PubMed

Urinary Metabolomic Approach Provides New Insights into Distinct Metabolic Profiles of Glutamine and N-Carbamylglutamate Supplementation in Rats. Nutrients. 2016;8(8) Authors: Liu G, Cao W, Fang T, Jia G, Zhao H, Chen X, Wu C, Wang J Abstract Glutamine and N-carbamylglutamate can enhance growth performance and health in animals, but the underlying mechanisms are not yet elucidated. This study aimed to investigate the effect of glutamine and N-carbamylglutamate supplementation in rat metabolism. Thirty rats were fed a control, glutamine, or N-carbamylglutamate diet for four weeks. Urine samples were analyzed by nuclear magnetic resonance (NMR)-based metabolomics, specifically high-resolution ¹H NMR metabolic profiling combined with multivariate data analysis. Glutamine significantly increased the urine levels of acetamide, acetate, citrulline, creatinine, and methymalonate, and decreased the urine levels of ethanol and formate (p < 0.05). Moreover, N-carbamylglutamate significantly increased the urine levels of creatinine, ethanol, indoxyl sulfate, lactate, methymalonate, acetoacetate, m-hydroxyphenylacetate, and sarcosine, and decreased the urine levels of acetamide, acetate, citrulline, creatine, glycine, hippurate, homogentisate, N-acetylglutamate, phenylacetyglycine, acetone, and p-hydroxyphenylacetate (p < 0.05). Results suggested that glutamine and N-carbamylglutamate could modify urinary metabolome related to nitrogen metabolism and gut microbiota metabolism. Moreover, N-carbamylglutamate could alter energy and lipid metabolism. These findings indicate that different arginine precursors may lead to differences in the biofluid profile in rats. PMID: 27527211 [PubMed - as supplied by publisher]

Exploratory Metabolomics Profiling in the Kainic Acid Rat Model Reveals Depletion of 25-Hydroxyvitamin D3 during Epileptogenesis. Sci Rep. 2016;6:31424 Authors: Heischmann S, Quinn K, Cruickshank-Quinn C, Liang LP, Reisdorph R, Reisdorph N, Patel M Abstract Currently, no reliable markers are available to evaluate the epileptogenic potential of a brain injury. The electroencephalogram is the standard method of diagnosis of epilepsy; however, it is not used to predict the risk of developing epilepsy. Biomarkers that indicate an individual's risk to develop epilepsy, especially those measurable in the periphery are urgently needed. Temporal lobe epilepsy (TLE), the most common form of acquired epilepsy, is characterized by spontaneous recurrent seizures following brain injury and a seizure-free "latent" period. Elucidation of mechanisms at play during epilepsy development (epileptogenesis) in animal models of TLE could enable the identification of predictive biomarkers. Our pilot study using liquid chromatography-mass spectrometry metabolomics analysis revealed changes (p-value ≤ 0.05, ≥1.5-fold change) in lipid, purine, and sterol metabolism in rat plasma and hippocampus during epileptogenesis and chronic epilepsy in the kainic acid model of TLE. Notably, disease development was associated with dysregulation of vitamin D3 metabolism at all stages and plasma 25-hydroxyvitamin D3 depletion in the acute and latent phase of injury-induced epileptogenesis. These data suggest that plasma VD3 metabolites reflect the severity of an epileptogenic insult and that a panel of plasma VD3 metabolites may be able to serve as a marker of epileptogenesis. PMID: 27526857 [PubMed - as supplied by publisher]

