PubMed

Conditional iron and pH-dependent activity of a non-enzymatic glycolysis and pentose phosphate pathway. Sci Adv. 2016 Jan;2(1):e1501235 Authors: Keller MA, Zylstra A, Castro C, Turchyn AV, Griffin JL, Ralser M Abstract Little is known about the evolutionary origins of metabolism. However, key biochemical reactions of glycolysis and the pentose phosphate pathway (PPP), ancient metabolic pathways central to the metabolic network, have non-enzymatic pendants that occur in a prebiotically plausible reaction milieu reconstituted to contain Archean sediment metal components. These non-enzymatic reactions could have given rise to the origin of glycolysis and the PPP during early evolution. Using nuclear magnetic resonance spectroscopy and high-content metabolomics that allowed us to measure several thousand reaction mixtures, we experimentally address the chemical logic of a metabolism-like network constituted from these non-enzymatic reactions. Fe(II), the dominant transition metal component of Archean oceanic sediments, has binding affinity toward metabolic sugar phosphates and drives metabolism-like reactivity acting as both catalyst and cosubstrate. Iron and pH dependencies determine a metabolism-like network topology and comediate reaction rates over several orders of magnitude so that the network adopts conditional activity. Alkaline pH triggered the activity of the non-enzymatic PPP pendant, whereas gentle acidic or neutral conditions favored non-enzymatic glycolytic reactions. Fe(II)-sensitive glycolytic and PPP-like reactions thus form a chemical network mimicking structural features of extant carbon metabolism, including topology, pH dependency, and conditional reactivity. Chemical networks that obtain structure and catalysis on the basis of transition metals found in Archean sediments are hence plausible direct precursors of cellular metabolic networks. PMID: 26824074 [PubMed]

The Need for Biomarkers in Diagnosis and Prognosis of Drug-Induced Liver Disease: Does Metabolomics Have Any Role? Biomed Res Int. 2015;2015:386186 Authors: Iruzubieta P, Arias-Loste MT, Barbier-Torres L, Martinez-Chantar ML, Crespo J Abstract Drug-induced liver injury (DILI) is a potentially fatal adverse event and the leading cause of acute liver failure in the US and in the majority of Europe. The liver can be affected directly, in a dose-dependent manner, or idiosyncratically, independently of the dose, and therefore unpredictably. Currently, DILI is a diagnosis of exclusion that physicians should suspect in patients with unexplained elevated liver enzymes. Therefore, new diagnostic and prognostic biomarkers are necessary to achieve an early and reliable diagnosis of DILI and thus improve the prognosis. Although several DILI biomarkers have been found through analytical and genetic tests and pharmacokinetic approaches, none of them have been able to display enough specificity and sensitivity, so new approaches are needed. In this sense, metabolomics is a strongly and promising emerging field that, from biofluids collected through minimally invasive procedures, can obtain early biomarkers of toxicity, which may constitute specific indicators of liver damage. PMID: 26824035 [PubMed - in process]

The metabolomic profile of gamma-irradiated human hepatoma and muscle cells reveals metabolic changes consistent with the Warburg effect. PeerJ. 2016;4:e1624 Authors: Wang M, Keogh A, Treves S, Idle JR, Beyoğlu D Abstract The two human cell lines HepG2 from hepatoma and HMCL-7304 from striated muscle were γ-irradiated with doses between 0 and 4 Gy. Abundant γH2AX foci were observed at 4 Gy after 4 h of culture post-irradiation. Sham-irradiated cells showed no γH2AX foci and therefore no signs of radiation-induced double-strand DNA breaks. Flow cytometry indicated that 41.5% of HepG2 cells were in G2/M and this rose statistically significantly with increasing radiation dose reaching a plateau at ∼47%. Cell lysates from both cell lines were subjected to metabolomic analysis using Gas Chromatography-Mass Spectrometry (GCMS). A total of 46 metabolites could be identified by GCMS in HepG2 cell lysates and 29 in HMCL-7304 lysates, most of which occurred in HepG2 cells. Principal Components Analysis (PCA) showed a clear separation of sham, 1, 2 and 4 Gy doses. Orthogonal Projection to Latent Structures-Discriminant Analysis (OPLS-DA) revealed elevations in intracellular lactate, alanine, glucose, glucose 6-phosphate, fructose and 5-oxoproline, which were found by univariate statistics to be highly statistically significantly elevated at both 2 and 4 Gy compared with sham irradiated cells. These findings suggested upregulation of cytosolic aerobic glycolysis (the Warburg effect), with potential shunting of glucose through aldose reductase in the polyol pathway, and consumption of reduced Glutathione (GSH) due to γ-irradiation. In HMCL-7304 myotubes, a putative Warburg effect was also observed only at 2 Gy, albeit a lesser magnitude than in HepG2 cells. It is anticipated that these novel metabolic perturbations following γ-irradiation of cultured cells will lead to a fuller understanding of the mechanisms of tissue damage following ionizing radiation exposure. PMID: 26823999 [PubMed]

