PubMed

Related Articles Ginseng alleviates cyclophosphamide-induced hepatotoxicity via reversing disordered homeostasis of glutathione and bile acid. Sci Rep. 2015;5:17536 Authors: Zhu H, Long MH, Wu J, Wang MM, Li XY, Shen H, Xu JD, Zhou L, Fang ZJ, Luo Y, Li SL Abstract Cyclophosphamide (CP), a chemotherapeutic agent, is restricted due to its side effects, especially hepatotoxicity. Ginseng has often been clinically used with CP in China, but whether and how ginseng reduces the hepatotoxicity is unknown. In this study, the hepatoprotective effects and mechanisms under the combined usage were investigated. It was found that ginseng could ameliorate CP-induced elevations of ALP, ALT, ALS, MDA and hepatic deterioration, enhance antioxidant enzymes' activities and GSH's level. Metabolomics study revealed that 33 endogenous metabolites were changed by CP, 19 of which were reversed when ginseng was co-administrated via two main pathways, i.e., GSH metabolism and primary bile acids synthesis. Furthermore, ginseng could induce expression of GCLC, GCLM, GS and GST, which associate with the disposition of GSH, and expression of FXR, CYP7A1, NTCP and MRP 3, which play important roles in the synthesis and transport of bile acids. In addition, NRF 2, one of regulatory elements on the expression of GCLC, GCLM, GS, GST, NTCP and MRP3, was up-regulated when ginseng was co-administrated. In conclusion, ginseng could alleviate CP-induced hepatotoxicity via modulating the disordered homeostasis of GSH and bile acid, which might be mediated by inducing the expression of NRF 2 in liver. PMID: 26625948 [PubMed - in process]

Related Articles Integration of tissue metabolomics, transcriptomics and immunohistochemistry reveals ERG- and gleason score- specific metabolomic alterations in prostate cancer. Oncotarget. 2015 Nov 23; Authors: Meller S, Meyer HA, Bethan B, Dietrich D, González Maldonado S, Lein M, Montani M, Reszka R, Schatz P, Peter E, Stephan C, Jung K, Kamlage B, Kristiansen G Abstract Integrated analysis of metabolomics, transcriptomics and immunohistochemistry can contribute to a deeper understanding of biological processes altered in cancer and possibly enable improved diagnostic or prognostic tests. In this study, a set of 254 metabolites was determined by gas-chromatography/liquid chromatography-mass spectrometry in matched malignant and non-malignant prostatectomy samples of 106 prostate cancer (PCa) patients. Transcription analysis of matched samples was performed on a set of 15 PCa patients using Affymetrix U133 Plus 2.0 arrays. Expression of several proteins was immunohistochemically determined in 41 matched patient samples and the association with clinico-pathological parameters was analyzed by an integrated data analysis. These results further outline the highly deregulated metabolism of fatty acids, sphingolipids and polyamines in PCa. For the first time, the impact of the ERG translocation on the metabolome was demonstrated, highlighting an altered fatty acid oxidation in TMPRSS2-ERG translocation positive PCa specimens. Furthermore, alterations in cholesterol metabolism were found preferentially in high grade tumors, enabling the cells to create energy storage. With this integrated analysis we could not only confirm several findings from previous metabolomic studies, but also contradict others and finally expand our concepts of deregulated biological pathways in PCa. PMID: 26623558 [PubMed - as supplied by publisher]

