Metabolic fingerprinting as a diagnostic tool

Research Spotlight: Biospectroscopy at the Manchester Interdisciplinary Biocentre

The Manchester Interdisciplinary Biocentre (MIB) at The University of Manchester (UK), is a large research facility located in central Manchester. The research undertaken in the MIB is said to address a number of grand challenges, including industrial biotechnology, energy and biofuels, and biomedical healthcare. These are realized via four main research themes: biomolecular mechanism and catalysis; synthetic and chemical biology; systems biology; and enabling technologies. This research spotlight focuses on biospectroscopy in the MIB, namely vibrational spectroscopies. This is just one area of research across just three of the many research groups in the MIB, which could be said to exemplify the fundamental and applied aspects of this field, its interdisciplinary nature and also the way it realizes several of the research themes and grand challenges already mentioned, with cutting edge and innovative research.

NMR-based plant metabolomics: where do we stand, where do we go?

NMR-based metabolomics is an important tool for studying biological systems and has been applied in various organisms, including animals, plants and microbes. NMR is able to provide a 'holistic view' of the metabolites under certain conditions, and thus is advantageous for metabolomic studies. To maximize the use of the information obtained, it is also important to create a platform to measure, store and share data. Public databases for storing and sharing information are still lacking for NMR-based metabolomic analysis in plants. Such databases are urgently needed to make metabolic profiling a real omics technology. In addition, to understand metabolic processes in depth, single-cell analysis and the turnover of metabolites in pathways (fluxomics) should be measured.

Metabolic signatures in apoptotic human cancer cell lines

Cancer cells have several specific metabolic features, which have been explored for targeted therapies. Agents that promote apoptosis in tumors are currently considered as a powerful tool for cancer therapeutics. The present study aimed to design a fast, reliable and robust system for metabolite measurements in cells lines to observe impact of apoptosis on the metabolome. For that purpose the NBS (newborn screen) mass spectrometry-based metabolomics assay was adapted for cell culture approach. In HEK 293 and in cancer cell lines HepG2, PC3, and MCF7 we searched for metabolic biomarkers of apoptosis differing from that of necrosis. Already nontreated cell lines revealed distinct concentrations of metabolites. Several metabolites indicative for apoptotic processes in cell culture including aspartate, glutamate, methionine, alanine, glycine, propionyl carnitine (C3-carnitine), and malonyl carnitine (C3DC-carnitine) were observed. In some cell lines metabolite changes were visible as early as 4 h after apoptosis induction and preceeding the detection by caspase 3/7 assay. We demonstrated for the first time that the metabolomic signatures might be used in the tests of efficacy of agents causing apoptosis in cell culture. These signatures could be obtained in fast high-throughput screening.

A metabolomic approach in an experimental model of hypoxia-reoxygenation in newborn piglets: urine predicts outcome

Perinatal asphyxia is one of the leading causes of morbidity and mortality in the neonatal period. Response to oxygen treatment is unpredictable and the optimum concentration of oxygen in neonatal resuscitation is still a matter of debate among neonatologists. A metabolomic approach was used to characterize the metabolic profiles of newborn hypoxic-reoxygenated piglets. Urine samples were collected from newborn piglets (n = 40) undergoing hypoxia followed by resuscitation at different oxygen concentrations (ranging from 18% to 100%) and analyzed by ¹H NMR spectroscopy. Despite reoxygenation 7 piglets, out of 10 which became asystolic, did not respond to resuscitation. Profiles of the ¹H NMR spectra were submitted to unsupervised (principal component analysis) and supervised (partial least squares-discriminant analysis) multivariate analysis. The supervised analyses showed differences in the metabolic profile of the urine collected before the induction of hypoxia between survivors and deaths. Metabolic variations were observed in the urine of piglets treated with different oxygen concentrations comparing T0 (basal value) and end of the experiment (resuscitation). Some of the individual metabolites discriminating between these groups were urea, creatinine, malonate, methylguanidine, hydroxyisobutyric acid. The metabolomic approach appears a promising tool for investigating newborn hypoxia over time, for monitoring the response to the treatment with different oxygen concentrations, and might lead to a tailored management of the disorder.

