PubMed
Characterization of metabolic profile of intact non-tumor and tumor breast cells by HR-MAS NMR spectroscopy.
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Characterization of metabolic profile of intact non-tumor and tumor breast cells by HR-MAS NMR spectroscopy.
Anal Biochem. 2015 Aug 3;
Authors: Maria RM, Altei WF, Andricopulo AD, Becceneri AB, Cominetti MR, Venâncio T, Colnago LA
Abstract
(1)H high-resolution magic angle spinning NMR ((1)H HR-MAS NMR) spectroscopy was used to analyze the metabolic profile of intact non-tumor breast cell line (MCF-10A) and intact breast tumor cell lines (MCF-7 and MDA-MB-231). In the spectra of MCF-10A cells six metabolites were assigned, with glucose and ethanol in higher concentration. Fifteen metabolites were assigned in MCF-7 and MDA-MB-231 (1)H HR-MAS NMR spectra. They did not show glucose and ethanol and the major component in both tumor cells was phosphocholine (higher in MDA-MB-231 than in MCF-7), which can be consider as a tumor biomarker of breast cancer malignant transformation. These tumor cells also show acetone signal that was higher in MDA-MB-231 than in MCF-7 cells. The high acetone level may be an indication of high demand for energy in MDA-MB-231 to maintain cell proliferation. The higher acetone and phosphocholine levels in MDA-MB-231cells, indicates the higher malignance of the cell line. Therefore, HR-MAS is a rapid, reproducible method to study the metabolic profile of intact breast cells, with minimal sample preparation and contamination, which are critical in the analyses of slow growth cells.
PMID: 26247715 [PubMed - as supplied by publisher]
MET-XAlign: A Metabolite Cross-alignment Tool for LC/MS-based Comparative Metabolomics.
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MET-XAlign: A Metabolite Cross-alignment Tool for LC/MS-based Comparative Metabolomics.
Anal Chem. 2015 Aug 6;
Authors: Zhang W, Lei Z, Huhman D, Sumner LW, Zhao PX
Abstract
Liquid chromatography-mass spectrometry (LC/MS) metabolite profiling has been widely used in comparative metabolomics studies; however, LC/MS-based comparative metabolomics currently faces several critical challenges. One of the greatest challenges is how to effectively align metabolites across different LC/MS profiles; a single metabolite can give rise to multiple peak features, and the grouped peak features that can be used to construct a spectrum pattern of single metabolite can vary greatly between biochemical experiments and even between instrument runs. Another major challenge is that the observed retention time for a single metabolite can also be significantly affected by experimental conditions. To overcome these two key challenges, we present a novel metabolite-based alignment approach entitled MET-XAlign to align metabolites across LC/MS metabolomics profiles. MET-XAlign takes the deduced molecular mass and estimated compound retention time information that can be extracted by our previously published tool, MET-COFEA, and aligns metabolites based on this information. We demonstrate that MET-XAlign is able to cross-align metabolite compounds, either known or unknown, in LC/MS profiles not only across different samples, but also across different biological experiments, and different electrospray ionization modes. Therefore, our proposed metabolite-based cross-alignment approach is a great step forward and its implementation, MET-XAlign, is a very useful tool in LC/MS-based comparative metabolomics. MET-XAlign has been successfully implemented with core algorithm coding in C++, making it very efficient, and visualization interface coding in the Microsoft .NET Framework. The MET-XAlign software along with demonstrative data is freely available at http://bioinfo.noble.org/manuscript-support/met-xalign/.
PMID: 26247233 [PubMed - as supplied by publisher]
Metabolic Consequences of LDHA inhibition by Epigallocatechin Gallate and Oxamate in MIA PaCa-2 Pancreatic Cancer Cells.
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Metabolic Consequences of LDHA inhibition by Epigallocatechin Gallate and Oxamate in MIA PaCa-2 Pancreatic Cancer Cells.
