Chronic polymicrobial lung infections in adult cystic fibrosis patients are typically dominated by high levels of Pseudomonas aeruginosa. Determining the impact of P. aeruginosa growth on airway secretion composition is fundamental to understanding both the behaviour of this pathogen in vivo, and its relationship with other potential colonising species. We hypothesised that the marked differences in the phenotypes of clinical isolates would be reflected in the metabolite composition of spent culture media. 1H NMR spectroscopy was used to characterise the impact of P. aeruginosa growth on a synthetic medium as part of an in vitro CF lower airways model system. Comparisons of 15 CF clinical isolates were made and four distinct metabolomic clusters identified. Highly significant relationships between P. aeruginosa isolate cluster membership and both patient lung function (FEV1) and spent culture pH were identified. This link between clinical isolate growth behaviour and FEV1 indicates characterisation of P. aeruginosa growth may find application in predicting patient lung function while the significant divergence in metabolite production and consumption observed between CF clinical isolates suggests dominant isolate characteristics have the potential to play both a selective role in microbiota composition and influence pseudomonal behaviour in vivo.
NMR; cystic fibrosis; Pseudomonal; lung function
Methamphetamine (MA) is an illegal stimulant drug of abuse with serious negative health consequences. The neurochemical effects of MA have been partially characterized, with a traditional focus on classical neurotransmitter systems. However, these directions have not yet led to novel drug treatments for MA abuse or toxicity. As an alternative approach, we describe here the first application of metabolomics to investigate the neurochemical consequences of MA exposure in the rodent brain. We examined single exposures at 3 mg/kg and repeated exposures at 3 mg/kg over 5 days in eight common inbred mouse strains. Brain tissue samples were assayed using high-throughput gas and liquid chromatography mass spectrometry, yielding quantitative data on >300 unique metabolites. Association testing and false discovery rate control yielded several metabolome-wide significant associations with acute MA exposure, including compounds such as lactate (p = 4.4 × 10−5, q = 0.013), tryptophan (p = 7.0 × 10−4, q = 0.035) and 2-hydroxyglutarate (p = 1.1 × 10−4, q = 0.022). Secondary analyses of MA-induced increase in locomotor activity showed associations with energy metabolites such as succinate (p = 3.8 × 10−7). Associations specific to repeated (5 day) MA exposure included phosphocholine (p = 4.0 × 10−4, q = 0.087) and ergothioneine (p = 3.0 × 10−4, q = 0.087). Our data appear to confirm and extend existing models of MA action in the brain, whereby an initial increase in energy metabolism, coupled with an increase in behavioral locomotion, gives way to disruption of mitochondria and phospholipid pathways and increased endogenous antioxidant response. Our study demonstrates the power of comprehensive MS-based metabolomics to identify drug-induced changes to brain metabolism and to develop neurochemical models of drug effects.
Drugs of abuse; Psychostimulants; Inbred mice; Mass spectrometry; Neurotoxicity
Lipids play multiple roles essential for proper mitochondrial function, from their involvement in membrane structure and fluidity, cellular energy storage, and signaling. Lipids are also major targets for reactive species, and their peroxidation byproducts themselves mediate further damage. Thousands of lipid species, from multiple classes and categories, are involved in these processes, suggesting lipid quantitative and structural analysis can help provide a better understanding of mitochondrial physiological status. Due to the diversity of lipids that contribute to and reflect mitochondrial function, analytical methods should ideally cover a wide range of lipid classes, and yield both quantitative and structural information. We developed a high resolution LC-MS method that is able to monitor the major lipid classes found in biospecimens (ie. biofluids, cells and tissues) with relative quantitation in an efficient, sensitive, and robust manner while also characterizing individual lipid side-chains, by all ion HCD fragmentation and chromatographic alignment. This method was used to profile the liver mitochondrial lipids from 192 rats undergoing a dietary macronutrient study in which changes in mitochondria function are related to changes in the major fat and glycemic index component of each diet. A total of 381 unique lipids, spanning 5 of the major LIPID MAPS defined categories, including fatty acyls, glycerophospholipids, glycerolipids, sphingolipids and prenols, were identified in mitochondria using the non-targeted LC-MS analysis in both positive and negative mode. The intention of this report is to show the breadth of this non-targeted LC-MS profiling method with regards to its ability to profile, identify and characterize the mitochondrial lipidome and the details of this will be discussed.
mitochondria; liquid chromatography; mass spectrometry; lipidomics; dietary macronutrients
Metabolomics plays an important role in phytochemical genomics and crop breeding; however, metabolite annotation is a significant bottleneck in metabolomic studies. In particular, in liquid chromatography–mass spectrometry (MS)-based metabolomics, which has become a routine technology for the profiling of plant-specialized metabolites, a substantial number of metabolites detected as MS peaks are still not assigned properly to a single metabolite. Oryza sativa (rice) is one of the most important staple crops in the world. In the present study, we isolated and elucidated the structures of specialized metabolites from rice by using MS/MS and NMR. Thirty-six compounds, including five new flavonoids and eight rare flavonolignan isomers, were isolated from the rice leaves. The MS/MS spectral data of the isolated compounds, with a detailed interpretation of MS fragmentation data, will facilitate metabolite annotation of the related phytochemicals by enriching the public mass spectral data depositories, including the plant-specific MS/MS-based database, ReSpect.