Recent and potential developments in the analysis of urine: a review

Analysis of urine is a widely used diagnostic tool that traditionally measured one or, at most, a few metabolites. However, the recognition of the need for a holistic approach to metabolism led to the application of metabolomics to urine for disease diagnostics. This review looks at various aspects of urinalysis including sampling and traditional approaches before reviewing recent developments using metabolomics. Spectrometric approaches are covered briefly since there are already a number of very good reviews on NMR spectroscopy and mass spectrometry and other spectrometries are not as highly developed in their applications to metabolomics. On the other hand, there has been a recent surge in chromatographic applications dedicated to characterising the human urinary metabolome. While developments in the analysis of urine encompassing both classical approaches of urinalysis and metabolomics are covered, it must be emphasized that these approaches are not orthogonal - they both have their uses and are complementary. Regardless, the need to normalise analytical data remains an important impediment.

A review of clinical diagnostic applications of liquid chromatography-tandem mass spectrometry

Liquid chromatography coupled with tandem mass spectrometry (LC/MS/MS) technology is emerging as a complementary method to traditional methodology used for clinical applications. Enhanced specificity and high-throughput capabilities are providing significant benefits to clinical diagnostic laboratories conducting routine analyses. This technology is expected to expand rapidly as scientists focus on more complicated challenges that can be solved efficiently by adding LC/MS/MS to their arsenal of techniques.

An introduction to biological nuclear magnetic resonance spectroscopy

Nuclear magnetic resonance (NMR) spectroscopy is one of the most powerful analytical techniques available to biology. This review is an introduction to the potential of this method and is aimed at readers who have little or no experience in acquiring or analyzing NMR spectra. We focus on spectroscopic applications of the magnetic resonance effect, rather than imaging ones, and explain how various aspects of the NMR phenomenon make it a versatile tool with which to address a number of biological problems. Using detailed examples, we discuss the use of (1) H NMR spectroscopy in mixture analysis and metabolomics, the use of (13) C NMR spectroscopy in tracking isotopomers and determining the flux through metabolic pathways ('fluxomics') and the use of (31) P NMR spectroscopy in monitoring ATP generation and intracellular pH homeotasis in vivo. Further examples demonstrate how NMR spectroscopy can be used to probe the physical environment of a cell by measuring diffusion and the tumbling rates of individual metabolites and how it can determine macromolecular structures by measuring the bonds and distances which separate individual atoms. We finish by outlining some of the key challenges which remain in NMR spectroscopy and we highlight how recent advances-such as increased magnet field strengths, cryogenic cooling, microprobes and hyperpolarisation-are opening new avenues for today's biological NMR spectroscopists.

Metabolomics and malaria biology

Metabolomics has ushered in a novel and multi-disciplinary realm in biological research. It has provided researchers with a platform to combine powerful biochemical, statistical, computational, and bioinformatics techniques to delve into the mysteries of biology and disease. The application of metabolomics to study malaria parasites represents a major advance in our approach towards gaining a more comprehensive perspective on parasite biology and disease etiology. This review attempts to highlight some of the important aspects of the field of metabolomics, and its ongoing and potential future applications to malaria research.

Raman chemical mapping reveals site of action of HIV protease inhibitors in HPV16 E6 expressing cervical carcinoma cells

It has been shown that the HIV protease inhibitors indinavir and lopinavir may have activity against the human papilloma virus (HPV) type 16 inhibiting HPV E6-mediated proteasomal degradation of p53 in cultured cervical carcinoma cells. However, their mode and site of action is unknown. HPV-negative C33A cervical carcinoma cells and the same cells stably transfected with E6 (C33AE6) were exposed to indinavir and lopinavir at concentrations of 1 mM and 30 μM, respectively. The intracellular distribution of metabolites and metabolic changes induced by these treatments were investigated by Raman microspectroscopic imaging combined with the analysis of cell fractionation products by liquid chromatography-mass spectrometry (LC-MS). A uniform cellular distribution of proteins was found in drug-treated cells irrespective of cell type. Indinavir was observed to co-localise with nucleic acid in the nucleus, but only in E6 expressing cells. Principal components analysis (PCA) score maps generated on the full Raman hypercube and the corresponding PCA loadings plots revealed that the majority of metabolic variations influenced by the drug exposure within the cells were associated with changes in nucleic acids. Analysis of cell fractionation products by LC-MS confirmed that the level of indinavir in nuclear extracts was approximately eight-fold greater than in the cytoplasm. These data demonstrate that indinavir undergoes enhanced nuclear accumulation in E6-expressing cells, which suggests that this is the most likely site of action for this compound against HPV.