Metabolomics. 2015 Feb;11(1):71-80
Authors: Lu QY, Zhang L, Yee JK, Go VW, Lee WN
Abstract
Lactate dehydrogenase A (LDHA) is the enzyme that converts pyruvate to lactate and oxidizes the reduced form of nicotinamide adenine dinucleotide (NADH) to NAD(+). Several human cancers including the pancreas display elevated expression of LDHA. Because of its essential role in cancer metabolism, LDHA has been considered to be a potential target for cancer therapy. Recently, we have shown that a green tea extract significantly down-regulated LDHA in HPAF-II pancreatic cancer cells using global proteomics profiling. The present study is to investigate how EGCG, a major biological active constituent of green tea, targets the metabolism of human pancreatic adenocarcinoma MIA PaCa-2 cells. We compared the effect of EGCG to that of oxamate, an inhibitor of LDHA, on the multiple metabolic pathways as measured by extracellular lactate production, glucose consumption, as well as intracellular aspartate and glutamate production, fatty acid synthesis, acetyl-CoA, RNA ribose and deoxyribose. Specific metabolic pathways were studied using [1, 2-(13)C2]-d-glucose as the single precursor metabolic tracer. Isotope incorporations in metabolites were analyzed using gas chromatography/mass spectrometry (GC/MS) and stable isotope-based dynamic metabolic profiling (SiDMAP). We found that the EGCG treatment of MIA PaCa-2 cells significantly reduced lactate production, anaerobic glycolysis, glucose consumption and glycolytic rate that are comparable to the inhibition of LDHA by oxamate treatment. Significant changes in intracellular glucose carbon re-distribution among major glucose-utilizing macromolecule biosynthesis pathways in response to EGCG and oxamate treatment were observed. The inhibition of LDHA by EGCG or oxamate impacts on various pathways of the cellular metabolic network and significantly modifies the cancer metabolic phenotype. These results suggest that phytochemical EGCG and LDHA inhibitor oxamate confer their anti-cancer activities by disrupting the balance of flux throughout the cellular metabolic network.
PMID: 26246802 [PubMed - as supplied by publisher]
Metabolic fingerprinting to understand therapeutic effects and mechanisms of silybin on acute liver damage in rat.
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Metabolic fingerprinting to understand therapeutic effects and mechanisms of silybin on acute liver damage in rat.
Pharmacogn Mag. 2015 Jul-Sep;11(43):586-93
Authors: Liang Q, Wang C, Li B, Zhang AH
Abstract
BACKGROUND: Metabolic fingerprinting is a rapid and noninvasive analysis, representing a powerful approach for the characterization of phenotypes and the distinction of specific metabolic states due to environmental alterations. It has become a valuable analytical approach for the characterization of phenotypes and is the rapidly evolving field of the comprehensive measurement of ideally all endogenous metabolites in bio-samples. Silybin has displayed bright prospects in the prevention and therapy of liver injury, and we had conducted a preliminary exploration on the molecular mechanism of the hepatoprotective effects of silybin. Because the knowledge on the metabolic responses of an acute liver damage rat to the silybin is still scarce, metabolic fingerprinting can provide relevant information on the intrinsic metabolic adjustments.
MATERIALS AND METHODS: Here, the physiological and metabolic changes in the acute liver damage rat were investigated by performing a metabolic analysis. The phenotypic response was assessed by liquid chromatography/mass spectrometry (LC/MS) combined with pattern recognition approaches such as principal components analysis and partial least squares projection to supervised latent structures and discriminant analysis. Multivariate analysis of the data showed trends in scores plots that were related to the concentration of the silybin.
RESULTS: Results indicate 10 ions (7 upregulated and 3 downregulated) as differentiating metabolites. Key observations include perturbations of metabolic pathways linked to glutathione metabolism, tryptophan metabolism, cysteine and methionine metabolism, etc., Overall, this investigation illustrates the power of the LC/MS combined with the pattern recognition methods that can engender new insights into silybin affecting on metabolism pathways of an acute liver damage rat.
CONCLUSION: The present study demonstrates that the combination of metabolic fingerprinting with appropriate chemometric analysis is a valuable approach for studying cellular responses to silybin drug and can provide additional insight into the mechanisms.
PMID: 26246736 [PubMed]
Accelerated protein digestion and amino acid absorption after Roux-en-Y gastric bypass.
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Accelerated protein digestion and amino acid absorption after Roux-en-Y gastric bypass.
Am J Clin Nutr. 2015 Aug 5;
Authors: Bojsen-Møller KN, Jacobsen SH, Dirksen C, Jørgensen NB, Reitelseder S, Jensen JB, Kristiansen VB, Holst JJ, van Hall G, Madsbad S
Abstract
BACKGROUND: Roux-en-Y gastric bypass (RYGB) involves exclusion of major parts of the stomach and changes in admixture of gastro-pancreatic enzymes, which could have a major impact on protein digestion and amino acid absorption.
OBJECTIVE: We investigated the effect of RYGB on amino acid appearance in the systemic circulation from orally ingested protein and from endogenous release.
DESIGN: Nine obese glucose-tolerant subjects, with a mean body mass index (in kg/m(2)) of 39.2 (95% CI: 35.2, 43.3) and mean glycated hemoglobin of 5.3% (95% CI: 4.9%, 5.6%), were studied before and 3 mo after RYGB. Leucine and phenylalanine kinetics were determined under basal conditions and during 4 postprandial hours by intravenous infusions of [3,3,3-(2)H3]-leucine and [ring-(2)D5]-phenylalanine combined with ingestion of [1-(13)C]-leucine intrinsically labeled caseinate as the sole protein source of the meal. Changes in body composition were assessed by dual-energy X-ray absorptiometry.