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Oryza sativa; Rice; Tandem mass spectrometry (MS/MS); Nuclear magnetic resonance (NMR); Specialized metabolites; Flavonoid
Many untargeted LC–ESI–HRMS based metabolomics studies are still hampered by the large proportion of non-biological sample derived signals included in the generated raw data. Here, a novel, powerful stable isotope labelling (SIL)-based metabolomics workflow is presented, which facilitates global metabolome extraction, improved metabolite annotation and metabolome wide internal standardisation (IS). The general concept is exemplified with two different cultivation variants, (1) co-cultivation of the plant pathogenic fungi Fusarium graminearum on non-labelled and highly 13C enriched culture medium and (2) experimental cultivation under native conditions and use of globally U-13C labelled biological reference samples as exemplified with maize and wheat. Subsequent to LC–HRMS analysis of mixtures of labelled and non-labelled samples, two-dimensional data filtering of SIL specific isotopic patterns is performed to better extract truly biological derived signals together with the corresponding number of carbon atoms of each metabolite ion. Finally, feature pairs are convoluted to feature groups each representing a single metabolite. Moreover, the correction of unequal matrix effects in different sample types and the improvement of relative metabolite quantification with metabolome wide IS are demonstrated for the F. graminearum experiment. Data processing employing the presented workflow revealed about 300 SIL derived feature pairs corresponding to 87–135 metabolites in F. graminearum samples and around 800 feature pairs corresponding to roughly 350 metabolites in wheat samples. SIL assisted IS, by the use of globally U-13C labelled biological samples, reduced the median CV value from 7.1 to 3.6 % for technical replicates and from 15.1 to 10.8 % for biological replicates in the respective F. graminearum samples.
13C-labelling; Internal standardisation; Metabolomics; Fusarium; Wheat; Maize
Immunoglobulin A nephropathy (IgAN) is a leading cause of chronic kidney disease, frequently associated with hypertension and renal inflammation. ω-3 fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) in fish oil (FO) improve kidney function in animal models, but have inconsistent metabolic effects in humans. Oxylipin profiles in serum from IgAN patients supplemented with either FO or corn oil (CO) placebo were analyzed by liquid chromatography coupled to tandem mass spectrometry. EPA cyclooxygenase and lipoxygenase metabolites, and EPA and DHA epoxides and diols were increased in response to FO supplementation, as were total epoxides and epoxide/diol ratios. Several of these metabolites were drivers of separation as assessed by multivariate analysis of FO patients pre- vs. post-supplementation, including 17,18-dihydroxyeicosatrienoic acid, prostaglandin D3, prostagalandin E3, Resolvin E1, 12-hydroxyeicosapentaenoic acid, and 10(11)-epoxydocosapentaenoic acid. In patients whose proteinuria improved, plasma total oxylipins as well as several hydroxyoctadecadienoic acids, hydroxyeicosatetraenoic acids, and leukotriene B4 metabolites were among the metabolites that were significantly lower than in patients whose proteinuria either did not improve or worsened. These data support the involvement of oxylipins in the inflammatory component of IgAN as well as the potential use of oxylipin profiles as biomarkers and for assessing responsiveness to ω-3 fatty acid supplementation in IgAN patients.
