PubMed

Targeted lipidomics reveals activation of resolution pathways in knee osteoarthritis in humans. Osteoarthritis Cartilage. 2017 Feb 08;: Authors: Jónasdóttir HS, Brouwers H, Kwekkeboom JC, van der Linden EM, Huizinga T, Kloppenburg M, Toes RE, Giera M, Ioan-Facsinay A Abstract OBJECTIVE: To investigate the presence of inflammation and resolution pathways in osteoarthritis (OA). DESIGN: Tissues were obtained from knee OA patients and control rheumatoid arthritis (RA) patients. Cells in synovial fluid (SF) were visualized by flow cytometry. Cytokines and chemokines were measured by multiplex assay. Lipid mediators (LMs) were determined by targeted lipidomics using liquid-chromatography mass spectrometry. RESULTS: SF of OA patients contained less cells, especially neutrophils, less cytokines and comparable levels of chemokines compared to RA controls. Thirty-seven lipids were detected in the soluble fraction of SF, including polyunsaturated fatty acids (PUFAs) and their pro-inflammatory and pro-resolving lipoxygenase (LOX) and cyclooxygenase (COX) pathway markers in both OA and RA patients. Among these, pro-inflammatory LM such as prostaglandin E2 and thromboxane B2, as well as precursors and pathway markers of resolution such as 17-HDHA and 18-HEPE were detected. Interestingly, the pro-resolving lipid RvD2 could also be detected, but only in the insoluble fraction (cells and undigested matrix). Ratios of metabolites to their precursors indicated a lower activity of 5-LOX and 15-LOX in OA compared to RA, with no apparent differences in COX-derived products. Interestingly, synovial tissue and SF cells could produce 5-LOX and 15-LOX metabolites, indicating these cells as possible source of LM. CONCLUSIONS: By using a state-of-the-art technique, we show for the first time that resolution pathways are present in OA patients. A better understanding of these pathways could guide us to more effective therapeutic approaches to inhibit inflammation and further structural damage in OA and RA. PMID: 28189826 [PubMed - as supplied by publisher]

Image-based cell quality evaluation to detect irregularities under same culture process of human induced pluripotent stem cells. J Biosci Bioeng. 2017 Feb 08;: Authors: Nagasaka R, Gotou Y, Yoshida K, Kanie K, Shimizu K, Honda H, Kato R Abstract To meet the growing demand for human induced pluripotent stem cells (iPSCs) for various applications, technologies that enable the manufacturing of iPSCs on a large scale should be developed. There are several technological challenges in iPSC manufacturing technology. Image-based cell quality evaluation technology for monitoring iPSC quality in culture enables the manufacture of intact cells for further applications. Although several studies have reported the effectiveness of image-based evaluation of iPSCs, it remains challenging to detect irregularities that may arise using the same processing operations during quality evaluation of automated processing. In this study, we investigated the evaluation performance of image-based cell quality analysis in detecting small differences that can result from human measurement, even when the same protocol is followed. To imitate such culture conditions, by image-analysis guided colony pickup, we changed the proportions of morphologically different subpopulations: "good morphology, regular morphology correlated with undifferentiation marker expression" and "bad morphology, irregular morphology correlated with loss of undifferentiation marker expression". In addition, comprehensive gene-expression and metabolomics analyses were carried out for the same samples to investigate performance differences. Our data shows an example of investigating the usefulness and sensitivity of quality evaluation methods for iPSC quality monitoring. PMID: 28189491 [PubMed - as supplied by publisher]

