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Twenty-eight sponge specimens were collected at a shallow water hydrothermal vent site north of Iceland. Extracts were prepared and tested in vitro for cytotoxic activity, and eight of them were shown to be cytotoxic. A mass spectrometry (MS)-based metabolomics approach was used to determine the chemical composition of the extracts. This analysis highlighted clear differences in the metabolomes of three sponge specimens, and all of them were identified as Haliclona (Rhizoniera) rosea (Bowerbank, 1866). Therefore, these specimens were selected for further investigation. Haliclona rosea metabolomes contained a class of potential key compounds, the 3-alkyl pyridine alkaloids (3-APA) responsible for the cytotoxic activity of the fractions. Several 3-APA compounds were tentatively identified including haliclamines, cyclostellettamines, viscosalines and viscosamines. Among these compounds, cyclostellettamine P was tentatively identified for the first time by using ion mobility MS in time-aligned parallel (TAP) fragmentation mode. In this work, we show the potential of applying metabolomics strategies and in particular the utility of coupling ion mobility with MS for the molecular characterization of sponge specimens., The authors would like to thank Erlendur Bogason for his assistance in sample collection as well as being the "protector" of Strytan, the hydrothermal vent site. This project was funded by the Eimskip University Fund, The University of Iceland Research Fund, and the Icelandic Research Fund (grant no.: 110403021).

The human gut microbiota plays a central role in human well-being and disease. In this study, we present an integrated, iterative approach of computational modeling, in vitro experiments, metabolomics, and genomic analysis to accelerate the identification of metabolic capabilities for poorly characterized (anaerobic) microorganisms. We demonstrate this approach for the beneficial human gut microbe Faecalibacterium prausnitzii strain A2-165. We generated an automated draft reconstruction, which we curated against the limited biochemical data. This reconstruction modeling was used to develop in silico and in vitro a chemically defined medium (CDM), which was validated experimentally. Subsequent metabolomic analysis of the spent medium for growth on CDM was performed. We refined our metabolic reconstruction according to in vitro observed metabolite consumption and secretion and propose improvements to the current genome annotation of F. prausnitzii A2-165. We then used the reconstruction to systematically characterize its metabolic properties. Novel carbon source utilization capabilities and inabilities were predicted based on metabolic modeling and validated experimentally. This study resulted in a functional metabolic map of F. prausnitzii , which is available for further applications. The presented workflow can be readily extended to other poorly characterized and uncharacterized organisms to yield novel biochemical insights about the target organism.

Metabolic models can provide a mechanistic framework to analyze information-rich omics data sets, and are increasingly being used to investigate metabolic alternations in human diseases. An expression of the altered metabolic pathway utilization is the selection of metabolites consumed and released by cells. However, methods for the inference of intracellular metabolic states from extracellular measurements in the context of metabolic models remain underdeveloped compared to methods for other omics data. Herein, we describe a workflow for such an integrative analysis emphasizing on extracellular metabolomics data. We demonstrate, using the lymphoblastic leukemia cell lines Molt-4 and CCRF-CEM, how our methods can reveal differences in cell metabolism. Our models explain metabolite uptake and secretion by predicting a more glycolytic phenotype for the CCRF-CEM model and a more oxidative phenotype for the Molt-4 model, which was supported by our experimental data. Gene expression analysis revealed altered expression of gene products at key regulatory steps in those central metabolic pathways, and literature query emphasized the role of these genes in cancer metabolism. Moreover, in silico gene knock-outs identified unique control points for each cell line model, e.g., phosphoglycerate dehydrogenase for the Molt-4 model. Thus, our workflow is well-suited to the characterization of cellular metabolic traits based on extracellular metabolomic data, and it allows the integration of multiple omics data sets into a cohesive picture based on a defined model context. Electronic supplementary material The online version of this article (doi:10.1007/s11306-014-0721-3) contains supplementary material, which is available to authorized users.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files. This article is open access. Metabolomics is a rapidly evolving analytical approach in life and health sciences. The structural elucidation of the metabolites of interest remains a major analytical challenge in the metabolomics workflow. Here, we investigate the use of ion mobility as a tool to aid metabolite identification. Ion mobility allows for the measurement of the rotationally averaged collision cross-section (CCS), which gives information about the ionic shape of a molecule in the gas phase. We measured the CCSs of 125 common metabolites using traveling-wave ion mobility-mass spectrometry (TW-IM-MS). CCS measurements were highly reproducible on instruments located in three independent laboratories (RSD < 5% for 99%). We also determined the reproducibility of CCS measurements in various biological matrixes including urine, plasma, platelets, and red blood cells using ultra performance liquid chromatography (UPLC) coupled with TW-IM-MS. The mean RSD was < 2% for 97% of the CCS values, compared to 80% of retention times. Finally, as proof of concept, we used UPLC-TW-IM-MS to compare the cellular metabolome of epithelial and mesenchymal cells, an in vitro model used to study cancer development. Experimentally determined and computationally derived CCS values were used as orthogonal analytical parameters in combination with retention time and accurate mass information to confirm the identity of key metabolites potentially involved in cancer. Thus, our results indicate that adding CCS data to searchable databases and to routine metabolomics workflows will increase the identification confidence compared to traditional analytical approaches. info:eu-repo/grantAgreement/EC/FP7/232816 NIH/1R01GM087714 NIRG-11-203674