The role of metabolites and metabolomics in clinically applicable biomarkers of disease

Metabolomics allows the simultaneous and relative quantification of thousands of different metabolites within a given sample using sensitive and specific methodologies such as gas or liquid chromatography coupled to mass spectrometry, typically in discovery phases of studies. Biomarkers are biological characteristics that are objectively measured and evaluated as indicators of normal biological processes, pathological processes or pharmacologic responses to a therapeutic intervention. Biomarkers are widely used in clinical practice for the diagnosis, assessment of severity and response to therapy in a number of clinical disease states. In human studies, metabolomics has been applied to define biomarkers related to prognosis or diagnosis of a disease or drug toxicity/efficacy and in doing so hopes to provide greater pathophysiological understanding of disease or therapeutic toxicity/efficacy. This review discusses the application of metabolomics in the discovery and subsequent application of biomarkers in the diagnosis and management of inborn errors of metabolism, cardiovascular disease and cancer. We critically appraise how novel biomarkers discovered through metabolomic analysis may be utilized in future clinical practice by addressing the following three fundamental questions: (1) Can the clinician measure them? (2) Do they add new information? (3) Do they help the clinician to manage patients? Although a number of novel biomarkers have been discovered through metabolomic studies of human diseases in the last decade, none have currently made the transition to routine use in clinical practice. Metabolites identified from these early studies will need to form the basis of larger, prospective, externally validated studies in clinical cohorts for their future use as biomarkers. At this stage, the absolute quantification of these biomarkers will need to be assessed epidemiologically, as will the ultimate deployment in the clinic via routine biochemistry, dip stick or similar rapid at- or near-patient care technologies.

Chronic myeloid leukemia patients sensitive and resistant to imatinib treatment show different metabolic responses

The BCR-ABL tyrosine kinase inhibitor imatinib is highly effective for chronic myeloid leukemia (CML). However, some patients gradually develop resistance to imatinib, resulting in therapeutic failure. Metabonomic and genomic profiling of patients' responses to drug interventions can provide novel information about the in vivo metabolism of low-molecular-weight compounds and extend our insight into the mechanism of drug resistance. Based on a multi-platform of high-throughput metabonomics, SNP array analysis, karyotype and mutation, the metabolic phenotypes and genomic polymorphisms of CML patients and their diverse responses to imatinib were characterized. The untreated CML patients (UCML) showed different metabolic patterns from those of healthy controls, and the discriminatory metabolites suggested the perturbed metabolism of the urea cycle, tricarboxylic acid cycle, lipid metabolism, and amino acid turnover in UCML. After imatinib treatment, patients sensitive to imatinib (SCML) and patients resistant to imatinib (RCML) had similar metabolic phenotypes to those of healthy controls and UCML, respectively. SCML showed a significant metabolic response to imatinib, with marked restoration of the perturbed metabolism. Most of the metabolites characterizing CML were adjusted to normal levels, including the intermediates of the urea cycle and tricarboxylic acid cycle (TCA). In contrast, neither cytogenetic nor metabonomic analysis indicated any positive response to imatinib in RCML. We report for the first time the associated genetic and metabonomic responses of CML patients to imatinib and show that the perturbed in vivo metabolism of UCML is independent of imatinib treatment in resistant patients. Thus, metabonomics can potentially characterize patients' sensitivity or resistance to drug intervention.

