Nuclear magnetic resonance (NMR)-based metabolomics

Thyroid cancer cell metabolism: A glance into cell culture system-based metabolomics approaches

Thyroid cancer is the most common malignancy of the endocrine system and the seventh most prevalent cancer in women worldwide. It is a complex and diverse disease characterized by heterogeneity, underscoring the importance of understanding the underlying metabolic alterations within tumor cells. Metabolomics technologies offer a powerful toolset to explore and identify endogenous and exogenous biochemical reaction products, providing crucial insights into the intricate metabolic pathways and processes within living cells. Metabolism plays a central role in cell function, making metabolomics a valuable reflection of a cell's phenotype. In the OMICs era, metabolomics analysis of cells brings numerous advantages over existing methods, propelling cell metabolomics as an emerging field with vast potential for investigating metabolic pathways and their perturbation in pathophysiological conditions. This review article aims to look into recent developments in applying metabolomics for characterizing and interpreting the cellular metabolome in thyroid cancer cell lines, exploring their unique metabolic characteristics. Understanding the metabolic alterations in tumor cells can lead to the identification of critical nodes in the metabolic network that could be targeted for therapeutic intervention.

Integrative metabolic profile of myelodysplastic syndrome based on UHPLC-MS

Myelodysplastic syndrome (MDS) is a neoplastic disease originating from hematopoietic stem cells. Currently, hematopoietic stem cell transplantation (HSCT) is the most effective cure, although lenalidomide, azacytidine, and decitabine have been applied to relieve symptoms of MDS. The purpose of this study was to evaluate the changes in endogenous metabolites by applying a UHPLC-MS (ultra-high-performance liquid chromatography-MS) metabolomics approach and to investigate metabolic pathways related to MDS. An untargeted metabolomics approach based on UHPLC-MS in combination with multivariate data analysis, including partial least squares discrimination analysis and orthogonal partial least squares discriminant analysis, was established to investigate potential biomarkers in the plasma of MDS patients. As a result, 29 biomarkers were identified to distinguish between MDS patients, HSCT patients, and healthy controls, which were mainly related to inflammation regulation, amino acid metabolism, fatty acid metabolism, and energy metabolism. To our knowledge, this is the first time where plasma metabolomics was combined with HSCT to study the pathogenesis and therapeutic target of MDS. The identification of biomarkers and analysis of metabolic pathways could offer the possibility of discovering new therapeutic targets for MDS in the future.

Insights into glucocorticoid responses derived from omics studies

Glucocorticoid drugs are commonly used in the treatment of several conditions, including autoimmune diseases, asthma and cancer. Despite their widespread use and knowledge of biological pathways via which they act, much remains to be learned about the cell type-specific mechanisms of glucocorticoid action and the reasons why patients respond differently to them. In recent years, human and in vitro studies have addressed these questions with genomics, transcriptomics and other omics approaches. Here, we summarize key insights derived from omics studies of glucocorticoid response, and we identify existing knowledge gaps related to mechanisms of glucocorticoid action that future studies can address.

Optimization of Synovial Fluid Collection and Processing for NMR Metabolomics and LC-MS/MS Proteomics

Synovial fluid (SF) is of great interest for the investigation of orthopedic pathologies, as it is in close proximity to various tissues that are primarily altered during these disease processes and can be collected using minimally invasive protocols. Multi-"omic" approaches are commonplace, although little consideration is often given for multiple analysis techniques at sample collection. Nuclear magnetic resonance (NMR) metabolomics and liquid chromatography tandem mass spectrometry (LC-MS/MS) proteomics are two complementary techniques particularly suited to the study of SF. However, currently there are no agreed upon standard protocols that are published for SF collection and processing for use with NMR metabolomic analysis. Furthermore, the large protein concentration dynamic range present within SF can mask the detection of lower abundance proteins in proteomics. While combinational ligand libraries (ProteoMiner columns) have been developed to reduce this dynamic range, their reproducibility when used in conjunction with SF, or on-bead protein digestion protocols, has yet to be investigated. Here we employ optimized protocols for the collection, processing, and storage of SF for NMR metabolite analysis and LC-MS/MS proteome analysis, including a Lys-C endopeptidase digestion step prior to tryptic digestion, which increased the number of protein identifications and improved reproducibility for on-bead ProteoMiner digestion.