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files. This article is open access. The metabolism of gluconate is well characterized in prokaryotes where it is known to be degraded following phosphorylation by gluconokinase. Less is known of gluconate metabolism in humans. Human gluconokinase activity was recently identified proposing questions about the metabolic role of gluconate in humans. Here we report the recombinant expression, purification and biochemical characterization of isoform I of human gluconokinase alongside substrate specificity and kinetic assays of the enzyme catalyzed reaction. The enzyme, shown to be a dimer, had ATP dependent phosphorylation activity and strict specificity towards gluconate out of 122 substrates tested. In order to evaluate the metabolic impact of gluconate in humans we modeled gluconate metabolism using steady state metabolic network analysis. The results indicate that significant metabolic flux changes in anabolic pathways linked to the hexose monophosphate shunt (HMS) are induced through a small increase in gluconate concentration. We argue that the enzyme takes part in a context specific carbon flux route into the HMS that, in humans, remains incompletely explored. Apart from the biochemical description of human gluconokinase, the results highlight that little is known of the mechanism of gluconate metabolism in humans despite its widespread use in medicine and consumer products. info:eu-repo/grantAgreement/EC/FP7/232816

BackgroundPlatelet (PLT) concentrates are routinely stored for 5 to 7 days. During storage they exhibit what has been termed PLT storage lesion (PSL), which is evident by a loss of hemostatic function when transfused into patients. The overall goal of this study was to obtain a comprehensive data set describing PLT metabolism during storage.Study Design and MethodsThe experimental approach adopted to achieve this goal combined a series of standard assays to monitor the quality of stored PLTs and a deep-coverage metabolomics study using liquid chromatography coupled with mass spectrometry performed on both the extracellular and the intracellular environments. During storage we measured 174 different variables in 6 PLT units, collected by apheresis. Samples were collected at eight different time points resulting in a data set containing more than 8000 measurements.ResultsStored PLTs did not undergo a monotonic decay, but experienced systematic changes in metabolism reflected in three discrete metabolic phenotypes: The first (Days 0-3) was associated with active glycolysis, pentose phosphate pathway, and glutathione metabolism and down regulation of tricarboxylic acid (TCA) cycle. The second (Days 4-6) was associated with a more active TCA cycle as well as increased purine metabolism. A third metabolic phenotype of less clinical relevance (Days 7-10) was associated with a faster decay of cellular metabolism.ConclusionPSL is not associated with a linear decay of metabolism, but rather with successive metabolic shifts. These findings may give new insight into the mechanisms underlying PSL and encourage the deployment of systems biology methods to PSL

Background: Recent years have witnessed a rising trend in exploring microalgae for valuable carotenoid products as the demand for lutein and many other carotenoids in global markets has increased significantly. In green microalgae lutein is a major carotenoid protecting cellular components from damage incurred by reactive oxygen species under stress conditions. In this study, we investigated the effects of abiotic stressors on lutein accumulation in a strain of the marine microalga D. salina which had been selected for growth under stress conditions of combined blue and red lights by adaptive laboratory evolution.Results: Nitrate concentration, salinity and light quality were selected as three representative influencing factors and their impact on lutein production in batch cultures of D. salina was evaluated using response surface analysis. D. salina was found to be more tolerant to hyper-osmotic stress than to hypo-osmotic stress which caused serious cell damage and death in a high proportion of cells while hyper-osmotic stress increased the average cell size of D. salina only slightly. Two models were developed to explain how lutein productivity depends on the stress factors and for predicting the optimal conditions for lutein productivity. Among the three stress variables for lutein production, stronger interactions were found between nitrate concentration and salinity than between light quality and the other two. The predicted optimal conditions for lutein production were close to the original conditions used for adaptive evolution of D. salina. This suggests that the conditions imposed during adaptive evolution may have selected for the growth optima arrived at.Conclusions: This study shows that systematic evaluation of the relationship between abiotic environmental stresses and lutein biosynthesis can help to decipher the key parameters in obtaining high levels of lutein productivity in D. salina. This study may benefit future stress-driven adaptive laboratory evolution experiments and a strategy of applying stress in a step-wise manner can be suggested for a rational design of experiments. © 2014 Fu et al.; licensee BioMed Central Ltd