Altered expression of TRAIL on mouse T cells via ERK phosphorylation by Rhodiola rosea L. and its marker compounds. Food Chem Toxicol. 2017 Feb 08;: Authors: Marchev AS, Dimitrova P, Koycheva IK, Georgiev MI Abstract Rhodiola rosea L. extracts have shown neuroprotective, anti-fatigue, anti-inflammatory and anti-tumor properties. However, the studies on their effect on T cell function are rather scarce. We examined the potential of R. rosea extract and its major constituents - salidroside, rosarin, rosavin and rosin to alter cell growth of human Jurkat T cells, apoptosis of splenic mouse CD3 T cells and expression of the surface markers and phosphorylation of extracellular signal-regulated kinase (ERK). The initial screening for cell viability in Jurkat T cells and for apoptosis of mouse T cells showed the strongest activity for rosavin and rosarin. Rosarin and rosavin did not alter significantly the dynamic of CD69 expression upon stimulation, but altered TNF-related apoptosis-inducing ligand (TRAIL) expression. Rosavin inhibited TRAIL up-regulation, while rosarin showed an opposite effect. Indeed, rosarin increased the frequencies of CD3(+)TRAIL(+) T cells and the fold inhibition of ERK phosphorylation. Our data showed that different effects of rosarin and rosavin on TRAIL expression can involve distinct action on ERK signaling and hence highlighted their potential to manipulate TRAIL as a tool to rescue the resistance to apoptosis in autoimmune diseases and cancer. PMID: 28189478 [PubMed - as supplied by publisher]

Metabolomics in Alzheimer's disease: The need of complementary analytical platforms for the identification of biomarkers to unravel the underlying pathology. J Chromatogr B Analyt Technol Biomed Life Sci. 2017 Feb 06;: Authors: González-Domínguez R, Sayago A, Fernández-Recamales Á Abstract Alzheimer's disease is a complex neurodegenerative disorder characterized by a multi-factorial etiology, not completely understood to date. In this context, the application of metabolomics is emerging in the last years because of its potential to monitor molecular alterations associated with disease pathogenesis and progression, as well as to discover candidate diagnostic biomarkers. However, the huge heterogeneity and dynamism of the human metabolome makes impossible the simultaneous determination of the entire set of metabolites from complex biological samples. Thus, the most common strategy to get a comprehensive overview of the organism's phenotypic expression is the combined use of complementary metabolomic platforms. In this review, we summarize the advantages and limitations of the most important analytical techniques usually employed in metabolomics, including nuclear magnetic resonance, direct infusion mass spectrometry and hyphenated approaches based on the coupling of orthogonal separation mechanisms (i.e. liquid chromatography, gas chromatography, capillary electrophoresis) with mass spectrometry. Moreover, the suitability of metabolomics to unravel the complex pathology underlying to Alzheimer's disease is also presented. PMID: 28189423 [PubMed - as supplied by publisher]

20 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2017/02/12PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Related Articles Copper-induced metabolic variation of oysters overwhelmed by salinity effects. Chemosphere. 2017 Feb 01;174:331-341 Authors: Cao C, Wang WX Abstract In estuarine environments, Cu (copper) contamination is simultaneously coupled with salinity variation. In this study, (1)H NMR was applied to investigate the metabolic disturbance of estuarine oysters Crassostrea hongkongensis under both Cu and salinity stresses. Oysters were exposed to dissolved Cu (50 μg L(-1)) at different salinities (10, 15 and 25 psu) for six weeks, and the Cu accumulation in the oyster tissues was higher at lowered salinity. Based on the NMR-metabolomics results, disturbances induced by Cu and salinity was mainly related to osmotic regulation, energy metabolism and glycerophospholipid metabolism, as indicated by the alteration of important metabolic biomarkers such as alanine, citrate, glucose, glycogen, betaine, taurine, hypotaurine and homarine in the gills. At lower salinity, oysters accumulated higher energy related compounds (e.g., glucose and glycogen) and amino acids (e.g., aspartate, dimethylglycine and lysine), with the enhancement of ATP/ADP production and accumulation of oxidizable amino acids catabolized from protein breakdown. With Cu exposure, the synthesis from glycine to dimethylglycine was observed to cope with severe osmotic stress, together with the elevation of lysine and homarine. The effects induced by Cu were much similar for each salinity treatment, but the combination of Cu and salinity turned out to be consistent with the singular salinity effects. Therefore, salinity played a dominant role in affecting the metabolites of oysters when combined with Cu exposure. This study indicated that salinity should be taken into consideration in order to predict the Cu toxicity in estuarine organisms. PMID: 28183059 [PubMed - as supplied by publisher]