Isolation, Characterization and Chemical Synthesis of Large Spectrum Antimicrobial Cyclic Dipeptide (l-leu-l-pro) from Streptomyces misionensisV16R3Y1 Bacteria Extracts. A Novel 1H NMR Metabolomic Approach

Streptomyces is the most frequently described genus of Actinomycetes, a producer of biologically active secondary metabolites. Indeed, the Streptomyces species produces about 70% of antibiotics and 60% of antifungal molecules used in agriculture. Our study was carried out with the goal of isolating and identifying antimicrobial secondary metabolites from Streptomyces misionensis V16R3Y1 isolated from the date palm rhizosphere (southern Tunisia). This strain presented a broad range of antifungal activity against Fusarium oxysporum, Aspergillus flavus, Penicillium expansum, Aspergillus niger, Candida albicans, Candida metapsilosis, and Candida parapsilosis and antibacterial activity against human pathogenic bacteria, including Escherichia fergusonii, Staphylococcus aureus, Salmonella enterica, Enterococcus faecalis, Bacillus cereus and Pseudomonas aeruginosa. The purification procedure entailed ethyl acetate extract, silica gel column, and thin layer chromatography. Based on ¹H NMR metabolomic procedure application, also supported by the GC-MS analysis, cyclic dipeptide (l-Leucyl-l-Proline) was identified as the major compound in the bioactive fraction. In order to confirm the identity of the active compound and to have a large quantity thereof, a chemical synthesis of the cyclic dipeptide was performed. The synthetic compound was obtained with a very good yield (50%) and presented almost the same effect compared to the extracted fraction. This study indicates for the first time that Streptomyces misionensis V16R3Y1 exhibits a broad spectrum of antimicrobial activities, produced cyclic dipeptide (l-Leucyl-l-Proline) and might have potential use as a natural agent for pharmaceutical and agri-food applications.

The impact of p53 on aristolochic acid I-induced nephrotoxicity and DNA damage in vivo and in vitro

Exposure to aristolochic acid (AA) is associated with human nephropathy and urothelial cancer. The tumour suppressor TP53 is a critical gene in carcinogenesis and frequently mutated in AA-induced urothelial tumours. We investigated the impact of p53 on AAI-induced nephrotoxicity and DNA damage in vivo by treating Trp53(+/+), Trp53(+/-) and Trp53(-/-) mice with 3.5 mg/kg body weight (bw) AAI daily for 2 or 6 days. Renal histopathology showed a gradient of intensity in proximal tubular injury from Trp53(+/+) to Trp53(-/-) mice, especially after 6 days. The observed renal injury was supported by nuclear magnetic resonance (NMR)-based metabonomic measurements, where a consistent Trp53 genotype-dependent trend was observed for urinary metabolites that indicate aminoaciduria (i.e. alanine), lactic aciduria (i.e. lactate) and glycosuria (i.e. glucose). However, Trp53 genotype had no impact on AAI-DNA adduct levels, as measured by 32P-postlabelling, in either target (kidney and bladder) or non-target (liver) tissues, indicating that the underlying mechanisms of p53-related AAI-induced nephrotoxicity cannot be explained by differences in AAI genotoxicity. Performing gas chromatography-mass spectrometry (GC-MS) on kidney tissues showed metabolic pathways affected by AAI treatment, but again Trp53 status did not clearly impact on such metabolic profiles. We also cultured primary mouse embryonic fibroblasts (MEFs) derived from Trp53(+/+), Trp53(+/-) and Trp53(-/-) mice and exposed them to AAI in vitro (50 µM for up to 48 h). We found that Trp53 genotype impacted on the expression of NAD(P)H:quinone oxidoreductase (Nqo1), a key enzyme involved in AAI bioactivation. Nqo1 induction was highest in Trp53(+/+) MEFs and lowest in Trp53(-/-) MEFs; and it correlated with AAI-DNA adduct formation, with lowest adduct levels being observed in AAI-exposed Trp53(-/-) MEFs. Overall, our results clearly demonstrate that p53 status impacts on AAI-induced renal injury, but the underlying mechanism(s) involved remain to be further explored. Despite the impact of p53 on AAI bioactivation and DNA damage in vitro, such effects were not observed in vivo.