Modeling therapy response and spatial tissue distribution of erlotinib in pancreatic cancer. Mol Cancer Ther. 2016 Jan 28; Authors: Grüner BM, Winkelmann I, Feuchtinger A, Sun N, Balluff B, Teichmann N, Herner A, Kalideris E, Steiger K, Braren R, Aichler M, Esposito I, Schmid RM, Walch A, Siveke JT Abstract Pancreatic ductal adenocarcinoma (PDAC) is likely the most aggressive and therapy-resistant of all cancers. Aim of this study was to investigate the emerging technology of matrix assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) as a powerful tool to study drug delivery and spatial tissue distribution in PDAC. We utilized an established genetically engineered mouse model of spontaneous PDAC to examine the distribution of the small molecule inhibitor erlotinib in healthy pancreas and PDAC. MALDI IMS was utilized on sections of single-dose or long-term-treated mice to measure drug tissue distribution. Histological and statistical analyses were performed to correlate morphology, drug distribution and survival. We found that erlotinib levels were significantly lower in PDAC compared to healthy tissue (p = 0.0078). Survival of long-term-treated mice did not correlate with overall levels of erlotinib or with overall histological tumor grade but both with the percentage of atypical glands in the cancer (p = 0.021, rs = 0.59) and the level of erlotinib in those atypical glands (p = 0.019, rs = 0.60). The results of this pilot study present MALDI IMS as a reliable technology to study drug delivery and spatial distribution compounds in a preclinical setting and supports drug imaging-based translational approaches. PMID: 26823494 [PubMed - as supplied by publisher]

ShockOmics: multiscale approach to the identification of molecular biomarkers in acute heart failure induced by shock. Scand J Trauma Resusc Emerg Med. 2016;24(1):9 Authors: Aletti F, Conti C, Ferrario M, Ribas V, Bollen Pinto B, Herpain A, Post E, Romay Medina E, Barlassina C, de Oliveira E, Pastorelli R, Tedeschi G, Ristagno G, Taccone FS, Schmid-Schönbein GW, Ferrer R, De Backer D, Bendjelid K, Baselli G Abstract BACKGROUND: The ShockOmics study (ClinicalTrials.gov identifier NCT02141607) is a multicenter prospective observational trial aimed at identifying new biomarkers of acute heart failure in circulatory shock, by means of a multiscale analysis of blood samples and hemodynamic data from subjects with circulatory shock. METHODS AND DESIGN: Ninety septic shock and cardiogenic shock patients will be recruited in three intensive care units (ICU) (Hôpital Erasme, Université Libre de Bruxelles, Belgium; Hospital Universitari Mutua Terrassa, Spain; Hôpitaux Universitaires de Genève, Switzerland). Hemodynamic signals will be recorded every day for up to seven days from shock diagnosis (time T0). Clinical data and blood samples will be collected for analysis at: i) T1 < 16 h from T0; ii) T2 = 48 h after T0; iii) T3 = day 7 or before discharge or before discontinuation of therapy in case of fatal outcome; iv) T4 = day 100. The inclusion criteria are: shock, Sequential Organ Failure Assessment (SOFA) score > 5 and lactate levels ≥ 2 mmol/L. The exclusion criteria are: expected death within 24 h since ICU admission; > 4 units of red blood cells or >1 fresh frozen plasma transfused; active hematological malignancy; metastatic cancer; chronic immunodepression; pre-existing end stage renal disease requiring renal replacement therapy; recent cardiac surgery; Child-Pugh C cirrhosis; terminal illness. Enrollment will be preceded by the signature of the Informed Consent by the patient or his/her relatives and by the physician in charge. Three non-shock control groups will be included in the study: a) healthy blood donors (n = 5); b) septic patients (n = 10); c) acute myocardial infarction or patients with prolonged acute arrhythmia (n = 10). The hemodynamic data will be downloaded from the ICU monitors by means of dedicated software. The blood samples will be utilized for transcriptomics, proteomics and metabolomics ("-omics") analyses. DISCUSSION: ShockOmics will provide new insights into the pathophysiological mechanisms underlying shock as well as new biomarkers for the timely diagnosis of cardiac dysfunction in shock and quantitative indices for assisting the therapeutic management of shock patients. PMID: 26822963 [PubMed - in process]