Eicosanoids; EPA; DHA; Inflammation; Metabolomics; ω-3 fatty acid; Oxylipins; Signaling lipids; Kidney function
The Berlin Fat Mouse Inbred (BFMI) line harbors a major recessive gene defect on chromosome 3 (jobes1) leading to juvenile obesity and metabolic syndrome. The present study aimed at the identification of metabolites that might be linked to recessively acting genes in the obesity locus. Firstly, serum metabolites were analyzed between obese BFMI and lean B6 and BFMI × B6 F1 mice to identify metabolites that are different. In a second step, a metabolite–protein network analysis was performed linking metabolites typical for BFMI mice with genes of the jobes1 region. The levels of 22 diacyl-phosphatidylcholines (PC aa), two lyso-PC and three carnitines were found to be significantly lower in obese mice compared with lean mice, while serine, glycine, arginine and hydroxysphingomyelin were higher for the same comparison. The network analysis identified PC aa C42:1 as functionally linked with the genes Ccna2 and Trpc3 via the enzymes choline kinase alpha and phospholipase A2 group 1B (PLA2G1B), respectively. Gene expression analysis revealed elevated Ccna2 expression in adipose tissue of BFMI mice. Furthermore, unique mutations were found in the Ccna2 promoter of BFMI mice which are located in binding sites for transcription factors or micro RNAs and could cause differential Ccna2 mRNA levels between BFMI and B6 mice. Increased expression of Ccna2 was consistent with higher mitotic activity of adipose tissue in BFMI mice. Therefore, we suggest a higher demand for PC necessary for adipose tissue growth and remodeling. This study highlights the relationship between metabolite profiles and the underlying genetics of obesity in the BFMI line.
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Adiposity; Metabolism; Phosphatidylcholine
Spatiotemporal information about biomolecules is indispensable for precise pathological analysis, but it remains largely unclear. Here we show a novel analytical platform combing mass spectrometry imaging (MSI) with its complementary technique, liquid chromatography–mass spectrometry (LC–MS), to elucidate more comprehensive metabolic behaviors, with spatiotemporal information, in tissues. Analysis of a rat transient middle cerebral artery occlusion (MCAO) brain tissue after ischemia–reperfusion was performed to characterize the detailed metabolomic response to pathological alterations. To compare the spatially resolved metabolic state between ischemic and contralateral hemispheres of the MCAO brain, coronally sliced tissues were subjected to MSI. We also measured the metabolites extracted from three different cerebral regions, including whole cortex (CTX), hippocampus (HI) and corpus striatum (CPu), by LC–MS. In the ischemic hemisphere, significant metabolic changes at the CTX and CPu were observed after reperfusion, while not at the HI. A region-specific metabolic behavior was observed in amino acid and nucleotide metabolism, as well as in the TCA cycle. Correlation between MSI and LC–MS data was relatively high in the CTX and CPu. Combination of both MS platforms visualized the diverse spatiotemporal metabolic dynamics during pathological progress. Thus, our proposed strategy will contribute to the understanding of the complex pathogenesis of ischemia–reperfusion.
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MSI; LC–MS; Pathological analysis; Metabolomic dynamics; Spatiotemporal behavior; Stroke
Many plants accumulate large quantities of specialized metabolites in secretory glandular trichomes (SGTs), which are specialized epidermal cells. In the genus Solanum, SGTs store a diverse collection of glucose and sucrose esters. Profiling of extracts from two accessions (LA1777 and LA1392) of Solanum habrochaites using ultra-high performance liquid chromatography–mass spectrometry (UHPLC/MS) revealed wide acylsugar diversity, with up to 11 isomers annotated for each individual elemental formula. These isomers arise from differences in ester chain lengths and their positions of substitution or branching. Since fragment ion masses were not sufficient to distinguish all isomers, 24 acylsucroses were purified from S. habrochaites accessions and cultivated tomato (Solanum lycopersicum M82) and characterized using NMR spectroscopy. Two-dimensional NMR spectra yielded assignments of positions of substitution of specific acyl groups, and locations of branching. The range of substitution was wider than reported earlier, and in contrast to previous reports, tetra- and penta-acylsucroses were substituted at position 2 with acyl groups other than acetate. Because UHPLC/MS fails to yield sufficient information about structure diversity, and quantitative NMR of acylsugar mixtures is confounded by structural redundancy, the strategic combination of NMR and UHPLC/MS provides a powerful approach for profiling a class of metabolites with great structural diversity across genotypes.
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Acylsugars; Glandular trichomes; Comparative profiling; Collision-induced dissociation; Metabolite identification
There is a general consensus that supports the need for standardized reporting of metadata or information describing large-scale metabolomics and other functional genomics data sets. Reporting of standard metadata provides a biological and empirical context for the data, facilitates experimental replication, and enables the re-interrogation and comparison of data by others. Accordingly, the Metabolomics Standards Initiative is building a general consensus concerning the minimum reporting standards for metabolomics experiments of which the Chemical Analysis Working Group (CAWG) is a member of this community effort. This article proposes the minimum reporting standards related to the chemical analysis aspects of metabolomics experiments including: sample preparation, experimental analysis, quality control, metabolite identification, and data pre-processing. These minimum standards currently focus mostly upon mass spectrometry and nuclear magnetic resonance spectroscopy due to the popularity of these techniques in metabolomics. However, additional input concerning other techniques is welcomed and can be provided via the CAWG on-line discussion forum at http://msi-workgroups.sourceforge.net/ or http://Msiemail@example.com. Further, community input related to this document can also be provided via this electronic forum.