NMR Based Metabolomics Comparison of Different Blood Sampling Techniques in Awake and Anesthetized Rats

The composition of body fluids has become one of the most commonly used methods for diagnosing various diseases or monitoring the drug responses, especially in serum/plasma. It is therefore vital for investigators to find an appropriate way to collect blood samples from laboratory animals. This study compared blood samples collected from different sites using the NMR based metabolomics approach. Blood samples were collected from the saphenous vein (awake state), tail vein (awake and anesthetized states after administration of sevoflurane or pentobarbital) and the inferior thoracic vena cava (ITVC, anesthetized state). These approaches from the saphenous and tail veins have the potential to enable the collection of multiple samples, and the approach from ITVC is the best method for the collection of blood for the terminate state. The compositions of small molecules in the serum were determined using the 1H-NMR method, and the data were analyzed with traditional correlation analysis, principle component analysis (PCA) and OPLS-DA methods. The results showed that acute anesthesia significantly influenced the composition of serum in a very short period, such as the significant increase in glucose, and decrease in lactate. This indicates that it is better to obtain blood samples under the awake state. From the perspective of animal welfare and multiple sampling, the current study shows that the saphenous vein and tail vein are the best locations to collect multiple blood samples for a reduced risk of injury in the awake state. Furthermore, it is also suitable for investigating pharmacokinetics and the effects of drug intervention on animals.

Microdialysis Workflow for Metabotyping Superficial Pathologies: Application to Burn Injury

Burn injury can be a devastating traumatic injury, with long-term personal and social implications for the patient. The many complex local and disseminating pathological processes underlying burn injury's clinical challenges are orchestrated from the site of injury and develop over time, yet few studies of the molecular basis of these mechanisms specifically explore the local signaling environment. Those that do are typically destructive in nature and preclude the collection of longitudinal temporal data. Burn injury therefore exemplifies a superficial temporally dynamic pathology for which experimental sampling typically prioritizes either specificity to the local burn site or continuous collection from circulation. Here, we present an exploratory approach to the targeted elucidation of complex, local, acutely temporally dynamic interstitia through its application to burn injury. Subcutaneous microdialysis is coupled with ultraperformance liquid chromatography-mass spectrometry (UPLC-MS) analysis, permitting the application of high-throughput metabolomic profiling to samples collected both continuously and specifically from the burn site. We demonstrate this workflow's high yield of burn-altered metabolites including the complete structural elucidation of niacinamide and uric acid, two compounds potentially involved in the pathology of burn injury. Further understanding the metabolic changes induced by burn injury will help to guide therapeutic intervention in the future. This approach is equally applicable to the analysis of other tissues and pathological conditions, so it may further improve our understanding of the metabolic changes underlying a wide variety of pathological processes.

Synovial Fluid Metabolites Differentiate between Septic and Nonseptic Joint Pathologies

Osteoarthritis (OA), osteochondrosis (OC), and synovial sepsis in horses cause loss of function and pain. Reliable biomarkers are required to achieve accurate and rapid diagnosis, with synovial fluid (SF) holding a unique source of biochemical information. Nuclear magnetic resonance (NMR) spectroscopy allows global metabolite analysis of a small volume of SF, with minimal sample preprocessing using a noninvasive and nondestructive method. Equine SF metabolic profiles from both nonseptic joints (OA and OC) and septic joints were analyzed using 1D 1H NMR spectroscopy. Univariate and multivariate statistical analyses were used to identify differential metabolite abundance between groups. Metabolites were annotated via 1H NMR using 1D NMR identification software Chenomx, with identities confirmed using 1D 1H and 2D 1H 13C NMR. Multivariate analysis identified separation between septic and nonseptic groups. Acetate, alanine, citrate, creatine phosphate, creatinine, glucose, glutamate, glutamine, glycine, phenylalanine, pyruvate, and valine were higher in the nonseptic group, while glycylproline was higher in sepsis. Multivariate separation was primarily driven by glucose; however, partial-least-squares discriminant analysis plots with glucose excluded demonstrated the remaining metabolites were still able to discriminate the groups. This study demonstrates that a panel of synovial metabolites can distinguish between septic and nonseptic equine SF, with glucose the principal discriminator.