Evaluation of O2PLS in Omics data integration. BMC Bioinformatics. 2016;17 Suppl 2:11 Authors: Bouhaddani SE, Houwing-Duistermaat J, Salo P, Perola M, Jongbloed G, Uh HW Abstract BACKGROUND: Rapid computational and technological developments made large amounts of omics data available in different biological levels. It is becoming clear that simultaneous data analysis methods are needed for better interpretation and understanding of the underlying systems biology. Different methods have been proposed for this task, among them Partial Least Squares (PLS) related methods. To also deal with orthogonal variation, systematic variation in the data unrelated to one another, we consider the Two-way Orthogonal PLS (O2PLS): an integrative data analysis method which is capable of modeling systematic variation, while providing more parsimonious models aiding interpretation. RESULTS: A simulation study to assess the performance of O2PLS showed positive results in both low and higher dimensions. More noise (50 % of the data) only affected the systematic part estimates. A data analysis was conducted using data on metabolomics and transcriptomics from a large Finnish cohort (DILGOM). A previous sequential study, using the same data, showed significant correlations between the Lipo-Leukocyte (LL) module and lipoprotein metabolites. The O2PLS results were in agreement with these findings, identifying almost the same set of co-varying variables. Moreover, our integrative approach identified other associative genes and metabolites, while taking into account systematic variation in the data. Including orthogonal components enhanced overall fit, but the orthogonal variation was difficult to interpret. CONCLUSIONS: Simulations showed that the O2PLS estimates were close to the true parameters in both low and higher dimensions. In the presence of more noise (50 %), the orthogonal part estimates could not distinguish well between joint and unique variation. The joint estimates were not systematically affected. Simultaneous analysis with O2PLS on metabolome and transcriptome data showed that the LL module, together with VLDL and HDL metabolites, were important for the metabolomic and transcriptomic relation. This is in agreement with an earlier study. In addition more gene expression and metabolites are identified being important for the joint covariation. PMID: 26822911 [PubMed - in process]

Metabolomics in amyotrophic lateral sclerosis: how far can it take us? Eur J Neurol. 2016 Jan 29; Authors: Blasco H, Patin F, Madji Hounoum B, Gordon PH, Vourc'h P, Andres CR, Corcia P Abstract Amyotrophic lateral sclerosis (ALS) is the most common adult-onset motor neuron disease. Alongside identification of aetiologies, development of biomarkers is a foremost research priority. Metabolomics is one promising approach that is being utilized in the search for diagnosis and prognosis markers. Our aim is to provide an overview of the principal research in metabolomics applied to ALS. References were identified using PubMed with the terms 'metabolomics' or 'metabolomic' and 'ALS' or 'amyotrophic lateral sclerosis' or 'MND' or 'motor neuron disorders'. To date, nine articles have reported metabolomics research in patients and a few additional studies examined disease physiology and drug effects in patients or models. Metabolomics contribute to a better understanding of ALS pathophysiology but, to date, no biomarker has been validated for diagnosis, principally due to the heterogeneity of the disease and the absence of applied standardized methodology for biomarker discovery. A consensus on best metabolomics methodology as well as systematic independent validation will be an important accomplishment on the path to identifying the long-awaited biomarkers for ALS and to improve clinical trial designs. PMID: 26822316 [PubMed - as supplied by publisher]