Distinguishing cell types or populations based on the computational analysis of their infrared spectra

Infrared (IR) spectroscopy of intact cells results in a fingerprint of their biochemistry in the form of an IR spectrum; this has given rise to the new field of biospectroscopy. This protocol describes sample preparation (a tissue section or cytology specimen), the application of IR spectroscopy tools, and computational analysis. Experimental considerations include optimization of specimen preparation, objective acquisition of a sufficient number of spectra, linking of the derived spectra with tissue architecture or cell type, and computational analysis. The preparation of multiple specimens (up to 50) takes 8 h; the interrogation of a tissue section can take up to 6 h (∼100 spectra); and cytology analysis (n = 50, 10 spectra per specimen) takes 14 h. IR spectroscopy generates complex data sets and analyses are best when initially based on a multivariate approach (principal component analysis with or without linear discriminant analysis). This results in the identification of class clustering as well as class-specific chemical entities.

Molecular ultrasound assessment of tumor angiogenesis

Angiogenesis, the growth of new blood vessels, plays a critical role in progression of tumor growth and metastasis, making it an attractive target for both cancer imaging and therapy. Several molecular markers, including those that are involved in the angiogenesis signaling pathway and those unique to tumor angiogenic vessels, have been identified and can be used as targets for molecular imaging of cancer. With the introduction of ultrasound contrast agents that can be targeted to those molecular markers, targeted contrast-enhanced ultrasound (molecular ultrasound) imaging has become an attractive imaging modality to non-invasively assess tumor angiogenesis at the molecular level. The advantages of molecular ultrasound imaging such as high temporal and spatial resolution, non-invasiveness, real-time imaging, relatively low cost, lack of ionizing irradiation and wide availability among the imaging community will further expand its roles in cancer imaging and drug development both in preclinical research and future clinical applications.

The role of mass spectrometry-based metabolomics in medical countermeasures against radiation

Radiation metabolomics can be defined as the global profiling of biological fluids to uncover latent, endogenous small molecules whose concentrations change in a dose-response manner following exposure to ionizing radiation. In response to the potential threat of nuclear or radiological terrorism, the Center for High-Throughput Minimally Invasive Radiation Biodosimetry was established to develop field-deployable biodosimeters based, in part, on rapid analysis by mass spectrometry of readily and easily obtainable biofluids. In this review, we briefly summarize radiation biology and key events related to actual and potential nuclear disasters, discuss the important contributions the field of mass spectrometry has made to the field of radiation metabolomics, and summarize current discovery efforts to use mass spectrometry-based metabolomics to identify dose-responsive urinary constituents, and ultimately to build and deploy a noninvasive high-throughput biodosimeter.

Dual metabolomics: a novel approach to understanding plant-pathogen interactions

One of the most well-characterised plant pathogenic interactions involves Arabidopsis thaliana and the bacteria Pseudomonas syringae pathovar tomato (Pst). The standard Pst inoculation procedure involves infiltration of large populations of bacteria into plant leaves which means that metabolite changes cannot be readily assigned to the host or pathogen. A plant cell-pathogen co-culture based approach has been developed where the plant and pathogen cells are separated after 12h of co-culture via differential filtering and centrifugation. Fourier transform infrared (FT-IR) spectroscopy was employed to assess the intracellular metabolomes (metabolic fingerprints) of both host and pathogen and their extruded (extracellular) metabolites (metabolic footprints) under conditions relevant to disease and resistance. We propose that this system will enable the metabolomic profiling of the separated host and pathogen (i.e. 'dual metabolomics') and will facilitate the modelling of reciprocal responses.

Protein Bioinformatics Infrastructure for the Integration and Analysis of Multiple High-Throughput "omics" Data

High-throughput “omics” technologies bring new opportunities for biological and biomedical researchers to ask complex questions and gain new scientific insights. However, the voluminous, complex, and context-dependent data being maintained in heterogeneous and distributed environments plus the lack of well-defined data standard and standardized nomenclature imposes a major challenge which requires advanced computational methods and bioinformatics infrastructures for integration, mining, visualization, and comparative analysis to facilitate data-driven hypothesis generation and biological knowledge discovery. In this paper, we present the challenges in high-throughput “omics” data integration and analysis, introduce a protein-centric approach for systems integration of large and heterogeneous high-throughput “omics” data including microarray, mass spectrometry, protein sequence, protein structure, and protein interaction data, and use scientific case study to illustrate how one can use varied “omics” data from different laboratories to make useful connections that could lead to new biological knowledge.