Metabolomic changes in vertebrate host during malaria disease progression

Metabolomics refers to top-down systems biological analysis of metabolites in biological specimens. Phenotypic proximity of metabolites makes them interesting candidates for studying biomarkers of environmental stressors such as parasitic infections. Moreover, the host-parasite interaction directly impinges upon metabolic pathways since the parasite uses the host metabolite pool as a biosynthetic resource. Malarial infection, although not recognized as a classic metabolic disorder, often leads to severe metabolic changes such as hypoglycemia and lactic acidosis. Thus, metabolomic analysis of the infection has become an invaluable tool for promoting a better understanding of the host-parasite interaction and for the development of novel therapeutics. In this review, we summarize the current knowledge obtained from metabolomic studies of malarial infection in rodent models and human patients. Metabolomic analysis of experimental rodent malaria has provided significant insights into the mechanisms of disease progression including utilization of host resources by the parasite, sexual dimorphism in metabolic phenotypes, and cellular changes in host metabolism. Moreover, these studies also provide proof of concept for prediction of cerebral malaria. On the other hand, metabolite analysis of patient biofluids generates extensive data that could be of use in identifying biomarkers of infection severity and in monitoring disease progression. Through the use of metabolomic datasets one hopes to assess crucial infection-specific issues such as clinical severity, drug resistance, therapeutic targets, and biomarkers. Also discussed are nascent or newly emerging areas of metabolomics such as pre-erythrocytic stages of the infection and the host immune response. This review is organized in four broad sections-methodologies for metabolomic analysis, rodent infection models, studies of human clinical specimens, and potential of immunometabolomics. Data summarized in this review should serve as a springboard for novel hypothesis testing and lead to a better understanding of malarial infection and parasite biology.

Hepatic metabolic effects of Curcuma longa extract supplement in high-fructose and saturated fat fed rats

The metabolic effects of an oral supplementation with a Curcuma longa extract, at a dose nutritionally relevant with common human use, on hepatic metabolism in rats fed a high fructose and saturated fatty acid (HFS) diet was evaluated. High-resolution magic-angle spinning NMR and GC/MS in combination with multivariate analysis have been employed to characterize the NMR metabolite profiles and fatty acid composition of liver tissue respectively. The results showed a clear discrimination between HFS groups and controls involving metabolites such as glucose, glycogen, amino acids, acetate, choline, lysophosphatidylcholine, phosphatidylethanolamine, and β-hydroxybutyrate as well as an increase of MUFAs and a decrease of n-6 and n-3 PUFAs. Although the administration of CL did not counteract deleterious effects of the HFS diet, some metabolites, namely some n-6 PUFA and n-3 PUFA, and betaine were found to increase significantly in liver samples from rats having received extract of curcuma compared to those fed the HFS diet alone. This result suggests that curcuminoids may affect the transmethylation pathway and/or osmotic regulation. CL extract supplementation in rats appears to increase some of the natural defences preventing the development of fatty liver by acting on the choline metabolism to increase fat export from the liver.