Genome-wide association study and targeted metabolomics identifies sex-specific association of CPS1 with coronary artery disease. Nat Commun. 2016;7:10558 Authors: Hartiala JA, Tang WH, Wang Z, Crow AL, Stewart AF, Roberts R, McPherson R, Erdmann J, Willenborg C, Hazen SL, Allayee H Abstract Metabolites derived from dietary choline and L-carnitine, such as trimethylamine N-oxide and betaine, have recently been identified as novel risk factors for atherosclerosis in mice and humans. We sought to identify genetic factors associated with plasma betaine levels and determine their effect on risk of coronary artery disease (CAD). A two-stage genome-wide association study (GWAS) identified two significantly associated loci on chromosomes 2q34 and 5q14.1. The lead variant on 2q24 (rs715) localizes to carbamoyl-phosphate synthase 1 (CPS1), which encodes a mitochondrial enzyme that catalyses the first committed reaction and rate-limiting step in the urea cycle. Rs715 is also significantly associated with decreased levels of urea cycle metabolites and increased plasma glycine levels. Notably, rs715 yield a strikingly significant and protective association with decreased risk of CAD in only women. These results suggest that glycine metabolism and/or the urea cycle represent potentially novel sex-specific mechanisms for the development of atherosclerosis. PMID: 26822151 [PubMed - in process]

Computational methods to identify metabolic sub-networks based on metabolomic profiles. Brief Bioinform. 2016 Jan 27; Authors: Frainay C, Jourdan F Abstract Untargeted metabolomics makes it possible to identify compounds that undergo significant changes in concentration in different experimental conditions. The resulting metabolomic profile characterizes the perturbation concerned, but does not explain the underlying biochemical mechanisms. Bioinformatics methods make it possible to interpret results in light of the whole metabolism. This knowledge is modelled into a network, which can be mined using algorithms that originate in graph theory. These algorithms can extract sub-networks related to the compounds identified. Several attempts have been made to adapt them to obtain more biologically meaningful results. However, there is still no consensus on this kind of analysis of metabolic networks. This review presents the main graph approaches used to interpret metabolomic data using metabolic networks. Their advantages and drawbacks are discussed, and the impacts of their parameters are emphasized. We also provide some guidelines for relevant sub-network extraction and also suggest a range of applications for most methods. PMID: 26822099 [PubMed - as supplied by publisher]

Related Articles The CDP-Ethanolamine Pathway Regulates Skeletal Muscle Diacylglycerol Content and Mitochondrial Biogenesis without Altering Insulin Sensitivity. Cell Metab. 2015 May 5;21(5):718-30 Authors: Selathurai A, Kowalski GM, Burch ML, Sepulveda P, Risis S, Lee-Young RS, Lamon S, Meikle PJ, Genders AJ, McGee SL, Watt MJ, Russell AP, Frank M, Jackowski S, Febbraio MA, Bruce CR Abstract Accumulation of diacylglycerol (DG) in muscle is thought to cause insulin resistance. DG is a precursor for phospholipids, thus phospholipid synthesis could be involved in regulating muscle DG. Little is known about the interaction between phospholipid and DG in muscle; therefore, we examined whether disrupting muscle phospholipid synthesis, specifically phosphatidylethanolamine (PtdEtn), would influence muscle DG content and insulin sensitivity. Muscle PtdEtn synthesis was disrupted by deleting CTP:phosphoethanolamine cytidylyltransferase (ECT), the rate-limiting enzyme in the CDP-ethanolamine pathway, a major route for PtdEtn production. While PtdEtn was reduced in muscle-specific ECT knockout mice, intramyocellular and membrane-associated DG was markedly increased. Importantly, however, this was not associated with insulin resistance. Unexpectedly, mitochondrial biogenesis and muscle oxidative capacity were increased in muscle-specific ECT knockout mice and were accompanied by enhanced exercise performance. These findings highlight the importance of the CDP-ethanolamine pathway in regulating muscle DG content and challenge the DG-induced insulin resistance hypothesis. PMID: 25955207 [PubMed - indexed for MEDLINE]