SERS-based diagnosis and biodetection

Surface-enhanced Raman scattering (SERS) spectroscopy is one of the most powerful analytical techniques for identification of molecular species, with the potential to reach single-molecule detection under ambient conditions. This Concept article presents a brief introduction and discussion of both recent advances and limitations of SERS in the context of diagnosis and biodetection, ranging from direct sensing to the use of encoded nanoparticles, in particular focusing on ultradetection of relevant bioanalytes, rapid diagnosis of diseases, marking of organelles within individual cells, and non-invasive tagging of anomalous tissues in living animals.

Mass spectrometry imaging of pharmacological compounds in tissue sections

The use of MS imaging (MSI) to resolve the spatial and pharmacodynamic distributions of compounds in tissues is emerging as a powerful tool for pharmacological research. Unlike established imaging techniques, only limited a priori knowledge is required and no extensive manipulation (e.g., radiolabeling) of drugs is necessary prior to dosing. MS provides highly multiplexed detection, making it possible to identify compounds, their metabolites and other changes in biomolecular abundances directly off tissue sections in a single pass. This can be employed to obtain near cellular, or potentially subcellular, resolution images. Consideration of technical limitations that affect the process is required, from sample preparation through to analyte ionization and detection. The techniques have only recently been adapted for imaging and novel variations to the established MSI methodologies will further enhance the application of MSI for pharmacological research.

Plasma metabolic fingerprinting of childhood obesity by GC/MS in conjunction with multivariate statistical analysis

Metabolic fingerprinting is a powerful tool for exploring systemic metabolic perturbations and potential biomarkers, thus may shed light on the pathophysiological mechanism of diseases. In this work, a new strategy of metabolic fingerprinting was proposed to exploit the disturbances of metabolic patterns and biomarker candidates of childhood obesity. Plasma samples from children with normal weight, overweight and obesity were first profiled by GC/MS. ULDA (uncorrelated linear discriminant analysis) then revealed that the metabolic patterns of the three groups were different. Furthermore, several metabolites, say isoleucine, glyceric acid, serine, 2,3,4-trihydroxybutyric acid and phenylalanine were screened as potential biomarkers of childhood obesity by both ULDA and CCA (canonical correlation analysis). CCA also shows satisfactory correlation between the metabolic patterns and clinical parameters, and the results further suggest that WHR (waist-hip ratio) together with TG (total triglycerides), TC (total cholesterol), HDL (high density lipoprotein) and LDL (low density lipoprotein) were the most important parameters which are associated closely with the metabolic perturbations of childhood obesity, so as to be paid more attention for dealing with metabolic disturbances of childhood obesity in clinical practice rather than regularly monitored BMI (body-mass index). The results have demonstrated that the proposed metabolic fingerprinting approach may be a useful tool for discovering metabolic abnormalities and possible biomarkers for childhood obesity.

The use of hepatocytes to investigate drug toxicity

The liver is very active in metabolizing foreign compounds and the major target for toxicity caused by drugs. Hepatotoxicity may be the result of the drug itself or, more frequently, a result of the bioactivation process and the production of reactive metabolites. Prioritization of compounds based on human hepatotoxicity potential is currently a key unmet need in drug discovery, as it can become a major problem for several lead compounds in later stages of the drug discovery pipeline. Therefore, evaluation of potential hepatotoxicity represents a critical step in the development of new drugs. Cultured hepatocytes are increasingly used by the pharmaceutical industry for the screening of hepatotoxic potential of new molecules. Hepatocytes in culture retain hepatic key functions and constitute a valuable tool to identify chemically induced cellular damage. Their use has notably contributed to the understanding of mechanisms responsible for hepatotoxicity (disruption of cellular energy status, alteration of Ca(2+) homeostasis, inhibition of transport systems, metabolic activation, oxidative stress, covalent binding, etc.). Assessment of current cytotoxicity and hepatic-specific biochemical effects is limited by the inability to measure a wide spectrum of potential mechanistic changes involved in the drug-induced toxic injury. A convenient selection of endpoints allows a multiparametric evaluation of drug toxicity. In this regard, cytomic, proteomic, toxicogenomic and metabonomic approaches help to define patterns of hepatotoxicity for early identification of potential adverse effects of the drug to the liver.