Mycotoxins are secondary metabolites produced by pathogenic fungi in crops worldwide. These compounds can undergo modification in plants, leading to the formation of a large number of possible modified forms, whose toxicological relevance and occurrence in food and feed is still largely unexplored. The analysis of modified mycotoxins by liquid chromatography-mass spectrometry remains a challenge because of their chemical diversity, the large number of isomeric forms, and the lack of analytical standards. Here, the potential benefits of high-resolution and ion mobility mass spectrometry as a tool for separation and structure confirmation of modified mycotoxins have been investigated/reviewed.

There is a particularly high interest to derive carotenoids such as β-carotene and lutein from higher plants and algae for the global market. It is well known that β-carotene can be overproduced in the green microalga Dunaliella salina in response to stressful light conditions. However, little is known about the effects of light quality on carotenoid metabolism, e.g., narrow spectrum red light. In this study, we present UPLC-UV-MS data from D. salina consistent with the pathway proposed for carotenoid metabolism in the green microalga Chlamydomonas reinhardtii. We have studied the effect of red light-emitting diode (LED) lighting on growth rate and biomass yield and identified the optimal photon flux for D. salina growth. We found that the major carotenoids changed in parallel to the chlorophyll b content and that red light photon stress alone at high level was not capable of upregulating carotenoid accumulation presumably due to serious photodamage. We have found that combining red LED (75 %) with blue LED (25 %) allowed growth at a higher total photon flux. Additional blue light instead of red light led to increased β-carotene and lutein accumulation, and the application of long-term iterative stress (adaptive laboratory evolution) yielded strains of D. salina with increased accumulation of carotenoids under combined blue and red light. Electronic supplementary material The online version of this article (doi:10.1007/s00253-012-4502-5) contains supplementary material, which is available to authorized users.

Efst á síðunni er hægt að nálgast greinina í heild sinni með því að smella á hlekkinn Metabolic network reconstructions define metabolic information within a target organism and can therefore be used to address incomplete metabolic information. In the present study we used a computational approach to identify human metabolites whose metabolism is incomplete on the basis of their detection in humans but exclusion from the human metabolic network reconstruction RECON 1. Candidate solutions, composed of metabolic reactions capable of explaining the metabolism of these compounds, were then identified computationally from a global biochemical reaction database. Solutions were characterized with respect to how metabolites were incorporated into RECON 1 and their biological relevance. Through detailed case studies we show that biologically plausible non-intuitive hypotheses regarding the metabolism of these compounds can be proposed in a semi-automated manner, in an approach that is similar to de novo network reconstruction. We subsequently experimentally validated one of the proposed hypotheses and report that C9orf103, previously identified as a candidate tumour suppressor gene, encodes a functional human gluconokinase. The results of the present study demonstrate how semi-automatic gap filling can be used to refine and extend metabolic reconstructions, thereby increasing their biological scope. Furthermore, we illustrate how incomplete human metabolic knowledge can be coupled with gene annotation in order to prioritize and confirm gene functions. info:eu-repo/grantAgreement/EC/FP7/232816

An extraction method for intracellular metabolite profiling should ideally be able to recover the broadest possible range of metabolites present in a sample. However, the development of such methods is hampered by the diversity of the physico-chemical properties of metabolites as well as by the specific characteristics of samples and cells. In this study, we report the optimization of an UPLC-MS method for the metabolite analysis of platelet samples. The optimal analytical protocol was determined by testing seven different extraction methods as well as by employing two different LC-MS methods, in which the metabolites were separated by using hydrophilic interaction liquid chromatography (HILIC) and reversed phase liquid chromatography (RPLC). The optimal conditions were selected using the coverage of the platelets' metabolome, the response of the identified metabolites, the reproducibility of the analytical method, and the time of the analysis as main evaluation criteria. Our results show that methanol-water (7:3) extraction coupled with HILIC-MS method provides the best compromise, allowing identification of 107 metabolites in a platelet cell extract sample, 91% of them with a RSD% lower than 20. A higher number of metabolites could be detected when analyzing the platelet samples with two different LC-MS methods or when using complementary extraction methods in parallel. © 2012 Elsevier B.V