Related Articles Comparative metabolic fingerprinting of Gentiana rhodantha from different geographical origins using LC-UV-MS/MS and multivariate statistical analysis. BMC Biochem. 2015;16:9 Authors: Pan Y, Zhang J, Shen T, Zhao YL, Wang YZ, Li WY Abstract BACKGROUNDS: Gentiana rhodantha, a rich source of iridoids and polyphenols, is a traditional ethnomedicine widely used in China. Metabolic fingerprinting based on a LC-UV-MS/MS method was applied to explore the chemical markers for discrimination of G. rhodantha from different geographical origins. RESULTS: Targeted compounds were separated on a Shim-pack XR-ODS III (150 × 2.0 mm, 2.2 μm), with a mobile phase consisted of acetonitrile and 0.1% formic acid in water, under gradient elution. In quantitative analysis, all of the calibration curves showed good linear regression (R(2) < less than 0.9991) within the tested ranges, and accuracy ranged from 97.8% to 104.2% and the %RSD of precision (less than 3%) were all within the required limits. The most abundant mangiferin (82.21 mg/g) found in sample from Zunyi, Guizhou province. Furthermore, 64 samples according to their geographical origins, could be classified by partial least-squares discriminate analysis (PLS-DA) and nine compounds including two new compounds identified by mass spectrometry could be regarded as characteristic compounds for discriminating samples from different geographical origins. CONCLUSIONS: The developed method appears to be a useful tool for analysis of G. rhodantha, which could provide potential indicators for differentiation of different geographical origins. PMID: 25880482 [PubMed - indexed for MEDLINE]

Isotopic Ratio Outlier Analysis (IROA) of the S. cerevisiae metabolome using accurate mass GC-TOF/MS: A new method for discovery. Anal Chem. 2016 Jan 28; Authors: Qiu Y, Moir R, Willis IM, Beecher C, Tsai YH, Garrett TJ, Yost RA, Kurland IJ Abstract Isotopic Ratio Outlier Analysis (IROA) is a 13C metabolomics profiling method that eliminates sample-to-sample variance, discriminates against noise and artifacts, and improves identification of compounds, previously done with accurate mass LC/MS. This is the first report using IROA technology in combination with accurate mass GC-TOFMS, here used to examine the S. cerevisiae metabolome. S. cerevisiae was grown in YNB media, containing randomized 95% 13C, or 5%13C glucose as the single carbon source, in order that the isotopomer pattern of all metabolites would mirror the labeled glucose. When these IROA experiments are combined, the abundance of the heavy isotopologues in the 5%13C extracts, or light isotopologues in the 95%13C extracts, follows the binomial distribution, showing mirrored peak pairs for the molecular ion. The mass difference between the 12C monoisotopic and the 13C monoisotopic equals the number of carbons in the molecules. The IROA-GC/MS protocol developed, using both Chemical and Electron Ionization, extends the information acquired from the isotopic peak patterns for formulae generation, a process that can be formulated as an algorithm, in which the number of carbons, as well as the number of methoximations and silylations, are used as search constraints. In Electron Impact (EI/IROA) spectra, the artifactual peaks are identified and easily removed, which has the potential to generate "clean" EI libraries. The combination of Chemical Ionization (CI) IROA and EI IROA affords a metabolite identification procedure that enables the identification of co-eluting metabolites, and allowed us to characterize 126 metabolites in the current study. PMID: 26820234 [PubMed - as supplied by publisher]