Related Articles Microbial, host and xenobiotic diversity in the cystic fibrosis sputum metabolome. ISME J. 2015 Dec 1; Authors: Quinn RA, Phelan VV, Whiteson KL, Garg N, Bailey BA, Lim YW, Conrad DJ, Dorrestein PC, Rohwer FL Abstract Cystic fibrosis (CF) lungs are filled with thick mucus that obstructs airways and facilitates chronic infections. Pseudomonas aeruginosa is a significant pathogen of this disease that produces a variety of toxic small molecules. We used molecular networking-based metabolomics to investigate the chemistry of CF sputa and assess how the microbial molecules detected reflect the microbiome and clinical culture history of the patients. Metabolites detected included xenobiotics, P. aeruginosa specialized metabolites and host sphingolipids. The clinical culture and microbiome profiles did not correspond to the detection of P. aeruginosa metabolites in the same samples. The P. aeruginosa molecules that were detected in sputum did not match those from laboratory cultures. The pseudomonas quinolone signal (PQS) was readily detectable from cultured strains, but absent from sputum, even when its precursor molecules were present. The lack of PQS production in vivo is potentially due to the chemical nature of the CF lung environment, indicating that culture-based studies of this pathogen may not explain its behavior in the lung. The most differentially abundant molecules between CF and non-CF sputum were sphingolipids, including sphingomyelins, ceramides and lactosylceramide. As these highly abundant molecules contain the inflammatory mediator ceramide, they may have a significant role in CF hyperinflammation. This study demonstrates that the chemical makeup of CF sputum is a complex milieu of microbial, host and xenobiotic molecules. Detection of a bacterium by clinical culturing and 16S rRNA gene profiling do not necessarily reflect the active production of metabolites from that bacterium in a sputum sample. PMID: 26623545 [PubMed - as supplied by publisher]

Related Articles Metabolomic analysis of riboswitch containing E. coli recombinant expression system. Mol Biosyst. 2015 Dec 1; Authors: Muhamadali H, Xu Y, Morra R, Trivedi DK, Rattray NJ, Dixon N, Goodacre R Abstract In this study we have employed metabolomics approaches to understand the metabolic effects of producing enhanced green fluorescent protein (eGFP) as a recombinant protein in Escherichia coli cells. This metabolic burden analysis was performed against a number of recombinant expression systems and control strains and included: (i) standard transcriptional recombinant expression control system BL21(DE3) with the expression plasmid pET-eGFP, (ii) the recently developed dual transcriptional-translational recombinant expression control strain BL21(IL3), with pET-eGFP, (iii) BL21(DE3) with an empty expression plasmid pET, (iv) BL21(IL3) with an empty expression plasmid, and (v) BL21(DE3) without an expression plasmid; all strains were cultured under various induction conditions. The growth profiles of all strains together with the results gathered by the analysis of the Fourier transform infrared (FT-IR) spectroscopy data, identified IPTG-dependent induction as the dominant factor hampering cellular growth and metabolism, which was in general agreement with the findings of GC-MS analysis of cell extracts and media samples. In addition, the exposure of host cells to the synthetic inducer ligand, pyrimido[4,5-d] pyrimidine-2,4-diamine (PPDA), of the orthogonal riboswitch containing expression system (BL21(IL3)) did not display any detrimental effects, and its detected levels in all the samples were at similar levels, emphasising the inability of the cells to metabolise PPDA. The overall results obtained in this study suggested that although the BL21(DE3)-EGFP and BL21(IL3)-EGFP strains produced comparable levels of recombinant eGFP, the presence of the orthogonal riboswitch seemed to be moderating the metabolic burden of eGFP production in the cells enabling higher biomass yield, whilst providing a greater level of control over protein expression. PMID: 26621574 [PubMed - as supplied by publisher]

Related Articles System-wide assembly of pathways and modules hierarchically reveal metabolic mechanism of cerebral ischemia. Sci Rep. 2015;5:17068 Authors: Zhu Y, Guo Z, Zhang L, Zhang Y, Chen Y, Nan J, Zhao B, Xiao H, Wang Z, Wang Y Abstract The relationship between cerebral ischemia and metabolic disorders is poorly understood, which is partly due to the lack of comparative fusing data for larger complete systems and to the complexity of metabolic cascade reactions. Based on the fusing maps of comprehensive serum metabolome, fatty acid and amino acid profiling, we identified 35 potential metabolic biomarkers for ischemic stroke. Our analyses revealed 8 significantly altered pathways by MetPA (Metabolomics Pathway Analysis, impact score >0.10) and 15 significantly rewired modules in a complex ischemic network using the Markov clustering (MCL) method; all of these pathways became more homologous as the number of overlapping nodes was increased. We then detected 24 extensive pathways based on the total modular nodes from the network analysis, 12 of which were new discovery pathways. We provided a new perspective from the viewpoint of abnormal metabolites for the overall study of ischemic stroke as well as a new method to simplify the network analysis by selecting the more closely connected edges and nodes to build a module map of stroke. PMID: 26621314 [PubMed - in process]

