PubMed

Related Articles Metabolism, Metabolomics, and Inflammation in Posttraumatic Stress Disorder. Biol Psychiatry. 2018 Feb 22;: Authors: Mellon SH, Gautam A, Hammamieh R, Jett M, Wolkowitz OM Abstract Posttraumatic stress disorder (PTSD) is defined by classic psychological manifestations, although among the characteristics are significantly increased rates of serious somatic comorbidities, such as cardiovascular disease, immune dysfunction, and metabolic syndrome. In this review, we assess the evidence for disturbances that may contribute to somatic pathology in inflammation, metabolic syndrome, and circulating metabolites (implicating mitochondrial dysfunction) in individuals with PTSD and in animal models simulating features of PTSD. The clinical and preclinical data highlight probable interrelated features of PTSD pathophysiology, including a proinflammatory milieu, metabolomic changes (implicating mitochondrial and other processes), and metabolic dysregulation. These data suggest that PTSD may be a systemic illness, or that it at least has systemic manifestations, and the behavioral manifestations are those most easily discerned. Whether somatic pathology precedes the development of PTSD (and thus may be a risk factor) or follows the development of PTSD (as a result of either shared pathophysiologies or lifestyle adaptations), comorbid PTSD and somatic illness is a potent combination placing affected individuals at increased physical as well as mental health risk. We conclude with directions for future research and novel treatment approaches based on these abnormalities. PMID: 29628193 [PubMed - as supplied by publisher]

Related Articles Rewiring carbohydrate catabolism differentially affects survival of pancreatic cancer cell lines with diverse metabolic profiles. Oncotarget. 2017 Jun 20;8(25):41265-41281 Authors: Tataranni T, Agriesti F, Ruggieri V, Mazzoccoli C, Simeon V, Laurenzana I, Scrima R, Pazienza V, Capitanio N, Piccoli C Abstract An increasing body of evidence suggests that targeting cellular metabolism represents a promising effective approach to treat pancreatic cancer, overcome chemoresistance and ameliorate patient's prognosis and survival. In this study, following whole-genome expression analysis, we selected two pancreatic cancer cell lines, PANC-1 and BXPC-3, hallmarked by distinct metabolic profiles with specific concern to carbohydrate metabolism. Functional comparative analysis showed that BXPC-3 displayed a marked deficit of the mitochondrial respiratory and oxidative phosphorylation activity and a higher production of reactive oxygen species and a reduced NAD+/NADH ratio, indicating their bioenergetic reliance on glycolysis and a different redox homeostasis as compared to PANC-1. Both cell lines were challenged to rewire their metabolism by substituting glucose with galactose as carbon source, a condition inhibiting the glycolytic flux and fostering full oxidation of the sugar carbons. The obtained data strikingly show that the mitochondrial respiration-impaired-BXPC-3 cell line was unable to sustain the metabolic adaptation required by glucose deprivation/substitution, thereby resulting in a G2\M cell cycle shift, unbalance of the redox homeostasis, apoptosis induction. Conversely, the mitochondrial respiration-competent-PANC-1 cell line did not show clear evidence of cell sufferance. Our findings provide a strong rationale to candidate metabolism as a promising target for cancer therapy. Defining the metabolic features at time of pancreatic cancer diagnosis and likely of other tumors, appears to be crucial to predict the responsiveness to therapeutic approaches or coadjuvant interventions affecting metabolism. PMID: 28476035 [PubMed - indexed for MEDLINE]

