with pattern recognition analysis of the data might provide an effective approach to the discrimination of Type 2 diabetic patients from healthy controls. And the applications of pattern recognition methods have improved the sensitivity and specificity greatly. (C) 2004 Elsevier B.V. All rights reserved.

Metabonomics of human amniotic fluid for prenatal diagnostics

O trabalho apresentado nesta tese teve como principais objectivos contribuir para o conhecimento da composição do líquido amniótico humano (LA), colhido no 2º trimestre de gravidez, assim como investigar possíveis alterações na sua composição devido à ocorrência de patologias pré-natais, recorrendo à metabonómica e procurando, assim, definir novos biomarcadores de doenças da grávida e do feto. Após uma introdução descrevendo o estado da arte relacionado com este trabalho (Capítulo 1) e os princípios das metodologias analíticas usadas (Capítulo 2), seguida de uma descrição dos aspectos experimentais associados a esta tese (Capítulo 3), apresentam-se os resultados da caracterização da composição química do LA (gravidez saudável) por espectroscopia de ressonância magnética nuclear (RMN), assim como da monitorização da sua estabilidade durante o armazenamento e após ciclos de congelamento-descongelamento (Capítulo 4). Amostras de LA armazenadas a -20°C registaram alterações significativas, tornando-se estas menos pronunciadas (mas ainda mensuráveis) a -70°C, temperatura recomendada para o armazenamento de LA. Foram também observadas alterações de composição após 1-2 ciclos de congelamento-descongelamento (a ter em conta aquando da reutilização de amostras), assim como à temperatura ambiente (indicando um período máximo de 4h para a manipulação e análise de LA). A aquisição de espectros de RMN de 1H de alta resolução e RMN acoplado (LC-NMR/MS) permitiu a detecção de 75 compostos no LA do 2º trimestre, 6 dos quais detectados pela primeira vez no LA. Experiências de difusão (DOSY) permitiram ainda a caracterização das velocidades de difusão e massas moleculares médias das proteínas mais abundantes. O Capítulo 5 descreve o estudo dos efeitos de malformações fetais (FM) e de cromossomopatias (CD) na composição do LA do 2º trimestre de gravidez. A extensão deste trabalho ao estudo dos efeitos de patologias no LA que ocorrem no 3º trimestre de gravidez é descrita no Capítulo 6, nomeadamente no que se refere ao parto pré-termo (PTD), pré-eclampsia (PE), restrição do crescimento intra-uterino (IUGR), ruptura prematura de membranas (PROM) e diabetes mellitus gestacional (GDM). Como complemento a estes estudos, realizou-se uma análise preliminar da urina materna do 2º trimestre para o estudo de FM e GDM, descrita no Capítulo 7. Para interpretação dos dados analíticos, obtidos por espectroscopia RMN de 1H, cromatografia líquida de ultra eficiência acoplada a espectrometria de massa (UPLC-MS) e espectroscopia do infravermelho médio (MIR), recorreu-se à análise discriminante pelos métodos dos mínimos quadrados parciais e o método dos mínimos quadrados parciais ortogonal (PLS-DA e OPLS-DA) e à correlação espectral. Após análise por validação cruzada de Monte-Carlo (MCCV), os modelos PLS-DA de LA permitiram distinguir as FM dos controlos (sensibilidades 69-85%, especificidades 80-95%, taxas de classificação 80-90%), revelando variações metabólicas ao nível do metabolismo energético, dos metabolismos dos aminoácidos e glícidos assim como possíveis alterações ao nível do funcionamento renal. Observou-se também um grande impacto das FM no perfil metabólico da urina materna (medido por UPLC-MS), tendo no entanto sido registados modelos PLS-DA com menor sensibilidade (40-60%), provavelmente devido ao baixo número de amostras e maior variabilidade da composição da urina (relativamente ao LA). Foram sugeridos possíveis marcadores relacionados com a ocorrência de FM, incluindo lactato, glucose, leucina, valina, glutamina, glutamato, glicoproteínas e conjugados de ácido glucurónico e/ou sulfato e compostos endógenos e/ou exógenos (<1 M) (os últimos visíveis apenas na urina). No LA foram também observadas variações metabólicas devido à ocorrência de vários tipos de cromossomopatias (CD), mas de menor magnitude. Os perfis metabólicos de LA associado a pré- PTD produziram modelos que, apesar do baixo poder de previsão, sugeriram alterações precoces no funcionamento da unidade fetoplacentária, hiperglicémia e stress oxidativo. Os modelos obtidos para os grupos pré- IUGR pré- PE, pré- PROM e pré-diagnóstico GDM (LA e urina materna) registaram baixo poder de previsão, indicando o pouco impacto destas condições na composição do LA e/ou urina do 2º trimestre. Os resultados obtidos demonstram as potencialidades da análise dos perfis metabólicos do LA (e, embora com base em menos estudos, da urina materna) do 2º trimestre para o desenvolvimento de novos e complementares métodos de diagnóstico, nomeadamente para FM e PTD.