Related Articles A systematic approach to expound the variations in taxane production under different dissolved oxygen conditions in Taxus chinensis cells. Plant Cell Rep. 2015 Nov 30; Authors: Zhao C, Song G, Fu C, Dong Y, Xu H, Zhang H, Yu LJ Abstract KEY MESSAGE: Our results provide an evidence that the changes in taxane production caused by dissolved oxygen shifts could be associated with the global variations in the cell central carbon metabolism. Taxol is an important taxane synthesized by the Taxus plant. A two-stage culture of Taxus in vitro has been considered as an attractive alternative approach to produce Taxol and its precursors. To investigate the consequences of dissolved oxygen (DO) shifts for cell primary and secondary metabolism, we conducted metabolomic and transcriptomic profiling analyses under low dissolved oxygen (LDO), medium dissolved oxygen (MDO), and high dissolved oxygen (HDO) conditions in a suspension culture of Taxus chinensis cells. Under LDO, the results indicate a significant increase in the production of Taxol and its main precursors by 3.4- to 1.4-fold compared with those under MDO and HDO on 9th day. Multiple acyl taxanes (MAT) are abundant taxanes in the cells, and exhibited only a slight increase under the same conditions. Metabolomic analysis based on 209 primary metabolites indicated that several pathways in central carbon metabolism were involved, including the enhancement of the glycolysis pathway of glucose-6-phosphate to fructose-6-phosphate and pyruvate and the mevalonate pathway of terpene biosynthesis, and decline in the tricarboxylic acid pathway under LDO. These results indicate the mechanism by which related taxanes accumulate through enhancing the supplies of substrates and expression levels of hydroxylases. Excess acetyl-CoA supply induced by high oxygen stress was found to be correlated with high productivity of MAT. Our results provide an evidence that the changes in taxane production caused by DO shifts could be associated with the global variations in the cell central carbon metabolism. PMID: 26620815 [PubMed - as supplied by publisher]

Related Articles (1) H NMR Metabolomics analysis of renal cell carcinoma cells: Effect of VHL inactivation on metabolism. Int J Cancer. 2015 Dec 1; Authors: Cuperlovic-Culf M, Cormier K, Touaibia M, Reyjal J, Robichaud S, Belbraouet M, Turcotte S Abstract Von Hippel-Lindau (VHL) is an onco-suppressor involved in oxygen and energy-dependent promotion of protein ubiquitination and proteosomal degradation. Loss of function mutations of VHL (VHL- cells) result in organ specific cancers with the best studied example in renal cell carcinomas. VHL has a well-established role in deactivation of hypoxia-inducible factor (HIF-1) and in regulation of PI3K/AKT/mTOR activity. Cell culture metabolomics analysis was utilized to determined effect of VHL and HIF-1α or HIF-2α on metabolism of renal cell carcinomas (RCC). RCC cells were stably transfected with VHL or shRNA designed to silence HIF-1α or HIF-2α genes. Obtained metabolic data was analysed qualitatively, searching for overall effects on metabolism as well as quantitatively, using methods developed in our group in order to determine specific metabolic changes. Analysis of the effect of VHL and HIF silencing on cellular metabolic footprints and fingerprints provided information about the metabolic pathways affected by VHL through HIF function as well as independently of HIF. Through correlation network analysis as well as statistical analysis of significant metabolic changes we have determined effects of VHL and HIF on energy production, amino acid metabolism, choline metabolism as well as cell regulation and signaling. VHL was shown to influence cellular metabolism through its effect on HIF proteins as well as by affecting activity of other factors. This article is protected by copyright. All rights reserved. PMID: 26620126 [PubMed - as supplied by publisher]