Sorting cells alters their redox state and cellular metabolome. Redox Biol. 2018 Mar 09;16:381-387 Authors: Llufrio EM, Wang L, Naser FJ, Patti GJ Abstract A growing appreciation of the metabolic artifacts of cell culture has generated heightened enthusiasm for performing metabolomics on populations of cells purified from tissues and biofluids. Fluorescence activated cell sorting, or FACS, is a widely used experimental approach to purify specific cell types from complex heterogeneous samples. Here we show that FACS introduces oxidative stress and alters the metabolic state of cells. Compared to unsorted controls, astrocytes subjected to FACS prior to metabolomic analysis showed altered ratios of GSSG to GSH, NADPH to NADP+, and NAD+ to NADH. Additionally, a 50% increase in reactive oxygen species was observed in astrocytes subjected to FACS relative to unsorted controls. At a more comprehensive scale, nearly half of the metabolomic features that we profiled by liquid chromatography/mass spectrometry were changed by at least 1.5-fold in intensity due to cell sorting. Some specific metabolites identified to have significantly altered levels as a result of cell sorting included glycogen, nucleosides, amino acids, central carbon metabolites, and acylcarnitines. Although the addition of fetal bovine serum to the cell-sorting buffer decreased oxidative stress and attenuated changes in metabolite concentrations, fetal bovine serum did not preserve the metabolic state of the cells during FACS. We conclude that, irrespective of buffer components and data-normalization strategies we examined, metabolomic results from sorted cells do not accurately reflect physiological conditions prior to sorting. PMID: 29627745 [PubMed - as supplied by publisher]

Biomedical analysis of formalin-fixed, paraffin-embedded tissue samples: The Holy Grail for molecular diagnostics. J Pharm Biomed Anal. 2018 Apr 02;155:125-134 Authors: Donczo B, Guttman A Abstract More than a century ago in 1893, a revolutionary idea about fixing biological tissue specimens was introduced by Ferdinand Blum, a German physician. Since then, a plethora of fixation methods have been investigated and used. Formalin fixation with paraffin embedment became the most widely used types of fixation and preservation method, due to its proper architectural conservation of tissue structures and cellular shape. The huge collection of formalin-fixed, paraffin-embedded (FFPE) sample archives worldwide holds a large amount of unearthed information about diseases that could be the Holy Grail in contemporary biomarker research utilizing analytical omics based molecular diagnostics. The aim of this review is to critically evaluate the omics options for FFPE tissue sample analysis in the molecular diagnostics field. PMID: 29627729 [PubMed - as supplied by publisher]

The depressed central carbon and energy metabolisms is associated to the acquisition of levofloxacin resistance in Vibrio alginolyticus. J Proteomics. 2018 Apr 05;: Authors: Cheng ZX, Yang MJ, Peng B, Peng XX, Lin XM, Li H Abstract The overuse and misuse of antibiotics lead to bacterial antibiotic resistance, challenging human health and intensive cultivation. It is especially required to understand for the mechanism of antibiotic resistance to control antibiotic-resistant pathogens. The present study characterized the differential proteome of levofloxacin-resistant Vibrio alginolyticus with the most advanced iTRAQ quantitative proteomics technology. A total of 160 proteins of differential abundance were identified, where 70 were decreased and 90 were increased. Further analysis demonstrated that crucial metabolic pathways like TCA cycle were significantly down-regulated. qRT-PCR analysis demonstrated the decreased gene expression of glycolysis/gluconeogenesis, the TCA cycle, and fatty acid biosynthesis. Moreover, Na(+)-NQR complex gene expression, membrane potential and the adenylate energy charge ratio were decreased, indicating that the decreased central carbon metabolism is associated to the acquisition of levofloxacin resistance. Therefore, the reduced central carbon and energy metabolisms form a characteristic feature as fitness costs of V. alginolyticus in resistance to levofloxacin. BIOLOGICAL SIGNIFICANCE: The overuse and misuse of antibiotics lead to bacterial antibiotic resistance, challenging human health and intensive cultivation. Understanding for the antibiotic resistance mechanisms is especially required to control these antibiotic-resistant pathogens. The present study characterized the differential proteome of levofloxacin-resistant Vibrio alginolyticus using the most advanced iTRAQ quantitative proteomics technology. A total of 160 differential abundance of proteins were identified with 70 decreases and 90 increases by liquid chromatography matrix assisted laser desorption ionization mass spectrometry. Most interestingly, crucial metabolic pathways such as the TCA cycle sharply fluctuated. This is the first report that the reduced central carbon and energy metabolisms form a characteristic feature as a mechanism of V. alginolyticus in resistance to levofloxacin. PMID: 29627625 [PubMed - as supplied by publisher]