Metabolomics; Metabolite profiling; Metabolite identification; Minimum reporting standards; Chemical analysis; Mass spectrometry; Nuclear magnetic resonance; Flux; Isotopomer analysis; GC-MS; LC-MS; CE-MS; NMR; Quality control; Method validation
Serum urate, the final breakdown product of purine metabolism, is causally involved in the pathogenesis of gout, and implicated in cardiovascular disease and type 2 diabetes. Serum urate levels highly differ between men and women; however the underlying biological processes in its regulation are still not completely understood and are assumed to result from a complex interplay between genetic, environmental and lifestyle factors. In order to describe the metabolic vicinity of serum urate, we analyzed 355 metabolites in 1,764 individuals of the population-based KORA F4 study and constructed a metabolite network around serum urate using Gaussian Graphical Modeling in a hypothesis-free approach. We subsequently investigated the effect of sex and urate lowering medication on all 38 metabolites assigned to the network. Within the resulting network three main clusters could be detected around urate, including the well-known pathway of purine metabolism, as well as several dipeptides, a group of essential amino acids, and a group of steroids. Of the 38 assigned metabolites, 25 showed strong differences between sexes. Association with uricostatic medication intake was not only confined to purine metabolism but seen for seven metabolites within the network. Our findings highlight pathways that are important in the regulation of serum urate and suggest that dipeptides, amino acids, and steroid hormones are playing a role in its regulation. The findings might have an impact on the development of specific targets in the treatment and prevention of hyperuricemia.
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Gaussian Graphical Modeling; Metabolite network; Pathway reconstruction; Allopurinol; Uric acid; Purine metabolism
The aim was to characterise associations between circulating thyroid hormones—free thyroxine (FT4) and thyrotropin (TSH)—and the metabolite profiles in serum samples from participants of the German population-based KORA F4 study. Analyses were based on the metabolite profile of 1463 euthyroid subjects. In serum samples, obtained after overnight fasting (≥8), 151 different metabolites were quantified in a targeted approach including amino acids, acylcarnitines (ACs), and phosphatidylcholines (PCs). Associations between metabolites and thyroid hormone concentrations were analysed using adjusted linear regression models. To draw conclusions on thyroid hormone related pathways, intra-class metabolite ratios were additionally explored. We discovered 154 significant associations (Bonferroni p < 1.75 × 10−04) between FT4 and various metabolites and metabolite ratios belonging to AC and PC groups. Significant associations with TSH were lacking. High FT4 levels were associated with increased concentrations of many ACs and various sums of ACs of different chain length, and the ratio of C2 by C0. The inverse associations observed between FT4 and many serum PCs reflected the general decrease in PC concentrations. Similar results were found in subgroup analyses, e.g., in weight-stable subjects or in obese subjects. Further, results were independent of different parameters for liver or kidney function, or inflammation, which supports the notion of an independent FT4 effect. In fasting euthyroid adults, higher serum FT4 levels are associated with increased serum AC concentrations and an increased ratio of C2 by C0 which is indicative of an overall enhanced fatty acyl mitochondrial transport and β-oxidation of fatty acids.
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Targeted metabolomics; Serum metabolites; Free thyroxine; Thyrotropin; Thyroid hormones; Epidemiology
Following a strategy similar to that used in baker’s yeast (Herrgård et al. Nat Biotechnol 26:1155–1160, 2008). A consensus yeast metabolic network obtained from a community approach to systems biology (Herrgård et al. 2008; Dobson et al. BMC Syst Biol 4:145, 2010). Further developments towards a genome-scale metabolic model of yeast (Dobson et al. 2010; Heavner et al. BMC Syst Biol 6:55, 2012). Yeast 5—an expanded reconstruction of the Saccharomyces cerevisiae metabolic network (Heavner et al. 2012) and in Salmonella typhimurium (Thiele et al. BMC Syst Biol 5:8, 2011). A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonellatyphimurium LT2 (Thiele et al. 2011), a recent paper (Thiele et al. Nat Biotechnol 31:419–425, 2013). A community-driven global reconstruction of human metabolism (Thiele et al. 2013) described a much improved ‘community consensus’ reconstruction of the human metabolic network, called Recon 2, and the authors (that include the present ones) have made it freely available via a database at http://humanmetabolism.org/ and in SBML format at Biomodels (http://identifiers.org/biomodels.db/MODEL1109130000). This short analysis summarises the main findings, and suggests some approaches that will be able to exploit the availability of this model to advantage.