Method for the Compound Annotation of Conjugates in Nontargeted Metabolomics Using Accurate Mass Spectrometry, Multistage Product Ion Spectra and Compound Database Searching. Mass Spectrom (Tokyo). 2015;4(1):A0036 Authors: Ogura T, Bamba T, Tai A, Fukusaki E Abstract Owing to biotransformation, xenobiotics are often found in conjugated form in biological samples such as urine and plasma. Liquid chromatography coupled with accurate mass spectrometry with multistage collision-induced dissociation provides spectral information concerning these metabolites in complex materials. Unfortunately, compound databases typically do not contain a sufficient number of records for such conjugates. We report here on the development of a novel protocol, referred to as ChemProphet, to annotate compounds, including conjugates, using compound databases such as PubChem and ChemSpider. The annotation of conjugates involves three steps: 1. Recognition of the type and number of conjugates in the sample; 2. Compound search and annotation of the deconjugated form; and 3. In silico evaluation of the candidate conjugate. ChemProphet assigns a spectrum to each candidate by automatically exploring the substructures corresponding to the observed product ion spectrum. When finished, it annotates the candidates assigning a rank for each candidate based on the calculated score that ranks its relative likelihood. We assessed our protocol by annotating a benchmark dataset by including the product ion spectra for 102 compounds, annotating the commercially available standard for quercetin 3-glucuronide, and by conducting a model experiment using urine from mice that had been administered a green tea extract. The results show that by using the ChemProphet approach, it is possible to annotate not only the deconjugated molecules but also the conjugated molecules using an automatic interpretation method based on deconjugation that involves multistage collision-induced dissociation and in silico calculated conjugation. PMID: 26819907 [PubMed]

Multi-Component Profiling of Trace Volatiles in Blood by Gas Chromatography/Mass Spectrometry with Dynamic Headspace Extraction. Mass Spectrom (Tokyo). 2015;4(1):A0034 Authors: Kakuta S, Yamashita T, Nishiumi S, Yoshida M, Fukusaki E, Bamba T Abstract A dynamic headspace extraction method (DHS) with high-pressure injection is described. This dynamic extraction method has superior sensitivity to solid phase micro extraction, SPME and is capable of extracting the entire gas phase by purging the headspace of a vial. Optimization of the DHS parameters resulted in a highly sensitive volatile profiling system with the ability to detect various volatile components including alcohols at nanogram levels. The average LOD for a standard volatile mixture was 0.50 ng mL(-1), and the average LOD for alcohols was 0.66 ng mL(-1). This method was used for the analysis of volatile components from biological samples and compared with acute and chronic inflammation models. The method permitted the identification of volatiles with the same profile pattern as in vitro oxidized lipid-derived volatiles. In addition, the concentration of alcohols and aldehydes from the acute inflammation model samples were significantly higher than that for the chronic inflammation model samples. The different profiles between these samples could also be identified by this method. Finally, it was possible to analyze alcohols and low-molecular-weight volatiles that are difficult to analyze by SPME in high sensitivity and to show volatile profiling based on multi-volatile simultaneous analysis. PMID: 26819905 [PubMed]

Ketones Step to the Plate: A Game Changer for Metabolic Remodeling in Heart Failure? Circulation. 2016 Jan 27; Authors: Kolwicz SC, Airhart S, Tian R Abstract It is increasingly recognized that metabolic remodeling is integral to heart failure development and progression.(1,2) In particular, impairments in the ability of cardiac mitochondria to oxidize fatty acids have been noted along with an increase in glycolysis that is uncoupled from glucose oxidation.(3,4) This overall reduction in the myocardial oxidative capacity is purported to be the root cause of energy deficiency in the failing heart. Although past research has primarily focused on myocardial use of glucose and fatty acids, the heart is an omnivore and capable of oxidizing other substrates such as lactate, ketone bodies, and amino acids. The current understanding of the contribution of lactate, ketone bodies, and amino acids to cardiac metabolism is limited, particularly in the setting of heart failure. In this issue of Circulation, two independent studies shed new insights on the reliance of the failing heart on ketone bodies for energy supply. Proteomics analysis in mouse models of heart failure by Aubert et al(5) and metabolomics analysis of end-stage human failing hearts by Bedi et al(6) demonstrate strong and concordant evidence of increased ketone oxidation in the failing heart. PMID: 26819375 [PubMed - as supplied by publisher]

