A tandem liquid chromatography–mass spectrometry (LC–MS) method for profiling small molecules in complex samples

Liquid chromatography–mass spectrometry (LC–MS) methods using either aqueous normal phase (ANP) or reversed phase (RP) columns are routinely used in small molecule or metabolomic analyses. These stationary phases enable chromatographic fractionation of polar and non-polar compounds, respectively. The application of a single chromatographic stationary phase to a complex biological extract results in a significant proportion of compounds which elute in the non-retained fraction, where they are poorly detected because of a combination of ion suppression and the co-elution of isomeric compounds. Thus coverage of both polar and non-polar components of the metabolome generally involves multiple analyses of the same sample, increasing the analysis time and complexity. In this study we describe a novel tandem in-line LC–MS method, in which compounds from one injection are sequentially separated in a single run on both ANP and RP LC-columns. This method is simple, robust, and enables the use of independent gradients customized for both RP and ANP columns. The MS signal is acquired in a single chromatogram which reduces instrument time and operator and data analysis errors. This method has been used to analyze a range of biological extracts, from plant and animal tissues, human serum and urine, microbial cell and culture supernatants. Optimized sample preparation protocols are described for this method as well as a library containing the retention times and accurate masses of 127 compounds.

Non-invasive strategy in assessing asthma through biofluids metabolomics exploration: exhaled breath and urine potentialities

Asthma is a significant health issue in the pediatric population with a noteworthy growth over the years. The proposed challenge for this PhD thesis was the development of advanced methodologies to establish metabolomic patterns in urine and exhaled breath associated with asthma whose applicability was subsequently exploited to evaluate the disease state, the therapy adhesion and effect and for diagnostic purposes. The volatile composition of exhaled breath was studied combining headspace solid phase microextraction (HS-SPME) with gas chromatography coupled to mass spectrometry or with comprehensive two-dimensional gas chromatography coupled to mass spectrometry with a high resolution time of flight analyzer (GC×GC–ToFMS). These methodologies allowed the identification of several hundred compounds from different chemical families. Multivariate analysis (MVA) led to the conclusion that the metabolomic profile of asthma individuals is characterized by higher levels of compounds associated with lipid peroxidation, possibly linked to oxidative stress and inflammation (alkanes and aldehydes) known to play an important role in asthma. For future applications in clinical settings a set of nine compounds was defined and the clinical applicability was proven in monitoring the disease status and in the evaluation of the effect and / or adherence to therapy. The global volatile metabolome of urine was also explored using an HSSPME/GC×GC–ToFMS method and c.a. 200 compounds were identified. A targeted analysis was performed, with 78 compounds related with lipid peroxidation and consequently to oxidative stress levels and inflammation. The urinary non-volatile metabolomic pattern of asthma was established using proton nuclear magnetic resonance (1H NMR). This analysis allowed identifying central metabolic pathways such as oxidative stress, amino acid and lipid metabolism, gut microflora alterations, alterations in the tricarboxylic acid (TCA) cycle, histidine metabolism, lactic acidosis, and modification of free tyrosine residues after eosinophil stimulation. The obtained results allowed exploring and demonstrating the potential of analyzing the metabolomic profile of exhaled air and urine in asthma. Besides the successful development of analysis methodologies, it was possible to explore through exhaled air and urine biochemical pathways affected by asthma, observing complementarity between matrices, as well as, verify the clinical applicability.