Metabolism; Modelling; Systems biology; Networks; Metabolic networks
Space flight is one of the most extreme conditions encountered by humans. Advances in Omics methodologies (genomics, transcriptomics, proteomics, and metabolomics) have revealed that unique differences exist between individuals. These differences can be amplified in extreme conditions, such as space flight. A better understanding of individual differences may allow us to develop personalized countermeasure packages that optimize the safety and performance of each astronaut. In this review, we explore the role of “Omics” in advancing our ability to: (1) more thoroughly describe the biological response of humans in space; (2) describe molecular attributes of individual astronauts that alter the risk profile prior to entering the space environment; (3) deploy Omics techniques in the development of personalized countermeasures; and (4) develop a comprehensive Omics-based assessment and countermeasure platform that will guide human space flight in the future. In this review, we advance the concept of personalized medicine in human space flight, with the goal of enhancing astronaut safety and performance. Because the field is vast, we explore selected examples where biochemical individuality might significantly impact countermeasure development. These include gene and small molecule variants associated with: (1) metabolism of therapeutic drugs used in space; (2) one carbon metabolism and DNA stability; (3) iron metabolism, oxidative stress and damage, and DNA stability; and (4) essential input (Mg and Zn) effects on DNA repair. From these examples, we advance the case that widespread Omics profiling should serve as the foundation for aerospace medicine and research, explore methodological considerations to advance the field, and suggest why personalized medicine may become the standard of care for humans in space.
Omics; Genomics; Proteomics; Transcriptomics; Metabolomics; Personalized medicine; Space flight; Human; Astronaut health; Exploration; Systems biology; Single nucleotide polymorphism; Oxidative stress; Human performance; Essential inputs; Micronutrient; DNA stability; DNA repair
Metformin, a generic glucose lowering drug, inhibits cancer growth expressly in models that employ high fat/cholesterol intake and/or low glucose availability. Here we use a targeted tracer fate association study (TTFAS) to investigate how cholesterol and metformin administration regulates glucose-derived intermediary metabolism and macromolecule synthesis in pancreatic cancer cells. Wild type K-ras BxPC-3 and HOM: GGT(Gly) → TGT(Cys) K12 transformed MIA PaCa-2 adenocarcinoma cells were cultured in the presence of [1,2-13C2]-d-glucose as the single tracer for 24 h and treated with either 100 μM metformin (MET), 1 mM cholesteryl hemisuccinate (CHS), or the dose matching combination of MET and CHS (CHS–MET). Wild type K-ras cells used 11.43 % (SD = ±0.32) of new acetyl-CoA for palmitate synthesis that was derived from glucose, while K-ras mutated MIA PaCa-2 cells shuttled less than half as much, 5.47 % [SD = ±0.28 (P < 0.01)] of this precursor towards FAS. Cholesterol treatment almost doubled glucose-derived acetyl-CoA enrichment to 9.54 % (SD = ±0.24) and elevated the fraction of new palmitate synthesis by over 2.5-fold in MIA PaCa-2 cells; whereby 100 μM MET treatment resulted in a 28 % inhibitory effect on FAS. Therefore, acetyl-CoA shuttling towards its carboxylase, from thiolase, produces contextual synthetic inhibition by metformin of new palmitate production. Thereby, metformin, mutated K-ras and high cholesterol each contributes to limit new fatty acid and potentially cell membrane synthesis, demonstrating a previously unknown mechanism for inhibiting cancer growth during the metabolic syndrome.
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Targeted tracer fate association study; TTFAS; System-wide association study; 13C glucose-derived acetyl-CoA; Cholesterol; Contextual drug effect
Cyclin-dependent kinases CDK4 and CDK6 are essential for the control of the cell cycle through the G1 phase. Aberrant expression of CDK4 and CDK6 is a hallmark of cancer, which would suggest that CDK4 and CDK6 are attractive targets for cancer therapy. Herein, we report that calcein AM (the calcein acetoxymethyl-ester) is a potent specific inhibitor of CDK4 and CDK6 in HCT116 human colon adenocarcinoma cells, inhibiting retinoblastoma protein (pRb) phosphorylation and inducing cell cycle arrest in the G1 phase. The metabolic effects of calcein AM on HCT116 cells were also evaluated and the flux between the oxidative and non-oxidative branches of the pentose phosphate pathway was significantly altered. To elucidate whether these metabolic changes were due to the inhibition of CDK4 and CDK6, we also characterized the metabolic profile of a CDK4, CDK6 and CDK2 triple knockout of mouse embryonic fibroblasts. The results show that the metabolic profile associated with the depletion of CDK4, CDK6 and CDK2 coincides with the metabolic changes induced by calcein AM on HCT116 cells, thus confirming that the inhibition of CDK4 and CDK6 disrupts the balance between the oxidative and non-oxidative branches of the pentose phosphate pathway. Taken together, these results indicate that low doses of calcein can halt cell division and kill tumor cells. Thus, selective inhibition of CDK4 and CDK6 may be of greater pharmacological interest, since inhibitors of these kinases affect both cell cycle progression and the robust metabolic profile of tumors.