Metabolite signatures of doxorubicin induced toxicity in human induced pluripotent stem cell-derived cardiomyocytes

Drug-induced off-target cardiotoxicity, particularly following anti-cancer therapy, is a major concern in new drug discovery and development. To ensure patient safety and efficient pharmaceutical drug development, there is an urgent need to develop more predictive cell model systems and distinct toxicity signatures. In this study, we applied our previously proposed repeated exposure toxicity methodology and performed ¹H NMR spectroscopy-based extracellular metabolic profiling in culture medium of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) exposed to doxorubicin (DOX), an anti-cancer agent. Single exposure to DOX did not show alteration in the basal level of extracellular metabolites while repeated exposure to DOX caused reduction in the utilization of pyruvate and acetate, and accumulation of formate compared to control culture medium. During drug washout, only pyruvate showed reversible effect and restored its utilization by hiPSC-CMs. On the other hand, formate and acetate showed irreversible effect in response to DOX exposure. DOX repeated exposure increased release of lactate dehydrogenase (LDH) in culture medium suggesting cytotoxicity events, while declined ATP levels in hiPSC-CMs. Our data suggests DOX perturbed mitochondrial metabolism in hiPSC-CMs. Pyruvate, acetate and formate can be used as metabolite signatures of DOX induced cardiotoxicity. Moreover, the hiPSC-CMs model system coupled with metabolomics technology offers a novel and powerful approach to strengthen cardiac safety assessment during new drug discovery and development.

HILIC-MS for metabolomics: An attractive and complementary approach to RPLC-MS

Hydrophilic interaction chromatography (HILIC) is an emerging separation mode of liquid chromatography (LC). Using highly hydrophilic stationary phases capable of retaining polar/ionic metabolites, and accompany with high organic content mobile phase that offer readily compatibility with mass spectrometry (MS) has made HILIC an attractive complementary tool to the widely used reverse-phase (RP) chromatographic separations in metabolomic studies. The combination of HILIC and RPLC coupled with an MS detector expands the number of detected analytes and provides more comprehensive metabolite coverage than use of only RP chromatography. This review describes the recent applications of HILIC-MS/MS in metabolomic studies, ranging from amino acids, lipids, nucleotides, organic acids, pharmaceuticals, and metabolites of specific nature. The biological systems investigated include microbials, cultured cell line, plants, herbal medicine, urine, and serum as well as tissues from animals and humans. Owing to its unique capability to measure more-polar biomolecules, the HILIC separation technique would no doubt enhance the comprehensiveness of metabolite detection, and add significant value for metabolomic investigations. © 2014 Wiley Periodicals, Inc. Mass Spec Rev 35:574-600, 2016.

Metabolomics, Lipidomics and Pharmacometabolomics of Human Hypertension

Hypertension is a common but complex human disease, which can lead to a heart attack, stroke, kidney disease or other complications. Since the pathogenesis of hypertension is heterogeneous and multifactorial, it is crucial to establish a comprehensive metabolomic approach to elucidate the molecular mechanism of hypertension. Although there have been limited metabolomic, lipidomic and pharmacometabolomic studies investigating this disease to date, metabolomic studies on hypertension have provided greater insights into the identification of disease-specific biomarkers, predicting treatment outcome and monitor drug safety and efficacy. Therefore, we discuss recent updates on the applications of metabolomics technology in human hypertension with a focus on metabolic biomarker discovery.

Metabolomics and diabetes: analytical and computational approaches

Diabetes is characterized by altered metabolism of key molecules and regulatory pathways. The phenotypic expression of diabetes and associated complications encompasses complex interactions between genetic, environmental, and tissue-specific factors that require an integrated understanding of perturbations in the network of genes, proteins, and metabolites. Metabolomics attempts to systematically identify and quantitate small molecule metabolites from biological systems. The recent rapid development of a variety of analytical platforms based on mass spectrometry and nuclear magnetic resonance have enabled identification of complex metabolic phenotypes. Continued development of bioinformatics and analytical strategies has facilitated the discovery of causal links in understanding the pathophysiology of diabetes and its complications. Here, we summarize the metabolomics workflow, including analytical, statistical, and computational tools, highlight recent applications of metabolomics in diabetes research, and discuss the challenges in the field.

