PubMed
The Role of CD44 in Glucose Metabolism in Prostatic Small Cell Neuroendocrine Carcinoma.
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The Role of CD44 in Glucose Metabolism in Prostatic Small Cell Neuroendocrine Carcinoma.
Mol Cancer Res. 2016 Apr;14(4):344-53
Authors: Li W, Cohen A, Sun Y, Squires J, Braas D, Graeber TG, Du L, Li G, Li Z, Xu X, Chen X, Huang J
Abstract
UNLABELLED: While prostatic adenocarcinomas are relatively indolent, some patients with advanced adenocarcinomas recur with small cell neuroendocrine carcinoma which is highly aggressive and lethal. Because glycolysis is a feature of malignancy and the degree of glycolysis generally correlates with tumor aggressiveness, we wanted to compare the metabolic differences and the molecular mechanisms involved between the two tumor types. In this study, and based on previous characterization, LNCaP and PC-3 prostate cancer cell lines were selected as models of prostatic adenocarcinoma and small cell neuroendocrine carcinoma, respectively. In addition to measuring glucose consumption, lactate secretion, and reactive oxygen species (ROS) levels, we performed metabolic profiling in these two model systems. The role of CD44 was studied by RNAi and lentivirus-mediated overexpression. Expression of key enzymes in glycolysis was studied using human tissue microarrays containing benign prostate, adenocarcinoma, and small cell neuroendocrine carcinoma. Results showed that glycolytic features of PC-3 cells were higher than that of LNCaP cells. PFKFB4 was overexpressed in human small cell carcinoma tissue versus adenocarcinoma tissue. CD44 regulated glucose metabolism, intracellular ROS, and cell proliferation in PC-3 cells. Inhibition of CD44 also sensitized PC-3 cells to carboplatin. In conclusion, this study suggests different pathways of glucose metabolism contribute to the disparate biologic behaviors of these two tumor types.
IMPLICATIONS: CD44 is an important regulator of glucose metabolism in small cell neuroendocrine carcinoma and may be an important therapeutic target.
PMID: 26832214 [PubMed - indexed for MEDLINE]
Using the knowns to discover the unknowns: MS-based dereplication uncovers structural diversity in 17-hydroxygeranyllinalool diterpene glycoside production in the Solanaceae.
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Using the knowns to discover the unknowns: MS-based dereplication uncovers structural diversity in 17-hydroxygeranyllinalool diterpene glycoside production in the Solanaceae.
Plant J. 2016 Feb;85(4):561-77
Authors: Heiling S, Khanal S, Barsch A, Zurek G, Baldwin IT, Gaquerel E
Abstract
Exploring the diversity of plant secondary metabolism requires efficient methods to obtain sufficient structural insights to discriminate previously known from unknown metabolites. De novo structure elucidation and confirmation of known metabolites (dereplication) remain a major bottleneck for mass spectrometry-based metabolomic workflows, and few systematic dereplication strategies have been developed for the analysis of entire compound classes across plant families, partly due to the complexity of plant metabolic profiles that complicates cross-species comparisons. 17-hydroxygeranyllinalool diterpene glycosides (HGL-DTGs) are abundant defensive secondary metabolites whose malonyl and glycosyl decorations are induced by jasmonate signaling in the ecological model plant Nicotiana attenuata. The multiple labile glycosidic bonds of HGL-DTGs result in extensive in-source fragmentation (IS-CID) during ionization. To reconstruct these IS-CID clusters from profiling data and identify precursor ions, we applied a deconvolution algorithm and created an MS/MS library from positive-ion spectra of purified HGL-DTGs. From this library, 251 non-redundant fragments were annotated, and a workflow to characterize leaf, flower and fruit extracts of 35 solanaceous species was established. These analyses predicted 105 novel HGL-DTGs that were restricted to Nicotiana, Capsicum and Lycium species. Interestingly, malonylation is a highly conserved step in HGL-DTG metabolism, but is differentially affected by jasmonate signaling among Nicotiana species. This MS-based workflow is readily applicable for cross-species re-identification/annotation of other compound classes with sufficient fragmentation knowledge, and therefore has the potential to support hypotheses regarding secondary metabolism diversification.