Desenvolvimento de método analítico para estudo metabolômico de cana-de-açucar

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

HPLC-DAD method for metabolic fingerprinting of the phenotyping of sugarcane genotypes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

CE-ESI-MS metabolic fingerprinting of Leishmania resistance to antimony treatment

Metabolomics has become an invaluable tool to unveil biology of pathogens, with immediate application to chemotherapy. It is currently accepted that there is not one single technique capable of obtaining the whole metabolic fingerprint of a biological system either due to their different physical-chemical properties or concentrations. In this work, we have explored the capability of capillary electrophoresis mass spectrometry with a sheathless interface with electrospray ionization (CE-ESI-TOF-MS) to separate metabolites in order to be used as a complementary technique to LC. As proof of concept, we have compared the metabolome of Leishmania infantum promastigotes BCN 150 (Sb (III) IC50 = 20.9 mu M) and its variation when treated with 120 mu M of Sb(III) potassium tartrate for 12 h, as well as with its Sb(III) resistant counterpart obtained by growth of the parasites under increasing Sb(III) in a step-wise manner up to 180 mu M. The number of metabolites compared were of 264 for BCN150 Sb(III) treated versus nontreated and of 195 for Sb(III) resistant versus susceptible parasites. After successive data filtering, differences in seven metabolites identified in databases for Leishmania pathways, showed the highest significant differences, corresponding mainly to amino acids or their metabolite surrogates. Most of them were assigned to sulfur containing amino acids and polyamine biosynthetic pathways, of special relevance considering the deterioration of the thiol-dependent redox metabolism in Leishmania by Sb(III). Given the low concentrations typical for most of these metabolites, the assay can be considered a success that should be explored for new biological questions.

Biochemistry in healthy and neoplastic human tissues: metabolic alteration revealed by HR-MAS nuclear magnetic resonance spectroscopy