Evaluation of Bisphenol A influence on endocannabinoid system in pregnant women. Chemosphere. 2018 Mar 30;203:387-392 Authors: Zbucka-Kretowska M, Zbucki R, Parfieniuk E, Maslyk M, Lazarek U, Miltyk W, Czerniecki J, Wolczynski S, Kretowski A, Ciborowski M Abstract Bisphenol A (BPA) is a synthetic chemical widely used in the industry, which may potentially evoke negative effects on human health, especially on reproductive processes and fetal development. BPA has been reported to act on estrogen, estrogen-related, androgen, thyroid hormone, pregnane X, peroxisome proliferation-activated, and aryl hydrocarbon receptors. However, other potential mechanisms of BPA action on pregnancy cannot be excluded. Comprehensive evaluation of BPA effect on pregnant women can be performed by use of metabolomics. In the present study LC-MS-based plasma metabolomics was performed in the group of pregnant women with known concentrations of free, conjugated and total BPA. Significant positive correlations were observed between several endocannabinoids (fatty acid amides) and free (r = 0.307-0.557, p-value = 0.05-0.00002) and total (r = 0.413-0.519, p-value = 0.008-0.00006) BPA concentrations. Palmitoleamide was positively correlated with conjugated (r = 0.348, p-value = 0.05) while lysophosphatidylethanolamine 18:0 with free (r = 0.519, p-value = 0.00006) BPA concentration. The docking calculations of BPA and fatty acid amide hydrolase (enzyme degrading endocannabinoids, FAAH) indicated that it can act as a competitive inhibitor by blocking FAAH catalytic residues. In vitro study showed that BPA moderately inhibits FAAH activity (15% decrease for 200 ng mL-1 and almost 50% for 200 μg mL-1 of BPA). In the present study for the first time inhibitory potential of BPA on FAAH hydrolase is reported. Inhibition of FAAH may lead to a rise of plasma endocannabinoids level. BPA exposure and increased level of endocannabinoids are miscarriage risk factors. Based on obtained results it can be hypothesized that BPA may induce adverse pregnancy outcomes by acting on endocannabinoid system. PMID: 29627605 [PubMed - as supplied by publisher]

Lipidomic profiling of plasma samples from patients with mitochondrial disease. Biochem Biophys Res Commun. 2018 Apr 05;: Authors: Ren C, Liu J, Zhou J, Liang H, Zhu Y, Wang Q, Leng Y, Zhang Z, Yuan Y, Wang Z, Yin Y Abstract Mitochondrial disease (MD) is a rare mitochondrial respiratory chain disorder with a high mortality and extremely challenging to treat. Although genomic, transcriptomic, and proteomic analyses have been performed to investigate the pathogenesis of MD, the role of metabolomics in MD, particularly of lipidomics remains unclear. This study was undertaken to identify potential lipid biomarkers of MD. An untargeted lipidomic approach was used to compare the plasma lipid metabolites in 20 MD patients and 20 controls through Liquid Chromatography coupled to Mass Spectrometry. Volcano plot analysis was performed to identify the different metabolites. Receiver operating characteristic (ROC) curves were constructed and the area under the ROC curves (AUC) was calculated to determine the potentially sensitive and specific biomarkers. A total of 41 lipids were significantly different in MD patients and controls. ROC curve analysis showed the top 5 AUC values of lipids (phosphatidylinositols 38:6, lysoPC 20:0, 19:0, 18:0, 17:0) are more than 0.99. Multivariate ROC curve based exploratory analysis showed the AUC of combination of top 5 lipids is 1, indicating they may be potentially sensitive and specific biomarkers for MD. We propose combination of these lipid species may be more valuable in predicting the development and progression of MD, and this will have important implications for the diagnosis and treatment of MD. PMID: 29627572 [PubMed - as supplied by publisher]