PMID: 26749139 [PubMed - indexed for MEDLINE]
Metabolomics
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Metabolomics
Book. 2012 02 10Authors: Roessner U
Abstract
Inflammation is a normal and extraordinarily important component of responses to infection and injury. The cardinal features of swelling, redness, stiffness and increasing temperature are strong indicators of the significant changes in tissue metabolism and the ingress of immune cells into the tissues. The increase in blood flow which underlies many of these changes may result in changes to the supply of nutrients and in particular the level of oxygen in the tissues. Inward migration of immune cells, which is also enabled by the increased blood flow, will put further stress on the metabolic environment of the tissues. The activity of macrophages and neutrophils in clearing infection and repairing tissue damage also have significant metabolic consequences particularly because of the production of cytokines and cytotoxic molecules such as reactive oxygen species and reactive nitrogen species, which are required to kill invading organisms. Production of these molecules will consume considerable quantities of oxygen, ATP and NADPH. These antimicrobial agents put considerable stress on host cells in the surrounding and distal tissues and can lead to significant loss of protective metabolites such as glutathione. Most infections and traumatic injuries are cleared or repaired relatively rapidly and metabolic homoeostasis is soon restored. However, there is a broad range of inflammatory diseases which involve chronic activation of the immune system and, as a result, chronic persistent inflammation. We have been studying the metabolic consequences of chronic inflammatory diseases with the aim of identifying metabolic fingerprints which may provide clues about why the localised tissue disease persists. For example, why in rheumatoid arthritis does persistent inflammation lead to widespread cartilage and joint destruction? However, the metabolic consequences of chronic inflammation are much more widespread than the localised disease and can lead on to important comorbidities such as accelerated atherosclerosis and cardiovascular disease. Metabolomic analysis may be able to distinguish between localised and systemic metabolic consequences of inflammation and provide novel targets for therapeutic intervention in these important human diseases.
PMID: 28045482
A fully validated GC-TOF-MS method for the quantification of fatty acids revealed alterations in the metabolic profile of fatty acids after smoking cessation.
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A fully validated GC-TOF-MS method for the quantification of fatty acids revealed alterations in the metabolic profile of fatty acids after smoking cessation.
J Chromatogr B Analyt Technol Biomed Life Sci. 2016 Dec 23;1041-1042:141-150
Authors: Goettel M, Niessner R, Pluym N, Scherer G, Scherer M
Abstract
We developed and validated an efficient and robust method for the simultaneous quantification of 44 fatty acid species in human plasma via GC-TOF-MS. The method is characterized by its robustness, accuracy and precision covering a wide range of fatty acid species with various saturation degrees including short chain fatty acids (beginning with FA 4:0) and long chain fatty acids (up to FA 32:0). The fatty acids were methylated prior to analyses and subsequently detected as fatty acid methyl esters by means of GC-TOF-MS. A highly substituted polar column allowed the separation of geometrical and positional isomers of fatty acid species. The method was applied to plasma samples of a strictly diet controlled clinical smoking cessation study including 39 smokers followed over the course of three months after having quit. Statistical significant alterations within the fatty acid profile were observed when comparing the baseline (subjects still smoking) with one week, one month and three months of smoking cessation. After 3 months of smoking cessation, a partial recovery of alterations in the fatty acid profile evoked by smoking was observed. In conclusion, the developed fatty acid profiling method using GC-TOF-MS has proven as a reliable tool for the quantitative determination of 44 individual fatty acid species within clinical studies.
PMID: 28039811 [PubMed - as supplied by publisher]
What computational non-targeted mass spectrometry-based metabolomics can gain from shotgun proteomics.
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What computational non-targeted mass spectrometry-based metabolomics can gain from shotgun proteomics.
Curr Opin Biotechnol. 2016 Dec 28;43:141-146
Authors: Hamzeiy H, Cox J
Abstract
Computational workflows for mass spectrometry-based shotgun proteomics and untargeted metabolomics share many steps. Despite the similarities, untargeted metabolomics is lagging behind in terms of reliable fully automated quantitative data analysis. We argue that metabolomics will strongly benefit from the adaptation of successful automated proteomics workflows to metabolomics. MaxQuant is a popular platform for proteomics data analysis and is widely considered to be superior in achieving high precursor mass accuracies through advanced nonlinear recalibration, usually leading to five to ten-fold better accuracy in complex LC-MS/MS runs. This translates to a sharp decrease in the number of peptide candidates per measured feature, thereby strongly improving the coverage of identified peptides. We argue that similar strategies can be applied to untargeted metabolomics, leading to equivalent improvements in metabolite identification.