Related Articles Metabolomic study on the antihypertensive effect of S-1-propenylcysteine in spontaneously hypertensive rats using liquid chromatography coupled with quadrupole-Orbitrap mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci. 2017 Jan 30;1046:147-155 Authors: Matsutomo T, Ushijima M, Kodera Y, Nakamoto M, Takashima M, Morihara N, Tamura K Abstract Aged garlic extract (AGE) has been shown to improve hypertension in both clinical trials and experimental animal models. However, the active ingredient of AGE remains unknown. In the present study, we investigated the antihypertensive effects of AGE and its major constituents including S-1-propenylcysteine (S1PC) and S-allylcysteine (SAC) using spontaneously hypertensive rats (SHR) and found that S1PC is an active substance to lower blood pressure in SHR. In addition, the metabolomics approach was used to investigate the potential mechanism of the antihypertensive action of S1PC in SHR. Treatment with AGE (2g/kg body weight) or S1PC (6.5mg/kg body weight; equivalent to AGE 2g/kg body weight) significantly decreased the systolic blood pressure (SBP) of SHR after the repeated administration for 10 weeks, whereas treatment with SAC (7.9mg/kg body weight; equivalent to AGE 2g/kg body weight) did not decrease the SBP. After the treatment for 10 weeks, the plasma samples obtained from Wistar Kyoto (WKY) rats and SHR were analyzed by means of ultra high performance liquid chromatography coupled with high-resolution quadrupole-Orbitrap mass spectrometry. Multivariate statistical analysis of LC-MS data showed a clear difference in the metabolite profiles between WKY rats and SHR. The results indicated that 30 endogenous metabolites significantly contributed to the difference and 7 of 30 metabolites were changed by the S1PC treatment. Furthermore, regression analysis showed correlation between SBP and the plasma levels of betaine, tryptophan and 3 LysoPCs. This metabolomics approach suggested that S1PC could exert its antihypertensive effect by affecting glycine, serine and threonine metabolism, tryptophan metabolism and glycerophospholipid metabolism. PMID: 28183044 [PubMed - as supplied by publisher]

Related Articles Mass Spectrometric Analysis of Non-canonical Cyclic Nucleotides. Handb Exp Pharmacol. 2017 Feb 09;: Authors: Bähre H, Kaever V Abstract Contemporary investigations regarding the (patho)physiological roles of the non-canonical cyclic nucleoside monophosphates (cNMP) cytidine 3',5'-cyclic monophosphate (cCMP) and uridine 3',5'-cyclic monophosphate (cUMP) have been hampered by the lack of highly specific and sensitive analytic methods for these analytes. In addition, the existence of 2',3'-cNMP besides 3',5'-cNMP has been described recently. HPLC coupled with tandem mass spectrometry (HPLC-MS/MS) is the method of choice for identification and quantification of low-molecular weight endogenous metabolites. In this chapter, recommendations for an HPLC-MS/MS method for 3',5'- and 2',3'-cNMP are summarized. PMID: 28181004 [PubMed - as supplied by publisher]

