PubMed

Soil Fungal:Bacterial Ratios Are Linked to Altered Carbon Cycling. Front Microbiol. 2016;7:1247 Authors: Malik AA, Chowdhury S, Schlager V, Oliver A, Puissant J, Vazquez PG, Jehmlich N, von Bergen M, Griffiths RI, Gleixner G Abstract Despite several lines of observational evidence, there is a lack of consensus on whether higher fungal:bacterial (F:B) ratios directly cause higher soil carbon (C) storage. We employed RNA sequencing, protein profiling and isotope tracer techniques to evaluate whether differing F:B ratios are associated with differences in C storage. A mesocosm (13)C labeled foliar litter decomposition experiment was performed in two soils that were similar in their physico-chemical properties but differed in microbial community structure, specifically their F:B ratio (determined by PLFA analyses, RNA sequencing and protein profiling; all three corroborating each other). Following litter addition, we observed a consistent increase in abundance of fungal phyla; and greater increases in the fungal dominated soil; implicating the role of fungi in litter decomposition. Litter derived (13)C in respired CO2 was consistently lower, and residual (13)C in bulk SOM was higher in high F:B soil demonstrating greater C storage potential in the F:B dominated soil. We conclude that in this soil system, the increased abundance of fungi in both soils and the altered C cycling patterns in the F:B dominated soils highlight the significant role of fungi in litter decomposition and indicate that F:B ratios are linked to higher C storage potential. PMID: 27555839 [PubMed]

Plasma metabolic profile delineates roles for neurodegeneration, pro-inflammatory damage and mitochondrial dysfunction in the FMR1 premutation. Biochem J. 2016 Aug 23; Authors: Giulivi C, Napoli E, Tassone F, Halmai J, Hagerman R Abstract Carriers of premutation CGG expansions in the fragile X mental retardation 1 ( FMR1 ) gene are at higher risk of developing a late-onset neurodegenerative disorder named Fragile X-tremor ataxia syndrome (FXTAS). Given that mitochondrial dysfunction has been identified in fibroblasts, PBMC and brain samples from carriers as well as in animal models of the premutation and that mitochondria are at the center of intermediary metabolism, the aim of this study was to provide a complete view of the metabolic pattern by uncovering plasma metabolic perturbations in premutation carriers. To this end, metabolic profiles were evaluated in plasma from 23 premutation individuals and 16 age- and sex- matched controls. Among the affected pathways, mitochondrial dysfunction was associated with a Warburg-like shift with increases in lactate levels and altered Krebs' intermediates, neurotransmitters, markers of neurodegeneration, and increases in oxidative stress-mediated damage to biomolecules. The number of CGG repeats correlated with a subset of plasma metabolites, which are implicated in mitochondrial disorders but also in other neurological diseases such as Parkinson's, Alzheimer's and Huntington's diseases. For the first time, the identified pathways shed light on disease mechanisms contributing to morbidity of the premutation, with the potential of assessing metabolites in longitudinal studies as indicators of morbidity or disease progression, especially at the early pre-clinical stages. PMID: 27555610 [PubMed - as supplied by publisher]

Targeting the endocannabinoid system: future therapeutic strategies. Drug Discov Today. 2016 Aug 20; Authors: Aizpurua-Olaizola O, Elezgarai I, Rico I, Zarandona I, Etxebarria N, Usobiaga A Abstract The endocannabinoid system (ECS) is involved in many physiological regulation pathways in the human body, which makes this system the target of many drugs and therapies. In this review, we highlight the latest studies regarding the role of the ECS and the drugs that target it, with a particular focus on the basis for the discovery of new cannabinoid-based drugs. In addition, we propose some key steps, such as the creation of a cannabinoid-receptor interaction matrix (CRIM) and the use of metabolomics, towards the development of improved and more specific drugs for each relevant disease. PMID: 27554802 [PubMed - as supplied by publisher]