Studying the Human Gut Microbiota in the Trans-Omics Era - Focus on Metagenomics and Metabonomics

The human gut microbiota comprises a diverse microbial consortium closely co-evolved with the human genome and diet. The importance of the gut microbiota in regulating human health and disease has however been largely overlooked due to the inaccessibility of the intestinal habitat, the complexity of the gut microbiota itself and the fact that many of its members resist cultivation and are in fact new to science. However, with the emergence of 16S rRNA molecular tools and "post-genomics" high resolution technologies for examining microorganisms as they occur in nature without the need for prior laboratory culture, this limited view of the gut microbiota is rapidly changing. This review will discuss the application of molecular microbiological tools to study the human gut microbiota in a culture independent manner. Genomics or metagenomics approaches have a tremendous capability to generate compositional data and to measure the metabolic potential encoded by the combined genomes of the gut microbiota. Another post-genomics approach, metabonomics, has the capacity to measure the metabolic kinetic or flux of metabolites through an ecosystem at a particular point in time or over a time course. Metabonomics thus derives data on the function of the gut microbiota in situ and how it responds to different environmental stimuli e. g. substrates like prebiotics, antibiotics and other drugs and in response to disease. Recently these two culture independent, high resolution approaches have been combined into a single "transgenomic" approach which allows correlation of changes in metabolite profiles within human biofluids with microbiota compositional metagenomic data. Such approaches are providing novel insight into the composition, function and evolution of our gut microbiota.

Studying the Human Gut Microbiota in the Trans-Omics Era - Focus on Metagenomics and Metabonomics

The human gut microbiota comprises a diverse microbial consortium closely co-evolved with the human genome and diet. The importance of the gut microbiota in regulating human health and disease has however been largely overlooked due to the inaccessibility of the intestinal habitat, the complexity of the gut microbiota itself and the fact that many of its members resist cultivation and are in fact new to science. However, with the emergence of 16S rRNA molecular tools and "post-genomics" high resolution technologies for examining microorganisms as they occur in nature without the need for prior laboratory culture, this limited view of the gut microbiota is rapidly changing. This review will discuss the application of molecular microbiological tools to study the human gut microbiota in a culture independent manner. Genomics or metagenomics approaches have a tremendous capability to generate compositional data and to measure the metabolic potential encoded by the combined genomes of the gut microbiota. Another post-genomics approach, metabonomics, has the capacity to measure the metabolic kinetic or flux of metabolites through an ecosystem at a particular point in time or over a time course. Metabonomics thus derives data on the function of the gut microbiota in situ and how it responds to different environmental stimuli e.g. substrates like prebiotics, antibiotics and other drugs and in response to disease. Recently these two culture independent, high resolution approaches have been combined into a single "transgenomic" approach which allows correlation of changes in metabolite profiles within human biofluids with microbiota compositional metagenomic data. Such approaches are providing novel insight into the composition, function and evolution of our gut microbiota.