PMID: 28039739 [PubMed - as supplied by publisher]
Micafungin alters the amino acid, nucleic acid and central carbon metabolism of Candida albicans at subinhibitory concentrations: novel insights into mechanisms of action.
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Micafungin alters the amino acid, nucleic acid and central carbon metabolism of Candida albicans at subinhibitory concentrations: novel insights into mechanisms of action.
J Antimicrob Chemother. 2016 Dec 30;:
Authors: Katragkou A, Williams M, Sternberg S, Pantazatos D, Roilides E, Walsh TJ
Abstract
BACKGROUND: Echinocandins are an important class of antifungal agents in the treatment of invasive candidiasis. However, little is known about the metabolomic effects of echinocandins on Candida We therefore performed LC-high-resolution MS (LC-HRMS)-based metabolomics profiling of the response of Candida albicans cells to increasing concentrations of micafungin to determine the metabolic response of Candida to micafungin subinhibitory injury.
METHODS: Isolates of C. albicans were cultured on nitrocellulose filters to mid-logarithmic phase of growth and micafungin (0-0.25 mg/L) was added. At mid-logarithmic phase, replicates were metabolically quenched. Intracellular metabolites were analysed by LC-HRMS. Changes in pool sizes of individual metabolites were analysed by Student's t-test adjusted for multiple hypothesis testing by Benjamini-Hochberg correction. Metabolites were ascribed by the Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways database.
RESULTS: Among 3446 detected metabolites, 204 were identified by comparison against pure standard or comparison against a library of mass-retention-time pairs. Fifty had significantly altered abundances in response to increasing micafungin concentrations. Pool sizes of amino acids, nucleic acids and polyamine metabolism were significantly increased at subinhibitory concentrations, while exposure to inhibitory concentrations resulted in a precipitous decrease consistent with fungicidal activity.
CONCLUSIONS: Micafungin induces a re-routing of metabolic pathways inhibiting protein synthesis and cell replication. These results shed light on new mechanisms of action of echinocandins.
PMID: 28039272 [PubMed - as supplied by publisher]
Recent Advances in Lipidomics: Analytical and Clinical Perspectives.
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Recent Advances in Lipidomics: Analytical and Clinical Perspectives.
Prostaglandins Other Lipid Mediat. 2016 Dec 27;:
Authors: Sethi S, Brietzke E
Abstract
Lipidomics or lipid-profiling is a lipid-targeted metabolomics approach aiming at comprehensive analysis of lipids in biological systems. The extent of information in the genomic and proteomic fields is greater than that in the lipidomics field, because of the complex nature of lipids and the limitations of tools for analysis. Modern technological advances in mass spectrometry and chromatography have greatly improved the developments and applications of metabolic profiling of diverse lipids in complex biological samples. Lipidomics will not only provide insights into the specific functions of lipid species in health and disease, but will also identify potential biomarkers for establishing preventive or therapeutic programs for human diseases. In this review, emphasis is given to the current advances in lipidomics technologies and their applications in disease biomarker discovery, and its clinical application. The application of lipidomics in clinical studies may provide new insights into lipid profiling and pathophysiological mechanisms. We also discuss the lipidomics for the future perspectives and their potential problems.
PMID: 28039059 [PubMed - as supplied by publisher]
Metabotypes of breast cancer cell lines revealed by non-targeted metabolomics.
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Metabotypes of breast cancer cell lines revealed by non-targeted metabolomics.
Metab Eng. 2016 Dec 27;:
Authors: Dubuis S, Baenke F, Scherbichler N, Alexander LT, Schulze A, Zamboni N
Abstract
We present an analysis of intracellular metabolism by non-targeted, high-throughput metabolomics profiling of 18 breast cell lines. We profiled >900 putatively annotated metabolite ions for >100 samples collected under both normoxic and hypoxic conditions and revealed extensive heterogeneity across all metabolic pathways and cell lines. Cell line-specific metabolome profiles dominated over patterns associated with malignancy or with the clinical nomenclature of breast cancer cells. Such characteristic metabolome profiles were reproducible across different laboratories and experiments and exhibited mild to robust changes with change in experimental conditions. To extract a functional overview of cell line heterogeneity, we devised an unsupervised metabotyping procedure that for each pathway automatically recognized metabolic types from metabolome data and assigned cell lines. Our procedure provided a condensed yet global representation of cell line metabolism, revealing the fine structure of metabolic heterogeneity across all tested pathways and cell lines. In follow-up experiments on selected pathways, we confirmed that different metabolic types correlated to differences in the underlying fluxes and difference sensitivity to gene knockdown or pharmacological inhibition. Thus, the identified metabotypes recapitulated functional differences at the pathway level. Metabotyping provides a powerful compression of multi-dimensional data that preserves functional information and serves as a resource for reconciling or understanding heterogeneous metabolic phenotypes or response to inhibition of metabolic pathways.