Alterations of choline phospholipid metabolism in endometrial cancer are caused by choline kinase alpha overexpression and a hyperactivated deacylation pathway

Metabolic rearrangements subsequent to malignant transformation are not well characterized in endometrial cancer. Identification of altered metabolites could facilitate imaging-guided diagnosis, treatment surveillance, and help to identify new therapeutic options. Here, we used high-resolution magic angle spinning magnetic resonance mass spectroscopy on endometrial cancer surgical specimens and normal endometrial tissue to investigate the key modulators that might explain metabolic changes, incorporating additional investigations using qRT-PCR, Western blotting, tissue microarrays (TMA), and uptake assays of [(3)H]-labeled choline. Lipid metabolism was severely dysregulated in endometrial cancer with various amino acids, inositols, nucleobases, and glutathione also altered. Among the most important lipid-related alterations were increased phosphocholine levels (increased 70% in endometrial cancer). Mechanistic investigations revealed that changes were not due to altered choline transporter expression, but rather due to increased expression of choline kinase α (CHKA) and an activated deacylation pathway, as indicated by upregulated expression of the catabolic enzymes LYPLA1, LYPLA2, and GPCPD1. We confirmed the significance of CHKA overexpression on a TMA, including a large series of endometrial hyperplasia, atypical hyperplasia, and adenocarcinoma tissues, supporting a role for CHKA in malignant transformation. Finally, we documented several-fold increases in the uptake of [(3)H]choline in endometrial cancer cell lines compared with normal endometrial stromal cells. Our results validate deregulated choline biochemistry as an important source of noninvasive imaging biomarkers for endometrial cancer.

Mammalian cell metabolomics: experimental design and sample preparation

Metabolomics represents the global assessment of metabolites in a biological sample and reports the closest information to the phenotype of the biological system under study. Mammalian cell metabolomics has emerged as a promising tool with potential applications in many biotechnology and research areas. Metabolomics workflow includes experimental design, sampling, sample processing, metabolite analysis, and data processing. Given their influence on metabolite content and biological interpretation of data, a good experimental design and the appropriate choice of a sample processing method are prerequisites for success in any metabolomic study. The use of mammalian cells in the metabolomics field involves harder sample processing methods, including metabolism quenching and metabolite extraction, as compared to the use of body fluids, although such critical issues are frequently overlooked. This review aims to overview the common experimental procedures used in mammalian cell metabolomics based on mass spectrometry, by placing special emphasis on discussing sample preparation approaches, although other aspects, such as cell metabolomics applications, culture systems, cellular models, analytical platforms, and data analysis, are also briefly covered. This review intends to be a helpful tool to assist researchers in addressing decisions when planning a metabolomics study involving the use of mammalian cells.

Choline-releasing glycerophosphodiesterase EDI3 drives tumor cell migration and metastasis

Metastasis from primary tumors remains a major problem for tumor therapy. In the search for markers of metastasis and more effective therapies, the tumor metabolome is relevant because of its importance to the malignant phenotype and metastatic capacity of tumor cells. Altered choline metabolism is a hallmark of cancer. More specifically, a decreased glycerophosphocholine (GPC) to phosphocholine (PC) ratio was reported in breast, ovarian, and prostate cancers. Improved strategies to exploit this altered choline metabolism are therefore required. However, the critical enzyme cleaving GPC to produce choline, the initial step in the pathway controlling the GPC/PC ratio, remained unknown. In the present work, we have identified the enzyme, here named EDI3 (endometrial differential 3). Purified recombinant EDI3 protein cleaves GPC to form glycerol-3-phosphate and choline. Silencing EDI3 in MCF-7 cells decreased this enzymatic activity, increased the intracellular GPC/PC ratio, and decreased downstream lipid metabolites. Downregulating EDI3 activity inhibited cell migration via disruption of the PKCα signaling pathway, with stable overexpression of EDI3 showing the opposite effect. EDI3 was originally identified in our screening study comparing mRNA levels in metastasizing and nonmetastasizing endometrial carcinomas. Both Kaplan-Meier and multivariate analyses revealed a negative association between high EDI3 expression and relapse-free survival time in both endometrial (P < 0.001) and ovarian (P = 0.029) cancers. Overall, we have identified EDI3, a key enzyme controlling GPC and choline metabolism. Because inhibition of EDI3 activity corrects the GPC/PC ratio and decreases the migration capacity of tumor cells, it represents a possible target for therapeutic intervention.