GTPase domain driven dimerization of SEPT7 is dispensable for the critical role of septins in fibroblast cytokinesis. Sci Rep. 2016;6:20007 Authors: Abbey M, Hakim C, Anand R, Lafera J, Schambach A, Kispert A, Taft MH, Kaever V, Kotlyarov A, Gaestel M, Menon MB Abstract Septin 7 (SEPT7) has been described to be essential for successful completion of cytokinesis in mouse fibroblasts, and Sept7-deficiency in fibroblasts constitutively results in multinucleated cells which stop proliferation. Using Sept7(flox/flox)fibroblasts we generated a cellular system, where the cytokinetic defects of Cre-mediated deletion of the Sept7 gene can be rescued by ectopically expressed doxycycline-inducible wild type SEPT7. Using this system, we analyzed the ability of SEPT7-mutants with alterations in their GTPase domain-dependent dimerization to prevent multinucleation and rescue proliferation. Although biochemical analysis of the mutants demonstrates differences in homo- and/or hetero-polymerization, in GTP-binding and/or GTPase activities, all analyzed mutants were able to rescue the cytokinesis phenotype of Sept7(flox/flox)fibroblasts associated with Cre-mediated deletion of endogenous Sept7. These findings indicate that the ability of septins to assemble into well-defined SEPT7-dimerization dependent native filaments is dispensable for cytokinesis in fibroblasts and opens the way to search for other mechanisms of the involvement of SEPT7 in cytokinesis. PMID: 26818767 [PubMed - in process]

Higher plasma levels of lysophosphatidylcholine 18:0 are related to a lower risk of common cancers in a prospective metabolomics study. BMC Med. 2016;14(1):13 Authors: Kühn T, Floegel A, Sookthai D, Johnson T, Rolle-Kampczyk U, Otto W, von Bergen M, Boeing H, Kaaks R Abstract BACKGROUND: First metabolomics studies have indicated that metabolic fingerprints from accessible tissues might be useful to better understand the etiological links between metabolism and cancer. However, there is still a lack of prospective metabolomics studies on pre-diagnostic metabolic alterations and cancer risk. METHODS: Associations between pre-diagnostic levels of 120 circulating metabolites (acylcarnitines, amino acids, biogenic amines, phosphatidylcholines, sphingolipids, and hexoses) and the risks of breast, prostate, and colorectal cancer were evaluated by Cox regression analyses using data of a prospective case-cohort study including 835 incident cancer cases. RESULTS: The median follow-up duration was 8.3 years among non-cases and 6.5 years among incident cases of cancer. Higher levels of lysophosphatidylcholines (lysoPCs), and especially lysoPC a C18:0, were consistently related to lower risks of breast, prostate, and colorectal cancer, independent of background factors. In contrast, higher levels of phosphatidylcholine PC ae C30:0 were associated with increased cancer risk. There was no heterogeneity in the observed associations by lag time between blood draw and cancer diagnosis. CONCLUSION: Changes in blood lipid composition precede the diagnosis of common malignancies by several years. Considering the consistency of the present results across three cancer types the observed alterations point to a global metabolic shift in phosphatidylcholine metabolism that may drive tumorigenesis. PMID: 26817443 [PubMed - in process]