Related Articles Metabolomic signatures associated with disease severity in multiple sclerosis. Neurol Neuroimmunol Neuroinflamm. 2017 Mar;4(2):e321 Authors: Villoslada P, Alonso C, Agirrezabal I, Kotelnikova E, Zubizarreta I, Pulido-Valdeolivas I, Saiz A, Comabella M, Montalban X, Villar L, Alvarez-Cermeño JC, Fernández O, Alvarez-Lafuente R, Arroyo R, Castro A Abstract OBJECTIVE: To identify differences in the metabolomic profile in the serum of patients with multiple sclerosis (MS) compared to controls and to identify biomarkers of disease severity. METHODS: We studied 2 cohorts of patients with MS: a retrospective longitudinal cohort of 238 patients and 74 controls and a prospective cohort of 61 patients and 41 controls with serial serum samples. Patients were stratified into active or stable disease based on 2 years of prospective assessment accounting for presence of clinical relapses or changes in disability measured with the Expanded Disability Status Scale (EDSS). Metabolomic profiling (lipids and amino acids) was performed by ultra-high-performance liquid chromatography coupled to mass spectrometry in serum samples. Data analysis was performed using parametric methods, principal component analysis, and partial least square discriminant analysis for assessing the differences between cases and controls and for subgroups based on disease severity. RESULTS: We identified metabolomics signatures with high accuracy for classifying patients vs controls as well as for classifying patients with medium to high disability (EDSS >3.0). Among them, sphingomyelin and lysophosphatidylethanolamine were the metabolites that showed a more robust pattern in the time series analysis for discriminating between patients and controls. Moreover, levels of hydrocortisone, glutamic acid, tryptophan, eicosapentaenoic acid, 13S-hydroxyoctadecadienoic acid, lysophosphatidylcholines, and lysophosphatidylethanolamines were associated with more severe disease (non-relapse-free or increase in EDSS). CONCLUSIONS: We identified metabolomic signatures composed of hormones, lipids, and amino acids associated with MS and with a more severe course. PMID: 28180139 [PubMed - in process]

Related Articles Investigations in the possibility of early detection of colorectal cancer by gas chromatography/triple-quadrupole mass spectrometry. Oncotarget. 2017 Feb 04;: Authors: Nishiumi S, Kobayashi T, Kawana S, Unno Y, Sakai T, Okamoto K, Yamada Y, Sudo K, Yamaji T, Saito Y, Kanemitsu Y, Okita NT, Saito H, Tsugane S, Azuma T, Ojima N, Yoshida M Abstract In developed countries, the number of patients with colorectal cancer has been increasing, and colorectal cancer is one of the most common causes of cancer death. To improve the quality of life of colorectal cancer patients, it is necessary to establish novel screening methods that would allow early detection of colorectal cancer. We performed metabolome analysis of a plasma sample set from 282 stage 0/I/II colorectal cancer patients and 291 healthy volunteers using gas chromatography/triple-quadrupole mass spectrometry in an attempt to identify metabolite biomarkers of stage 0/I/II colorectal cancer. The colorectal cancer patients included patients with stage 0 (N=79), I (N=80), and II (N=123) in whom invasion and metastasis were absent. Our analytical system detected 64 metabolites in the plasma samples, and the levels of 29 metabolites differed significantly (Bonferroni-corrected p=0.000781) between the patients and healthy volunteers. Based on these results, a multiple logistic regression analysis of various metabolite biomarkers was carried out, and a stage 0/I/II colorectal cancer prediction model was established. The area under the curve, sensitivity, and specificity values of this model for detecting stage 0/I/II colorectal cancer were 0.996, 99.3%, and 93.8%, respectively. The model's sensitivity and specificity values for each disease stage were >90%, and surprisingly, its sensitivity for stage 0, specificity for stage 0, and sensitivity for stage II disease were all 100%. Our predictive model can aid early detection of colorectal cancer and has potential as a novel screening test for cases of colorectal cancer that do not involve lymph node or distant metastasis. PMID: 28179577 [PubMed - as supplied by publisher]