What can metabolomics learn from genomics and proteomics?

After nearly a decade, metabolomics has begun to acquire some credence in the scientific community although its acceptance cannot be compared with that of its forerunners, genomics and proteomics. The legitimization of metabolomics as a valid scientific entity depends on the size of the research community it influences. By far the most effective medium for inoculation is the web infrastructure: public servers that accommodate experimental data, simple formats and guidelines for their interpretation, and connectivity between data and tools for analysis. When these elements satisfy the condition to initiate a social epidemic, metabolomics will be accepted as a fundamental data-driven science that can unite hitherto independently conducted research disciplines.

Monitoring healthy metabolic trajectories with nutritional metabonomics

Metabonomics is a well established analytical approach for the analysis of physiological regulatory processes via the metabolic profiling of biofluids and tissues in living organisms. Its potential is fully exploited in the field of “nutrimetabonomics” that aims at assessing the metabolic effects of active ingredients and foods in individuals. Yet, one of the greatest challenges in nutrition research is to decipher the critical interactions between mammalian organisms and environmental factors, including the gut microbiota. “Nutrimetabonomics” is today foreseen as a powerful approach for future nutritional programs tailored at health maintenance and disease prevention.

Multivariate modeling strategy for intercompartmental analysis of tissue and plasma 1H NMR spectrotypes

Multicompartmental metabolic profiling combined with multivariate data analysis offers a unique opportunity to explore the multidimensional metabolic relationships between various biological matrices. Here, we applied unsupervised chemometric methods for integrating 1H NMR metabolic profiles from mouse plasma, liver, pancreas, adrenal gland and kidney cortex matrices in order to infer intercompartments functional links. Principal Component Analysis (PCA) revealed metabolic differences between matrices but contained limited information on intercompartment metabolic relationships. Multiway PCA enabled the assessment of interindividual metabolic variability across multiple compartments in a single model and, therefore, metabolic correlations between different organs and circulating biofluids. However, this approach does not provide information on the relative contribution of one compartment to another. Integration of metabolic profiles using Multivariate Curve Resolution (MCR) and Parallel Factor Analysis (PARAFAC) methods provided an overview of functional relationships across matrices and enabled the characterization of compartment-specific metabolite signatures, the spectrotypes. In particular, the spectrotypes describe biochemical profiles specific or common to different biological compartments. Consequently, MCR-ALS and PARAFAC appeared to be better adapted for stepwise variable and compartment selection for further correlation analysis. Such a combination of chemometric techniques could provide new research avenues to assess the efficacy of drug or nutritional interventions on targeted organs.

A metabonomic study of hepatitis B-induced liver cirrhosis and hepatocellular carcinoma by using RP-LC and HILIC coupled with mass spectrometry

Liver cirrhosis and hepatocellular carcinoma (HCC) are fatal sequelaes of chronic hepatitis B in China. The sera from HCC and cirrhosis were profiled by rapid resolution liquid chromatography coupled with quadrupole time-of-flight (Q-TOF) mass spectrometry. Reversed-phased (RP) liquid chromatography and hydrophilic interaction chromatography (HILIC) were used for the data acquisition. The normalized and combined data were handled by chemometric analysis, and the combination proved to be effective and reliable for the orthogonal projection to latent structures (OPLS) analysis. Metabonomic profiles and the potential biomarkers were found based on the OPLS models. Shared and unique structure (SUS) plots were used for the evaluation of the potential biomarkers. Glycocholic acid, glycochenodeoxycholic acid, taurocholic acid and taurochenodesoxycholic acid were found to be potential biomarkers related to liver cirrhosis, while dihydrosphingosine and phytosphingosine were potential diagnostic biomarkers of HCC. The other identified metabolites were considered as common potential biomarkers for the two liver diseases. Correlation networks based on these metabolites were also built for the systemic understanding of these diseases and the possible biological implications are discussed. This metabonomic approach may provide insight into discovery and identification of new diagnostic biomarkers for liver cancer and associated diseases.