This thesis is focused on the metabolomic study of human cancer tissues by ex vivo High Resolution-Magic Angle Spinning (HR-MAS) nuclear magnetic resonance (NMR) spectroscopy. This new technique allows for the acquisition of spectra directly on intact tissues (biopsy or surgery), and it has become very important for integrated metabonomics studies. The objective is to identify metabolites that can be used as markers for the discrimination of the different types of cancer, for the grading, and for the assessment of the evolution of the tumour. Furthermore, an attempt to recognize metabolites, that although involved in the metabolism of tumoral tissues in low concentration, can be important modulators of neoplastic proliferation, was performed. In addition, NMR data was integrated with statistical techniques in order to obtain semi-quantitative information about the metabolite markers. In the case of gliomas, the NMR study was correlated with gene expression of neoplastic tissues. Chapter 1 begins with a general description of a new “omics” study, the metabolomics. The study of metabolism can contribute significantly to biomedical research and, ultimately, to clinical medical practice. This rapidly developing discipline involves the study of the metabolome: the total repertoire of small molecules present in cells, tissues, organs, and biological fluids. Metabolomic approaches are becoming increasingly popular in disease diagnosis and will play an important role on improving our understanding of cancer mechanism. Chapter 2 addresses in more detail the basis of NMR Spectroscopy, presenting the new HR-MAS NMR tool, that is gaining importance in the examination of tumour tissues, and in the assessment of tumour grade. Some advanced chemometric methods were used in an attempt to enhance the interpretation and quantitative information of the HR-MAS NMR data are and presented in chapter 3. Chemometric methods seem to have a high potential in the study of human diseases, as it permits the extraction of new and relevant information from spectroscopic data, allowing a better interpretation of the results. Chapter 4 reports results obtained from HR-MAS NMR analyses performed on different brain tumours: medulloblastoma, meningioms and gliomas. The medulloblastoma study is a case report of primitive neuroectodermal tumor (PNET) localised in the cerebellar region by Magnetic Resonance Imaging (MRI) in a 3-year-old child. In vivo single voxel 1H MRS shows high specificity in detecting the main metabolic alterations in the primitive cerebellar lesion; which consist of very high amounts of the choline-containing compounds and of very low levels of creatine derivatives and N-acetylaspartate. Ex vivo HR-MAS NMR, performed at 9.4 Tesla on the neoplastic specimen collected during surgery, allows the unambiguous identification of several metabolites giving a more in-depth evaluation of the metabolic pattern of the lesion. The ex vivo HR-MAS NMR spectra show higher detail than that obtained in vivo. In addition, the spectroscopic data appear to correlate with some morphological features of the medulloblastoma. The present study shows that ex vivo HR-MAS 1H NMR is able to strongly improve the clinical possibility of in vivo MRS and can be used in conjunction with in vivo spectroscopy for clinical purposes. Three histological subtypes of meningiomas (meningothelial, fibrous and oncocytic) were analysed both by in vivo and ex vivo MRS experiments. The ex vivo HR-MAS investigations are very helpful for the assignment of the in vivo resonances of human meningiomas and for the validation of the quantification procedure of in vivo MR spectra. By using one- and two dimensional experiments, several metabolites in different histological subtypes of meningiomas, were identified. The spectroscopic data confirmed the presence of the typical metabolites of these benign neoplasms and, at the same time, that meningomas with different morphological characteristics have different metabolic profiles, particularly regarding macromolecules and lipids. The profile of total choline metabolites (tCho) and the expression of the Kennedy pathway genes in biopsies of human gliomas were also investigated using HR-MAS NMR, and microfluidic genomic cards. 1H HR-MAS spectra, allowed the resolution and relative quantification by LCModel of the resonances from choline (Cho), phosphorylcholine (PC) and glycerolphorylcholine (GPC), the three main components of the combined tCho peak observed in gliomas by in vivo 1H MRS spectroscopy. All glioma biopsies depicted an increase in tCho as calculated from the addition of Cho, PC and GPC HR-MAS resonances. However, the increase was constantly derived from augmented GPC in low grade NMR gliomas or increased PC content in the high grade gliomas, respectively. This circumstance allowed the unambiguous discrimination of high and low grade gliomas by 1H HR-MAS, which could not be achieved by calculating the tCho/Cr ratio commonly used by in vivo 1H MR spectroscopy. The expression of the genes involved in choline metabolism was investigated in the same biopsies. The present findings offer a convenient procedure to classify accurately glioma grade using 1H HR-MAS, providing in addition the genetic background for the alterations of choline metabolism observed in high and low gliomas grade. Chapter 5 reports the study on human gastrointestinal tract (stomach and colon) neoplasms. The human healthy gastric mucosa, and the characteristics of the biochemical profile of human gastric adenocarcinoma in comparison with that of healthy gastric mucosa were analyzed using ex vivo HR-MAS NMR. Healthy human mucosa is mainly characterized by the presence of small metabolites (more than 50 identified) and macromolecules. The adenocarcinoma spectra were dominated by the presence of signals due to triglycerides, that are usually very low in healthy gastric mucosa. The use of spin-echo experiments enable us to detect some metabolites in the unhealthy tissues and to determine their variation with respect to the healthy ones. Then, the ex vivo HR-MAS NMR analysis was applied to human gastric tissue, to obtain information on the molecular steps involved in the gastric carcinogenesis. A microscopic investigation was also carried out in order to identify and locate the lipids in the cellular and extra-cellular environments. Correlation of the morphological changes detected by transmission (TEM) and scanning (SEM) electron microscopy, with the metabolic profile of gastric mucosa in healthy, gastric atrophy autoimmune diseases (AAG), Helicobacter pylori-related gastritis and adenocarcinoma subjects, were obtained. These ultrastructural studies of AAG and gastric adenocarcinoma revealed lipid intra- and extra-cellularly accumulation associated with a severe prenecrotic hypoxia and mitochondrial degeneration. A deep insight into the metabolic profile of human healthy and neoplastic colon tissues was gained using ex vivo HR-MAS NMR spectroscopy in combination with multivariate methods: Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA). The NMR spectra of healthy tissues highlight different metabolic profiles with respect to those of neoplastic and microscopically normal colon specimens (these last obtained at least 15 cm far from the adenocarcinoma). Furthermore, metabolic variations are detected not only for neoplastic tissues with different histological diagnosis, but also for those classified identical by histological analysis. These findings suggest that the same subclass of colon carcinoma is characterized, at a certain degree, by metabolic heterogeneity. The statistical multivariate approach applied to the NMR data is crucial in order to find metabolic markers of the neoplastic state of colon tissues, and to correctly classify the samples. Significant different levels of choline containing compounds, taurine and myoinositol, were observed. Chapter 6 deals with the metabolic profile of normal and tumoral renal human tissues obtained by ex vivo HR-MAS NMR. The spectra of human normal cortex and medulla show the presence of differently distributed osmolytes as markers of physiological renal condition. The marked decrease or disappearance of these metabolites and the high lipid content (triglycerides and cholesteryl esters) is typical of clear cell renal carcinoma (RCC), while papillary RCC is characterized by the absence of lipids and very high amounts of taurine. This research is a contribution to the biochemical classification of renal neoplastic pathologies, especially for RCCs, which can be evaluated by in vivo MRS for clinical purposes. Moreover, these data help to gain a better knowledge of the molecular processes envolved in the onset of renal carcinogenesis.