PMID: 28038952 [PubMed - as supplied by publisher]
Proteome alterations associated with transformation of multiple myeloma to secondary plasma cell leukemia.
Proteome alterations associated with transformation of multiple myeloma to secondary plasma cell leukemia.
Oncotarget. 2016 Dec 27;:
Authors: Zatula A, Dikic A, Mulder C, Sharma A, Vågbø CB, Sousa MM, Waage A, Slupphaug G
Abstract
Plasma cell leukemia is a rare and aggressive plasma cell neoplasm that may either originate de novo (primary PCL) or by leukemic transformation of multiple myeloma (MM) to secondary PCL (sPCL). The prognosis of sPCL is very poor, and currently no standard treatment is available due to lack of prospective clinical studies. In an attempt to elucidate factors contributing to transformation, we have performed super-SILAC quantitative proteome profiling of malignant plasma cells collected from the same patient at both the MM and sPCL stages of the disease. 795 proteins were found to be differentially expressed in the MM and sPCL samples. Gene ontology analysis indicated a metabolic shift towards aerobic glycolysis in sPCL as well as marked down-regulation of enzymes involved in glycan synthesis, potentially mediating altered glycosylation of surface receptors. There was no significant change in overall genomic 5-methylcytosine or 5-hydroxymethylcytosine at the two stages, indicating that epigenetic dysregulation was not a major driver of transformation to sPCL. The present study constitutes the first attempt to provide a comprehensive map of the altered protein expression profile accompanying transformation of MM to sPCL in a single patient, identifying several candidate proteins that can be targeted by currently available small molecule drugs. Our dataset furthermore constitutes a reference dataset for further proteomic analysis of sPCL transformation.
PMID: 28038447 [PubMed - as supplied by publisher]
The integration of GC-MS and LC-MS to assay the metabolomics profiling in Panax ginseng and Panax quinquefolius reveals a tissue- and species-specific connectivity of primary metabolites and ginsenosides accumulation.
The integration of GC-MS and LC-MS to assay the metabolomics profiling in Panax ginseng and Panax quinquefolius reveals a tissue- and species-specific connectivity of primary metabolites and ginsenosides accumulation.
J Pharm Biomed Anal. 2016 Dec 23;135:176-185
Authors: Liu J, Liu Y, Wang Y, Abozeid A, Zu YG, Tang ZH
Abstract
The traditional medicine Ginseng mainly including Panax ginseng and Panax quinquefolius is the most widely consumed herbal product in the world. Despite the extensive investigation of biosynthetic pathway of the active compounds ginsenosides, our current understanding of the metabolic interlink between ginsenosides synthesis and primary metabolism at the whole-plant level. In this study, the tissue-specific profiling of primary and the secondary metabolites in two different species of ginseng were investigated by gas chromatography- and liquid chromatography coupled to mass spectrometry. A complex continuous coordination of primary- and secondary-metabolic network was modulated by tissues and species factors during growth. The results showed that altogether 149 primary compounds and 10 ginsenosides were identified from main roots, lateral roots, stems, petioles and leaves in P. ginseng and P. quinquefolius. The partial least squares-discriminate analysis (PLS-DA) revealed obvious compounds distinction among tissue-specific districts relative to species. To survey the dedication of carbon and nitrogen metabolism in different tissues to the accumulation of ginsenosides, we inspected the tissue-specific metabolic changes. Our study testified that the ginsenosides content was dependent on main roots and lateral roots energy metabolism, whereas independent of leaves and petiole photosynthesis during ginsenosides accumulation. When tow species were compared, the results indicated that high rates of C assimilation to C accumulation are closely associated with ginsenosides accumulation in P. ginseng main roots and P. quinquefolius lateral roots, respectively. Taken together, our results suggest that tissue-specific metabolites profiling dynamically changed in process of ginsenosides biosynthesis, which may offer a new train of thoughts to the mechanisms of the ginsenosides biosynthesis at the metabolite level.