Related Articles Prediction of Anti-inflammatory Plants and Discovery of Their Biomarkers by Machine Learning Algorithms and Metabolomic Studies. Planta Med. 2015 Apr;81(6):450-8 Authors: Chagas-Paula DA, Oliveira TB, Zhang T, Edrada-Ebel R, Da Costa FB Abstract Nonsteroidal anti-inflammatory drugs are the most used anti-inflammatory medicines in the world. Side effects still occur, however, and some inflammatory pathologies lack efficient treatment. Cyclooxygenase and lipoxygenase pathways are of utmost importance in inflammatory processes; therefore, novel inhibitors are currently needed for both of them. Dual inhibitors of cyclooxygenase-1 and 5-lipoxygenase are anti-inflammatory drugs with high efficacy and low side effects. In this work, 57 leaf extracts (EtOH-H2O 7 : 3, v/v) from Asteraceae species with in vitro dual inhibition of cyclooxygenase-1 and 5-lipoxygenase were analyzed by high-performance liquid chromatography-high-resolution-ORBITRAP-mass spectrometry analysis and subjected to in silico studies using machine learning algorithms. The data from all samples were processed by employing differential expression analysis software coupled to the Dictionary of Natural Products for dereplication studies. The 6052 chromatographic peaks (ESI positive and negative modes) of the extracts were selected by a genetic algorithm according to their respective anti-inflammatory properties; after this procedure, 1241 of them remained. A study using a decision tree classifier was carried out, and 11 compounds were determined to be biomarkers due to their anti-inflammatory potential. Finally, a model to predict new biologically active extracts from Asteraceae species using liquid chromatography-mass spectrometry information with no prior knowledge of their biological data was built using a multilayer perceptron (artificial neural networks) with the back-propagation algorithm using the biomarker data. As a result, a new and robust artificial neural network model for predicting the anti-inflammatory activity of natural compounds was obtained, resulting in a high percentage of correct predictions (81 %), high precision (100 %) for dual inhibition, and low error values (mean absolute error = 0.3), as also shown in the validation test. Thus, the biomarkers of the Asteraceae extracts were statistically correlated with their anti-inflammatory activities and can therefore be useful to predict new anti-inflammatory extracts and their anti-inflammatory compounds using only liquid chromatography-mass spectrometry data. PMID: 25615275 [PubMed - indexed for MEDLINE]

Erratum to: Screening newborns for metabolic disorders based on targeted metabolomics using tandem mass spectrometry. Ann Pediatr Endocrinol Metab. 2015 Dec;20(4):238 Authors: Yoon HR Abstract [This corrects the article on p. 119 in vol. 20, PMID: 26512346.]. PMID: 26817013 [PubMed - as supplied by publisher]

Lipotoxicity in steatohepatitis occurs despite an increase in tricarboxylic acid cycle activity. Am J Physiol Endocrinol Metab. 2016 Jan 26;:ajpendo.00492.2015 Authors: Patterson RE, Kalavalapalli S, Williams CM, Nautiyal M, Mathew JT, Martinez J, Reinhard MK, McDougall DJ, Rocca JR, Yost RA, Cusi K, Garrett TJ, Sunny NE Abstract The hepatic tri-carboxylic acid (TCA) cycle is central to integrating macronutrient metabolism, and is closely coupled to cellular respiration, free radical generation and inflammation. Oxidative flux through the TCA cycle is induced during hepatic insulin resistance, in mice and humans with simple steatosis, reflecting early compensatory remodeling of mitochondrial energetics. We hypothesized that progressive severity of hepatic insulin resistance and the onset of nonalcoholic steatohepatitis (NASH) would impair oxidative flux through hepatic TCA cycle. Mice (C57/BL6) were fed a high trans-fat high fructose diet (TFD) for 8-weeks to induce simple steatosis and NASH by 24-weeks. In vivo fasting hepatic mitochondrial fluxes were determined by (13)C-nuclear magnetic resonance (NMR) based isotopomer analysis. Hepatic metabolic intermediates were quantified utilizing mass spectrometry based targeted metabolomics. Hepatic triglyceride accumulation and insulin resistance preceded alterations in mitochondrial metabolism as TCA cycle fluxes remained normal during simple steatosis. However, mice with NASH had a 2-fold induction (p < 0.05) of mitochondrial fluxes (µmoles/ min) through the TCA cycle (2.6 ±0.5 vs. 5.4 ±0.6), anaplerosis (9.1 ±1.2 vs. 16.9 ±2.2) and pyruvate cycling (4.9 ±1.0 vs. 11.1 ±1.9), compared to their age matched controls. Induction of the TCA cycle activity during NASH was concurrent with blunted ketogenesis, and accumulation of hepatic diacylglycerols (DAGs), ceramides (Cer) and long chain acylcarnitines suggesting inefficient oxidation and disposal of excess free fatty acids (FFA). Sustained induction of mitochondrial TCA cycle failed to prevent accretion of "lipotoxic" metabolites in the liver, and could hasten inflammation and the metabolic transition to NASH. PMID: 26814015 [PubMed - as supplied by publisher]