Efst á síðunni er hægt að nálgast greinina í heild sinni með því að smella á hlekkinn With increasingly stringent regulations regarding deferral and elimination of blood donors it will become increasingly important to extend the expiration date of blood components beyond the current allowed storage periods. One reason for the storage time limit for blood components is that platelets and red blood cells develop a condition called storage lesions during their storage in plastic blood containers. Systems biology provides comprehensive bio-chemical descriptions of organisms through quantitative measurements and data integration in mathematical models. The biological knowledge for a target organism can be translated in a mathematical format and used to compute physiological properties. The use of systems biology represents a concrete solution in the study of blood cell storage lesions, and it may open up new avenues towards developing better storage methods and better storage media, thereby extending the storage period of blood components. This article is part of a Special Issue entitled: Integrated omics. info:eu-repo/grantAgreement/EC/FP7/232816

Free carnitine and acylcarnitines play an important role in the metabolism of fatty acids. Sterols are structural lipids found in the membranes of many eukaryotic cells, and they also have functional roles such as the regulation of membrane permeability and fluidity, activity of membrane-bound enzymes and signals transduction. Abnormal profiles of these compounds in biological fluids may be useful markers of metabolic changes. In this review, we describe the subset of the lipidome represented by acylcarnitines and sterols, and we summarize how these compounds have been analyzed in the past. Over the last 50 years, lipid mass spectrometry (MS) has evolved to become one of the most useful techniques for metabolic analysis. Today, the introduction of new ambient ionization techniques coupled to MS (AMS), which are characterized by the direct desorbing/ionizing of molecules from solid samples, is generating new possibilities for in situ analysis. Recently, we developed an AMS approach called APTDCI to desorb/ionize using a heated gas flow and an electrical discharge to directly analyze sterols and indirectly investigate acylcarnitines in dried blood or plasma spot samples. Here, we also describe the APTDCI method and some of its clinical applications, and we underline the common complications and issues that remain to be resolved. This article is part of a Special Issue entitled: Lipodomics and Imaging Mass Spectrometry. © 2011 Elsevier B.V

Molecular imaging of separate but still incompletely resolved spots on high-performance thin-layer chromatography (HPTLC) plates is used for the direct analysis of porcine brain lipids by desorption electrospray ionization mass spectrometry (DESI-MS). Eight class-specific spots were imaged in the negative ion mode and shown to contain more than fifty lipids. A low lateral resolution of 400 × 400 ftra allowed simple, rapid, and incomplete separation to be combined with DESI imaging for the identification of many components of these extremely complex mixtures. In this work, tandem mass spectrometry (MS/MS) was also employed to confirm the identity of particular lipids directly on HPTIX plates. © 2010 American Chemical Society

Since the early 1960s, dried blood spots (DBS) on filter paper have been used in clinical applications. The first key milestone in the use of DBS was the screening of phenylketonuria and other inborn errors of metabolism using microbiological and enzymatic analytical methods. 20 years after its introduction, advanced mass spectrometers and new soft ionization techniques have permitted the coupling of liquid chromatography with MS and tandem MS (MS/MS) and since the 1990s, DBS analysis by LC-MS/MS expanded screening to many inborn errors of metabolism simultaneously. Recently, DBS-LC-MS/MS analysis has been used in other fields such as pharmacology, toxicology and forensic sciences. Today, new ambient ionization techniques, coupled to MS, directly desorb/ionize molecules from solid samples. This presents new opportunities for the in situ analysis of DBS. Most likely, ambient MS methods will be used to analyze DBS, increasing the clinical applications of MS within the next 10 years. © 2010 Future Science Ltd

Orotic acid (ORA) is an intermediate metabolite in the pathway of pyrimidine nucleotides; its urinary excretion is useful to diagnose the hereditary orotic aciduria and some hyperammonemic inherited defects of urea cycle enzymes and amino acid transporters. ORA analysis is based on stable isotope dilution by GC-MS or LC-MS/MS methods. We developed a fast assay that measures the ORA in dried blood spots (DBS), plasma and urine using hydrophilic interaction LC-MS/MS. Within- and between-day analytical imprecision (CV%) of three quality control levels, in plasma, DBS and urine, ranged from 0.8 to 14.1%, while the inaccuracy ranged from -13.5 to 9.4%. In healthy children (n520), ORA concentrations were less than 0.69 μM in plasma, less than 0.82 μM in DBS and from 0.2 to 1.4 mmol/mol of creatinine in urine. A patient with citrullinemia showed ORA levels of 133 μM in plasma and 39 mM in DBS. A patient with hyperammonemiahyperornithinemia- homocitrullinemia (HHH) syndrome presented a urinary ORA level of 9.1 mmol/mol of creatinine. The method is potentially able to discriminate affected patients from reference subjects; the clinical validation should be expanded on a higher number of patients. © 2010 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