Related Articles Energy transfer within self-assembled cyclic multichromophoric arrays based on orthogonally arranged donor-acceptor building blocks. Faraday Discuss. 2015;185:433-54 Authors: Karakostas N, Kaloudi-Chantzea A, Martinou E, Seintis K, Pitterl F, Oberacher H, Fakis M, Kallitsis JK, Pistolis G Abstract We herein present the coordination-driven supramolecular synthesis and photophysics of a [4+4] and a [2+2] assembly, built up by alternately collocated donor-acceptor chromophoric building blocks based, respectively, on the boron dipyrromethane (Bodipy) and perylene bisimide dye (PBI). In these multichromophoric scaffolds, the intensely absorbing/emitting dipoles of the Bodipy subunit are, by construction, cyclically arranged at the corners and aligned perpendicular to the plane formed by the closed polygonal chain comprising the PBI units. Steady-state and fs time-resolved spectroscopy reveal the presence of efficient energy transfer from the vertices (Bodipys) to the edges (PBIs) of the polygons. Fast excitation energy hopping - leading to a rapid excited state equilibrium among the low energy perylene-bisimide chromophores - is revealed by fluorescence anisotropy decays. The dynamics of electronic excitation energy hopping between the PBI subunits was approximated on the basis of a theoretical model within the framework of Förster energy transfer theory. All energy-transfer processes are quantitatively describable with Förster theory. The influence of structural deformations and orientational fluctuations of the dipoles in certain kinetic schemes is discussed. PMID: 26396034 [PubMed - indexed for MEDLINE]

Related Articles The oncolytic peptide LTX-315 kills cancer cells through Bax/Bak-regulated mitochondrial membrane permeabilization. Oncotarget. 2015 Sep 29;6(29):26599-614 Authors: Zhou H, Forveille S, Sauvat A, Sica V, Izzo V, Durand S, Müller K, Liu P, Zitvogel L, Rekdal Ø, Kepp O, Kroemer G Abstract LTX-315 has been developed as an amphipathic cationic peptide that kills cancer cells. Here, we investigated the putative involvement of mitochondria in the cytotoxic action of LTX-315. Subcellular fractionation of LTX-315-treated cells, followed by mass spectrometric quantification, revealed that the agent was enriched in mitochondria. LTX-315 caused an immediate arrest of mitochondrial respiration without any major uncoupling effect. Accordingly, LTX-315 disrupted the mitochondrial network, dissipated the mitochondrial inner transmembrane potential, and caused the release of mitochondrial intermembrane proteins into the cytosol. LTX-315 was relatively inefficient in stimulating mitophagy. Cells lacking the two pro-apoptotic multidomain proteins from the BCL-2 family, BAX and BAK, were less susceptible to LTX-315-mediated killing. Moreover, cells engineered to lose their mitochondria (by transfection with Parkin combined with treatment with a protonophore causing mitophagy) were relatively resistant against LTX-315, underscoring the importance of this organelle for LTX-315-mediated cytotoxicity. Altogether, these results support the notion that LTX-315 kills cancer cells by virtue of its capacity to permeabilize mitochondrial membranes. PMID: 26378049 [PubMed - indexed for MEDLINE]

Related Articles Identification of Promising Urinary MicroRNA Biomarkers in Two Rat Models of Glomerular Injury. Toxicol Sci. 2015 Nov;148(1):35-47 Authors: Nassirpour R, Homer BL, Mathur S, Li Y, Li Z, Brown T, Carraher D, Warneke J, Bailey S, Percival K, O'Neil SP, Whiteley LO Abstract MicroRNAs (miRNAs) are small, noncoding RNAs that regulate protein levels posttranscriptionally. miRNAs play important regulatory roles in many cellular processes and have been implicated in several diseases. Recent studies have reported significant levels of miRNAs in a variety of body fluids, raising the possibility that miRNAs could serve as useful biomarkers. Here, changes in miRNA expression patterns are described in 2 different rodent models of glomerular injury (acute puromycin aminonucleoside nephropathy and passive Heymann nephritis). By employing 2 different modes of glomerular insult, oxidative stress and immune-mediated toxicity, miRNA changes in both isolated glomeruli as well as urine specimens allow for identification of urinary miRNA biomarkers that are suggestive of drug-induced injury specifically to the glomerulus. Subsets of glomerular urinary miRNAs associated with these different modes of glomerular toxicity seem to be dependent on the mechanism of the induced injury, while 9 miRNAs that changed early in both glomerular and urine specimens were common to both studies. We further show that the miRNAs identified as mechanism-specific early glomerular injury biomarkers target key pathways and transcripts relevant to the type of insult, while the insult-independent changes might serve as ideal glomerular injury biomarkers. PMID: 26253709 [PubMed - indexed for MEDLINE]