Metabolite changes in risk of type 2 diabetes mellitus in cohort studies: A systematic review and meta-analysis. Diabetes Res Clin Pract. 2018 Apr 04;: Authors: Park JE, Lim H, Woo Kim J, Shin KH Abstract AIMS: Fasting plasma glucose, oral glucose tolerance test, and glycated hemoglobin are diagnostic markers for type 2 diabetes mellitus (T2DM). However, it is necessary to detect physiological changes in T2DM rapidly and stratify diabetic stage using other biomarkers. We performed a systematic review and meta-analysis to contribute to the development of objective and sensitive diagnostic indicators by integrating metabolite biomarkers derived from large-scale cohort studies. METHODS: We searched for metabolomics studies of T2DM cohort in PubMed, Scopus, and Web of Science for studies published within the last 10 years from January 2008 to February 2017. The concentrations of metabolites and odds ratios (ORs) were integrated and risk ratio (RR) values were estimated to distinguish subjects with T2DM and normal participants. RESULTS: Fourteen cohort studies were investigated in this meta-analysis. There were 4,592 patients in the case group and 11,492 participants in the control group. We noted a 1.89-, 1.63-, and 1.87-fold higher risk of T2DM associated with leucine (RR 1.89 [95% CI 1.57-2.29]), alanine (RR 1.63 [95% CI 1.48-1.79]), and oleic acid (RR 1.87 [95% CI 1.62-2.17]), respectively. Lysophosphatidylcholine C18:0 (RR 0.80 [95% CI 0.72-0.90]) and creatinine (RR 0.63 [95% CI 0.53-0.74]) were associated with 20% and 37% decreased T2DM risks, respectively. CONCLUSIONS: Most amino acids in patients were positively related to diabetes, while creatinine and some lysophosphatidylcholines showed a negative relationship. This suggests that diabetic risk prediction using metabolites that sensitively reflect changes in the body will improve individual diagnosis and personalize medicine. PMID: 29626587 [PubMed - as supplied by publisher]

Related Articles Discriminating gastric cancer and gastric ulcer using human plasma amino acid metabolic profile. IUBMB Life. 2018 Apr 06;: Authors: Jing F, Hu X, Cao Y, Xu M, Wang Y, Jing Y, Hu X, Gao Y, Zhu Z Abstract Patients with gastric ulcer (GU) have a significantly higher risk of developing gastric cancer (GC), especially within 2 years after diagnosis. The main way to improve the prognosis of GC is to predict the tumorigenesis and metastasis in the early stage. The objective of this study was to demonstrate the ability of human plasma amino acid metabolic profile for discriminating GC and GU. In this study, we first used liquid chromatography-tandem mass spectrometry technique to characterize the plasma amino acid metabolism in GC and GU patients. Plasma samples were collected from 84 GC patients and 82 GU patients, and 22 amino acids were detected in each patient. Partial least squares-discriminant analysis model was performed to analyze the data of these amino acids. We observed seven differential amino acids between GC and GU. A regression analysis model was established using these seven amino acids. Finally, a panel of five differential amino acids, including glutamine, ornithine, histidine, arginine and tryptophan, was identified for discriminating GC and GU with good specificity and sensitivity. The receiver operating characteristic curve was used to evaluate diagnostic ability of the regression model and area under the curve was 0.922. In conclusion, this study demonstrated the potential values of plasma amino acid metabolic profile and metabolomic analysis technique in assisting diagnosis of GC. More studies are needed to highlight the theoretical strengths of metabolomics to understand the potential metabolic mechanisms in GC. © 2018 IUBMB Life, 2018. PMID: 29626382 [PubMed - as supplied by publisher]