PMID: 28038384 [PubMed - as supplied by publisher]
Fully Automated Trimethylsilyl (TMS) Derivatisation Protocol for Metabolite Profiling by GC-MS.
Fully Automated Trimethylsilyl (TMS) Derivatisation Protocol for Metabolite Profiling by GC-MS.
Metabolites. 2016 Dec 29;7(1):
Authors: Zarate E, Boyle V, Rupprecht U, Green S, Villas-Boas SG, Baker P, Pinu FR
Abstract
Gas Chromatography-Mass Spectrometry (GC-MS) has long been used for metabolite profiling of a wide range of biological samples. Many derivatisation protocols are already available and among these, trimethylsilyl (TMS) derivatisation is one of the most widely used in metabolomics. However, most TMS methods rely on off-line derivatisation prior to GC-MS analysis. In the case of manual off-line TMS derivatisation, the derivative created is unstable, so reduction in recoveries occurs over time. Thus, derivatisation is carried out in small batches. Here, we present a fully automated TMS derivatisation protocol using robotic autosamplers and we also evaluate a commercial software, Maestro available from Gerstel GmbH. Because of automation, there was no waiting time of derivatised samples on the autosamplers, thus reducing degradation of unstable metabolites. Moreover, this method allowed us to overlap samples and improved throughputs. We compared data obtained from both manual and automated TMS methods performed on three different matrices, including standard mix, wine, and plasma samples. The automated TMS method showed better reproducibility and higher peak intensity for most of the identified metabolites than the manual derivatisation method. We also validated the automated method using 114 quality control plasma samples. Additionally, we showed that this online method was highly reproducible for most of the metabolites detected and identified (RSD < 20) and specifically achieved excellent results for sugars, sugar alcohols, and some organic acids. To the very best of our knowledge, this is the first time that the automated TMS method has been applied to analyse a large number of complex plasma samples. Furthermore, we found that this method was highly applicable for routine metabolite profiling (both targeted and untargeted) in any metabolomics laboratory.
PMID: 28036063 [PubMed]
Targeted metabolomics reveals differences in the extended postprandial plasma metabolome of healthy subjects after intake of whole-grain rye porridges versus refined wheat bread.
Targeted metabolomics reveals differences in the extended postprandial plasma metabolome of healthy subjects after intake of whole-grain rye porridges versus refined wheat bread.
Mol Nutr Food Res. 2016 Dec 30;:
Authors: Shi L, Brunius C, Lindelöf M, Shameh SA, Wu H, Lee I, Landberg R, Moazzami AA
Abstract
SCOPE: We previously found that whole-grain (WG) rye porridges suppressed appetite and improved glucose metabolism. The present work aimed to investigate potential plasma metabolites that may be related to differences in those appetite and glucose responses.
METHODS AND RESULTS: Twenty-one health subjects consumed six isocaloric breakfasts in a randomised cross-over study. Plain WG rye porridges (40 g and 55 g), rye porridge enriched with different inulin: gluten proportions (9:3 g; 6:6 g; 3:9 g), and a 55 g refined wheat bread (control) were served as part of complete breakfast, followed by a standardized lunch. NMR metabolomics assessed 36 plasma metabolites and short chain fatty acids were measured by GC-MS from baseline up to 8 h. Pre-lunch plasma essential amino acids reflected protein composition and post-lunch plasma short chain fatty acids varied with fibre content in breakfasts. No correlations were observed between measured metabolites and glucose, insulin, or appetite responses.
CONCLUSIONS: Differences in protein and fibre contents in breakfasts altered postprandial plasma amino acids and short chain fatty acids, respectively, but were unrelated to appetite and glucose responses. Further studies are warrant to identify the underlying mechanisms for the beneficial effects on appetite and second meal glucose responses after rye-based foods. This article is protected by copyright. All rights reserved.
PMID: 28035736 [PubMed - as supplied by publisher]
The Association Between Musculoskeletal Pain and Circulating Ornithine: A Population-Based Study.
The Association Between Musculoskeletal Pain and Circulating Ornithine: A Population-Based Study.