Related Articles Pharmacokinetics, Pharmacodynamics, and Pharmacogenomics of Immunosuppressants in Allogeneic Hematopoietic Cell Transplantation: Part II. Clin Pharmacokinet. 2015 Nov 30; Authors: McCune JS, Bemer MJ, Long-Boyle J Abstract Part I of this article included a pertinent review of allogeneic hematopoietic cell transplantation (alloHCT), the role of postgraft immunosuppression in alloHCT, and the pharmacokinetics, pharmacodynamics, and pharmacogenomics of the calcineurin inhibitors and methotrexate. In this article (Part II), we review the pharmacokinetics, pharmacodynamics, and pharmacogenomics of mycophenolic acid (MPA), sirolimus, and the antithymocyte globulins (ATG). We then discuss target concentration intervention (TCI) of these postgraft immunosuppressants in alloHCT patients, with a focus on current evidence for TCI and on how TCI may improve clinical management in these patients. Currently, TCI using trough concentrations is conducted for sirolimus in alloHCT patients. Several studies demonstrate that MPA plasma exposure is associated with clinical outcomes, with an increasing number of alloHCT patients needing TCI of MPA. Compared with MPA, there are fewer pharmacokinetic/dynamic studies of rabbit ATG and horse ATG in alloHCT patients. Future pharmacokinetic/dynamic research of postgraft immunosuppressants should include '-omics'-based tools: pharmacogenomics may be used to gain an improved understanding of the covariates influencing pharmacokinetics as well as proteomics and metabolomics as novel methods to elucidate pharmacodynamic responses. PMID: 26620047 [PubMed - as supplied by publisher]

Related Articles Molecular Aspects of Conifer Zygotic and Somatic Embryo Development: A Review of Genome-Wide Approaches and Recent Insights. Methods Mol Biol. 2016;1359:167-207 Authors: Trontin JF, Klimaszewska K, Morel A, Hargreaves C, Lelu-Walter MA Abstract Genome-wide profiling (transcriptomics, proteomics, metabolomics) is providing unprecedented opportunities to unravel the complexity of coordinated gene expression during embryo development in trees, especially conifer species harboring "giga-genome." This knowledge should be critical for the efficient delivery of improved varieties through seeds and/or somatic embryos in fluctuating markets and to cope with climate change. We reviewed "omics" as well as targeted gene expression studies during both somatic and zygotic embryo development in conifers and tentatively puzzled over the critical processes and genes involved at the specific developmental and transition stages. Current limitations to the interpretation of these large datasets are going to be lifted through the ongoing development of comprehensive genome resources in conifers. Nevertheless omics already confirmed that master regulators (e.g., transcription and epigenetic factors) play central roles. As in model angiosperms, the molecular regulation from early to late embryogenesis may mainly arise from spatiotemporal modulation of auxin-, gibberellin-, and abscisic acid-mediated responses. Omics also showed the potential for the development of tools to assess the progress of embryo development or to build genotype-independent, predictive models of embryogenesis-specific characteristics. PMID: 26619863 [PubMed - in process]

The first protocol of stable isotope ratio assessment in tumor tissues based on original research. Pol J Pathol. 2015;66(3):288-295 Authors: Taran K, Frączek T, Kamiński R, Sitkiewicz A, Kobos J, Paneth P Abstract Thanks to proteomics and metabolomics, for the past several years there has been a real explosion of information on the biology of cancer, which has been achieved by spectroscopic methods, including mass spectrometry. These modern techniques can provide answers to key questions about tissue structure and mechanisms of its pathological changes. However, despite the thousands of spectroscopic studies in medicine, there is no consensus on issues ranging from the choice of research tools, acquisition and preparation of test material to the interpretation and validation of the results, which greatly reduces the possibility of transforming the achieved knowledge to progress in the treatment of individual patients. The aim of this study was to verify the utility of isotope ratio mass spectrometry in the evaluation of tumor tissues. Based on experimentation on animal tissues and human neoplasms, the first protocol of stable isotope ratio assessment of carbon and nitrogen isotopes in tumor tissues was established. PMID: 26619108 [PubMed - as supplied by publisher]