Related Articles Routine immunohistochemical staining in membranous nephropathy: in situ detection of phospholipase A2 receptor and thrombospondin type 1 containing 7A domain. J Nephrol. 2018 Apr 06;: Authors: L'Imperio V, Pieruzzi F, Sinico RA, Nebuloni M, Granata A, Smith A, Radice A, Pagni F Abstract BACKGROUND: Membranous nephropathy (MN) can be idiopathic (iMN) or manifest as a result of systemic underlying conditions as a secondary epiphenomenon. For the prognostic and predictive consequences of this discrimination, the routine use of reliable markers is crucial. This large MN series aimed to evaluate the routine and standardized immunohistochemical (IHC) employment of a panel of 3 biomarkers-phospholipase A2 receptor (PLA2R), thrombospondin type-1 domain-containing 7A (THSD7A), and immunoglobulin (Ig)G4-in the differential diagnosis of MN forms, contributing to the validation of the technique and the correct interpretation of reproducible patterns of reactivity. METHODS: We classified 95 patients with a biopsy proven diagnosis of MN as primary (n = 72) or secondary (n = 23) cases based on clinical data. After performing an IHC assay directed against PLA2R, THSD7A and IgG4 antigens, samples were interpreted by three different nephropathologists to assess the positivity/negativity of the staining according to new interpretation criteria. RESULTS: Useful interpretation criteria were introduced to exclude false positive patterns of reactivity and to identify only true granular membranous or mesangial deposits in MN. The IHC directed against PLA2R resulted positive in 51 iMN cases and negative in 21, while 4/23 secondary forms were considered positive. Based on these data the technique showed a sensitivity of 71% and specificity of 83%. On the other hand, the IHC analysis for IgG4 resulted positive in 44 cases of iMN and negative in 28 cases, while only 4/23 secondary forms were positive (same cases positive to PLA2R). Finally, THSD7A was found to be positive only in 1 case, which was negative to PLA2R and IgG4. The combination of the results allowed a classification of the series into two major groups: "double-positive" (PLA2R+/IgG4+/THSD7A-) and "triple-negative" (PLA2R-/IgG4-/THSD7A-) cases. CONCLUSIONS: Based on these data, the diagnostic performance of the three biomarkers used in a "tandem fashion" can reach 79% sensitivity and 83% specificity, significantly reducing the risk of a false-positive or false-negative result and improving the routine characterization of this frequent glomerulonephritis. PMID: 29626294 [PubMed - as supplied by publisher]

Related Articles Metabolomics insights into early type 2 diabetes pathogenesis and detection in individuals with normal fasting glucose. Diabetologia. 2018 Apr 06;: Authors: Merino J, Leong A, Liu CT, Porneala B, Walford GA, von Grotthuss M, Wang TJ, Flannick J, Dupuis J, Levy D, Gerszten RE, Florez JC, Meigs JB Abstract AIMS/HYPOTHESIS: Identifying the metabolite profile of individuals with normal fasting glucose (NFG [<5.55 mmol/l]) who progressed to type 2 diabetes may give novel insights into early type 2 diabetes disease interception and detection. METHODS: We conducted a population-based prospective study among 1150 Framingham Heart Study Offspring cohort participants, age 40-65 years, with NFG. Plasma metabolites were profiled by LC-MS/MS. Penalised regression models were used to select measured metabolites for type 2 diabetes incidence classification (training dataset) and to internally validate the discriminatory capability of selected metabolites beyond conventional type 2 diabetes risk factors (testing dataset). RESULTS: Over a follow-up period of 20 years, 95 individuals with NFG developed type 2 diabetes. Nineteen metabolites were selected repeatedly in the training dataset for type 2 diabetes incidence classification and were found to improve type 2 diabetes risk prediction beyond conventional type 2 diabetes risk factors (AUC was 0.81 for risk factors vs 0.90 for risk factors + metabolites, p = 1.1 × 10-4). Using pathway enrichment analysis, the nitrogen metabolism pathway, which includes three prioritised metabolites (glycine, taurine and phenylalanine), was significantly enriched for association with type 2 diabetes risk at the false discovery rate of 5% (p = 0.047). In adjusted Cox proportional hazard models, the type 2 diabetes risk per 1 SD increase in glycine, taurine and phenylalanine was 0.65 (95% CI 0.54, 0.78), 0.73 (95% CI 0.59, 0.9) and 1.35 (95% CI 1.11, 1.65), respectively. Mendelian randomisation demonstrated a similar relationship for type 2 diabetes risk per 1 SD genetically increased glycine (OR 0.89 [95% CI 0.8, 0.99]) and phenylalanine (OR 1.6 [95% CI 1.08, 2.4]). CONCLUSIONS/INTERPRETATION: In individuals with NFG, information from a discrete set of 19 metabolites improved prediction of type 2 diabetes beyond conventional risk factors. In addition, the nitrogen metabolism pathway and its components emerged as a potential effector of earliest stages of type 2 diabetes pathophysiology. PMID: 29626220 [PubMed - as supplied by publisher]