Pain Med. 2016 Dec 29;:
Authors: Mäntyselkä P, Ali-Sisto T, Kautiainen H, Niskanen L, Viinamäki H, Velagapudi V, Lehto SM
Abstract
OBJECTIVE: Based on several previous clinical studies, we hypothesized that ornithine levels are different among subjects with persistent musculoskeletal pain compared with other subjects in the population.
DESIGN: The study sample consisted of 221 adults with nonpersistent pain, 76 with persistent pain, and 61 with no pain. Concentrations of glutamic acid, ornithine, citrulline, arginine, proline, and spermidine were analyzed using a mass spectrometer.
SETTING: Lapinlahti municipality in Finland.
RESULTS: For the subjects with no pain, nonpersistent pain, and persistent pain, the ornithine concentrations for men were 85.3 µmol/L (SD = 28.9 µmol/L), 98.9 µmol/L (SD = 37.8 µmol/L), and 102.1 µmol/L (SD = 37.1 µmol/L; P = 0.033), respectively. The corresponding concentrations for women were 82.8 µmol/L (SD = 25.2 µmol/L), 83.7 µmol/L (SD = 27.8 µmol/L), and 103.2 µmol/L (SD = 34.9 µmol/L; P = 0.0031). There were no significant differences between the pain groups for any of the other investigated amino acids. Relative sex-specific ornithine concentration adjusted for age, glomerular filtration rate, smoking, body mass index, physical activity, and depressive symptoms was associated with pain (P = 0.025), the ornithine level being higher in the persistent pain group than in the no pain (P = 0.006) and nonpersistent pain (P = 0.032) groups.
CONCLUSION: Ornithine levels are elevated in general population subjects with persistent pain.
PMID: 28034972 [PubMed - as supplied by publisher]
Temporal bacterial and metabolic development of the preterm gut reveals specific signatures in health and disease.
Temporal bacterial and metabolic development of the preterm gut reveals specific signatures in health and disease.
Microbiome. 2016 Dec 29;4(1):67
Authors: Stewart CJ, Embleton ND, Marrs EC, Smith DP, Nelson A, Abdulkadir B, Skeath T, Petrosino JF, Perry JD, Berrington JE, Cummings SP
Abstract
BACKGROUND: The preterm microbiome is crucial to gut health and may contribute to necrotising enterocolitis (NEC), which represents the most significant pathology affecting preterm infants. From a cohort of 318 infants, <32 weeks gestation, we selected 7 infants who developed NEC (defined rigorously) and 28 matched controls. We performed detailed temporal bacterial (n = 641) and metabolomic (n = 75) profiling of the gut microbiome throughout the disease.
RESULTS: A core community of Klebsiella, Escherichia, Staphyloccocus, and Enterococcus was present in all samples. Gut microbiota profiles grouped into six distinct clusters, termed preterm gut community types (PGCTs). Each PGCT reflected dominance by the core operational taxonomic units (OTUs), except of PGCT 6, which had high diversity and was dominant in bifidobacteria. While PGCTs 1-5 were present in infants prior to NEC diagnosis, PGCT 6 was comprised exclusively of healthy samples. NEC infants had significantly more PGCT transitions prior to diagnosis. Metabolomic profiling identified significant pathways associated with NEC onset, with metabolites involved in linoleate metabolism significantly associated with NEC diagnosis. Notably, metabolites associated with NEC were the lowest in PGCT 6.
CONCLUSIONS: This is the first study to integrate sequence and metabolomic stool analysis in preterm neonates, demonstrating that NEC does not have a uniform microbial signature. However, a diverse gut microbiome with a high abundance of bifidobacteria may protect preterm infants from disease. These results may inform biomarker development and improve understanding of gut-mediated mechanisms of NEC.
PMID: 28034304 [PubMed - in process]
Pharmacometabolomics-aided Pharmacogenomics in Autoimmune Disease.
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Pharmacometabolomics-aided Pharmacogenomics in Autoimmune Disease.
EBioMedicine. 2016 Mar;5:40-5
Authors: Katsila T, Konstantinou E, Lavda I, Malakis H, Papantoni I, Skondra L, Patrinos GP
Abstract
Inter-individual variability has been a major hurdle to optimize disease management. Precision medicine holds promise for improving health and healthcare via tailor-made therapeutic strategies. Herein, we outline the paradigm of "pharmacometabolomics-aided pharmacogenomics" in autoimmune diseases. We envisage merging pharmacometabolomic and pharmacogenomic data (to address the interplay of genomic and environmental influences) with information technologies to facilitate data analysis as well as sense- and decision-making on the basis of synergy between artificial and human intelligence. Humans can detect patterns, which computer algorithms may fail to do so, whereas data-intensive and cognitively complex settings and processes limit human ability. We propose that better-informed, rapid and cost-effective omics studies need the implementation of holistic and multidisciplinary approaches.