Characterization of novel probiotics and prebiotics

The role of the human gut microbiota in impacting host’s health has been widely studied in the last decade. Notably, it has been recently demonstrated that diet and nutritional status are among the most important modifiable determinants of human health, through a plethora of presumptive mechanisms among which microbiota-mediated processes are thought to have a relevant role. At present, probiotics and prebiotics represent a useful dietary approach for influencing the composition and activity of the human gut microbial community. The present study is composed of two main sections, aimed at elucidating the probiotic potential of the yeast strain K. marxianus B0399, as well as the promising putative prebiotic activity ascribable to four different flours, naturally enriched in dietary fibres content. Here, by in vitro studies we demonstrated that K. marxianus B0399 possesses a number of beneficial and strain-specific properties desirable for a microorganism considered for application as a probiotics. Successively, we investigated the impact of a novel probiotic yoghurt containing B. animalis subsp. lactis Bb12 and K. marxianus B0399 on the gut microbiota of a cohort of subjects suffering from IBS and enrolled in a in vivo clinical study. We demonstrated that beneficial effects described for the probiotic yoghurt were not associated to significant modifications of the human intestinal microbiota. Additionally, using a colonic model system we investigated the impact of different flours (wholegrain rye and wheat, chickpeas and lentils 50:50, and barley milled grains) on the intestinal microbiota composition and metabolomic output, combining molecular and cellular analysis with a NMR metabolomics approach. We demonstrated that each tested flour showed peculiar and positive modulations of the intestinal microbiota composition and its small molecule metabolome, thus supporting the utilisation of these ingredients in the development of a variety of potentially prebiotic food products aimed at improving human health.

Expression profiling und rationale Expressionsoptimierung am Beispiel eines prokaryontischen Wirt-,Vektor-Systems