Related Articles Translational science in albuminuria: a new view of de novo albuminuria under chronic RAS suppression. Clin Sci (Lond). 2018 Apr 16;132(7):739-758 Authors: Baldan-Martin M, Rodríguez-Sánchez E, González-Calero L, Ruilope LM, Alvarez-Llamas G, Barderas MG, Ruiz-Hurtado G Abstract The development of de novo albuminuria during chronic renin-angiotensin system (RAS) suppression is a clinical entity that remains poorly recognized in the biomedical literature. It represents a clear increment in global cardiovascular (CV) and renal risk that cannot be counteracted by RAS suppression. Although not specifically considered, it is clear that this entity is present in most published and ongoing trials dealing with the different forms of CV and renal disease. In this review, we focus on the mechanisms promoting albuminuria, and the predictors and new markers of de novo albuminuria, as well as the potential treatment options to counteract the excretion of albumin. The increase in risk that accompanies de novo albuminuria supports the search for early markers and predictors that will allow practising physicians to assess and prevent the development of de novo albuminuria in their patients. PMID: 29626149 [PubMed - in process]

Related Articles Restoring mitochondrial calcium uniporter expression in diabetic mouse heart improves mitochondrial calcium handling and cardiac function. J Biol Chem. 2018 Apr 06;: Authors: Suarez J, Cividini F, Scott BT, Lehmann K, Diaz-Juarez J, Diemer T, Dai A, Suarez JA, Jain M, Dillmann WH Abstract Diabetes mellitus is a growing health care problem, resulting in significant cardiovascular morbidity and mortality. Diabetes also increases the risk for heart failure (HF) and decreased cardiac myocyte function, which are linked to changes in cardiac mitochondrial energy metabolism. The free mitochondrial calcium level ([Ca2+]m) is fundamental in activating the mitochondrial respiratory chain complexes and ATP production and is also known to regulate pyruvate dehydrogenase complex (PDC) activity. The mitochondrial calcium uniporter (MCU) complex (MCUC) plays a major role in mediating mitochondrial Ca2+ import, and its expression and function therefore have a marked impact on cardiac myocyte metabolism and function. Here, we investigated MCU's role in mitochondrial Ca2+ handling, mitochondrial function, glucose oxidation, and cardiac function in the heart of diabetic mice. We found that diabetic mouse hearts exhibit altered expression of MCU and MCUC members and a resulting decrease in [Ca2+]m, mitochondrial Ca2+ uptake, mitochondrial energetic function, and cardiac function. Adeno-associated virus-based normalization of MCU levels in these hearts restored mitochondrial Ca2+ handling, reduced PDC phosphorylation levels, and increased PDC activity. These changes were associated with cardiac metabolic reprogramming toward normal physiological glucose oxidation. This reprogramming likely contributed to the restoration of both cardiac myocyte and heart function to non-diabetic levels without any observed detrimental effects. These findings support the hypothesis that abnormal mitochondrial Ca2+ handling and its negative consequences can be ameliorated in diabetes by restoring MCU levels via adeno-associated virus-based MCU transgene expression. PMID: 29626093 [PubMed - as supplied by publisher]