Cyclin-dependent kinases; CDK-inhibitor; Tracer-based metabolomics; Pentose phosphate pathway; Phase-plane analysis
Because uranium is a natural element present in the earth’s crust, the population may be chronically exposed to low doses of it through drinking water. Additionally, the military and civil uses of uranium can also lead to environmental dispersion that can result in high or low doses of acute or chronic exposure. Recent experimental data suggest this might lead to relatively innocuous biological reactions. The aim of this study was to assess the biological changes in rats caused by ingestion of natural uranium in drinking water with a mean daily intake of 2.7 mg/kg for 9 months and to identify potential biomarkers related to such a contamination. Subsequently, we observed no pathology and standard clinical tests were unable to distinguish between treated and untreated animals. Conversely, LC–MS metabolomics identified urine as an appropriate biofluid for discriminating the experimental groups. Of the 1,376 features detected in urine, the most discriminant were metabolites involved in tryptophan, nicotinate, and nicotinamide metabolic pathways. In particular, N-methylnicotinamide, which was found at a level seven times higher in untreated than in contaminated rats, had the greatest discriminating power. These novel results establish a proof of principle for using metabolomics to address chronic low-dose uranium contamination. They open interesting perspectives for understanding the underlying biological mechanisms and designing a diagnostic test of exposure.
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Uranium; Low-dose; Chronic; Metabolomics; Urine; N-methylnicotinamide
The quantitative profiling of the organic acid intermediates of the citric acid cycle (CAC) presents a challenge due to the lack of commercially available internal standards for all of the organic acid intermediates. We developed an analytical method that enables the quantitation of all the organic acids in the CAC in a single stable isotope dilution GC/MS analysis with deuterium-labeled analogs used as internal standards. The unstable α-keto acids are rapidly reduced with sodium borodeuteride to the corresponding stable α-deutero-α-hydroxy acids and these, along with their unlabeled analogs and other CAC organic acid intermediates, are converted to their tert-butyldimethylsilyl derivatives. Selected ion monitoring is employed with electron ionization. We validated this method by treating an untransformed mouse mammary epithelial cell line with well-known mitochondrial toxins affecting the electron transport chain and ATP synthase, which resulted in profound perturbations of the concentration of CAC intermediates.
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GC/MS; Citric acid cycle; Metabolite profiling; Mitochondrial toxins
The rationale of this dose matching/dose escalating study was to compare a panel of flavonoids—luteolin, resveratrol, and quercetin—against the metabolite flux-controlling properties of a synthetic targeted fatty acid synthase inhibitor drug C75 on multiple macromolecule synthesis pathways in pancreatic tumor cells using [1,2-13C2]-d-glucose as the single precursor metabolic tracer. MIA PaCa-2 pancreatic adenocarcinoma cells were cultured for 48 h in the presence of 0.1% DMSO (control), or 50 or 100 μM of each test compound, while intracellular glycogen, RNA ribose, palmitate and cholesterol as well as extra cellular 13CO2, lactate and glutamate production patterns were measured using gas chromatography/mass spectrometry (GC/MS) and stable isotope-based dynamic metabolic profiling (SiDMAP). The use of 50% [1,2-13C2]-d-glucose as tracer resulted in an average of 24 excess 13CO2 molecules for each 1,000 CO2 molecule in the culture media, which was decreased by 29 and 33% (P < 0.01) with 100 μM C75 and luteolin treatments, respectively. Extracellular tracer glucose-derived 13C-labeled lactate fractions (Σm) were between 45.52 and 47.49% in all cultures with a molar ratio of 2.47% M + 1/Σm lactate produced indirectly by direct oxidation of glucose in the pentose cycle in control cultures; treatment with 100 μM C75 and luteolin decreased this figure to 1.80 and 1.67%. The tracer glucose-derived 13C labeled fraction (Σm) of ribonucleotide ribose was 34.73% in controls, which was decreased to 20.58 and 8.45% with C75, 16.15 and 6.86% with luteolin, 27.66 and 19.25% with resveratrol, and 30.09 and 25.67% with quercetin, respectively. Luteolin effectively decreased nucleotide precursor synthesis pentose cycle flux primarily via the oxidative branch, where we observed a 41.74% flux (M + 1/Σm) in control cells, in comparison with only a 37.19%, 32.74%, or a 26.57%, 25.47% M + 1/Σm