Development and validation of a gas chromatography/mass spectrometry method for the metabolic profiling of human colon tissue

In this study, a gas chromatography/mass spectrometry (GC/MS) method was developed and validated for the metabolic profiling of human colon tissue. Each colon tissue sample (20 mg) was ultra-sonicated with 1 mL of a mixture of chloroform/methanol/water in the ratio of 20:50:20 (v/v/v), followed by centrifugation, collection of supernatant, drying, removal of moisture using anhydrous toluene and finally derivatization using N-methyl-N-trifluoroacetamide (MSTFA) with 1% trimethylchlorosilane (TMCS). A volume of 1 microL of the derivatized mixture was injected into the GC/MS system. A total of 53 endogenous metabolites were separated and identified in the GC/MS chromatogram, all of which were selected to evaluate the sample stability and precision of the method. Of the identified endogenous metabolites 19 belonging to diverse chemical classes and covering a wide range of the GC retention times (Rt) were selected to investigate the quantitative linearity of the method. The developed GC/MS method demonstrated good reproducibility with intra- and inter-day precision within relative standard deviation (RSD) of +/-15%. The metabolic profiles of the intact tissue were determined to be stable (100 +/- 15%) for up to 90 days at -80 degrees C. Satisfactory results were also obtained in the case of other stability-indicating studies such as freeze/thaw cycle stability, bench-top stability and autosampler stability. The developed method showed a good linear response for each of the 19 analytes tested (r(2) > 0.99). Our GC/MS metabolic profiling method was successfully applied to discriminate biopsied colorectal cancer (CRC) tissue from their matched normal tissue obtained from six CRC patients using orthogonal partial least-squares discriminant analysis [two latent variables, R(2)Y = 0.977 and Q(2) (cumulative) = 0.877].

Protein identification and quantification by two-dimensional infrared spectroscopy: implications for an all-optical proteomic platform

Electron-vibration-vibration two-dimensional coherent spectroscopy, a variant of 2DIR, is shown to be a useful tool to differentiate a set of 10 proteins based on their amino acid content. Two-dimensional vibrational signatures of amino acid side chains are identified and the corresponding signal strengths used to quantify their levels by using a methyl vibrational feature as an internal reference. With the current apparatus, effective differentiation can be achieved in four to five minutes per protein, and our results suggest that this can be reduced to <1 min per protein by using the same technology. Finally, we show that absolute quantification of protein levels is relatively straightforward to achieve and discuss the potential of an all-optical high-throughput proteomic platform based on two-dimensional infrared spectroscopic measurements.

Capillary electrophoresis-time of flight-mass spectrometry using noncovalently bilayer-coated capillaries for the analysis of amino acids in human urine

A capillary electrophoresis-time of flight-mass spectrometry (CE-TOF-MS) method for the analysis of amino acids in human urine was developed. Capillaries noncovalently coated with a bilayer of Polybrene (PB) and poly(vinyl sulfonate) (PVS) provided a considerable EOF at low pH, thus facilitating the fast separation of amino acids using a BGE of 1 M formic acid (pH 1.8). The PB-PVS coating proved to be very consistent yielding stable CE-MS patterns of amino acids in urine with favorable migration time repeatability (RSDs <2%). The relatively low sample loading capacity of CE was circumvented by an in-capillary preconcentration step based on pH-mediated stacking allowing 100-nL sample injection (i.e. ca. 4% of capillary volume). As a result, LODs for amino acids were down to 20 nM while achieving satisfactory separation efficiencies. Preliminary validation of the method with urine samples showed good linear responses for the amino acids (R(2) >0.99), and RSDs for peak areas were <10%. Special attention was paid to the influence of matrix effects on the quantification of amino acids. The magnitude of ion suppression by the matrix was similar for different urine samples. The CE-TOF-MS method was used for the analysis of urine samples of patients with urinary tract infection (UTI). Concentrations of a subset of amino acids were determined and compared with concentrations in urine of healthy controls. Furthermore, partial least squares-discriminant analysis (PLS-DA) of the CE-TOF-MS dataset in the 50-450 m/z region showed a distinctive grouping of the UTI samples and the control samples. Examination of score and loadings plot revealed a number of compounds, including phenylalanine, to be responsible for grouping of the samples. Thus, the CE-TOF-MS method shows good potential for the screening of body fluids based on the analysis of endogenous low-molecular weight metabolites such as amino acids and related compounds.