The essential role of coumarin secretion for Fe acquisition from alkaline soil. Plant Signal Behav. 2015 Nov 30;:0 Authors: Clemens S, Weber M Abstract Plant productivity is limited by the scarcity of the essential micronutrient iron particularly in alkaline soils. The root secretion of phenolics has long been recognized as a component of the acidification-reduction strategy to acquire iron (strategy I). However, very little molecular insight into this process was available until recently several research groups independently discovered the important role of coumarins for the growth of Arabidopsis thaliana under Fe-limited conditions. Genome-wide analyses of iron deficiency responses, mutant screening and metabolomics experiments all converged on the finding that the synthesis and root exudation of scopoletin, esculetin and other coumarins is essential for iron uptake from substrates with low iron availability. Here we describe the evidence supporting this conclusion and discuss important questions that now have to be addressed in order to better understand the mechanistic basis of coumarin-dependent iron uptake and its significance within the plant kingdom. PMID: 26618918 [PubMed - as supplied by publisher]

An evolving computational platform for biological mass spectrometry: workflows, statistics and data mining with MASSyPup64. PeerJ. 2015;3:e1401 Authors: Winkler R Abstract In biological mass spectrometry, crude instrumental data need to be converted into meaningful theoretical models. Several data processing and data evaluation steps are required to come to the final results. These operations are often difficult to reproduce, because of too specific computing platforms. This effect, known as 'workflow decay', can be diminished by using a standardized informatic infrastructure. Thus, we compiled an integrated platform, which contains ready-to-use tools and workflows for mass spectrometry data analysis. Apart from general unit operations, such as peak picking and identification of proteins and metabolites, we put a strong emphasis on the statistical validation of results and Data Mining. MASSyPup64 includes e.g., the OpenMS/TOPPAS framework, the Trans-Proteomic-Pipeline programs, the ProteoWizard tools, X!Tandem, Comet and SpiderMass. The statistical computing language R is installed with packages for MS data analyses, such as XCMS/metaXCMS and MetabR. The R package Rattle provides a user-friendly access to multiple Data Mining methods. Further, we added the non-conventional spreadsheet program teapot for editing large data sets and a command line tool for transposing large matrices. Individual programs, console commands and modules can be integrated using the Workflow Management System (WMS) taverna. We explain the useful combination of the tools by practical examples: (1) A workflow for protein identification and validation, with subsequent Association Analysis of peptides, (2) Cluster analysis and Data Mining in targeted Metabolomics, and (3) Raw data processing, Data Mining and identification of metabolites in untargeted Metabolomics. Association Analyses reveal relationships between variables across different sample sets. We present its application for finding co-occurring peptides, which can be used for target proteomics, the discovery of alternative biomarkers and protein-protein interactions. Data Mining derived models displayed a higher robustness and accuracy for classifying sample groups in targeted Metabolomics than cluster analyses. Random Forest models do not only provide predictive models, which can be deployed for new data sets, but also the variable importance. We demonstrate that the later is especially useful for tracking down significant signals and affected pathways in untargeted Metabolomics. Thus, Random Forest modeling supports the unbiased search for relevant biological features in Metabolomics. Our results clearly manifest the importance of Data Mining methods to disclose non-obvious information in biological mass spectrometry . The application of a Workflow Management System and the integration of all required programs and data in a consistent platform makes the presented data analyses strategies reproducible for non-expert users. The simple remastering process and the Open Source licenses of MASSyPup64 (http://www.bioprocess.org/massypup/) enable the continuous improvement of the system. PMID: 26618079 [PubMed - as supplied by publisher]