21 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2016/08/16PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Defining and Detecting Complex Peak Relationships in Mass Spectral Data: The mz.unity Algorithm. Anal Chem. 2016 Aug 11; Authors: Mahieu NG, Spalding JL, Gelman SJ, Patti GJ Abstract Analysis of a single analyte by mass spectrometry can result in the detection of more than one hundred degenerate peaks. These degenerate peaks complicate spectral interpretation and are challenging to annotate. In mass spectrometry-based metabolomics, this degeneracy leads to inflated false discovery rates, datasets containing an order of magnitude more features than analytes, and an inefficient use of resources during data analysis. Although software has been introduced to annotate spectral degeneracy, current approaches are unable to represent several important classes of peak relationships. These include heterodimers and higher complex adducts, distal fragments, relationships between peaks in different polarities, and complex adducts between features and background peaks. Here we outline sources of peak degeneracy in mass spectra that are not annotated by current approaches and introduce a software package called mz.unity to detect these relationships in accurate mass data. Using mz.unity, we find that datasets contain many more complex relationships than we anticipated. Examples include the adduct of glutamate and NAD, fragments of NAD detected in the same or opposite polarities, and the adduct of glutamate and a background peak. Further, the complex relationships we identify show that several assumptions commonly made when interpreting mass spectral degeneracy do not hold in general. These contributions provide new tools and insight to aid in the annotation of complex spectral relationships and provide a foundation for improved dataset annotation. Mz.unity is an R package and is freely available at https://github.com/nathaniel-mahieu/mz.unity as well as our laboratory Web site http://pattilab.wustl.edu/software/. PMID: 27513885 [PubMed - as supplied by publisher]

Mild heat treatments induce long-term changes in metabolites associated with energy metabolism in Drosophila melanogaster. Biogerontology. 2016 Aug 10; Authors: Sarup P, Petersen SM, Nielsen NC, Loeschcke V, Malmendal A Abstract Heat-induced hormesis, the beneficial effect of mild heat-induced stress, increases the average lifespan of many organisms. Yet little is known about the mechanisms underlying this effect. We used nuclear magnetic resonance spectroscopy to investigate the long-term effects of repeated mild heat treatments on the metabolome of male Drosophila melanogaster. 10 days after the heat treatment, metabolic aging appears to be slowed down, and a treatment response with 40 % higher levels of alanine and lactate and lower levels of aspartate and glutamate were measured. All treatment effects had disappeared 16 days later. Metabolic reprogramming has been associated with the life extending effects of dietary restriction. The metabolite changes induced by the hormetic treatment suggest that the positive effects might not be limited to the repair pathways induced, but that there also is a change in energy metabolism. A possible direct link between changes in energy metabolism and heat induced increase in Hsp70 expression is discussed. PMID: 27511372 [PubMed - as supplied by publisher]

Nitrogen assimilation system in maize is regulated by developmental and tissue-specific mechanisms. Plant Mol Biol. 2016 Aug 10; Authors: Plett D, Holtham L, Baumann U, Kalashyan E, Francis K, Enju A, Toubia J, Roessner U, Bacic A, Rafalski A, Dhugga KS, Tester M, Garnett T, Kaiser BN Abstract KEY MESSAGE: We found metabolites, enzyme activities and enzyme transcript abundances vary significantly across the maize lifecycle, but weak correlation exists between the three groups. We identified putative genes regulating nitrate assimilation. Progress in improving nitrogen (N) use efficiency (NUE) of crop plants has been hampered by the complexity of the N uptake and utilisation systems. To understand this complexity we measured the activities of seven enzymes and ten metabolites related to N metabolism in the leaf and root tissues of Gaspe Flint maize plants grown in 0.5 or 2.5 mM NO3 (-) throughout the lifecycle. The amino acids had remarkably similar profiles across the lifecycle except for transient responses, which only appeared in the leaves for aspartate or in the roots for asparagine, serine and glycine. The activities of the enzymes for N assimilation were also coordinated to a certain degree, most noticeably with a peak in root activity late in the lifecycle, but with wide variation in the activity levels over the course of development. We analysed the transcriptional data for gene sets encoding the measured enzymes and found that, unlike the enzyme activities, transcript levels of the corresponding genes did not exhibit the same coordination across the lifecycle and were only weakly correlated with the levels of various amino acids or individual enzyme activities. We identified gene sets which were correlated with the enzyme activity profiles, including seven genes located within previously known quantitative trait loci for enzyme activities and hypothesise that these genes are important for the regulation of enzyme activities. This work provides insights into the complexity of the N assimilation system throughout development and identifies candidate regulatory genes, which warrant further investigation in efforts to improve NUE in crop plants. PMID: 27511191 [PubMed - as supplied by publisher]