flux (P < 0.001) after 50 or 100 μM C75 or luteolin treatment. Intracellular de novo fatty acid palmitate (C16:0) synthesis was severely and equally blocked by C75 and luteolin treatments indicated by the 5.49% (control), 2.29 or 2.47% (C75) and 2.21 or 2.73% (luteolin) tracer glucose-derived 13C-labeled fractions, respectively. On the other hand there was a significant 192 and 159% (P < 0.001), and a 103 and 117% (P < 0.01) increase in tracer glucose-derived cholesterol after C75 or luteolin treatment. Only resveratrol and quercetin at 100 μM inhibited tracer glucose-derived glycogen labeling (Σm) and turnover by 34.8 and 23.8%, respectively. The flavonoid luteolin possesses equal efficacy to inhibit fatty acid palmitate de novo synthesis as well as nucleotide RNA ribose turnover via the oxidative branch of the pentose cycle in comparison with the targeted fatty acid synthase inhibitor synthetic compound C75. Luteolin is also effective in stringently controlling glucose entry and anaplerosis in the TCA cycle, while it promotes less glucose flux towards cholesterol synthesis than that of C75. In contrast, quercetin and resveratrol inhibit glycogen synthesis and turnover as their underlying mechanism of controlling tumor cell proliferation. Therefore the flavonoid luteolin controls fatty and nucleic acid syntheses as well as energy production with pharmacological strength, which can be explored as a non-toxic natural treatment modality for pancreatic cancer.
Metabolic profile; Phytochemicals; Pancreatic cancer; Fatty acid synthase; Lipogenesis; Luteolin; Resveratrol; Quercetin; C75
The analysis of volatile organic compounds (VOC) as biomarkers of cancer is both promising and challenging. In this pilot study, we used an untargeted approach to compare volatile metabolomic signatures of melanoma and matched control non-neoplastic skin from the same patient. VOC from fresh (non-fixed) biopsied tissue were collected using the headspace solid phase micro extraction method (HS SPME) and analyzed by gas chromatography and mass spectrometry (GCMS). We applied the XCMS analysis platform and MetaboAnalyst software to reveal many differentially expressed metabolic features. Our analysis revealed increased levels of lauric acid (C12:0) and palmitic acid (C16:0) in melanoma. The identity of these compounds was confirmed by comparison with chemical standards. Increased levels of these fatty acids are likely to be a consequence of up-regulated de novo lipid synthesis, a known characteristic of cancer. Increased oxidative stress is likely to cause an additional increase in lauric acid. Implementation of this study design on larger number of cases will be necessary for the future metabolomics biomarker discovery applications.
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Volatile organic compounds; Skin cancer; Metabolites; GCMS; Palmitic acid
Continuous exposure of breast cancer cells to adriamycin induces high expression of P-gp and multiple drug resistance. However, the biochemical process and the underlying mechanisms for the gradually induced resistance are not clear. To explore the underlying mechanism and evaluate the anti-tumor effect and resistance of adriamycin, the drug-sensitive MCF-7S and the drug-resistant MCF-7Adr breast cancer cells were used and treated with adriamycin, and the intracellular metabolites were profiled using gas chromatography mass spectrometry. Principal components analysis of the data revealed that the two cell lines showed distinctly different metabolic responses to adriamycin. Adriamycin exposure significantly altered metabolic pattern of MCF-7S cells, which gradually became similar to the pattern of MCF-7Adr, indicating that metabolic shifts were involved in adriamycin resistance. Many intracellular metabolites involved in various metabolic pathways were significantly modulated by adriamycin treatment in the drug-sensitive MCF-7S cells, but were much less affected in the drug-resistant MCF-7Adr cells. Adriamycin treatment markedly depressed the biosynthesis of proteins, purines, pyrimidines and glutathione, and glycolysis, while it enhanced glycerol metabolism of MCF-7S cells. The elevated glycerol metabolism and down-regulated glutathione biosynthesis suggested an increased reactive oxygen species (ROS) generation and a weakened ability to balance ROS, respectively. Further studies revealed that adriamycin increased ROS and up-regulated P-gp in MCF-7S cells, which could be reversed by N-acetylcysteine treatment. It is suggested that adriamycin resistance is involved in slowed metabolism and aggravated oxidative stress. Assessment of cellular metabolomics and metabolic markers may be used to evaluate anti-tumor effects and to screen for candidate anti-tumor agents.