PMID: 27077110 [PubMed - indexed for MEDLINE]
Evaluation of carbohydrate-cysteamine thiazolidines as pro-drugs for the treatment of cystinosis.
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Evaluation of carbohydrate-cysteamine thiazolidines as pro-drugs for the treatment of cystinosis.
Carbohydr Res. 2016 Dec 18;439:9-15
Authors: Ramazani Y, Levtchenko EN, Van Den Heuvel L, Van Schepdael A, Paul P, Ivanova EA, Pastore A, Hartman TM, Price NP
Abstract
Cystinosis is a genetic disorder caused by malfunction of cystinosin and is characterized by accumulation of cystine. Cysteamine, the medication used in cystinosis, causes halitosis resulting in poor patient compliance. Halitosis is mainly caused by the formation of dimethylsulfide as the final product in the cysteamine metabolism pathway. We have synthesized carbohydrate-cysteamine thiazolidines, and hypothesized that the hydrolytic breakdown of cysteamine-thiazolidines can result in free cysteamine being released in target organs. To examine our hypothesis, we tested these analogs in vitro in patient-derived fibroblasts. Cystinotic fibroblasts were treated with different concentrations of arabinose-cysteamine, glucose-cysteamine and maltose-cysteamine. We demonstrated that the analogs break down into cysteamine extracellularly and might therefore not be fully taken up by the cells under the form of the pro-drug. Potential modifications of the analogs that enable their intracellular rather than extracellular breakdown, is necessary to pursue the potential of these analogs as pro-drugs.
PMID: 28033491 [PubMed - as supplied by publisher]
BluePen Biomarkers LLC: integrated biomarker solutions.
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BluePen Biomarkers LLC: integrated biomarker solutions.
Future Sci OA. 2016 Jun;2(2):FSO124
Authors: Blair IA, Mesaros C, Lilley P, Nunez M
Abstract
BluePen Biomarkers provides a unique comprehensive multi-omics biomarker discovery and validation platform. We can quantify, integrate and analyze genomics, proteomics, metabolomics and lipidomics biomarkers, alongside clinical data, demographics and other phenotypic data. A unique bio-inspired signal processing analytic approach is used that has the proven ability to identify biomarkers in a wide variety of diseases. The resulting biomarkers can be used for diagnosis, prognosis, mechanistic studies and predicting treatment response, in contexts from core research through clinical trials. BluePen Biomarkers provides an additional groundbreaking research goal: identifying surrogate biomarkers from different modalities. This not only provides new biological insights, but enables least invasive, least-cost tests that meet or exceed the predictive quality of current tests.
PMID: 28031971 [PubMed]
Noninvasive metabolic profiling for painless diagnosis of human diseases and disorders.
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Noninvasive metabolic profiling for painless diagnosis of human diseases and disorders.
Future Sci OA. 2016 Jun;2(2):FSO106
Authors: Mal M
Abstract
Metabolic profiling provides a powerful diagnostic tool complementary to genomics and proteomics. The pain, discomfort and probable iatrogenic injury associated with invasive or minimally invasive diagnostic methods, render them unsuitable in terms of patient compliance and participation. Metabolic profiling of biomatrices like urine, breath, saliva, sweat and feces, which can be collected in a painless manner, could be used for noninvasive diagnosis. This review article covers the noninvasive metabolic profiling studies that have exhibited diagnostic potential for diseases and disorders. Their potential applications are evident in different forms of cancer, metabolic disorders, infectious diseases, neurodegenerative disorders, rheumatic diseases and pulmonary diseases. Large scale clinical validation of such diagnostic methods is necessary in future.
PMID: 28031956 [PubMed]
Identifying biomarkers of dietary patterns by using metabolomics.
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Identifying biomarkers of dietary patterns by using metabolomics.