Is there a role for stool metabolomics in cystic fibrosis? Pediatr Int. 2016 Aug;58(8):808-11 Authors: Kaakoush NO, Pickford R, Jaffe A, Ooi CY Abstract A number of studies utilizing metabolomics have focused on the pathophysiology of cystic fibrosis (CF) lung disease. Here, we performed fecal metabolomics on pancreatic insufficient (PI) and sufficient (PS) children with CF and compared them with healthy controls (HC). Fecal metabolomics can differentiate between PS-CF and PI-CF. We identified a potential biomarker of disease severity or cystic fibrosis transmembrane conductance regulator function (m/z, 463.247; retention time, 0.570717 min) that discriminates between HC versus PS-CF versus PI-CF. We also identified lipoyl-GMP as a potential novel inflammatory biomarker, and elevation in fecal glycerol 1,2-didodecanoate 3-tetradecanoate may provide clues to the pathogenesis of intestinal inflammation. For the first time, we demonstrate the potential applications of fecal metabolomics in CF. PMID: 27553892 [PubMed - in process]

A Japanese case of β-ureidopropionase deficiency with dysmorphic features. Brain Dev. 2016 Aug 20; Authors: Akiyama T, Shibata T, Yoshinaga H, Kuhara T, Nakajima Y, Kato T, Maeda Y, Ohse M, Oka M, Kageyama M, Kobayashi K Abstract β-Ureidopropionase deficiency is a rare autosomal recessive disease affecting the last step of pyrimidine degradation, and it is caused by a mutation in the UPB1 gene. Approximately 30 cases have been reported to date, with a phenotypical variability ranging from asymptomatic to severe neurological illness. Non-neurological symptoms have been rarely reported. We describe a case of this disease with developmental delay and dysmorphic features. Gas chromatography-mass spectrometry-based urine metabolomics demonstrated significant (⩾+4.5 standard deviation after logarithmic transformation) elevations of β-ureidopropionic acid and β-ureidoisobutyric acid, strongly suggesting a diagnosis of β-ureidopropionase deficiency. Subsequent quantitative analysis of pyrimidines by liquid chromatography-tandem mass spectrometry supported this finding. Genetic testing of the UPB1 gene confirmed compound heterozygosity of a novel mutation (c.976C>T) and a previously-reported mutation (c.977G>A) that is common in East Asians. β-Ureidopropionase deficiency is probably underdiagnosed, considering a wide phenotypical variability, non-specific neurological presentations, and an estimated prevalence of 1/5000-6000. Urine metabolomics should be considered for patients with unexplained neurological symptoms. PMID: 27553092 [PubMed - as supplied by publisher]

Related Articles Mitochondrial and nuclear DNA matching shapes metabolism and healthy ageing. Nature. 2016 Jul 28;535(7613):561-5 Authors: Latorre-Pellicer A, Moreno-Loshuertos R, Lechuga-Vieco AV, Sánchez-Cabo F, Torroja C, Acín-Pérez R, Calvo E, Aix E, González-Guerra A, Logan A, Bernad-Miana ML, Romanos E, Cruz R, Cogliati S, Sobrino B, Carracedo Á, Pérez-Martos A, Fernández-Silva P, Ruíz-Cabello J, Murphy MP, Flores I, Vázquez J, Enríquez JA Abstract Human mitochondrial DNA (mtDNA) shows extensive within population sequence variability. Many studies suggest that mtDNA variants may be associated with ageing or diseases, although mechanistic evidence at the molecular level is lacking. Mitochondrial replacement has the potential to prevent transmission of disease-causing oocyte mtDNA. However, extension of this technology requires a comprehensive understanding of the physiological relevance of mtDNA sequence variability and its match with the nuclear-encoded mitochondrial genes. Studies in conplastic animals allow comparison of individuals with the same nuclear genome but different mtDNA variants, and have provided both supporting and refuting evidence that mtDNA variation influences organismal physiology. However, most of these studies did not confirm the conplastic status, focused on younger animals, and did not investigate the full range of physiological and phenotypic variability likely to be influenced by mitochondria. Here we systematically characterized conplastic mice throughout their lifespan using transcriptomic, proteomic,metabolomic, biochemical, physiological and phenotyping studies. We show that mtDNA haplotype profoundly influences mitochondrial proteostasis and reactive oxygen species generation,insulin signalling, obesity, and ageing parameters including telomere shortening and mitochondrial dysfunction, resulting in profound differences in health longevity between conplastic strains. PMID: 27383793 [PubMed - indexed for MEDLINE]