Top-down systems biology integration of conditional prebiotic modulated transgenomic interactions in a humanized microbiome mouse model

Gut microbiome-host metabolic interactions affect human health and can be modified by probiotic and prebiotic supplementation. Here, we have assessed the effects of consumption of a combination of probiotics (Lactobacillus paracasei or L. rhamnosus) and two galactosyl-oligosaccharide prebiotics on the symbiotic microbiome-mammalian supersystem using integrative metabolic profiling and modeling of multiple compartments in germ-free mice inoculated with a model of human baby microbiota. We have shown specific impacts of two prebiotics on the microbial populations of HBM mice when co-administered with two probiotics. We observed an increase in the populations of Bifidobacterium longum and B. breve, and a reduction in Clostridium perfringens, which were more marked when combining prebiotics with L. rhamnosus. In turn, these microbial effects were associated with modulation of a range of host metabolic pathways observed via changes in lipid profiles, gluconeogenesis, and amino-acid and methylamine metabolism associated to fermentation of carbohydrates by different bacterial strains. These results provide evidence for the potential use of prebiotics for beneficially modifying the gut microbial balance as well as host energy and lipid homeostasis.

Metabolomics in biomarker discovery: future uses for cancer prevention

Metabolomics is the systematic study of small-molecular-weight substances in cells, tissues and/or whole organisms as influenced by multiple factors including genetics, diet, lifestyle and pharmaceutical interventions. These substances may directly or indirectly interact with molecular targets and thereby influence the risk and complications associated with various diseases, including cancer. Since the interaction between metabolites and specific targets is dynamic, knowledge regarding genetics, susceptibility factors, timing, and degree of exposure to an agent (drug or food component) is fundamental to understanding the metabolome and its potential use for predicting and preventing early phenotypic changes. The future of metabolomics rests with its ability to monitor subtle changes in the metabolome that occur prior to the detection of a gross phenotypic change reflecting disease. The integrated analysis of metabolomics and other 'omics' may provide more sensitive ways to detect changes related to disease and discover novel biomarkers. Knowledge regarding these multivariant characteristics is critical for establishing validated and predictive metabolomic models for cancer prevention. Understanding the metabolome will not only provide insights into the critical sites of regulation in health promotion, but will also assist in identifying intermediate or surrogate cancer biomarkers for establishing preemptive/preventative or therapeutic approaches for health. While unraveling the metabolome will not be simple, the societal implications are enormous.

Metabolomic technologies and their application to the study of plants and plant-host interactions

Metabolomics is perhaps the ultimate level of post-genomic analysis as it can reveal changes in metabolite fluxes that are controlled by only minor changes within gene expression measured using transcriptomics and/or by analysing the proteome that elucidates post-translational control over enzyme activity. Metabolic change is a major feature of plant genetic modification and plant interactions with pathogens, pests, and their environment. In the assessment of genetically modified plant tissues, metabolomics has been used extensively to explore by-products resulting from transgene expression and scenarios of substantial equivalence. Many studies have concentrated on the physiological development of plant tissues as well as on the stress responses involved in heat shock or treatment with stress-eliciting molecules such as methyl jasmonic acid, yeast elicitor or bacterial lipopolysaccharide. Plant-host interactions represent one of the most biochemically complex and challenging scenarios that are currently being assessed by metabolomic approaches. For example, the mixtures of pathogen-colonised and non-challenged plant cells represent an extremely heterogeneous and biochemically rich sample; there is also the further complication of identifying which metabolites are derived from the plant host and which are from the interacting pathogen. This review will present an overview of the analytical instrumentation currently applied to plant metabolomic analysis, literature within the field will be reviewed paying particular regard to studies based on plant-host interactions and finally the future prospects on the metabolomic analysis of plants and plant-host interactions will be discussed.