Plasma 24-metabolite Panel Predicts Preclinical Transition to Clinical Stages of Alzheimer's Disease. Front Neurol. 2015;6:237 Authors: Fiandaca MS, Zhong X, Cheema AK, Orquiza MH, Chidambaram S, Tan MT, Gresenz CR, FitzGerald KT, Nalls MA, Singleton AB, Mapstone M, Federoff HJ Abstract We recently documented plasma lipid dysregulation in preclinical late-onset Alzheimer's disease (LOAD). A 10 plasma lipid panel, predicted phenoconversion and provided 90% sensitivity and 85% specificity in differentiating an at-risk group from those that would remain cognitively intact. Despite these encouraging results, low positive predictive values limit the clinical usefulness of this panel as a screening tool in subjects aged 70-80 years or younger. In this report, we re-examine our metabolomic data, analyzing baseline plasma specimens from our group of phenoconverters (n = 28) and a matched set of cognitively normal subjects (n = 73), and discover and internally validate a panel of 24 plasma metabolites. The new panel provides a classifier with receiver operating characteristic area under the curve for the discovery and internal validation cohort of 1.0 and 0.995 (95% confidence intervals of 1.0-1.0, and 0.981-1.0), respectively. Twenty-two of the 24 metabolites were significantly dysregulated lipids. While positive and negative predictive values were improved compared to our 10-lipid panel, low positive predictive values provide a reality check on the utility of such biomarkers in this age group (or younger). Through inclusion of additional significantly dysregulated analyte species, our new biomarker panel provides greater accuracy in our cohort but remains limited by predictive power. Unfortunately, the novel metabolite panel alone may not provide improvement in counseling and management of at-risk individuals but may further improve selection of subjects for LOAD secondary prevention trials. We expect that external validation will remain challenging due to our stringent study design, especially compared with more diverse subject cohorts. We do anticipate, however, external validation of reduced plasma lipid species as a predictor of phenoconversion to either prodromal or manifest LOAD. PMID: 26617567 [PubMed - as supplied by publisher]

Novel application of heuristic optimisation enables the creation and thorough evaluation of robust support vector machine ensembles for machine learning applications. Metabolomics. 2016;12(1):16 Authors: Chatzimichali EA, Bessant C Abstract Today's researchers have access to an unprecedented range of powerful machine learning tools with which to build models for classifying samples according to their metabolomic profile (e.g. separating diseased samples from healthy controls). However, such powerful tools need to be used with caution and the diagnostic performance of models produced by them should be rigorously evaluated if their output is to be believed. This involves considerable processing time, and has hitherto required expert knowledge in machine learning. By adopting a constrained nonlinear simplex optimisation for the tuning of support vector machines (SVMs) we have reduced SVM training times more than tenfold compared to a traditional grid search, allowing us to implement a high performance R package that makes it possible for a typical bench scientist to produce powerful SVM ensemble classifiers within a reasonable timescale, with automated bootstrapped training and rigorous permutation testing. This puts a state-of-the-art open source multivariate classification pipeline into the hands of every metabolomics researcher, allowing them to build robust classification models with realistic performance metrics. PMID: 26617479 [PubMed - as supplied by publisher]