Metabolomics in cancer: a bench-to-bedside intersection

The field of oncology is a rapidly evolving science mostly due to extensive basic, translational and clinical research which have provided more insights into the tumor biology and set grounds for the development of new therapies. Metabolomics is the upcoming new science in the omics field with the potential to further increment our knowledge of cancer biology. In this review we intend to explore the potential role of metabolomics in understanding cancer process, improving cancer staging, refining tumor characterization and in the search for predictive biomarkers of response and toxicity.

Bioinformatics Tools for Mass Spectroscopy-Based Metabolomic Data Processing and Analysis

Biological systems are increasingly being studied in a holistic manner, using omics approaches, to provide quantitative and qualitative descriptions of the diverse collection of cellular components. Among the omics approaches, metabolomics, which deals with the quantitative global profiling of small molecules or metabolites, is being used extensively to explore the dynamic response of living systems, such as organelles, cells, tissues, organs and whole organisms, under diverse physiological and pathological conditions. This technology is now used routinely in a number of applications, including basic and clinical research, agriculture, microbiology, food science, nutrition, pharmaceutical research, environmental science and the development of biofuels. Of the multiple analytical platforms available to perform such analyses, nuclear magnetic resonance and mass spectrometry have come to dominate, owing to the high resolution and large datasets that can be generated with these techniques. The large multidimensional datasets that result from such studies must be processed and analyzed to render this data meaningful. Thus, bioinformatics tools are essential for the efficient processing of huge datasets, the characterization of the detected signals, and to align multiple datasets and their features. This paper provides a state-of-the-art overview of the data processing tools available, and reviews a collection of recent reports on the topic. Data conversion, pre-processing, alignment, normalization and statistical analysis are introduced, with their advantages and disadvantages, and comparisons are made to guide the reader.

Chiral metabonomics: 1H NMR-based enantiospecific differentiation of metabolites in human urine via direct cosolvation with β-cyclodextrin

Differences in molecular chirality remain an important issue in drug metabolism and pharmacokinetics for the pharmaceutical industry and regulatory authorities, and chirality is an important feature of many endogenous metabolites. We present a method for the rapid, direct differentiation and identification of chiral drug enantiomers in human urine without pretreatment of any kind. Using the well-known anti-inflammatory chemical ibuprofen as one example, we demonstrate that the enantiomers of ibuprofen and the diastereoisomers of one of its main metabolites, the glucuronidated carboxylate derivative, can be resolved by (1)H NMR spectroscopy as a consequence of direct addition of the chiral cosolvating agent (CSA) β-cyclodextrin (βCD). This approach is simple, rapid, and robust, involves minimal sample manipulation, and does not require derivatization or purification of the sample. In addition, the method should allow the enantiodifferentiation of endogenous chiral metabolites, and this has potential value for differentiating metabolites from mammalian and microbial sources in biofluids. From these initial findings, we propose that more extensive and detailed enantiospecific metabolic profiling could be possible using CSA-NMR spectroscopy than has been previously reported.

Metabolomics of B to plasma cell differentiation

When small B lymphocytes bind antigen in the context of suitable signals, a profound geno-proteomic metamorphosis is activated that generates antibody-secreting cells. To study the metabolic changes associated with this differentiation program, we compared the exometabolome of differentiating murine B lymphoma cells and primary B cells by monodimensional proton nuclear magnetic resonance spectroscopy and mass spectrometry coupled to liquid chromatography. Principal component analysis, a multivariate statistical analysis, highlighted metabolic hallmarks of the sequential differentiation phases discriminating between the proliferation and antibody secreting phases and revealing novel metabolic pathways. During proliferation, lactate production increased together with consumption of essential amino acids; massive Ig secretion was paralleled by alanine and glutamate production, glutamine being used as carbon and energy sources. Notably, ethanol and 5'-methylthioadenosine were produced during the last phase of protein secretion and the proliferative burst, respectively. Our metabolomics results are in agreement with previous genoproteomics studies. Thus, metabolic profiling of extracellular medium is a useful tool to characterize the functional state of differentiating B cells and to identify novel underlying metabolic pathways.