Related Articles Increases in Plasma Tryptophan Are Inversely Associated with Incident Cardiovascular Disease in the Prevención con Dieta Mediterránea (PREDIMED) Study. J Nutr. 2017 Feb 08;: Authors: Yu E, Ruiz-Canela M, Guasch-Ferré M, Zheng Y, Toledo E, Clish CB, Salas-Salvadó J, Liang L, Wang DD, Corella D, Fitó M, Gómez-Gracia E, Lapetra J, Estruch R, Ros E, Cofán M, Arós F, Romaguera D, Serra-Majem L, Sorlí JV, Hu FB, Martinez-Gonzalez MA Abstract Background: During development of cardiovascular disease (CVD), interferon-γ-mediated inflammation accelerates degradation of tryptophan into downstream metabolites. A Mediterranean diet (MedDiet) consisting of a high intake of extra-virgin olive oil (EVOO), nuts, fruits, vegetables, and cereals has been demonstrated to lower the risk of CVD. The longitudinal relation between tryptophan and its downstream metabolites and CVD in the context of a MedDiet is unstudied.Objective: We sought to investigate the relation between metabolites in the tryptophan-kynurenine pathway and CVD in the context of a MedDiet pattern.Methods: We used a case-cohort design nested in the Prevención con Dieta Mediterránea randomized controlled trial. There were 231 CVD cases (stroke, myocardial infarction, cardiovascular death) among 985 participants over a median of 4.7 y of follow-up [mean ± SD age: 67.6 ± 6.1 y; 53.7% women; mean ± SD body mass index (in kg/m(2)): 29.7 ± 3.7]. We assessed plasma tryptophan, kynurenine, kynurenic acid, 3-hydroxyanthranilic acid, and quinolinic acid concentrations at baseline and after 1 y of intervention with a MedDiet. We combined these metabolites in a kynurenine risk score (KRS) by weighting each metabolite by the adjusted coefficient of its associations with CVD. Cox models were used in the primary analysis.Results: Increases in tryptophan after 1 y were associated with a lower risk of composite CVD (HR per SD: 0.79; 95% CI: 0.63, 0.98). The baseline kynurenic acid concentration was associated with a higher risk of myocardial infarction and coronary artery disease death but not stroke. A higher KRS was more strongly associated with CVD in the control group than in the 2 intervention groups (P-interaction = 0.003). Adjustment for changes in plasma tryptophan attenuated the inverse association between MedDiet+EVOO and CVD.Conclusions: An increase in the plasma tryptophan concentration was significantly associated with a decreased risk of CVD. A MedDiet may counteract the deleterious effects of a high tryptophan risk score. PMID: 28179491 [PubMed - as supplied by publisher]

Related Articles Plasma Metabolites and Risk of Radiation-induced Esophagitis: A Secondary Analysis from a Prospective Study. Anticancer Res. 2017 02;37(2):719-725 Authors: Tandberg DJ, Holt T, Kelsey CR Abstract AIM: Metabolic profiling was performed on plasma samples obtained prior to and during radiation therapy (RT) for locally advanced lung cancer to identify metabolites predictive of RT-induced esophagitis. PATIENTS AND METHODS: Patients received cisplatin/etoposide with RT as part of a prospective dose-escalation study (n=24). Plasma samples were collected at baseline, weeks 2 and 5 during RT, and 6 weeks post-RT. Metabolites were measured by ultrahigh-performance liquid chromatography-tandem mass spectroscopy at each time-point. Metabolite concentrations were compared between patients developing grade 0-1 and those with grade 2 or more esophagitis. RESULTS: At baseline, 23 metabolites differed significantly (p<0.05) between patients with grade 0-1 esophagitis and those with grade 2 or esophagitis. Sixty-seven metabolites were different at week 2. None reached statistical significance (q<0.05) after corrections for multiple comparisons. On random forest modeling, the predictive accuracy of the metabolite data was 33% at baseline and 50% at 2 weeks. CONCLUSION: No individual metabolite or group of metabolites was predictive of acute RT-induced esophagitis. PMID: 28179322 [PubMed - in process]