Global metabolomics reveals metabolic dysregulation in ischemic retinopathy. Metabolomics. 2016;12(1):15 Authors: Paris LP, Johnson CH, Aguilar E, Usui Y, Cho K, Hoang LT, Feitelberg D, Benton HP, Westenskow PD, Kurihara T, Trombley J, Tsubota K, Ueda S, Wakabayashi Y, Patti GJ, Ivanisevic J, Siuzdak G, Friedlander M Abstract Proliferative diabetic retinopathy (PDR) is the most severe form of diabetic retinopathy and, along with diabetic macular edema, is responsible for the majority of blindness in adults below the age of 65. Therapeutic strategies for PDR are ineffective at curtailing disease progression in all cases; however a deeper understanding of the ocular metabolic landscape in PDR through metabolomic analysis may offer new therapeutic targets. Here, global and targeted mass spectrometry-based metabolomics were used to investigate metabolism. Initial analyses on vitreous humor from patients with PDR (n = 9) and non-diabetic controls (n = 11) revealed an increase of arginine and acylcarnitine metabolism in PDR. The oxygen-induced-retinopathy (OIR) mouse model, which exhibits comparable pathological manifestations to human PDR, revealed similar increases of arginine and other metabolites in the urea cycle, as well as downregulation of purine metabolism. We validated our findings by targeted multiple reaction monitoring and through the analysis of a second set of patient samples [PDR (n = 11) and non-diabetic controls (n = 20)]. These results confirmed a predominant and consistent increase in proline in both the OIR mouse model and vitreous samples from patients with PDR, suggesting that over activity in the arginine-to-proline pathway could be used as a therapeutic target in diabetic retinopathy. PMID: 26617478 [PubMed - as supplied by publisher]

Beta-glucan-depleted, glycopeptide-rich extracts from Brewer's and Baker's yeast (Saccharomyces cerevisiae) lower interferon-gamma production by stimulated human blood cells in vitro. Food Chem. 2016 Apr 15;197(Pt A):761-8 Authors: Williams R, Dias DA, Jayasinghe N, Roessner U, Bennett LE Abstract Regulation of the human immune system requires controlled pro- and anti-inflammatory responses for host defence against infection and disease states. Yeasts (Saccharomyces cerevisiae), as used in brewing and baking, are mostly known for ability to stimulate the human immune-system predominantly reflecting the pro-inflammatory cell wall β-glucans. However, in this study, using food-compatible processing methods, glycopeptide-enriched and β-glucan-depleted products were each prepared from Brewer's and Baker's yeasts, which suppressed production of interferon-γ (IFN-γ) in human whole blood cell assay, signifying that anti-inflammatory factors are also present in yeast. Anti-inflammatory bioactivities of products prepared from Brewer's and Baker's yeast were compared with the commercial yeast product, Epicor®. While unfractionated Epicor was inactive, the C18 resin-binding fractions of Brewer's and Baker's yeast products and Epicor dose-dependently lowered IFN-γ, demonstrating that Epicor also contained both pro-inflammatory (β-glucans) and anti-inflammatory components. Anti-inflammatory activity was attributed to C18 resin-binding species glyco-peptides in Epicor and experimental yeast products. This study demonstrated that pro- and anti-inflammatory factors could be resolved and enriched in yeasts by suitable processing, with potential to improve specific activities. PMID: 26617014 [PubMed - in process]

A metabolomic study on the biological effects of metal pollutions in oysters Crassostrea sikamea. Mar Pollut Bull. 2015 Nov 23; Authors: Ji C, Wang Q, Wu H, Tan Q, Wang WX Abstract Metal pollution has become a great threat to organisms in the estuaries in South China. In the present study, the oysters Crassostrea sikamea were collected from one clean (Jiuzhen) and five metal polluted sites (Baijiao, Fugong, Gongqian, Jinshan and Songyu). The tissue metal concentrations in oysters indicated that the five metal sites were polluted by several metals, including Cr, Ni, Co, Cu, Zn, Ag, Cd and Pb with different patterns. Especially, Cu and Zn were the major contaminants in Baijiao, Fugong and Jinshan sites. The metabolic responses in oysters C. sikamea indicated that the metal pollutions in BJ, FG, JS and SY sites induced disturbances in osmotic regulation and energy metabolism via different metabolic pathways. However, the metal pollution in GQ site mainly influenced the osmotic regulation in the oysters C. sikamea. This study demonstrates that NMR-based metabolomics is useful to characterize metabolic responses induced by metal pollution. PMID: 26616746 [PubMed - as supplied by publisher]