Related Articles Development of a general method for quantifying IgG-based therapeutic monoclonal antibodies in human plasma using protein G purification coupled with a two internal standard calibration strategy using LC-MS/MS. Anal Chim Acta. 2018 Aug 17;1019:93-102 Authors: Chiu HH, Liao HW, Shao YY, Lu YS, Lin CH, Tsai IL, Kuo CH Abstract Monoclonal antibody (mAb) drugs have generated much interest in recent years for treating various diseases. Immunoglobulin G (IgG) represents a high percentage of mAb drugs that have been approved by the Food and Drug Administration (FDA). To facilitate therapeutic drug monitoring and pharmacokinetic/pharmacodynamic studies, we developed a general liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to quantify the concentration of IgG-based mAbs in human plasma. Three IgG-based drugs (bevacizumab, nivolumab and pembrolizumab) were selected to demonstrate our method. Protein G beads were used for sample pretreatment due to their universal ability to trap IgG-based drugs. Surrogate peptides that were obtained after trypsin digestion were quantified by using LC-MS/MS. To calibrate sample preparation errors and matrix effects that occur during LC-MS/MS analysis, we used two internal standards (IS) method that include the IgG-based drug-IS tocilizumab and post-column infused IS. Using two internal standards was found to effectively improve quantification accuracy, which was within 15% for all mAb drugs that were tested at three different concentrations. This general method was validated in term of its precision, accuracy, linearity and sensitivity for 3 demonstration mAb drugs. The successful application of the method to clinical samples demonstrated its' applicability in clinical analysis. It is anticipated that this general method could be applied to other mAb-based drugs for use in precision medicine and clinical studies. PMID: 29625688 [PubMed - in process]

Related Articles Evaluation of batch effect elimination using quality control replicates in LC-MS metabolite profiling. Anal Chim Acta. 2018 Aug 17;1019:38-48 Authors: Sánchez-Illana Á, Piñeiro-Ramos JD, Sanjuan-Herráez JD, Vento M, Quintás G, Kuligowski J Abstract Systematic variation of the instrument's response both within- and between-batches is frequently observed in untarget LC-MS metabolomics involving the analysis of a large number of samples. The so-called batch effect decreases the statistical power and has a negative impact on repeatability and reproducibility of the results. As there is no standard way of assessing or correcting LC-MS batch effects and there is no single method providing optimal results in all situations, the selection of the optimal approach is not trivial. This work explores the effectiveness of a set of tools for batch effect assessment. Qualitative tools include the monitoring of spiked internal standards, principal component analysis and hierarchical cluster analysis. Quantitative tools comprise the distribution of RSDQC values, the median Pearson correlation coefficient in QCs, the ratio of random features in QCs using the runs test, as well as multivariate tools such as the δ-statistic, Silhouette plots, Principal Variance Component Analysis and the expected technical variation in the prediction. Results show that qualitative and quantitative approaches are complementary and that by limiting the analysis to QCs the power to detect and evaluate both within and between batch effects is increased. Besides, the graphical integration of outputs from multiple quantitative tools facilitates the evaluation of batch effects and it is proposed as a straightforward way for comparing and tailoring batch effect elimination approaches. PMID: 29625683 [PubMed - in process]

Related Articles PepsNMR for 1H NMR metabolomic data pre-processing. Anal Chim Acta. 2018 Aug 17;1019:1-13 Authors: Martin M, Legat B, Leenders J, Vanwinsberghe J, Rousseau R, Boulanger B, Eilers PHC, De Tullio P, Govaerts B Abstract In the analysis of biological samples, control over experimental design and data acquisition procedures alone cannot ensure well-conditioned 1H NMR spectra with maximal information recovery for data analysis. A third major element affects the accuracy and robustness of results: the data pre-processing/pre-treatment for which not enough attention is usually devoted, in particular in metabolomic studies. The usual approach is to use proprietary software provided by the analytical instruments' manufacturers to conduct the entire pre-processing strategy. This widespread practice has a number of advantages such as a user-friendly interface with graphical facilities, but it involves non-negligible drawbacks: a lack of methodological information and automation, a dependency of subjective human choices, only standard processing possibilities and an absence of objective quality criteria to evaluate pre-processing quality. This paper introduces PepsNMR to meet these needs, an R package dedicated to the whole processing chain prior to multivariate data analysis, including, among other tools, solvent signal suppression, internal calibration, phase, baseline and misalignment corrections, bucketing and normalisation. Methodological aspects are discussed and the package is compared to the gold standard procedure with two metabolomic case studies. The use of PepsNMR on these data shows better information recovery and predictive power based on objective and quantitative quality criteria. Other key assets of the package are workflow processing speed, reproducibility, reporting and flexibility, graphical outputs and documented routines. PMID: 29625674 [PubMed - in process]