Knowns and unknowns in metabolomics identified by multidimensional NMR and hybrid MS/NMR methods. Curr Opin Biotechnol. 2016 Aug 20;43:17-24 Authors: Bingol K, Brüschweiler R Abstract Metabolomics continues to make rapid progress through the development of new and better methods and their applications to gain insight into the metabolism of a wide range of different biological systems from a systems biology perspective. Customization of NMR databases and search tools allows the faster and more accurate identification of known metabolites, whereas the identification of unknowns, without a need for extensive purification, requires new strategies to integrate NMR with mass spectrometry, cheminformatics, and computational methods. For some applications, the use of covalent and non-covalent attachments in the form of labeled tags or nanoparticles can significantly reduce the complexity of these tasks. PMID: 27552705 [PubMed - as supplied by publisher]

GC-MS metabolomics analysis of mesenchymal stem cells treated with copper oxide nanoparticles. Toxicol Mech Methods. 2016 Aug 23;:1-9 Authors: Murgia A, Mancuso L, Manis C, Caboni P, Cao G Abstract Human exposure to copper oxide (CuO) nanoparticles (NPs) is rapidly increasing and for this reason reliable toxicity test systems are urgently needed. Recently, the acute cytotoxicity of CuO NPs using the new toxicity test based on human bone marrow mesenchymal stem cells (hBMMSCs) has been evaluated. It was shown that CuO NPs are much more toxic when compared to CuO microparticles (MPs). Several studies associate CuO toxicity to a possible alteration of reactive oxygen species (ROS) system. Unluckily, the mechanism that causes the toxicity is still not clear. In this work, the polar metabolite pool of treated cells, at the corresponding IC50 value, for CuO micro and NPs has been studied by gas chromatography coupled to mass spectrometry (GC-MS) and multivariate statistical data analysis. By the same means, differences due to different treatments, on samples, were investigated. Results of discriminant analysis were considered with the aim of finding the relevant metabolites unique for each class. Serine, glyceric acid, and succinic acid were upregulated on samples treated with CuO microparticles, while glutamine was the only discriminant metabolite for the class of samples treated with nanoparticles. PMID: 27552400 [PubMed - as supplied by publisher]

Metabolic profile and pharmacokinetics of Polyphyllin I, an anticancer candidate, in rats by UPLC-QTOF-MS/MS and LC-TQ-MS/MS. Biomed Chromatogr. 2016 Aug 23; Authors: Liu YC, Zhu H, Shakya S, Wu JW Abstract Polyphyllin I (PPI), a natural steroidal saponin originated from rihzome of Paris polyphylla, is recognized as one of potential anticancer candidates. Previous pharmacokinetics study showed that the oral bioavailability of PPI was very low, which suggested that certain amount of PPI might be metabolized in vivo. However, up to date, information regarding the final metabolic fates of PPI was very limited. In this study, metabolites of PPI and their pharmacokinetics in rats were investigated using UPLC-QTOF-MS/MS and LC-TQ-MS/MS. A total of seven putative metabolites, including six phase I and one phase II metabolites, were detected and identified with three exact structures through comparing with authentic standards for the first time. Oxidation, deglycosylation and glucuronidation were found to be the major metabolic processes of the compound in rats. Pharmacokinetics of Prosapogenin A (PSA), Trillin (TRL) and Diosgenin (DSN), three deglycosylation metabolites of PPI with definite anti-cancer effects, were further studied, which suggested that the metabolites underwent a prolonged absorption and slower elimination after intragastric administration of PPI at the dose of 500 mg/kg. This study provides valuable and new information on the metabolic fate of PPI, which will be helpful in further understanding its mechanism of action. PMID: 27552088 [PubMed - as supplied by publisher]