Related Articles Identification of polyvalent protective immunogens from outer membrane proteins in Vibrio parahaemolyticus to protect fish against bacterial infection. Fish Shellfish Immunol. 2016 Jul;54:204-10 Authors: Peng B, Ye JZ, Han Y, Zeng L, Zhang JY, Li H Abstract Vaccination is one of the most effective and economic way to prevent infectious diseases in aquaculture. The development of effective vaccines, however, is still limited, especially for polyvalent vaccines, which are against multiple species. With this regard, identification of polyvalent protective immunogens, serving as polyvalent vaccines, became a key step in vaccine development. In the current study, 17 outer membrane proteins from Vibrio parahaemolyticus were identified as immunogens. Further, four of the 17 proteins including VP2309, VP0887, VPA0548 and VP1019 were characterized as efficiently protective immunogens against V. parahaemolyticus' infection through passive and active immunizations in zebrafish. Importantly, these four proteins showed cross-protective capability against infections by Aeromonas hydrophila or/and Pseudomonas fluorescens, which shared similar epitopes with V. parahaemolyticus in homology of these proteins. Further investigation showed that the expression level of the four protective immunogens elevated in response to fish plasma in a dose-dependent manner. These results indicate that the four protective immunogens are polyvalent vaccine candidates in aquaculture. PMID: 27071519 [PubMed - indexed for MEDLINE]

31 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2017/02/09PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Related Articles Urine and Serum Metabolomics Analyses May Distinguish between Stages of Renal Cell Carcinoma. Metabolites. 2017 Feb 03;7(1): Authors: Falegan OS, Ball MW, Shaykhutdinov RA, Pieroraio PM, Farshidfar F, Vogel HJ, Allaf ME, Hyndman ME Abstract Renal cell carcinoma (RCC) is a heterogeneous disease that is usually asymptomatic until late in the disease. There is an urgent need for RCC specific biomarkers that may be exploited clinically for diagnostic and prognostic purposes. Preoperative fasting urine and serum samples were collected from patients with clinical renal masses and assessed with ¹H NMR and GCMS (gas chromatography-mass spectrometry) based metabolomics and multivariate statistical analysis. Alterations in levels of glycolytic and tricarboxylic acid (TCA) cycle intermediates were detected in RCC relative to benign masses. Orthogonal Partial Least Square Discriminant Analysis plots discriminated between benign vs. pT1 (R2 = 0.46, Q2 = 0.28; AUC = 0.83), benign vs. pT3 (R2 = 0.58, Q2 = 0.37; AUC = 0.87) for ¹H NMR-analyzed serum and between benign vs. pT1 (R2 = 0.50, Q2 = 0.37; AUC = 0.83), benign vs. pT3 (R2 = 0.72, Q2 = 0.68, AUC = 0.98) for urine samples. Separation was observed between benign vs. pT3 (R2 = 0.63, Q2 = 0.48; AUC = 0.93), pT1 vs. pT3 (R2 = 0.70, Q2 = 0.54) for GCMS-analyzed serum and between benign vs. pT3 (R2Y = 0.87; Q2 = 0.70; AUC = 0.98) for urine samples. This pilot study suggests that urine and serum metabolomics may be useful in differentiating benign renal tumors from RCC and for staging RCC. PMID: 28165361 [PubMed - in process]