Durch globale Expressionsprofil-Analysen auf Transkriptom-, Proteom- oder Metabolom-Ebene können biotechnologische Produktionsprozesse besser verstanden und die Erkenntnisse für die zielgerichtete, rationale Optimierung von Expressionssystemen genutzt werden. In der vorliegenden Arbeit wurde die Überexpression einer Glukose-Dehydrogenase (EC 1.1.5.2), die von der Roche Diagnostics GmbH für die diagnostische Anwendung optimiert worden war, in Escherichia coli untersucht. Die Enzymvariante unterscheidet sich in sieben ihrer 455 Aminosäuren vom Wildtyp-Enzym und wird im sonst isogenen Wirt-/Vektor-System in signifikant geringeren Mengen (Faktor 5) gebildet. Das prokaryontische Expressionssystem wurde auf Proteom-Ebene charakterisiert. Die 2-dimensionale differenzielle Gelelektrophorese (DIGE) wurde zuvor unter statistischen Aspekten untersucht. Unter Berücksichtigung von technischen und biologischen Variationen, falsch-positiven (α-) und falsch-negativen (β-) Fehlern sowie einem daraus abgeleiteten Versuchsdesign konnten Expressionsunterschiede als signifikant quantifiziert werden, wenn sie um den Faktor ≥ 1,4 differierten. Durch eine Hauptkomponenten-Analyse wurde gezeigt, dass die DIGE-Technologie für die Expressionsprofil-Analyse des Modellsystems geeignet ist. Der Expressionsstamm für die Enzymvariante zeichnete sich durch eine höhere Variabilität an Enzymen für den Zuckerabbau und die Nukleinsäure-Synthese aus. Im Expressionssystem für das Wildtyp-Enzym wurde eine unerwartet erhöhte Plasmidkopienzahl nachgewiesen. Als potenzieller Engpass in der Expression der rekombinanten Glukose-Dehydrogenase wurde die Löslichkeitsvermittlung identifiziert. Im Expressionsstamm für das Wildtyp-Enzym wurden viele Proteine für die Biogenese der äußeren Membran verstärkt exprimiert. Als Folge dessen wurde ein sog. envelope stress ausgelöst und die Zellen gingen in die stationäre Wuchsphase über. Die Ergebnisse der Proteomanalyse wurden weiterführend dazu genutzt, die Produktionsleistung für die Enzymvariante zu verbessern. Durch den Austausch des Replikationsursprungs im Expressionsvektor wurde die Plasmidkopienzahl erhöht und die zelluläre Expressionsleistung für die diagnostisch interessantere Enzymvariante um Faktor 7 - 9 gesteigert. Um die Löslichkeitsvermittlung während der Expression zu verbessern, wurde die Plasmidkopienzahl gesenkt und die Coexpression von Chaperonen initiiert. Die Ausbeuten aktiver Glukose-Dehydrogenase wurden durch die Renaturierung inaktiven Produkts aus dem optimierten Expressionssystem insgesamt um einen Faktor von 4,5 erhöht. Somit führte im Rahmen dieser Arbeit eine proteombasierte Expressionsprofil-Analyse zur zielgerichteten, rationalen Expressionsoptimierung eines prokaryontischen Modellsystems.

Xenobiotic metabolism: a view through the metabolometer

The combination of advanced ultraperformance liquid chromatography coupled with mass spectrometry, chemometrics, and genetically modified mice provide an attractive raft of technologies with which to examine the metabolism of xenobiotics. Here, a reexamination of the metabolism of the food mutagen PhIP (2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine), the suspect carcinogen areca alkaloids (arecoline, arecaidine, and arecoline 1-oxide), the hormone supplement melatonin, and the metabolism of the experimental cancer therapeutic agent aminoflavone is presented. In all cases, the metabolic maps of the xenobiotics were considerably enlarged, providing new insights into their toxicology. The inclusion of transgenic mice permitted unequivocal attribution of individual and often novel metabolic pathways to particular enzymes. Last, a future perspective for xenobiotic metabolomics is discussed and its impact on the metabolome is described. The studies reviewed here are not specific to the mouse and can be adapted to study xenobiotic metabolism in any animal species, including humans. The view through the metabolometer is unique and visualizes a metabolic space that contains both established and unknown metabolites of a xenobiotic, thereby enhancing knowledge of their modes of toxic action.

UPLC-MS-based urine metabolomics reveals indole-3-lactic acid and phenyllactic acid as conserved biomarkers for alcohol-induced liver disease in the Ppara-null mouse model

Since the development and prognosis of alcohol-induced liver disease (ALD) vary significantly with genetic background, identification of a genetic background-independent noninvasive ALD biomarker would significantly improve screening and diagnosis. This study explored the effect of genetic background on the ALD-associated urinary metabolome using the Ppara-null mouse model on two different backgrounds, C57BL/6 (B6) and 129/SvJ (129S), along with their wild-type counterparts. Reversed-phase gradient UPLC-ESI-QTOF-MS analysis revealed that urinary excretion of a number of metabolites, such as ethylsulfate, 4-hydroxyphenylacetic acid, 4-hydroxyphenylacetic acid sulfate, adipic acid, pimelic acid, xanthurenic acid, and taurine, were background-dependent. Elevation of ethyl-β-d-glucuronide and N-acetylglycine was found to be a common signature of the metabolomic response to alcohol exposure in wild-type as well as in Ppara-null mice of both strains. However, increased excretion of indole-3-lactic acid and phenyllactic acid was found to be a conserved feature exclusively associated with the alcohol-treated Ppara-null mouse on both backgrounds that develop liver pathologies similar to the early stages of human ALD. These markers reflected the biochemical events associated with early stages of ALD pathogenesis. The results suggest that indole-3-lactic acid and phenyllactic acid are potential candidates for conserved and pathology-specific high-throughput noninvasive biomarkers for early stages of ALD.