Influence of galacto-oligosaccharide mixture (B-GOS) on gut microbiota, immune parameters and metabonomics in elderly persons

It is recognised that ageing induces various changes to the human colonic microbiota. Most relevant is a reduction in bifidobacteria, which is a health-positive genus. Prebiotics, such as galacto-oligosaccharides (GOS), are dietary ingredients that selectively fortify beneficial gut microbial groups. Therefore, they have the potential to reverse the age-related decline in bifidobacteria and modulate associated health parameters. We assessed the effect of GOS mixture (Bimuno (B-GOS)) on gut microbiota, markers of immune function and metabolites in forty elderly (age 65-80 years) volunteers in a randomised, double-blind, placebo (maltodextrin)-controlled, cross-over study. The intervention periods consisted of 10 weeks with daily doses of 5·5 g/d with a 4-week washout period in between. Blood and faecal samples were collected for the analyses of faecal bacterial populations and immune and metabolic biomarkers. B-GOS consumption led to significant increases in bacteroides and bifidobacteria, the latter correlating with increased lactic acid in faecal waters. Higher IL-10, IL-8, natural killer cell activity and C-reactive protein and lower IL-1β were also observed. Administration of B-GOS to elderly volunteers may be useful in positively affecting the microbiota and some markers of immune function associated with ageing.

NMR, Metabonomics and Molecular Profiles: Applications to the Quality Assessment of Foodstuffs

Nuclear Magnetic Resonance (NMR) is a branch of spectroscopy that is based on the fact that many atomic nuclei may be oriented by a strong magnetic field and will absorb radiofrequency radiation at characteristic frequencies. The parameters that can be measured on the resulting spectral lines (line positions, intensities, line widths, multiplicities and transients in time-dependent experi-ments) can be interpreted in terms of molecular structure, conformation, molecular motion and other rate processes. In this way, high resolution (HR) NMR allows performing qualitative and quantitative analysis of samples in solution, in order to determine the structure of molecules in solution and not only. In the past, high-field NMR spectroscopy has mainly concerned with the elucidation of chemical structure in solution, but today is emerging as a powerful exploratory tool for probing biochemical and physical processes. It represents a versatile tool for the analysis of foods. In literature many NMR studies have been reported on different type of food such as wine, olive oil, coffee, fruit juices, milk, meat, egg, starch granules, flour, etc using different NMR techniques. Traditionally, univariate analytical methods have been used to ex-plore spectroscopic data. This method is useful to measure or to se-lect a single descriptive variable from the whole spectrum and , at the end, only this variable is analyzed. This univariate methods ap-proach, applied to HR-NMR data, lead to different problems due especially to the complexity of an NMR spectrum. In fact, the lat-ter is composed of different signals belonging to different mole-cules, but it is also true that the same molecules can be represented by different signals, generally strongly correlated. The univariate methods, in this case, takes in account only one or a few variables, causing a loss of information. Thus, when dealing with complex samples like foodstuff, univariate analysis of spectra data results not enough powerful. Spectra need to be considered in their wholeness and, for analysing them, it must be taken in consideration the whole data matrix: chemometric methods are designed to treat such multivariate data. Multivariate data analysis is used for a number of distinct, differ-ent purposes and the aims can be divided into three main groups: • data description (explorative data structure modelling of any ge-neric n-dimensional data matrix, PCA for example); • regression and prediction (PLS); • classification and prediction of class belongings for new samples (LDA and PLS-DA and ECVA). The aim of this PhD thesis was to verify the possibility of identify-ing and classifying plants or foodstuffs, in different classes, based on the concerted variation in metabolite levels, detected by NMR spectra and using the multivariate data analysis as a tool to inter-pret NMR information. It is important to underline that the results obtained are useful to point out the metabolic consequences of a specific modification on foodstuffs, avoiding the use of a targeted analysis for the different metabolites. The data analysis is performed by applying chemomet-ric multivariate techniques to the NMR dataset of spectra acquired. The research work presented in this thesis is the result of a three years PhD study. This thesis reports the main results obtained from these two main activities: A1) Evaluation of a data pre-processing system in order to mini-mize unwanted sources of variations, due to different instrumental set up, manual spectra processing and to sample preparations arte-facts; A2) Application of multivariate chemiometric models in data analy-sis.

Development of methodologies for fish freshness assessment using metabonomics applications.