RESULTS: After RYGB, basal plasma leucine concentration did not change, but marked changes were seen postprandially with 1.7-fold increased peak concentrations (before: mean: 217 μmol/L; 95% CI: 191, 243 μmol/L; 3 mo: mean: 377 μmol/L; 95% CI: 252, 502 μmol/L; P = 0.012) and 2-fold increased incremental AUC (before: mean: 4.1 mmol · min/L; 95% CI: 2.7, 5.5 mmol · min/L; 3 mo: mean: 9.5 mmol · min/L; 95% CI: 4.9, 14.2 mmol · min/L; P = 0.032). However, the postprandial hyperleucinemia was transient, and concentrations were below basal concentrations in the fourth postprandial hour. These concentration differences were mainly caused by changes in leucine appearance rate from orally ingested caseinate: peak rate increased nearly 3-fold [before: mean: 0.5 μmol/(kg fat-free mass · min); 95% CI: 0.4, 0.5 μmol/(kg fat-free mass · min); 3 mo: mean 1.4 μmol/(kg fat-free mass · min); 95% CI: 0.8, 1.9 μmol/(kg fat-free mass · min); P = 0.002], and time to peak was much shorter (before: mean: 173 min; 95% CI: 137, 209 min; 3 mo: mean: 65 min; 95% CI: 46, 84 min; P < 0.001). Only minor changes were seen in endogenous leucine release after RYGB.
CONCLUSIONS: RYGB accelerates caseinate digestion and amino acid absorption, resulting in faster and higher but more transient postprandial elevation of plasma amino acids. Changes are likely mediated by accelerated intestinal nutrient entry and clearly demonstrate that protein digestion is not impaired after RYGB. This trial was registered at clinicaltrials.gov as NCT01559792.
PMID: 26245808 [PubMed - as supplied by publisher]
A NMR-based, non-targeted multistep metabolic profiling revealed L-rhamnitol as a metabolite that characterised apples from different geographic origins.
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A NMR-based, non-targeted multistep metabolic profiling revealed L-rhamnitol as a metabolite that characterised apples from different geographic origins.
Food Chem. 2015 May 1;174:163-72
Authors: Tomita S, Nemoto T, Matsuo Y, Shoji T, Tanaka F, Nakagawa H, Ono H, Kikuchi J, Ohnishi-Kameyama M, Sekiyama Y
Abstract
This study utilises (1)H NMR-based metabolic profiling to characterise apples of five cultivars grown either in Japan (Fuji, Orin, and Jonagold) or New Zealand (Fuji, Jazz, and Envy). Principal component analysis (PCA) showed a clear separation between the Fuji-Orin-Jonagold class and the Jazz-Envy class, primarily corresponding to the differences in sugar signals, such as sucrose, glucose, and fructose. Multistep PCA removed the influence of dominant sugars and highlighted minor metabolites such as aspartic acid, 2-methylmalate, and an unidentified compound. These minor metabolites separated the apples into two classes according to different geographical areas. Subsequent partial least squares discriminant analysis (PLS-DA) indicated the importance of the unidentified metabolite. This metabolite was isolated using charcoal chromatography, and was identified as L-rhamnitol by 2D NMR and LC/MS analyses. The remarkable contribution of L-rhamnitol to geographic discrimination suggests that apples may be characterised according to various factors, including storage duration, cultivation method, and climate.
PMID: 25529666 [PubMed - indexed for MEDLINE]
Automated genomic context analysis and experimental validation platform for discovery of prokaryote transcriptional regulator functions.
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Automated genomic context analysis and experimental validation platform for discovery of prokaryote transcriptional regulator functions.
BMC Genomics. 2014;15:1142
Authors: Martí-Arbona R, Mu F, Nowak-Lovato KL, Wren MS, Unkefer CJ, Unkefer PJ
Abstract
BACKGROUND: The clustering of genes in a pathway and the co-location of functionally related genes is widely recognized in prokaryotes. We used these characteristics to predict the metabolic involvement for a Transcriptional Regulator (TR) of unknown function, identified and confirmed its biological activity.
RESULTS: A software tool that identifies the genes encoded within a defined genomic neighborhood for the subject TR and its homologs was developed. The output lists of genes in the genetic neighborhoods, their annotated functions, the reactants/products, and identifies the metabolic pathway in which the encoded-proteins function. When a set of TRs of known function was analyzed, we observed that their homologs frequently had conserved genomic neighborhoods that co-located the metabolically related genes regulated by the subject TR. We postulate that TR effectors are metabolites in the identified pathways; indeed the known effectors were present. We analyzed Bxe_B3018 from Burkholderia xenovorans, a TR of unknown function and predicted that this TR was related to the glycine, threonine and serine degradation. We tested the binding of metabolites in these pathways and for those that bound, their ability to modulate TR binding to its specific DNA operator sequence. Using rtPCR, we confirmed that methylglyoxal was an effector of Bxe_3018.