A research agenda for malaria eradication: basic science and enabling technologies

Today's malaria control efforts are limited by our incomplete understanding of the biology of Plasmodium and of the complex relationships between human populations and the multiple species of mosquito and parasite. Research priorities include the development of in vitro culture systems for the complete life cycle of P. falciparum and P. vivax and the development of an appropriate liver culture system to study hepatic stages. In addition, genetic technologies for the manipulation of Plasmodium need to be improved, the entire parasite metabolome needs to be characterized to identify new druggable targets, and improved information systems for monitoring the changes in epidemiology, pathology, and host-parasite-vector interactions as a result of intensified control need to be established to bridge the gap between bench, preclinical, clinical, and population-based sciences.

Pancreatic carcinoma, pancreatitis, and healthy controls: metabolite models in a three-class diagnostic dilemma

Metabolomics as one of the most rapidly growing technologies in the "-omics" field denotes the comprehensive analysis of low molecular-weight compounds and their pathways. Cancer-specific alterations of the metabolome can be detected by high-throughput mass-spectrometric metabolite profiling and serve as a considerable source of new markers for the early differentiation of malignant diseases as well as their distinction from benign states. However, a comprehensive framework for the statistical evaluation of marker panels in a multi-class setting has not yet been established. We collected serum samples of 40 pancreatic carcinoma patients, 40 controls, and 23 pancreatitis patients according to standard protocols and generated amino acid profiles by routine mass-spectrometry. In an intrinsic three-class bioinformatic approach we compared these profiles, evaluated their selectivity and computed multi-marker panels combined with the conventional tumor marker CA 19-9. Additionally, we tested for non-inferiority and superiority to determine the diagnostic surplus value of our multi-metabolite marker panels. Compared to CA 19-9 alone, the combined amino acid-based metabolite panel had a superior selectivity for the discrimination of healthy controls, pancreatitis, and pancreatic carcinoma patients [Formula: see text] We combined highly standardized samples, a three-class study design, a high-throughput mass-spectrometric technique, and a comprehensive bioinformatic framework to identify metabolite panels selective for all three groups in a single approach. Our results suggest that metabolomic profiling necessitates appropriate evaluation strategies and-despite all its current limitations-can deliver marker panels with high selectivity even in multi-class settings.

Isolation of plant growth promoting bacteria from torch lake sediments and their role in phytoremediation of metal contaminated soil

In this study, we isolated eight copper-resistant bacteria from Torch Lake sediment contaminated by copper mine tailings (stamp sand). Sequence analysis of gyrB and rpoD genes revealed that these organisms are closer to various Pseudomonas species. These eight bacterial isolates were also resistant to zinc, cesium, lead, arsenate and mercury. Further characterization showed that all the strains produced plant growth promoting indole-3-acetic acid (IAA), iron chelating siderophore and solubilized mineral phosphate and metals. The effect of bacterial inoculation on plant growth and copper uptake by maize (Zea mays) and sunflower (Helianthus annuus) was investigated using one of the isolates (Pseudomonas sp. TLC 6-6.5-4) with higher IAA production and phosphate and metal soubilization, which resulted in a significant increase in copper accumulation in maize and sunflower, and an increase in the total biomass of maize. Genes involved in copper resistance of Pseudomonas sp. TLC 6-6.5-4 was analyzed by transposon mutational analysis. Two copper sensitive mutants with significant reduction in copper resistance were identified: CSM1, a mutant disrupted in trp A gene (tryptophan synthase alpha subunit); CSM2, a mutant disrupted in clpA gene (ATP-dependent Clp protease). Proteomic and metabolomic analysis were performed to identify biochemical and molecular mechanisms involved in copper resistance using CSM2 due to its lower minimum inhibitory concentration compared with CSM1 and the wild type. The effect of different bacterial inoculation methods on plant growth, copper uptake and soil enzyme activities was investigated. Four different delivery methods were used including soil inoculation (before or after plant emergence), seed coating and root dipping. Soil inoculation before sowing seeds and coating seeds with PGPB led to better growth of maize, higher copper uptake and an increase in soil invertase and dehydrogenase activities. Proteomic and metabolomic analyses were performed to investigate the effect of bacterial inoculation on maize grown in normal soil and stamp sand. Our results revealed that bacterial inoculation led to environment-dependent effects on maize proteome and metabolome.