Comparing metabolite profiles of habitual diet in serum and urine. Am J Clin Nutr. 2016 Aug 10; Authors: Playdon MC, Sampson JN, Cross AJ, Sinha R, Guertin KA, Moy KA, Rothman N, Irwin ML, Mayne ST, Stolzenberg-Solomon R, Moore SC Abstract BACKGROUND: Diet plays an important role in chronic disease etiology, but some diet-disease associations remain inconclusive because of methodologic limitations in dietary assessment. Metabolomics is a novel method for identifying objective dietary biomarkers, although it is unclear what dietary information is captured from metabolites found in serum compared with urine. OBJECTIVE: We compared metabolite profiles of habitual diet measured from serum with those measured from urine. DESIGN: We first estimated correlations between consumption of 56 foods, beverages, and supplements assessed by a food-frequency questionnaire, with 676 serum and 848 urine metabolites identified by untargeted liquid chromatography mass spectrometry, ultra-high performance liquid chromatography tandem mass spectrometry, and gas chromatography mass spectrometry in a colon adenoma case-control study (n = 125 cases and 128 controls) while adjusting for age, sex, smoking, fasting, case-control status, body mass index, physical activity, education, and caloric intake. We controlled for multiple comparisons with the use of a false discovery rate of <0.1. Next, we created serum and urine multiple-metabolite models to predict food intake with the use of 10-fold crossvalidation least absolute shrinkage and selection operator regression for 80% of the data; predicted values were created in the remaining 20%. Finally, we compared predicted values with estimates obtained from self-reported intake for metabolites measured in serum and urine. RESULTS: We identified metabolites associated with 46 of 56 dietary items; 417 urine and 105 serum metabolites were correlated with ≥1 food, beverage, or supplement. More metabolites in urine (n = 154) than in serum (n = 39) were associated uniquely with one food. We found previously unreported metabolite associations with leafy green vegetables, sugar-sweetened beverages, citrus, added sugar, red meat, shellfish, desserts, and wine. Prediction of dietary intake from multiple-metabolite profiles was similar between biofluids. CONCLUSIONS: Candidate metabolite biomarkers of habitual diet are identifiable in both serum and urine. Urine samples offer a valid alternative or complement to serum for metabolite biomarkers of diet in large-scale clinical or epidemiologic studies. PMID: 27510537 [PubMed - as supplied by publisher]

Related Articles Friend or foe: differential responses of rice to invasion by mutualistic or pathogenic fungi revealed by RNAseq and metabolite profiling. Sci Rep. 2015;5:13624 Authors: Xu XH, Wang C, Li SX, Su ZZ, Zhou HN, Mao LJ, Feng XX, Liu PP, Chen X, Hugh Snyder J, Kubicek CP, Zhang CL, Lin FC Abstract The rice endophyte Harpophora oryzae shares a common pathogenic ancestor with the rice blast fungus Magnaporthe oryzae. Direct comparison of the interactions between a single plant species and two closely-related (1) pathogenic and (2) mutualistic fungi species can improve our understanding of the evolution of the interactions between plants and fungi that lead to either mutualistic or pathogenic interactions. Differences in the metabolome and transcriptome of rice in response to challenge by H. or M. oryzae were investigated with GC-MS, RNA-seq, and qRT-PCR. Levels of metabolites of the shikimate and lignin biosynthesis pathways increased continuously in the M. oryzae-challenged rice roots (Mo-roots); these pathways were initially induced, but then suppressed, in the H. oryzae-challenged rice roots (Ho-roots). Compared to control samples, concentrations of sucrose and maltose were reduced in the Ho-roots and Mo-roots. The expression of most genes encoding enzymes involved in glycolysis and the TCA cycle were suppressed in the Ho-roots, but enhanced in the Mo-roots. The suppressed glycolysis in Ho-roots would result in the accumulation of glucose and fructose which was not detected in the Mo-roots. A novel co-evolution pattern of fungi-host interaction is proposed which highlights the importance of plant host in the evolution of fungal symbioses. PMID: 26346313 [PubMed - indexed for MEDLINE]