Nitric oxide (NO) is one of the most important mediators and neurotransmitters and its levels change under pathological conditions. NO production may be regulated by endogenous nitric oxide synthase (NOS) inhibitors, in particular asymmetric dimethylarginine (ADMA). Most of the interest is focused on ADMA, since this compound is present in plasma and urine and accumulation of ADMA has been described in many disease states but little is known about cerebrospinal fluid (CSF) concentrations of this compound and of its structural isomer symmetric dimethyl-arginine (SDMA). To determine the levels of methylarginines, we here present a new hydrophilic interaction chromatography (HILIC)-MS/MS method for the precise determination of these substances in CSF from microdialysis samples of rat prefrontal cortex (PFC). The method requires only minimal sample preparation and features isotope-labelled internal standards. © 2008 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

A new method to analyze free amino acids using desorption electrospray ionization (DESI) has been implemented. The method is based on the neutral loss mode determination of underivatized amino acids using a tandem quadrupole mass spectrometer equipped with an unmodified atmospheric interface. Qualitative and quantitative optimization of DESI parameters, including ESI voltage, solvent flow rate, angle of collection and incidence, gas flow and temperatures, was performed for amino acids detection. The parameters for DESI analysis were evaluated using a mixture of valine, leucine, methionine, phenylalanine and tyrosine standards. A few microliters of this mixture were deposited on a slide, dried and analyzed at a flow rate of 2 μL/min. The optimal ionization response was obtained using laboratory glass slides and an equivalent solution of water/methanol doped with 2% of formic acid. The method specificity was evaluated by comparing product ion spectra and neutral loss analysis of amino acids obtained either by DESI or by electrospray ionization flow injection analysis (ESI-FIA). To evaluate the quantitative response on amino acids analyzed by DESI, calibration curves were performed on amino acid standard solutions spiked with a fixed amount of labelled amino acids. The method was also employed to analyze free amino acids from blood spots, after a rapid solvent extraction without other sample pretreatment, from positive and negative subjects. The method enables one to analyze biological samples and to discriminate healthy subjects from patients affected by inherited metabolic diseases. The intrinsic high-throughput analysis of DESI represents an opportunity, because of its potential application in clinical chemistry, for the expanded screening of some inborn errors of metabolism. Copyright © 2007 John Wiley & Sons, Ltd

A fast, sensitive and specific LC/MS/MS method for the simultaneous analysis of oxcarbazepine (OXC), 10-hydroxycarbazepine (MHD) and trans-diol-carbazepine (DHD), in human serum, has been developed and validated. Serum drugs were extracted by C8 solid-phase cartridges (SPE) and separated in less than 3 min on a C18 reverse-phase column using an isocratic elution. A tandem mass spectrometer, as detector, was used for quantitative analysis in positive mode by a multiple reaction monitoring. Calibration curves, obtained on two ranges of concentration (0.78-50 mg/L for MHD and 0.078-5.0 mg/L for OXC and DHD), showed correlation coefficients (r) better than 0.997. Within day and between days quality controls imprecision, as CV%, ranged from 0.3 to 4.6% and from 1.9 to 5.8%, respectively. Cyheptamide (CYE) was used as internal standard. No detectable carry-over and no relevant cross-talk and matrix effect occurred. Samples from 24 treated patients were analysed and drug serum concentrations obtained by this method are in agreement with those of other methods and also are well correlated (r = 0.88) in comparison to our routine HPLC-UV method. Based on the analytical results and short run time, the method is suitable to support routine analysis of therapeutic drugs monitoring from human serum of treated patients or for pharmacokinetic studies. © 2007 Elsevier B.V. All rights reserved

Disclosed herein are methods, biomarkers, systems, compositions and kits for determining the phase or metabolic state (e.g. First Phase, Second Phase, or Third Phase) of a red blood cell (RBC) sample or for determining the phase or metabolic state (e.g., First Phase or Second Phase) of a platelet (PLT) cell sample. The methods disclosed herein are related to the use of isolated RBC sample or isolated PLT sample and analytical tools for providing information that is relevant to the phase or metabolic state of the RBC sample or the PLT sample. The system disclosed herein utilizes isolated RBC sample or isolated PLT sample and at least one analytical tool or an output from the at least one analytical tool. The compositions and kits described herein utilize RBC samples or PLT samples, including compositions in a form that allows for analysis of the RBC sample or the PLT sample.