In-situ Protein-SIP highlights Burkholderiaceae as key players degrading toluene by para ring hydroxylation in a constructed wetland model. Environ Microbiol. 2015 Nov 30; Authors: Lünsmann V, Kappelmeyer U, Benndorf R, Martinez-Lavanchy PM, Taubert A, Adrian L, Duarte M, Pieper DH, von Bergen M, Müller JA, Heipieper HJ, Jehmlich N Abstract In constructed wetlands, organic pollutants are mainly degraded via microbial processes. Helophytes, plants that are commonly used in these systems, provide oxygen and root exudates to the rhizosphere stimulating microbial degradation. While the treatment performance of constructed wetlands can be remarkable, a mechanistic understanding of microbial degradation processes in the rhizosphere is still limited. We investigated microbial toluene removal in a constructed wetland model system combining 16S rRNA gene sequencing, metaproteomics and (13) C-toluene in situ protein-based stable isotope probing (Protein-SIP). The rhizospheric bacterial community was dominated by Burkholderiales and Rhizobiales which contributed each about 20% to total taxon abundances. Protein-SIP data revealed that members of Burkholderiaceae, which proteins showed about 73% of (13) C-incorporation, were main degraders of toluene in the planted system, while members of the Comamonadaceae were involved to a lesser extent in degradation (about 64% (13) C-incorporation). Among the Burkholderiaceae, one of the key players of toluene degradation could be assigned to Ralstonia pickettii. We observed that the main pathway of toluene degradation occurred via two subsequent monooxygenations of the aromatic ring. Our study provides a suitable approach to assess the key processes and microbes which are involved in the degradation of organic pollutants in complex rhizospheric ecosystems. PMID: 26616584 [PubMed - as supplied by publisher]

Metformin suppressed the proliferation of LoVo cells and induced a time-dependent metabolic and transcriptional alteration. Sci Rep. 2015;5:17423 Authors: He J, Wang K, Zheng N, Qiu Y, Xie G, Su M, Jia W, Li H Abstract Metformin is a widely used anti-diabetic drug with potential anti-tumor activity. However, little is known about its global metabolic and transcriptional impacts on tumor cells. In current study, we performed a metabolic profiling on human-derived colon cancer LoVo cells treated by 10 mM metformin for 8, 24 and 48 h. An obvious time-dependent metabolic alteration was observed from 8 to 48 h, prior to the reduction of cell viability. A total of 47, 45 and 66 differential metabolites were identified between control and metformin-treated cells at three time points. Most of the metabolites were up-regulated at 8 h, but down-regulated at 24 and 48 h by metformin. These metabolites were mainly involved in carbohydrates, lipids, amino acids, vitamins and nucleotides metabolism pathways. Meanwhile, the transcirptomic profile revealed 134 and 3061 differentially expressed genes at 8 and 24 h by metformin. In addition to the cancer signaling pathways, expression of genes involved in cell energy metabolism pathways was significantly altered, which were further validated with genes in glucose metabolism pathway. Altogether, our current data indicate that metformin suppressed the proliferation of LoVo cells, which may be due to the modulation on cell energy metabolism at both metabolic and transcriptional levels in a time-dependent way. PMID: 26616174 [PubMed - in process]

Circulating RNA: looking at the liver through a frosted glass. Biomarkers. 2015 Sep;20(6-7):339-54 Authors: Falcon-Perez JM, Royo F Abstract CONTEXT: The evaluation of the liver condition, based on serum enzymatic activity and biopsies, is insufficient. Therefore, it is a priority to find a correlation between circulating RNAs and liver damage. METHODS: Publications were retrieved by the search terms "circulating RNA AND liver". RESULTS: Although differences exist between studies, a profile of RNAs that repeatedly appeared as indicators of liver damage was identified. DISCUSSION: We highlight those circulating RNAs useful to diagnostic, and discuss the transport mechanisms. CONCLUSION: Several studies have proven that circulating RNAs are useful to establish a diagnostic and a prognosis of liver diseases. PMID: 26616145 [PubMed - in process]