Related Articles Human embryonic and induced pluripotent stem cells maintain phenotype but alter their metabolism after exposure to ROCK inhibitor. Sci Rep. 2017 Feb 06;7:42138 Authors: Vernardis SI, Terzoudis K, Panoskaltsis N, Mantalaris A Abstract Human pluripotent stem cells (hPSCs) are adhesion-dependent cells that require cultivation in colonies to maintain growth and pluripotency. Robust differentiation protocols necessitate single cell cultures that are achieved by use of ROCK (Rho kinase) inhibitors. ROCK inhibition enables maintenance of stem cell phenotype; its effects on metabolism are unknown. hPSCs were exposed to 10 μM ROCK inhibitor for varying exposure times. Pluripotency (TRA-1-81, SSEA3, OCT4, NANOG, SOX2) remained unaffected, until after prolonged exposure (96 hrs). Gas chromatography-mass spectrometry metabolomics analysis identified differences between ROCK-treated and untreated cells as early as 12 hrs. Exposure for 48 hours resulted in reduction in glycolysis, glutaminolysis, the citric acid (TCA) cycle as well as the amino acids pools, suggesting the adaptation of the cells to the new culture conditions, which was also reflected by the expression of the metabolic regulators, mTORC1 and tp53 and correlated with cellular proliferation status. While gene expression and protein levels did not reveal any changes in the physiology of the cells, metabolomics revealed the fluctuating state of the metabolism. The above highlight the usefulness of metabolomics in providing accurate and sensitive information on cellular physiological status, which could lead to the development of robust and optimal stem cell bioprocesses. PMID: 28165055 [PubMed - in process]

Related Articles Novel Approach to Classify Plants Based on Metabolite-Content Similarity. Biomed Res Int. 2017;2017:5296729 Authors: Liu K, Abdullah AA, Huang M, Nishioka T, Altaf-Ul-Amin M, Kanaya S Abstract Secondary metabolites are bioactive substances with diverse chemical structures. Depending on the ecological environment within which they are living, higher plants use different combinations of secondary metabolites for adaptation (e.g., defense against attacks by herbivores or pathogenic microbes). This suggests that the similarity in metabolite content is applicable to assess phylogenic similarity of higher plants. However, such a chemical taxonomic approach has limitations of incomplete metabolomics data. We propose an approach for successfully classifying 216 plants based on their known incomplete metabolite content. Structurally similar metabolites have been clustered using the network clustering algorithm DPClus. Plants have been represented as binary vectors, implying relations with structurally similar metabolite groups, and classified using Ward's method of hierarchical clustering. Despite incomplete data, the resulting plant clusters are consistent with the known evolutional relations of plants. This finding reveals the significance of metabolite content as a taxonomic marker. We also discuss the predictive power of metabolite content in exploring nutritional and medicinal properties in plants. As a byproduct of our analysis, we could predict some currently unknown species-metabolite relations. PMID: 28164123 [PubMed - in process]

Related Articles Mitochondrial mutations and metabolic adaptation in pancreatic cancer. Cancer Metab. 2017;5:2 Authors: Hardie RA, van Dam E, Cowley M, Han TL, Balaban S, Pajic M, Pinese M, Iconomou M, Shearer RF, McKenna J, Miller D, Waddell N, Pearson JV, Grimmond SM, Australian Pancreatic Cancer Genome Initiative, Sazanov L, Biankin AV, Villas-Boas S, Hoy AJ, Turner N, Saunders DN Abstract BACKGROUND: Pancreatic cancer has a five-year survival rate of ~8%, with characteristic molecular heterogeneity and restricted treatment options. Targeting metabolism has emerged as a potentially effective therapeutic strategy for cancers such as pancreatic cancer, which are driven by genetic alterations that are not tractable drug targets. Although somatic mitochondrial genome (mtDNA) mutations have been observed in various tumors types, understanding of metabolic genotype-phenotype relationships is limited. METHODS: We deployed an integrated approach combining genomics, metabolomics, and phenotypic analysis on a unique cohort of patient-derived pancreatic cancer cell lines (PDCLs). Genome analysis was performed via targeted sequencing of the mitochondrial genome (mtDNA) and nuclear genes encoding mitochondrial components and metabolic genes. Phenotypic characterization of PDCLs included measurement of cellular oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) using a Seahorse XF extracellular flux analyser, targeted metabolomics and pathway profiling, and radiolabelled glutamine tracing. RESULTS: We identified 24 somatic mutations in the mtDNA of 12 patient-derived pancreatic cancer cell lines (PDCLs). A further 18 mutations were identified in a targeted study of ~1000 nuclear genes important for mitochondrial function and metabolism. Comparison with reference datasets indicated a strong selection bias for non-synonymous mutants with predicted functional effects. Phenotypic analysis showed metabolic changes consistent with mitochondrial dysfunction, including reduced oxygen consumption and increased glycolysis. Metabolomics and radiolabeled substrate tracing indicated the initiation of reductive glutamine metabolism and lipid synthesis in tumours. CONCLUSIONS: The heterogeneous genomic landscape of pancreatic tumours may converge on a common metabolic phenotype, with individual tumours adapting to increased anabolic demands via different genetic mechanisms. Targeting resulting metabolic phenotypes may be a productive therapeutic strategy. PMID: 28163917 [PubMed]