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Cellular metabolomics; Adriamycin; Breast cancer MCF-7 cell line; Drug resistance; Reactive oxygen species; Biomarkers
Fourier-transform ion-cyclotron resonance mass spectrometry (FT-ICR-MS) detection of oxidized cellular metabolites is described using isotopologic, carbonyl-selective derivatizing agents that integrate aminooxy functionality for carbonyl capture, quaternary nitrogen for electrospray enhancement, and a hydrophobic domain for sample cleanup. These modular structural features enable rapid, sensitive analysis of complex mixtures of metabolite-derivatives by FT-ICR-MS via continuous nanoelectrospray infusion. Specifically, this approach can be used to globally assess levels of low abundance and labile aldehyde and ketone metabolites quantitatively and in high throughput manner. These metabolites are often key and unique indicators of various biochemical pathways and their perturbations. Analysis of lung adenocarcinoma A549 cells established a profile of carbonyl metabolites spanning multiple structural classes. We also demonstrate a procedure for metabolite quantification using pyruvate as a model analyte.
metabolite profiling; mass spectrometry; ketone; aldehyde; cellular oxidation state; pyruvate; α-ketoglutarate; oxaloacetate
To facilitate the high-throughput acquisition of nuclear magnetic resonance (NMR) experimental data on large sets of samples, we have developed a simple and straightforward automated methodology that capitalizes on recent advances in Bruker BioSpin NMR spectrometer hardware and software. Given the daunting challenge for non-NMR experts to collect quality spectra, our goal was to increase user accessibility, provide customized functionality, and improve the consistency and reliability of resultant data. This methodology, NMRbot, is encoded in a set of scripts written in the Python programming language accessible within the Bruker BioSpin TopSpin™ software. NMRbot improves automated data acquisition and offers novel tools for use in optimizing experimental parameters on the fly. This automated procedure has been successfully implemented for investigations in metabolomics, small-molecule library profiling, and protein–ligand titrations on four Bruker BioSpin NMR spectrometers at the National Magnetic Resonance Facility at Madison. The investigators reported benefits from ease of setup, improved spectral quality, convenient customizations, and overall time savings.
NMR spectroscopy; Metabolomics; Compound screening; Automation; Data collection; Python scripting
Fourier transform-ion cyclotron resonance-mass spectrometry (FTICR-MS) is capable of acquiring unmatched quality of isotopologue data for stable isotope resolved metabolomics (SIRM). This capability drives the need for a continuous ion introduction for obtaining optimal isotope ratios. Here we report the simultaneous analysis of mono and dinucleotides from crude polar extracts by FTICR-MS by adapting an ion-pairing sample preparation method for LC-MS analysis. This involves a rapid cleanup of extracted nucleotides on pipet tips containing a C18 stationary phase, which enabled global analysis of nucleotides and their 13C isotopologues at nanomolar concentrations by direct infusion nanoelectrospray FTICR-MS with 5 minutes of data acquisition. The resolution and mass accuracy enabled computer-assisted unambiguous assignment of most nucleotide species, including all phosphorylated forms of the adenine, guanine, uracil and cytosine nucleotides, NAD+, NADH, NADP+, NADPH, cyclic nucleotides, several UDP-hexoses, and all their 13C isotopologues. The method was applied to a SIRM study on human lung adenocarcinoma A549 cells grown in [U-13C] glucose with or without the anti-cancer agent methylseleninic acid. At m/z resolving power of 400,000, 13C-isotopologues of nucleotides were fully resolved from all other elemental isotopologues, thus allowing their 13C fractional enrichment to be accurately determined. The method achieves both high sample and high information throughput analysis of nucleotides for metabolic pathway reconstruction in SIRM investigations.
nucleotides; stable isotope-resolved metabolomics (SIRM); direct-infusion; simultaneous detection; FTICR MS; ion-pair; 13C-glucose; A549; methylseleninic acid
Increases in 1H nuclear magnetic resonance spectroscopy (NMR) visible lipids are a well-documented sign of treatment response in cancers. Lipids in cytoplasmic lipid droplets (LDs) are the main contributors to the NMR lipid signals. Two human primitive neuroectodermal tumour cell lines with different sensitivities to cisplatin treatment were studied. Increases in NMR visible saturated and unsaturated lipids in cisplatin treated DAOY cells were associated with the accumulation of LDs prior to DNA fragmentation due to apoptosis. An increase in unsaturated fatty acids (UFAs) was detected in isolated LDs from DAOY cells, in contrast to a slight decrease in UFAs in lipid extracts from whole cells. Oleic acid and linoleic acid were identified as the accumulating UFAs in LDs by heteronuclear single quantum coherence spectroscopy (HSQC). 1H NMR lipids in non-responding PFSK-1 cells were unchanged by exposure to 10 μM cisplatin. These findings support the potential of NMR detectable UFAs to serve as a non-invasive marker of tumour cell response to treatment.
Lipid droplets; 1H NMR; Isolation; Cisplatin