16 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 2018/04/07PubMed 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.

16 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 2018/04/06PubMed 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 Fermentation products in the cystic fibrosis airways induce aggregation and dormancy-associated expression profiles in a CF clinical isolate of Pseudomonas aeruginosa. FEMS Microbiol Lett. 2018 Mar 29;: Authors: Phan J, Gallagher T, Oliver A, England W, Whiteson K Abstract Pseudomonas aeruginosa is a well-known dominant opportunistic pathogen in cystic fibrosis (CF) with a wide range of metabolic capacities. However, P. aeruginosa does not colonize the airways alone, and benefits from the metabolic products of neighboring cells-especially volatile molecules that can travel between different parts of the airways easily. Here, we present a study that investigates the metabolic, gene expression profiles, and phenotypic responses of a P. aeruginosa clinical isolate to fermentation products lactic acid and 2,3-butanediol, metabolites that are produced by facultative anaerobic members of the CF polymicrobial community and potential biomarkers of disease progression. Although previous studies have successfully investigated the metabolic and transcriptional profiles of P. aeruginosa, most have used common lab reference strains that may differ in important ways from clinical isolates. Using transcriptomics and metabolomics with gas chromatography time of flight mass spectrometry (GCTOF-MS), we observe that fermentation products induce pyocyanin production along with expression of genes involved in P. aeruginosa amino acid utilization, dormancy and aggregative or biofilm modes of growth. These findings have important implications for how interactions within the diverse CF microbial community influence microbial physiology, with potential clinical consequences. PMID: 29617986 [PubMed - as supplied by publisher]

Related Articles Molecular Characterization and Clinical Relevance of Metabolic Expression Subtypes in Human Cancers. Cell Rep. 2018 Apr 03;23(1):255-269.e4 Authors: Peng X, Chen Z, Farshidfar F, Xu X, Lorenzi PL, Wang Y, Cheng F, Tan L, Mojumdar K, Du D, Ge Z, Li J, Thomas GV, Birsoy K, Liu L, Zhang H, Zhao Z, Marchand C, Weinstein JN, Cancer Genome Atlas Research Network, Bathe OF, Liang H Abstract Metabolic reprogramming provides critical information for clinical oncology. Using molecular data of 9,125 patient samples from The Cancer Genome Atlas, we identified tumor subtypes in 33 cancer types based on mRNA expression patterns of seven major metabolic processes and assessed their clinical relevance. Our metabolic expression subtypes correlated extensively with clinical outcome: subtypes with upregulated carbohydrate, nucleotide, and vitamin/cofactor metabolism most consistently correlated with worse prognosis, whereas subtypes with upregulated lipid metabolism showed the opposite. Metabolic subtypes correlated with diverse somatic drivers but exhibited effects convergent on cancer hallmark pathways and were modulated by highly recurrent master regulators across cancer types. As a proof-of-concept example, we demonstrated that knockdown of SNAI1 or RUNX1-master regulators of carbohydrate metabolic subtypes-modulates metabolic activity and drug sensitivity. Our study provides a system-level view of metabolic heterogeneity within and across cancer types and identifies pathway cross-talk, suggesting related prognostic, therapeutic, and predictive utility. PMID: 29617665 [PubMed - in process]