Related Articles Postnatal Growth Restriction Augments Oxygen-Induced Pulmonary Hypertension in a Neonatal Rat Model of Bronchopulmonary Dysplasia. Pediatr Res. 2016 Aug 10; Authors: Wedgwood S, Warford C, Agvateesiri SC, Thai P, Berkelhamer SK, Perez M, Underwood MA, Steinhorn RH Abstract BACKGROUND: Prematurity and fetal growth restriction are risk factors for pulmonary hypertension (PH) in infants with bronchopulmonary dysplasia (BPD). Neonatal rats develop PH and vascular remodeling when exposed to hyperoxia. We hypothesize that postnatal growth restriction (PNGR) due to under-nutrition increases the severity of PH induced by hyperoxia in neonatal rats. METHODS: Pups were randomized at birth to litters maintained in room air or 75% oxygen (hyperoxia), together with litters of normal milk intake (10 pups) or PNGR (17 pups). After 14d, right ventricular hypertrophy (RVH) was assessed by Fulton's index (right ventricular weight/left ventricular plus septal weight) and PH by echocardiography. Lungs were analyzed by immunohistochemistry, morphometrics, Western blotting and metabolomics. RESULTS: Hyperoxia and PNGR each significantly increased pulmonary arterial pressure, RVH and pulmonary arterial medial wall thickness, and significantly decreased pulmonary vessel number. These changes were significantly augmented in pups exposed to both insults. Hyperoxia and PNGR both significantly decreased expression of proteins involved in lung development and vasodilation. CONCLUSION: PNGR induces right ventricular and pulmonary vascular remodeling and augments the effects of oxygen in neonatal rats. This may be a powerful tool to investigate the mechanisms that induce PH in low birth weight preterm infants with BPD. PMID: 27509009 [PubMed - as supplied by publisher]

Related Articles PLS-Based and Regularization-Based Methods for the Selection of Relevant Variables in Non-targeted Metabolomics Data. Front Mol Biosci. 2016;3:35 Authors: Bujak R, Daghir-Wojtkowiak E, Kaliszan R, Markuszewski MJ Abstract Non-targeted metabolomics constitutes a part of the systems biology and aims at determining numerous metabolites in complex biological samples. Datasets obtained in the non-targeted metabolomics studies are high-dimensional due to sensitivity of mass spectrometry-based detection methods as well as complexity of biological matrices. Therefore, a proper selection of variables which contribute into group classification is a crucial step, especially in metabolomics studies which are focused on searching for disease biomarker candidates. In the present study, three different statistical approaches were tested using two metabolomics datasets (RH and PH study). The orthogonal projections to latent structures-discriminant analysis (OPLS-DA) without and with multiple testing correction as well as the least absolute shrinkage and selection operator (LASSO) with bootstrapping, were tested and compared. For the RH study, OPLS-DA model built without multiple testing correction selected 46 and 218 variables based on the VIP criteria using Pareto and UV scaling, respectively. For the PH study, 217 and 320 variables were selected based on the VIP criteria using Pareto and UV scaling, respectively. In the RH study, OPLS-DA model built after correcting for multiple testing, selected 4 and 19 variables as in terms of Pareto and UV scaling, respectively. For the PH study, 14 and 18 variables were selected based on the VIP criteria in terms of Pareto and UV scaling, respectively. In the RH and PH study, the LASSO selected 14 and 4 variables with reproducibility between 99.3 and 100%, respectively. In the light of PLS-based models, the larger the search space the higher the probability of developing models that fit the training data well with simultaneous poor predictive performance on the validation set. The LASSO offers potential improvements over standard linear regression due to the presence of the constrain, which promotes sparse solutions. This paper is the first one to date utilizing the LASSO penalized logistic regression in untargeted metabolomics studies. PMID: 27508208 [PubMed]