CONCLUSION: These studies provide the proof of concept and validation of a systematic approach to the discovery of the biological activity for proteins of unknown function, in this case a TR. Bxe_B3018 is a methylglyoxal responsive TR that controls the expression of an operon composed of a putative efflux system.
PMID: 25523622 [PubMed - indexed for MEDLINE]
Knowledge-driven approaches for engineering complex metabolic pathways in plants.
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Knowledge-driven approaches for engineering complex metabolic pathways in plants.
Curr Opin Biotechnol. 2015 Apr;32:54-60
Authors: Farré G, Twyman RM, Christou P, Capell T, Zhu C
Abstract
Plant metabolic pathways are complex and often feature multiple levels of regulation. Until recently, metabolic engineering in plants relied on the laborious testing of ad hoc modifications to achieve desirable changes in the metabolic profile. However, technological advances in data mining, modeling, multigene engineering and genome editing are now taking away much of the guesswork by allowing the impact of modifications to be predicted more accurately. In this review we discuss recent developments in knowledge-based metabolic engineering strategies, that is the gathering and mining of genomic, transcriptomic, proteomic and metabolomic data to generate models of metabolic pathways that help to define and refine optimal intervention strategies.
PMID: 25448233 [PubMed - indexed for MEDLINE]
Immune-dependent antineoplastic effects of cisplatin plus pyridoxine in non-small-cell lung cancer.
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Immune-dependent antineoplastic effects of cisplatin plus pyridoxine in non-small-cell lung cancer.
Oncogene. 2015 Jun 4;34(23):3053-62
Authors: Aranda F, Bloy N, Pesquet J, Petit B, Chaba K, Sauvat A, Kepp O, Khadra N, Enot D, Pfirschke C, Pittet M, Zitvogel L, Kroemer G, Senovilla L
Abstract
cis-Diamminedichloroplatinum(II) (CDDP), which is mostly referred to as cisplatin, is a widely used antineoplastic. The efficacy of cisplatin can be improved by combining it with the vitamin B6 precursor pyridoxine. Here, we evaluated the putative synergistic interaction of CDDP with pyridoxine in the treatment of an orthotopic mouse model of non-small-cell lung cancer (NSCLC). CDDP and pyridoxine exhibited hyperadditive therapeutic effects. However, this synergy was only observed in the context of an intact immune system and disappeared when the otherwise successful drug combination was applied to the same NSCLC cancer implanted in the lungs of athymic mice (which lack T lymphocytes). Immunocompetent mice that had been cured from NSCLC by the combined regimen of CDDP plus pyridoxine became resistant against subcutaneous rechallenge with the same (but not with an unrelated) cancer cell line. In vitro, CDDP and pyridoxine did not only cause synergistic killing of NSCLC cells but also elicited signs of immunogenic cell death including an endoplasmic reticulum stress response and exposure of calreticulin at the surface of the NSCLC cells. NSCLC cells treated with CDDP plus pyridoxine in vitro elicited a protective anticancer immune response upon their injection into immunocompetent mice. Altogether, these results suggest that the combined regimen of cisplatin plus pyridoxine mediates immune-dependent antineoplastic effects against NSCLC.
PMID: 25065595 [PubMed - indexed for MEDLINE]
Quantifying Diet-Induced Metabolic Changes of the Human Gut Microbiome.
Quantifying Diet-Induced Metabolic Changes of the Human Gut Microbiome.
Cell Metab. 2015 Aug 4;22(2):320-331
Authors: Shoaie S, Ghaffari P, Kovatcheva-Datchary P, Mardinoglu A, Sen P, Pujos-Guillot E, de Wouters T, Juste C, Rizkalla S, Chilloux J, Hoyles L, Nicholson JK, MICRO-Obes Consortium, Dore J, Dumas ME, Clement K, Bäckhed F, Nielsen J
Abstract
The human gut microbiome is known to be associated with various human disorders, but a major challenge is to go beyond association studies and elucidate causalities. Mathematical modeling of the human gut microbiome at a genome scale is a useful tool to decipher microbe-microbe, diet-microbe and microbe-host interactions. Here, we describe the CASINO (Community And Systems-level INteractive Optimization) toolbox, a comprehensive computational platform for analysis of microbial communities through metabolic modeling. We first validated the toolbox by simulating and testing the performance of single bacteria and whole communities in vitro. Focusing on metabolic interactions between the diet, gut microbiota, and host metabolism, we demonstrated the predictive power of the toolbox in a diet-intervention study of 45 obese and overweight individuals and validated our predictions by fecal and blood metabolomics data. Thus, modeling could quantitatively describe altered fecal and serum amino acid levels in response to diet intervention.