Nanoflow-nanospray mass spectrometry metabolomics reveals disruption of the urinary metabolite profiles of HIV-positive patients on combination antiretroviral therapy. J Acquir Immune Defic Syndr. 2016 Aug 16; Authors: Chetwynd AJ, Samarawickrama A, Vera JH, Bremner SA, Abdul-Sada A, Gilleece Y, Holt SG, Hill EM Abstract BACKGROUND: The use of combination antiretroviral therapy (cART) has substantially improved the outlook for patients with HIV infection. However, lifelong exposure to cART is also associated with adverse metabolic changes and an enhanced risk of renal, hepatic and cardiovascular dysfunction. This study investigated disruptions of the urinary metabolome of cART-exposed patients, thereby furthering our understanding of some of the side effects of pharmaceutical intervention. METHODS: HIV-positive patients were recruited from an HIV clinic and divided into cART-naïve and cART-exposed groups. HIV-negative patients were recruited from a sexual health clinic. All 89 subjects were white males. Targeted biochemistry analyses were performed on plasma samples. Urine samples were collected following an overnight fast and analysed with a highly sensitive untargeted metabolomic method using nanoflow/nanospray liquid chromatography-time of flight mass spectrometry. Datasets were analysed using projection modelling to detect metabolite markers of cART exposure. RESULTS: Metabolites or parent compounds of all cART drugs were detected in urine extracts of all but one of the cART-exposed patients confirming adherence to the pharmaceutical regimen. Analysis of urine samples from patients on cART revealed significant reductions in selected bile acids, lipid, nucleoside and androgen metabolites. However, plasma concentrations of free or conjugated testosterone were unchanged indicating possible disruption of androgen transport or excretion in urine of patients on cART. CONCLUSIONS: Discovery-based metabolomics reveals the potential to identify novel markers of cART intervention and metabolite disruption in HIV-positive patients, which may enable the efficacy, compliance and side effects of these pharmaceutical mixtures to be investigated. PMID: 27552076 [PubMed - as supplied by publisher]

Regulatory network analysis reveals novel regulators of seed desiccation tolerance in Arabidopsis thaliana. Proc Natl Acad Sci U S A. 2016 Aug 22; Authors: González-Morales SI, Chávez-Montes RA, Hayano-Kanashiro C, Alejo-Jacuinde G, Rico-Cambron TY, de Folter S, Herrera-Estrella L Abstract Desiccation tolerance (DT) is a remarkable process that allows seeds in the dry state to remain viable for long periods of time that in some instances exceed 1,000 y. It has been postulated that seed DT evolved by rewiring the regulatory and signaling networks that controlled vegetative DT, which itself emerged as a crucial adaptive trait of early land plants. Understanding the networks that regulate seed desiccation tolerance in model plant systems would provide the tools to understand an evolutionary process that played a crucial role in the diversification of flowering plants. In this work, we used an integrated approach that included genomics, bioinformatics, metabolomics, and molecular genetics to identify and validate molecular networks that control the acquisition of DT in Arabidopsis seeds. Two DT-specific transcriptional subnetworks were identified related to storage of reserve compounds and cellular protection mechanisms that act downstream of the embryo development master regulators LEAFY COTYLEDON 1 and 2, FUSCA 3, and ABSCICIC ACID INSENSITIVE 3. Among the transcription factors identified as major nodes in the DT regulatory subnetworks, PLATZ1, PLATZ2, and AGL67 were confirmed by knockout mutants and overexpression in a desiccation-intolerant mutant background to play an important role in seed DT. Additionally, we found that constitutive expression of PLATZ1 in WT plants confers partial DT in vegetative tissues. PMID: 27551092 [PubMed - as supplied by publisher]

Metabolomic biosignature differentiates melancholic depressive patients from healthy controls. BMC Genomics. 2016;17:669 Authors: Liu Y, Yieh L, Yang T, Drinkenburg W, Peeters P, Steckler T, Narayan VA, Wittenberg G, Ye J Abstract BACKGROUND: Major depressive disorder (MDD) is a heterogeneous disease at the level of clinical symptoms, and this heterogeneity is likely reflected at the level of biology. Two clinical subtypes within MDD that have garnered interest are "melancholic depression" and "anxious depression". Metabolomics enables us to characterize hundreds of small molecules that comprise the metabolome, and recent work suggests the blood metabolome may be able to inform treatment decisions for MDD, however work is at an early stage. Here we examine a metabolomics data set to (1) test whether clinically homogenous MDD subtypes are also more biologically homogeneous, and hence more predictiable, (2) devise a robust machine learning framework that preserves biological meaning, and (3) describe the metabolomic biosignature for melancholic depression. RESULTS: With the proposed computational system we achieves around 80 % classification accuracy, sensitivity and specificity for melancholic depression, but only ~72 % for anxious depression or MDD, suggesting the blood metabolome contains more information about melancholic depression.. We develop an ensemble feature selection framework (EFSF) in which features are first clustered, and learning then takes place on the cluster centroids, retaining information about correlated features during the feature selection process rather than discarding them as most machine learning methods will do. Analysis of the most discriminative feature clusters revealed differences in metabolic classes such as amino acids and lipids as well as pathways studied extensively in MDD such as the activation of cortisol in chronic stress. CONCLUSIONS: We find the greater clinical homogeneity does indeed lead to better prediction based on biological measurements in the case of melancholic depression. Melancholic depression is shown to be associated with changes in amino acids, catecholamines, lipids, stress hormones, and immune-related metabolites. The proposed computational framework can be adapted to analyze data from many other biomedical applications where the data has similar characteristics. PMID: 27549765 [PubMed - in process]