Related Articles Preliminary study of urine metabolism in type two diabetic patients based on GC-MS. Am J Transl Res. 2016;8(7):2889-96 Authors: Zhang N, Geng F, Hu ZH, Liu B, Wang YQ, Liu JC, Qi YH, Li LJ Abstract OBJECTIVE: Comparative study of type 2 diabetes and healthy controls by metabolomics methods to explore the pathogenesis of Type II diabetes. METHODS: Gas chromatography - mass spectrometry (GC-MS) with a variety of multivariate statistical analysis methods to the healthy control group 58 cases, 68 cases of Type II diabetes group were analyzed. Chromatographic conditions: DB-5MS column; the carrier gas He; flow rate of 1 mL·min(-1), the injection volume 1 uL; split ratio is 100: 1. MS conditions: electron impact (EI) ion source, an auxiliary temperature of 280°C, the ion source 230°C, quadrupole 150°C; mass scan range 30~600 mAu. RESULTS: Established analytical method based on urine metabolomics GC-MS of Type II diabetes, determine the urine succinic acid, L-leucine, L-isoleucine, tyrosine, slanine, acetoace acid, mannose, L-isoleucine, L-threonine, Phenylalanine, fructose, D-glucose, palmi acid, oleic acid and arachidonic acid were significantly were significantly changed. CONCLUSION: Based on metabolomics of GC-MS detection and analysis metabolites can be found differences between type 2 diabetes and healthy control group, PCA diagram can effectively distinguish Type II diabetes and healthy control group, with load diagrams and PLS-DA VIP value metabolite screening, the resulting differences in metabolic pathways involved metabolites, including amino acid metabolism, lipid metabolism, glucose metabolism and energy metabolism. PMID: 27508010 [PubMed]

Related Articles Gut Microbiota Profiling: Metabolomics Based Approach to Unravel Compounds Affecting Human Health. Front Microbiol. 2016;7:1144 Authors: Vernocchi P, Del Chierico F, Putignani L Abstract The gut microbiota is composed of a huge number of different bacteria, that produce a large amount of compounds playing a key role in microbe selection and in the construction of a metabolic signaling network. The microbial activities are affected by environmental stimuli leading to the generation of a wide number of compounds, that influence the host metabolome and human health. Indeed, metabolite profiles related to the gut microbiota can offer deep insights on the impact of lifestyle and dietary factors on chronic and acute diseases. Metagenomics, metaproteomics and metabolomics are some of the meta-omics approaches to study the modulation of the gut microbiota. Metabolomic research applied to biofluids allows to: define the metabolic profile; identify and quantify classes and compounds of interest; characterize small molecules produced by intestinal microbes; and define the biochemical pathways of metabolites. Mass spectrometry and nuclear magnetic resonance spectroscopy are the principal technologies applied to metabolomics in terms of coverage, sensitivity and quantification. Moreover, the use of biostatistics and mathematical approaches coupled with metabolomics play a key role in the extraction of biologically meaningful information from wide datasets. Metabolomic studies in gut microbiota-related research have increased, focusing on the generation of novel biomarkers, which could lead to the development of mechanistic hypotheses potentially applicable to the development of nutritional and personalized therapies. PMID: 27507964 [PubMed]

Related Articles The Cell Wall Polymer Lipoteichoic Acid Becomes Nonessential in Staphylococcus aureus Cells Lacking the ClpX Chaperone. MBio. 2016;7(4) Authors: Bæk KT, Bowman L, Millership C, Dupont Søgaard M, Kaever V, Siljamäki P, Savijoki K, Varmanen P, Nyman TA, Gründling A, Frees D Abstract UNLABELLED: Lipoteichoic acid (LTA) is an important cell wall component of Gram-positive bacteria and a promising target for the development of vaccines and antimicrobial compounds against Staphylococcus aureus Here we demonstrate that mutations in the conditionally essential ltaS (LTA synthase) gene arise spontaneously in an S. aureus mutant lacking the ClpX chaperone. A wide variety of ltaS mutations were selected, and among these, a substantial portion resulted in premature stop codons and other changes predicted to abolish LtaS synthesis. Consistent with this assumption, the clpX ltaS double mutants did not produce LTA, and genetic analyses confirmed that LTA becomes nonessential in the absence of the ClpX chaperone. In fact, inactivation of ltaS alleviated the severe growth defect conferred by the clpX deletion. Microscopic analyses showed that the absence of ClpX partly alleviates the septum placement defects of an LTA-depleted strain, while other phenotypes typical of LTA-negative S. aureus mutants, including increased cell size and decreased autolytic activity, are retained. In conclusion, our results indicate that LTA has an essential role in septum placement that can be bypassed by inactivating the ClpX chaperone. IMPORTANCE: Lipoteichoic acid is an essential component of the Staphylococcus aureus cell envelope and an attractive target for the development of vaccines and antimicrobials directed against antibiotic-resistant Gram-positive bacteria such as methicillin-resistant S. aureus and vancomycin-resistant enterococci. In this study, we showed that the lipoteichoic acid polymer is essential for growth of S. aureus only as long as the ClpX chaperone is present in the cell. Our results indicate that lipoteichoic acid and ClpX play opposite roles in a pathway that controls two key cell division processes in S. aureus, namely, septum formation and autolytic activity. The discovery of a novel functional connection in the genetic network that controls cell division in S. aureus may expand the repertoire of possible strategies to identify compounds or compound combinations that kill antibiotic-resistant S. aureus. PMID: 27507828 [PubMed - in process]