Am J Clin Nutr. 2016 Dec 28;:
Authors: Playdon MC, Moore SC, Derkach A, Reedy J, Subar AF, Sampson JN, Albanes D, Gu F, Kontto J, Lassale C, Liao LM, Männistö S, Mondul AM, Weinstein SJ, Irwin ML, Mayne ST, Stolzenberg-Solomon R
Abstract
BACKGROUND: Healthy dietary patterns that conform to national dietary guidelines are related to lower chronic disease incidence and longer life span. However, the precise mechanisms involved are unclear. Identifying biomarkers of dietary patterns may provide tools to validate diet quality measurement and determine underlying metabolic pathways influenced by diet quality.
OBJECTIVE: The objective of this study was to examine the correlation of 4 diet quality indexes [the Healthy Eating Index (HEI) 2010, the Alternate Mediterranean Diet Score (aMED), the WHO Healthy Diet Indicator (HDI), and the Baltic Sea Diet (BSD)] with serum metabolites.
DESIGN: We evaluated dietary patterns and metabolites in male Finnish smokers (n = 1336) from 5 nested case-control studies within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study cohort. Participants completed a validated food-frequency questionnaire and provided a fasting serum sample before study randomization (1985-1988). Metabolites were measured with the use of mass spectrometry. We analyzed cross-sectional partial correlations of 1316 metabolites with 4 diet quality indexes, adjusting for age, body mass index, smoking, energy intake, education, and physical activity. We pooled estimates across studies with the use of fixed-effects meta-analysis with Bonferroni correction for multiple comparisons, and conducted metabolic pathway analyses.
RESULTS: The HEI-2010, aMED, HDI, and BSD were associated with 23, 46, 23, and 33 metabolites, respectively (17, 21, 11, and 10 metabolites, respectively, were chemically identified; r-range: -0.30 to 0.20; P = 6 × 10(-15) to 8 × 10(-6)). Food-based diet indexes (HEI-2010, aMED, and BSD) were associated with metabolites correlated with most components used to score adherence (e.g., fruit, vegetables, whole grains, fish, and unsaturated fat). HDI correlated with metabolites related to polyunsaturated fat and fiber components, but not other macro- or micronutrients (e.g., percentages of protein and cholesterol). The lysolipid and food and plant xenobiotic pathways were most strongly associated with diet quality.
CONCLUSIONS: Diet quality, measured by healthy diet indexes, is associated with serum metabolites, with the specific metabolite profile of each diet index related to the diet components used to score adherence. This trial was registered at clinicaltrials.gov as NCT00342992.
PMID: 28031192 [PubMed - as supplied by publisher]
A novel non-canonical Wnt signature for prostate cancer aggressiveness.
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A novel non-canonical Wnt signature for prostate cancer aggressiveness.
Oncotarget. 2016 Dec 24;:
Authors: Sandsmark E, Hansen AF, Selnæs KM, Bertilsson H, Bofin AM, Wright AJ, Viset T, Richardsen E, Drabløs F, Bathen TF, Tessem MB, Rye MB
Abstract
Activation of the Canonical Wnt pathway (CWP) has been linked to advanced and metastatic prostate cancer, whereas the Wnt5a-induced non-canonical Wnt pathway (NCWP) has been associated with both good and poor prognosis. A newly discovered NCWP, Wnt5/Fzd2, has been shown to induce epithelial-to-mesenchymal transition (EMT) in cancers, but has not been investigated in prostate cancer. The aim of this study was to investigate if the CWP and NCWP, in combination with EMT, are associated with metabolic alterations, aggressive disease and biochemical recurrence in prostate cancer. An initial analysis was performed using integrated transcriptomics, ex vivo and in vivo metabolomics, and histopathology of prostatectomy samples (n=129), combined with at least five-year follow-up. This analysis detected increased activation of NCWP through Wnt5a/ Fzd2 as the most common mode of Wnt activation in prostate cancer. This activation was associated with increased expression of EMT markers and higher Gleason score. The transcriptional association between NCWP and EMT was confirmed in five other publicly available patient cohorts (1519 samples in total). A novel gene expression signature of concordant activation of NCWP and EMT (NCWP-EMT) was developed, and this signature was significantly associated with metastasis and shown to be a significant predictor of biochemical recurrence. The NCWP-EMT signature was also associated with decreased concentrations of the metabolites citrate and spermine, which have previously been linked to aggressive prostate cancer. Our results demonstrate the importance of NCWP and EMT in prostate cancer aggressiveness, suggest a novel gene signature for improved risk stratification, and give new molecular insight.
PMID: 28030815 [PubMed - as supplied by publisher]