PMID: 26244934 [PubMed - as supplied by publisher]
A proteomic perspective of the interplay of Staphylococcus aureus and human alveolar epithelial cells during infection.
A proteomic perspective of the interplay of Staphylococcus aureus and human alveolar epithelial cells during infection.
J Proteomics. 2015 Aug 2;
Authors: Surmann K, Simon M, Hildebrandt P, Pförtner H, Michalik S, Stentzel S, Steil L, Dhople VM, Bernhardt J, Schlüter R, Depke M, Gierok P, Lalk M, Bröker BM, Schmidt F, Völker U
Abstract
Infectious diseases caused by pathogens such as Staphylococcus aureus are still a major threat for human health. Proteome analyses allow detailed monitoring of the molecular interplay between pathogen and host upon internalization. However, the investigation of the responses of both partners is complicated by the large excess of host cell proteins compared to bacterial proteins as well as by the fact that only a fraction of host cells are infected. In the present study we infected human alveolar epithelial A549 cells with S. aureus HG001 pMV158GFP and separated intact bacteria from host cell debris or infected from non-infected A549 cells by cell sorting to enable detailed proteome analysis. During the first 6.5h in the intracellular milieu S. aureus displayed reduced growth rate, induction of the stringent response, adaptation to microaerobic conditions as well as cell wall stress. Interestingly, both truly infected host cells and those not infected but exposed to secreted S. aureus proteins and host cell factors showed differences in the proteome pattern compared to A549 cells which had never been in contact with S. aureus. However, adaptation reactions were more pronounced in infected compared to non-infected A549 bystander cells. Biological significance When studying interactions between pathogen and host, proteome analyses of internalization models in cell culture provide valuable information about the adaptation of both, host and pathogen, to infection. A comprehensive understanding of the bacterial invasion, spreading, and survival mechanisms within the host as well as of the defense strategies of infected host cells will provide new options to prevent and combat bacterial infections. However, such proteome studies are complicated by the low amount of bacterial proteins available in such models as well as by the fact that only a fraction of eukaryotic host cells are indeed infected. Thus, in previous studies, either the adaptation reactions of the pathogen or the host were investigated separately. Using bacteria continuously expressing GFP, we are now able to enrich the intra-cellular S. aureus bacteria after lysis of the infected host cells and also to separate infected from non-infected airway epithelial cells (A549). Thus, we could simultaneously monitor the responses of the host and the pathogen after infection. In the future such studies could be extended to comparative analysis of different S. aureus strains/ mutants after co-infection to explore the specific influence of virulence factors or regulatory proteins on the outcome of infection.
PMID: 26244908 [PubMed - as supplied by publisher]
Arteriovenous Blood Metabolomics: A Readout of Intra-Tissue Metabostasis.
Arteriovenous Blood Metabolomics: A Readout of Intra-Tissue Metabostasis.
Sci Rep. 2015;5:12757
Authors: Ivanisevic J, Elias D, Deguchi H, Averell PM, Kurczy M, Johnson CH, Tautenhahn R, Zhu Z, Watrous J, Jain M, Griffin J, Patti GJ, Siuzdak G
Abstract
The human circulatory system consists of arterial blood that delivers nutrients to tissues, and venous blood that removes the metabolic by-products. Although it is well established that arterial blood generally has higher concentrations of glucose and oxygen relative to venous blood, a comprehensive biochemical characterization of arteriovenous differences has not yet been reported. Here we apply cutting-edge, mass spectrometry-based metabolomic technologies to provide a global characterization of metabolites that vary in concentration between the arterial and venous blood of human patients. Global profiling of paired arterial and venous plasma from 20 healthy individuals, followed up by targeted analysis made it possible to measure subtle (<2 fold), yet highly statistically significant and physiologically important differences in water soluble human plasma metabolome. While we detected changes in lactic acid, alanine, glutamine, and glutamate as expected from skeletal muscle activity, a number of unanticipated metabolites were also determined to be significantly altered including Krebs cycle intermediates, amino acids that have not been previously implicated in transport, and a few oxidized fatty acids. This study provides the most comprehensive assessment of metabolic changes in the blood during circulation to date and suggests that such profiling approach may offer new insights into organ homeostasis and organ specific pathology.
PMID: 26244428 [PubMed - as supplied by publisher]
Metabolomic profiling of hormone-dependent cancers: a bird's eye view.
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Metabolomic profiling of hormone-dependent cancers: a bird's eye view.