Related Articles Seed coat color and seed weight contribute differential responses of targeted metabolites in soybean seeds. Food Chem. 2017 Jan 1;214:248-58 Authors: Lee J, Hwang YS, Kim ST, Yoon WB, Han WY, Kang IK, Choung MG Abstract The distribution and variation of targeted metabolites in soybean seeds are affected by genetic and environmental factors. In this study, we used 192 soybean germplasm accessions collected from two provinces of Korea to elucidate the effects of seed coat color and seeds dry weight on the metabolic variation and responses of targeted metabolites. The effects of seed coat color and seeds dry weight were present in sucrose, total oligosaccharides, total carbohydrates and all measured fatty acids. The targeted metabolites were clustered within three groups. These metabolites were not only differently related to seeds dry weight, but also responded differentially to seed coat color. The inter-relationship between the targeted metabolites was highly present in the result of correlation analysis. Overall, results revealed that the targeted metabolites were diverged in relation to seed coat color and seeds dry weight within locally collected soybean seed germplasm accessions. PMID: 27507473 [PubMed - in process]

Related Articles Validation of a metabolite panel for early diagnosis of type 2 diabetes. Metabolism. 2016 Sep;65(9):1399-408 Authors: Carter TC, Rein D, Padberg I, Peter E, Rennefahrt U, David DE, McManus V, Stefanski E, Martin S, Schatz P, Schrodi SJ Abstract BACKGROUND: Accurate, early diagnosis of type 2 diabetes (T2D) would enable more effective clinical management and a reduction in T2D complications. Therefore, we sought to identify plasma metabolite and protein biomarkers that, in combination with glucose, can better predict future T2D compared with glucose alone. METHODS: In this case-control study, we used plasma samples from the Bavarian Red Cross Blood Transfusion Center study (61 T2D cases and 78 non-diabetic controls) for discovering T2D-associated metabolites, and plasma samples from the Personalized Medicine Research Project in Wisconsin (56 T2D cases and 445 non-diabetic controls) for validation. All samples were obtained before or at T2D diagnosis. We tested whether the T2D-associated metabolites could distinguish incident T2D cases from controls, as measured by the area under the receiver operating characteristic curve (AUC). Additionally, we tested six metabolic/pro-inflammatory proteins for their potential to augment the ability of the metabolites to distinguish cases from controls. RESULTS: A panel of 10 metabolites discriminated better between T2D cases and controls than glucose alone (AUCs: 0.90 vs 0.87; p=2.08×10(-5)) in Bavarian samples, and associations between these metabolites and T2D were confirmed in Wisconsin samples. With use of either a Bayesian network classifier or ridge logistic regression, the metabolites, with or without the proteins, discriminated incident T2D cases from controls marginally better than glucose in the Wisconsin samples, although the difference in AUCs was not statistically significant. However, when the metabolites and proteins were added to two previously reported T2D prediction models, the AUCs were higher than those of each prediction model alone (AUCs: 0.92 vs 0.87; p=3.96×10(-2) and AUCs: 0.91 vs 0.71; p=1.03×10(-5), for each model, respectively). CONCLUSIONS: Compared with glucose alone or with previously described T2D prediction models, a panel of plasma biomarkers showed promise for improved discrimination of incident T2D, but more investigation is needed to develop an early diagnostic marker. PMID: 27506746 [PubMed - in process]