This study focuses on the use of metabonomics applications in measuring fish freshness in various biological species and in evaluating how they are stored. This metabonomic approach is innovative and is based upon molecular profiling through nuclear magnetic resonance (NMR). On one hand, the aim is to ascertain if a type of fish has maintained, within certain limits, its sensory and nutritional characteristics after being caught; and on the second, the research observes the alterations in the product’s composition. The spectroscopic data obtained through experimental nuclear magnetic resonance, 1H-NMR, of the molecular profiles of the fish extracts are compared with those obtained on the same samples through analytical and conventional methods now in practice. These second methods are used to obtain chemical indices of freshness through biochemical and microbial degradation of the proteic nitrogen compounds and not (trimethylamine, N-(CH3)3, nucleotides, amino acids, etc.). At a later time, a principal components analysis (PCA) and a linear discriminant analysis (PLS-DA) are performed through a metabonomic approach to condense the temporal evolution of freshness into a single parameter. In particular, the first principal component (PC1) under both storage conditions (4 °C and 0 °C) represents the component together with the molecular composition of the samples (through 1H-NMR spectrum) evolving during storage with a very high variance. The results of this study give scientific evidence supporting the objective elements evaluating the freshness of fish products showing those which can be labeled “fresh fish.”

Thyroxine and reserpine-induced changes in metabolic profiles of rat urine and the therapeutic effect of Liu Wei Di Huang Wan detected by UPLC-HDMS

The promise of metabonomics, a new "omics" technique, to validate Chinese medicines and the compatibility of Chinese formulas has been appreciated. The present study was undertaken to explore the excretion pattern of low molecular mass metabolites in the male Wistar-derived rat model of kidney yin deficiency induced with thyroxine and reserpine as well as the therapeutic effect of Liu Wei Di Huang Wan (LW) and its separated prescriptions, a classic traditional Chinese medicine formula for treating kidney yin deficiency in China. The study utilized ultra-performance liquid chromatography/electrospray ionization synapt high definition mass spectrometry (UPLC/ESI-SYNAPT-HDMS) in both negative and positive electrospray ionization (ESI). At the same time, blood biochemistry was examined to identify specific changes in the kidney yin deficiency. Distinct changes in the pattern of metabolites, as a result of daily administration of thyroxine and reserpine, were observed by UPLC-HDMS combined with a principal component analysis (PCA). The changes in metabolic profiling were restored to their baseline values after treatment with LW according to the PCA score plots. Altogether, the current metabonomic approach based on UPLC-HDMS and orthogonal projection to latent structures discriminate analysis (OPLS-DA) indicated 20 ions (14 in the negative mode, 8 in the positive mode, and 2 in both) as "differentiating metabolites".

The -Omics in drug development

New advancement in genomics, proteomics, and metabonomics created significant excitement about the use of these relatively new technologies in drug design, discovery, development, and molecular-targeted therapeutics by identifying new drug targets and better tools for safety and efficacy studies in preclinical and clinical stages of drug development as well as diagnostics. In this chapter, we will briefly discuss the application of genomics, proteomics, and metabonomics in drug discovery and development

Solid-state MAS NMR measurements of intact articular bovine cartilage

Articular cartilage (AC), an avascular connective tissue lining articulating surfaces of the long bones, comprises extracellular biopolymers. In functionally compromised states such as osteoarthritis, thinned or lost AC causes reduced mobility and increased health-care costs. Understanding of the characteristics responsible for the load bearing efficiency of AC and the factors leading to its degradation are incomplete. DTI shows the structural alignment of collagen in AC [1] and T2 relaxation measurements suggest that the average director of reorientational motion of water molecules depends on the degree of alignment of collagen in AC [2]. Information on the nature of the chemical interactions involved in functional AC is lacking. The need for AC structural integrity makes solid state NMR an ideal tool to study this tissue. We examined the contribution of water in different functional ‘compartments’ using 1H-MAS, 13C-MAS and 13C-CPMAS NMR of bovine patellar cartilage incubated in D2O. 1H-MAS spectra signal intensity was reduced due to H/D exchange without a measureable redistribution of relative signal intensity. Chemical shift anisotropy was estimated by lineshape analysis of multiple peaks in the 1H-MAS spinning sidebands. These asymmetrical sidebands suggested the presence of multiple water species in AC. Therefore, water was added in small aliquots to D2O saturated AC and the influence of H2O and D2O on organic components was studied with 13C-MAS-NMR and 13C-CPMAS-NMR. Signal intensity in 13C-MAS spectra showed no change in relative signal intensity throughout the spectrum. In 13C-CPMAS spectra, displacement of water by D2O resulted in a loss of signal in the aliphatic region due to a reduction in proton availability for cross-polarization. These results complement dehydration studies of cartilage using osmotic manipulation [3] and demonstrate components of cartilage that are in contact with mobile water.