A survey of metabolic changes in potato leaves by NMR-based metabolic profiling in relation to resistance to late blight disease under field conditions. Magn Reson Chem. 2016 Aug 23; Authors: Tomita S, Ikeda S, Tsuda S, Someya N, Asano K, Kikuchi J, Chikayama E, Ono H, Sekiyama Y Abstract Non-targeted nuclear magnetic resonance (NMR)-based metabolic profiling was applied to potato leaves to survey metabolic changes associated with late blight resistance under field conditions. Potato plants were grown in an experimental field and the compound leaves with no visible symptoms were collected from 20 cultivars/lines at two sampling time points: (i) the time of initial presentation of symptoms in susceptible cultivars and (ii) 12 days before this initiation. (1) H NMR spectra of the foliar metabolites soluble in deuterium oxide- or methanol-d4 -based buffers were measured and used for multivariate analysis. Principal component analysis for six cultivars at symptom initiation showed a class separation corresponding to their levels of late blight resistance. This separation was primarily explained by higher levels of malic acid, methanol, and rutin and a lower level of sucrose in the resistant cultivars than in the susceptible ones. Partial least squares regression revealed that the levels of these metabolites were strongly associated with the disease severity measured in this study under field conditions. These associations were observed only for the leaves harvested at the symptom initiation stage, but not for those collected 12 days beforehand. Subsequently, a simple, alternative enzymatic assay for l-malic acid was used to estimate late blight resistance, as a model for applying the potential metabolic marker obtained. This study demonstrated the potential of metabolomics for field-grown plants in combination with targeted methods for quantifying marker levels, moving towards marker-assisted screening of new cultivars with durable late blight resistance. PMID: 27549366 [PubMed - as supplied by publisher]

Variant rs10911021 that associates with coronary heart disease in type 2 diabetes, is associated with lower concentrations of circulating HDL cholesterol and large HDL particles but not with amino acids. Cardiovasc Diabetol. 2016;15(1):115 Authors: Beaney KE, Cooper JA, McLachlan S, Wannamethee SG, Jefferis BJ, Whincup P, Ben-Shlomo Y, Price JF, Kumari M, Wong A, Ong K, Hardy R, Kuh D, Kivimaki M, Kangas AJ, Soininen P, Ala-Korpela M, Drenos F, Humphries SE, UCLEB consortium Abstract AIMS: An intergenic locus on chromosome 1 (lead SNP rs10911021) was previously associated with coronary heart disease (CHD) in type 2 diabetes (T2D). Using data from the UCLEB consortium we investigated the relationship between rs10911021 and CHD in T2D, whether rs10911021 was associated with levels of amino acids involved in the γ-glutamyl cycle or any conventional risk factors (CRFs) for CHD in the T2D participants. METHODS: Four UCLEB studies (n = 6531) had rs10911021 imputation, CHD in T2D, CRF and metabolomics data determined using a nuclear magnetic resonance based platform. RESULTS: The expected direction of effect between rs10911021 and CHD in T2D was observed (1377 no CHD/160 CHD; minor allele OR 0.80, 95 % CI 0.60-1.06) although this was not statistically significant (p = 0.13). No association between rs10911021 and CHD was seen in non-T2D participants (11218 no CHD/1274 CHD; minor allele OR 1.00 95 % CIs 0.92-1.10). In T2D participants, while no associations were observed between rs10911021 and the nine amino acids measured, rs10911021 was associated with HDL-cholesterol (p = 0.0005) but the minor "protective" allele was associated with lower levels (-0.034 mmol/l per allele). Focusing more closely on the HDL-cholesterol subclasses measured, we observed that rs10911021 was associated with six large HDL particle measures in T2D (all p < 0.001). No significant associations were seen in non-T2D subjects. CONCLUSIONS: Our findings are consistent with a true association between rs10911021 and CHD in T2D. The protective minor allele was associated with lower HDL-cholesterol and reductions in HDL particle traits. Our results indicate a complex relationship between rs10911021 and CHD in T2D. PMID: 27549350 [PubMed - in process]