Related Articles Imbalance of plasma amino acids, metabolites and lipids in patients with lysinuric protein intolerance (LPI). Metabolism. 2016 Sep;65(9):1361-75 Authors: Kurko J, Tringham M, Tanner L, Näntö-Salonen K, Vähä-Mäkilä M, Nygren H, Pöhö P, Lietzen N, Mattila I, Olkku A, Hyötyläinen T, Orešič M, Simell O, Niinikoski H, Mykkänen J Abstract BACKGROUND: Lysinuric protein intolerance (LPI [MIM 222700]) is an aminoaciduria with defective transport of cationic amino acids in epithelial cells in the small intestine and proximal kidney tubules due to mutations in the SLC7A7 gene. LPI is characterized by protein malnutrition, failure to thrive and hyperammonemia. Many patients also suffer from combined hyperlipidemia and chronic kidney disease (CKD) with an unknown etiology. METHODS: Here, we studied the plasma metabolomes of the Finnish LPI patients (n=26) and healthy control individuals (n=19) using a targeted platform for analysis of amino acids as well as two analytical platforms with comprehensive coverage of molecular lipids and polar metabolites. RESULTS: Our results demonstrated that LPI patients have a dichotomy of amino acid profiles, with both decreased essential and increased non-essential amino acids. Altered levels of metabolites participating in pathways such as sugar, energy, amino acid and lipid metabolism were observed. Furthermore, of these metabolites, myo-inositol, threonic acid, 2,5-furandicarboxylic acid, galactaric acid, 4-hydroxyphenylacetic acid, indole-3-acetic acid and beta-aminoisobutyric acid associated significantly (P<0.001) with the CKD status. Lipid analysis showed reduced levels of phosphatidylcholines and elevated levels of triacylglycerols, of which long-chain triacylglycerols associated (P<0.01) with CKD. CONCLUSIONS: This study revealed an amino acid imbalance affecting the basic cellular metabolism, disturbances in plasma lipid composition suggesting hepatic steatosis and fibrosis and novel metabolites correlating with CKD in LPI. In addition, the CKD-associated metabolite profile along with increased nitrite plasma levels suggests that LPI may be characterized by increased oxidative stress and apoptosis, altered microbial metabolism in the intestine and uremic toxicity. PMID: 27506743 [PubMed - in process]

Related Articles Amino Acid Metabolomics Using LC-MS/MS: Assessment of Cancer-Cell Resistance in a Simulated Tumor Microenvironment. Anal Sci. 2016;32(8):893-900 Authors: Tomita R, Todoroki K, Maruoka H, Yoshida H, Fujioka T, Nakashima M, Yamaguchi M, Nohta H Abstract We performed a comprehensive quantification of 20 amino acids in RPMI 1640 medium-cultured human colorectal adenocarcinoma cells to evaluate the efficacy of 5-fluorouracil treatment under hypoxic and hypoglycemic conditions, which mimic the tumor microenvironment. In this study, we developed a simple and comprehensive analytical method by using LC-MS/MS connected to the Intrada amino acid column, which eluted amino acids within 9 min. The present method covered a linearity range of 3.6 - 1818 μM, except for Gly (227 - 1818 μM), Ala, Asp, His (7.1 - 1818 μM each), and Trp (3.6 - 909 μM). The limits of detection were in the range of 0.02 - 38.0 pmol per injection in a standard solution. Amino acid concentration data were analyzed using principal-component analysis to represent samples on two-dimensional graphs. Linear discriminant analysis was used to classify samples on the score plots. Using this approach, the effect of 5-fluorouracil treatment could be successfully discriminated at high discrimination rates. Moreover, several amino acids were extracted from corresponding loading plots as candidate markers for distinguishing the effects of the 5-fluorouracil treatment or tumor microenvironmental conditions. These results suggest that our proposed method might be a useful tool for evaluating the efficacy of anticancer drugs in the tumor microenvironment. PMID: 27506717 [PubMed - in process]