Trends Endocrinol Metab. 2015 Aug 1;
Authors: Lloyd SM, Arnold J, Sreekumar A
Abstract
Hormone-dependent cancers present a significant public health challenge, because they are among the most common cancers in the world. One factor associated with cancer development and progression is metabolic reprogramming. By understanding these alterations, we can identify potential markers and novel biochemical therapeutic targets. Metabolic profiling is an advanced technology that allows investigators to assess low-molecular-weight compounds that reflect physiological alterations. Current research in metabolomics on prostate (PCa) and breast cancer (BCa) have made great strides in uncovering specific metabolic pathways that are associated with cancer development, progression, and resistance. In this review, we highlight some of the major findings and potential therapeutic advances that have been reported utilizing this technology.
PMID: 26242817 [PubMed - as supplied by publisher]
Trauma/hemorrhagic shock instigates aberrant metabolic flux through glycolytic pathways, as revealed by preliminary (13)C-glucose labeling metabolomics.
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Trauma/hemorrhagic shock instigates aberrant metabolic flux through glycolytic pathways, as revealed by preliminary (13)C-glucose labeling metabolomics.
J Transl Med. 2015;13:253
Authors: D'Alessandro A, Slaughter AL, Peltz ED, Moore EE, Silliman CC, Wither M, Nemkov T, Bacon AW, Fragoso M, Banerjee A, Hansen KC
Abstract
BACKGROUND: Metabolic derangement is a key hallmark of major traumatic injury. The recent introduction of mass spectrometry-based metabolomics technologies in the field of trauma shed new light on metabolic aberrations in plasma that are triggered by trauma and hemorrhagic shock. Alteration in metabolites associated with catabolism, acidosis and hyperglycemia have been identified. However, the mechanisms underlying fluxes driving such metabolic adaptations remain elusive.
METHODS: A bolus of U-(13)C-glucose was injected in Sprague-Dawley rats at different time points. Plasma extracts were analyzed via ultra-high performance liquid chromatography-mass spectrometry to detect quantitative fluctuations in metabolite levels as well as to trace the distribution of heavy labeled carbon isotopologues.
RESULTS: Rats experiencing trauma did not show major plasma metabolic aberrations. However, trauma/hemorrhagic shock triggered severe metabolic derangement, resulting in increased glucose levels, lactate and carboxylic acid accumulation. Isotopologue distributions in late Krebs cycle metabolites (especially succinate) suggested a blockade at complex I and II of the electron transport chain, likely due to mitochondrial uncoupling. Urate increased after trauma and hemorrhage. Increased levels of unlabeled mannitol and citramalate, metabolites of potential bacterial origin, were also observed in trauma/hemorrhagic shock rats, but not trauma alone or controls.
CONCLUSIONS: These preliminary results are consistent with observations we have recently obtained in humans, and expand upon our early results on rodent models of trauma and hemorrhagic shock by providing the kinetics of glucose fluxes after trauma and hemorrhage. Despite the preliminary nature of this study, owing to the limited number of biological replicates, results highlight a role for shock, rather than trauma alone, in eliciting systemic metabolic aberrations. This study provides the foundation for tracing experiments in rat models of trauma. The goal is to improve our understanding of substrate specific metabolic derangements in trauma/hemorrhagic shock, so as to design resuscitative strategies tailored toward metabolic alterations and the severity of trauma.
PMID: 26242576 [PubMed - in process]
[Metabolomics Study on Non-Small Cell Lung Cancer Patients with Different Chinese Medical Syndromes].
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[Metabolomics Study on Non-Small Cell Lung Cancer Patients with Different Chinese Medical Syndromes].
Zhongguo Zhong Xi Yi Jie He Za Zhi. 2015 Jun;35(6):659-63
Authors: Ma JJ, Wang XL, Liu HP
Abstract
OBJECTIVE: To study the relationship between Chinese medical syndrome types and metabolomics of non-small cell lung cancer (NSCLC) patients.
METHODS: Totally 120 NSCLC patients were assigned to asthenia syndrome group and sthenia syndrome group, 60 in each group. Meanwhile, 60 cases of benign pulmonary nodules in physical examinations were recruited as the control group. Tumor tissues or benign pulmonary nodules tissues were obtained by thoracoscope. Changes of their metabolites were observed using gas chromatography-mass spectrometry (GC-MS). Their differences were studied using principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA). ROC curve analysis was performed in different metabolic compounds of sthenia and asthenia syndromes groups. The area under the curve (AUC) was calculated to evaluate the sensitivity of diagnosing syndrome types.