Related Articles Probing the metabolic phenotype of breast cancer cells by multiple tracer Stable Isotope Resolved Metabolomics. Metab Eng. 2017 Feb 02;: Authors: Lane AN, Tan J, Wang Y, Yan J, Higashi RM, Fan TW Abstract Breast cancers vary by their origin and specific set of genetic lesions, which gives rise to distinct phenotypes and differential response to targeted and untargeted chemotherapies. To explore the functional differences of different breast cell types, we performed Stable Isotope Resolved Metabolomics (SIRM) studies of one primary breast (HMEC) and three breast cancer cells (MCF-7, MDAMB-231, and ZR75-1) having distinct genotypes and growth characteristics, using (13)C6-glucose, (13)C-1+2-glucose, (13)C5,(15)N2-Gln, (13)C3-glycerol, and (13)C8-octanoate as tracers. These tracers were designed to probe the central energy producing and anabolic pathways (glycolysis, pentose phosphate pathway, Krebs Cycle, glutaminolysis, nucleotide synthesis and lipid turnover). We found that glycolysis was not associated with the rate of breast cancer cell proliferation, glutaminolysis did not support lipid synthesis in primary breast or breast cancer cells, but was a major contributor to pyrimidine ring synthesis in all cell types; anaplerotic pyruvate carboxylation was activated in breast cancer versus primary cells. We also found that glucose metabolism in individual breast cancer cell lines differed between in vitro cultures and tumor xenografts, but not the metabolic distinctions between cell lines, which may reflect the influence of tumor architecture/microenvironment. PMID: 28163219 [PubMed - as supplied by publisher]

Related Articles Metabolomics analysis of serum from subjects after occupational exposure to acrylamide using UPLC-MS. Mol Cell Endocrinol. 2017 Feb 02;: Authors: Wang SY, Yu CP, Pan YL, Zhou XR, Xin R, Wang Y, Ma WW, Gao R, Wang C, Wu YH Abstract Since occupational exposure to acrylamide (ACR) may cause nerve damage, sensitive biomarkers to evaluate the early effects of ACR on human health are needed. In the present study, we have compared a group of individuals with occupational exposure to ACR (contact group, n = 65) with a group of individuals with no exposure (non-contact group, n = 60). Serum metabolomics analysis of the contact and non-contact groups was carried out using ultra performance liquid chromatograph/time of flight mass spectrometry, combined with multivariate analysis, to identify potential metabolites. Serum biochemical indexes of the contact and non-contact groups were also determined using an automatic biochemistry analyzer. There was a clear separation between the contact group and the non-contact group; receiver operator characteristic curve analysis suggested that phytosphingosine, 4E,15Z-bilirubin IXa and tryptophan were the best metabolites to use as biomarkers. Liver function was also found to be abnormal in the contact group. Important, ACR-related, metabolic changes were seen in the contact group and new biomarkers for assessing the toxicity of ACR on the central nervous system have been proposed. This study will provide a sound basis for exploring the toxic mechanisms and metabolic pathways of ACR. PMID: 28163100 [PubMed - as supplied by publisher]