Radiation metabolomics. 1. Identification of minimally invasive urine biomarkers for gamma-radiation exposure in mice

Gamma-radiation exposure has both short- and long-term adverse health effects. The threat of modern terrorism places human populations at risk for radiological exposures, yet current medical countermeasures to radiation exposure are limited. Here we describe metabolomics for gamma-radiation biodosimetry in a mouse model. Mice were gamma-irradiated at doses of 0, 3 and 8 Gy (2.57 Gy/min), and urine samples collected over the first 24 h after exposure were analyzed by ultra-performance liquid chromatography-time-of-flight mass spectrometry (UPLC-TOFMS). Multivariate data were analyzed by orthogonal partial least squares (OPLS). Both 3- and 8-Gy exposures yielded distinct urine metabolomic phenotypes. The top 22 ions for 3 and 8 Gy were analyzed further, including tandem mass spectrometric comparison with authentic standards, revealing that N-hexanoylglycine and beta-thymidine are urinary biomarkers of exposure to 3 and 8 Gy, 3-hydroxy-2-methylbenzoic acid 3-O-sulfate is elevated in urine of mice exposed to 3 but not 8 Gy, and taurine is elevated after 8 but not 3 Gy. Gene Expression Dynamics Inspector (GEDI) self-organizing maps showed clear dose-response relationships for subsets of the urine metabolome. This approach is useful for identifying mice exposed to gamma radiation and for developing metabolomic strategies for noninvasive radiation biodosimetry in humans.

UPLC-ESI-TOFMS-based metabolomics and gene expression dynamics inspector self-organizing metabolomic maps as tools for understanding the cellular response to ionizing radiation

Global transcriptomic and proteomic profiling platforms have yielded important insights into the complex response to ionizing radiation (IR). Nonetheless, little is known about the ways in which small cellular metabolite concentrations change in response to IR. Here, a metabolomics approach using ultraperformance liquid chromatography coupled with electrospray time-of-flight mass spectrometry was used to profile, over time, the hydrophilic metabolome of TK6 cells exposed to IR doses ranging from 0.5 to 8.0 Gy. Multivariate data analysis of the positive ions revealed dose- and time-dependent clustering of the irradiated cells and identified certain constituents of the water-soluble metabolome as being significantly depleted as early as 1 h after IR. Tandem mass spectrometry was used to confirm metabolite identity. Many of the depleted metabolites are associated with oxidative stress and DNA repair pathways. Included are reduced glutathione, adenosine monophosphate, nicotinamide adenine dinucleotide, and spermine. Similar measurements were performed with a transformed fibroblast cell line, BJ, and it was found that a subset of the identified TK6 metabolites were effective in IR dose discrimination. The GEDI (Gene Expression Dynamics Inspector) algorithm, which is based on self-organizing maps, was used to visualize dynamic global changes in the TK6 metabolome that resulted from IR. It revealed dose-dependent clustering of ions sharing the same trends in concentration change across radiation doses. "Radiation metabolomics," the application of metabolomic analysis to the field of radiobiology, promises to increase our understanding of cellular responses to stressors such as radiation.