RESULTS: Compared with the control group, difference existed in 16 compounds. Of them , contents of citric acid, pyruvic acid, alanine, choline phosphate, glycerol phosphate choline, linoleic acid, oleic acid, lactic acid, inositol were more in the two tumors group than in the control group. Difference existed in 10 compounds between the sthenia syndrome group and the asthenia syndrome group. Of them, citric acid, pyruvic acid, alanine, choline phosphate, glycerol phosphate choline, lactic acid, and inositol were more in the asthenia syndrome group than in the sthenia syndrome group. Contents of valine, glucose, and glutamine were more in the sthenia syndrome group than in the asthenia syndrome group. ROC curve analyses of different compounds indicated that AUC of lactic acid and glucose was more than 0.8 (P < 0.01); AUC of inositol, choline phosphate, and glycerol phosphate choline was more than 0.7 (P < 0.01); AUC of valine, citric acid, glutamine, alanine, and pyruvic acid was more than 0.6 (P < 0.05).
CONCLUSIONS: There existed certain correlation between CM syndrome types and metabolomics of lung cancer. Lactic acid, glucose, inositol, choline phosphate, glycerol phosphate choline, valine, citric acid, glutamine, alanine, pyruvic acid were sensitive diagnostic compounds, and the first four kinds were most sensitive compounds.
PMID: 26242114 [PubMed - in process]
Characterizing the in vivo role of trehalose in Saccharomyces cerevisiae using the AGT1 transporter.
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Characterizing the in vivo role of trehalose in Saccharomyces cerevisiae using the AGT1 transporter.
Proc Natl Acad Sci U S A. 2015 May 12;112(19):6116-21
Authors: Gibney PA, Schieler A, Chen JC, Rabinowitz JD, Botstein D
Abstract
Trehalose is a highly stable, nonreducing disaccharide of glucose. A large body of research exists implicating trehalose in a variety of cellular phenomena, notably response to stresses of various kinds. However, in very few cases has the role of trehalose been examined directly in vivo. Here, we describe the development and characterization of a system in Saccharomyces cerevisiae that allows us to manipulate intracellular trehalose concentrations independently of the biosynthetic enzymes and independently of any applied stress. We found that many physiological roles heretofore ascribed to intracellular trehalose, including heat resistance, are not due to the presence of trehalose per se. We also found that many of the metabolic and growth defects associated with mutations in the trehalose biosynthesis pathway are not abolished by providing abundant intracellular trehalose. Instead, we made the observation that intracellular accumulation of trehalose or maltose (another disaccharide of glucose) is growth-inhibitory in a carbon source-specific manner. We conclude that the physiological role of the trehalose pathway is fundamentally metabolic: i.e., more complex than simply the consequence of increased concentrations of the sugar and its attendant physical properties (with the exception of the companion paper where Tapia et al. [Tapia H, et al. (2015) Proc Natl Acad Sci USA, 10.1073/pnas.1506415112] demonstrate a direct role for trehalose in protecting cells against desiccation).
PMID: 25918382 [PubMed - indexed for MEDLINE]
Characterization and study of transgenic cultivars by capillary and microchip electrophoresis.
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Characterization and study of transgenic cultivars by capillary and microchip electrophoresis.
Int J Mol Sci. 2014;15(12):23851-77
Authors: Domínguez Vega E, Marina ML
Abstract
Advances in biotechnology have increased the demand for suitable analytical techniques for the analysis of genetically modified organisms. Study of the substantial equivalence, discrimination between transgenic and non-transgenic cultivars, study of the unintended effects caused by a genetic modification or their response to diverse situations or stress conditions (e.g., environmental, climatic, infections) are some of the concerns that need to be addressed. Capillary electrophoresis (CE) is emerging as an alternative to conventional techniques for the study and characterization of genetically modified organisms. This article reviews the most recent applications of CE for the analysis and characterization of transgenic cultivars in the last five years. Different strategies have been described depending on the level analyzed (DNA, proteins or metabolites). Capillary gel electrophoresis (CGE) has shown to be particularly useful for the analysis of DNA fragments amplified by PCR. Metabolites and proteins have been mainly separated using capillary zone electrophoresis (CZE) using UV and MS detection. Electrophoretic chips have also proven their ability in the analysis of transgenic cultivars and a section describing the new applications is also included.
PMID: 25535077 [PubMed - indexed for MEDLINE]
Peroxiredoxin 3 levels regulate a mitochondrial redox setpoint in malignant mesothelioma cells.
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Peroxiredoxin 3 levels regulate a mitochondrial redox setpoint in malignant mesothelioma cells.
Redox Biol. 2014;3:79-87
Authors: Cunniff B, Wozniak AN, Sweeney P, DeCosta K, Heintz NH
Abstract
Peroxiredoxin 3 (PRX3), a typical 2-Cys peroxiredoxin located exclusively in the mitochondrial matrix, is the principal peroxidase responsible for metabolizing mitochondrial hydrogen peroxide, a byproduct of cellular respiration originating from the mitochondrial electron transport chain. Mitochondrial oxidants are produced in excess in cancer cells due to oncogenic transformation and metabolic reorganization, and signals through FOXM1 and other redox-responsive factors to support a hyper-proliferative state. Over-expression of PRX3 in cancer cells has been shown to counteract oncogene-induced senescence and support tumor cell growth and survival making PRX3 a credible therapeutic target. Using malignant mesothelioma (MM) cells stably expressing shRNAs to PRX3 we show that decreased expression of PRX3 alters mitochondrial structure, function and cell cycle kinetics. As compared to control cells, knockdown of PRX3 expression increased mitochondrial membrane potential, basal ATP production, oxygen consumption and extracellular acidification rates. shPRX3 MM cells failed to progress through the cell cycle compared to wild type controls, with increased numbers of cells in G2/M phase. Diminished PRX3 expression also induced mitochondrial hyperfusion similar to the DRP1 inhibitor mdivi-1. Cell cycle progression and changes in mitochondrial networking were rescued by transient expression of either catalase or mitochondrial-targeted catalase, indicating high levels of hydrogen peroxide contribute to perturbations in mitochondrial structure and function in shPRX3 MM cells. Our results indicate that PRX3 levels establish a redox set point that permits MM cells to thrive in response to increased levels of mROS, and that perturbing the redox status governed by PRX3 impairs proliferation by altering cell cycle-dependent dynamics between mitochondrial networking and energy metabolism.
PMID: 25462069 [PubMed - indexed for MEDLINE]
LocFuse: human protein-protein interaction prediction via classifier fusion using protein localization information.
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LocFuse: human protein-protein interaction prediction via classifier fusion using protein localization information.
Genomics. 2014 Dec;104(6 Pt B):496-503
Authors: Zahiri J, Mohammad-Noori M, Ebrahimpour R, Saadat S, Bozorgmehr JH, Goldberg T, Masoudi-Nejad A
Abstract
UNLABELLED: Protein-protein interaction (PPI) detection is one of the central goals of functional genomics and systems biology. Knowledge about the nature of PPIs can help fill the widening gap between sequence information and functional annotations. Although experimental methods have produced valuable PPI data, they also suffer from significant limitations. Computational PPI prediction methods have attracted tremendous attentions. Despite considerable efforts, PPI prediction is still in its infancy in complex multicellular organisms such as humans. Here, we propose a novel ensemble learning method, LocFuse, which is useful in human PPI prediction. This method uses eight different genomic and proteomic features along with four types of different classifiers. The prediction performance of this classifier selection method was found to be considerably better than methods employed hitherto. This confirms the complex nature of the PPI prediction problem and also the necessity of using biological information for classifier fusion. The LocFuse is available at: http://lbb.ut.ac.ir/Download/LBBsoft/LocFuse.
BIOLOGICAL SIGNIFICANCE: The results revealed that if we divide proteome space according to the cellular localization of proteins, then the utility of some classifiers in PPI prediction can be improved. Therefore, to predict the interaction for any given protein pair, we can select the most accurate classifier with regard to the cellular localization information. Based on the results, we can say that the importance of different features for PPI prediction varies between differently localized proteins; however in general, our novel features, which were extracted from position-specific scoring matrices (PSSMs), are the most important ones and the Random Forest (RF) classifier performs best in most cases. LocFuse was developed with a user-friendly graphic interface and it is freely available for Linux, Mac OSX and MS Windows operating systems.
PMID: 25458812 [PubMed - indexed for MEDLINE]
Discovery of nutritional biomarkers: future directions based on omics technologies.
Discovery of nutritional biomarkers: future directions based on omics technologies.
Int J Food Sci Nutr. 2015 Jul;66(S1):S31-S40
Authors: Odriozola L, Corrales FJ
Abstract
Understanding the interactions between food and human biology is of utmost importance to facilitate the development of more efficient nutritional interventions that might improve our wellness status and future health outcomes by reducing risk factors for non-transmittable chronic diseases, such as cardiovascular diseases, cancer, obesity and metabolic syndrome. Dissection of the molecular mechanisms that mediate the physiological effects of diets and bioactive compounds is one of the main goals of current nutritional investigation and the food industry as might lead to the discovery of novel biomarkers. It is widely recognized that the availability of robust nutritional biomarkers represents a bottleneck that delays the innovation process of the food industry. In this regard, omics sciences have opened up new avenues of research and opportunities in nutrition. Advances in mass spectrometry, nuclear magnetic resonance, next generation sequencing and microarray technologies allow massive genome, gene expression, proteomic and metabolomic profiling, obtaining a global and in-depth analysis of physiological/pathological scenarios. For this reason, omics platforms are most suitable for the discovery and characterization of novel nutritional markers that will define the nutritional status of both individuals and populations in the near future, and to identify the nutritional bioactive compounds responsible for the health outcomes.
PMID: 26241009 [PubMed - as supplied by publisher]