Urine metabolomic profiling of children with respiratory tract infections in the emergency department: a pilot study. BMC Infect Dis. 2016;16(1):439 Authors: Adamko DJ, Saude E, Bear M, Regush S, Robinson JL Abstract BACKGROUND: Clinicians lack objective tests to help determine the severity of bronchiolitis or to distinguish a viral from bacterial causes of respiratory distress. We hypothesized that children with respiratory syncytial virus (RSV) infection would have a different metabolomic profile compared to those with bacterial infection or healthy controls, and this might also vary with bronchiolitis severity. METHODS: Clinical information and urine-based metabolomic data were collected from healthy age-matched children (n = 37) and those admitted to hospital with a proven infection (RSV n = 55; Non-RSV viral n = 16; bacterial n = 24). Nuclear magnetic resonance (NMR) measured 86 metabolites per urine sample. Partial least squares discriminant analysis (PLS-DA) was performed to create models of separation. RESULTS: Using a combination of metabolites, a strong PLS-DA model (R2 = 0.86, Q2 = 0.76) was created differentiating healthy children from those with RSV infection. This model had over 90 % accuracy in classifying blinded infants with similar illness severity. Two other models differentiated length of hospitalization and viral versus bacterial infection. CONCLUSION: While the sample sizes remain small, this is the first report suggesting that metabolomic analysis of urine samples has the potential to become a diagnostic aid. Future studies with larger sample sizes are required to validate the utility of metabolomics in pediatric patients with respiratory distress. PMID: 27549246 [PubMed - in process]

Variations in the metabolome in response to disease activity of rheumatoid arthritis. BMC Musculoskelet Disord. 2016;17(1):353 Authors: Tatar Z, Migne C, Petera M, Gaudin P, Lequerre T, Marotte H, Tebib J, Pujos Guillot E, Soubrier M Abstract BACKGROUND: Anti-Tumor Necrosis Factor (TNF) therapies are able to control rheumatoid arthritis (RA) disease activity and limit structural damage. Yet no predictive factor of response to anti-TNF has been identified. Metabolomic profile is known to vary in response to different inflammatory rheumatisms so determining it could substantially improve diagnosis and, consequently, prognosis. The aim of this study was to use mass spectrometry to determine whether there is variation in the metabolome in patients treated with anti-TNF and whether any particular metabolomic profile can serve as a predictor of therapeutic response. METHODS: Blood samples were analyzed in 140 patients with active RA before initiation of anti-TNF treatment and after 6 months of Anti-TNF treatment (100 good responders and 40 non-responders). Plasma was deproteinized, extracted and analyzed by reverse-phase chromatography-QToF mass spectrometry. Extracted and normalized ions were tested by univariate and ANOVA analysis followed by partial least-squares regression-discriminant analysis (PLS-DA). Orthogonal Signal Correction (OSC) was also used to filter data from unwanted non-related effects. Disease activity scores (DAS 28) obtained at 6 months were correlated with metabolome variation findings to identify a metabolite that is predictive of therapeutic response to anti-TNF. RESULTS: After 6 months of anti-TNF therapy, 100 patients rated as good responders and 40 patients as non-responders according to EULAR criteria. Metabolomic investigations suggested two different metabolic fingerprints splitting the good-responders group and the non-responders group, without differences in anti-TNF therapies. Univariate analysis revealed 24 significant ions in positive mode (p < 0.05) and 31 significant ions in negative mode (p < 0.05). Once intersected with PLS results, only 35 ions remained. Carbohydrate derivates emerged as strong candidate determinants of therapeutic response. CONCLUSIONS: This is the first study describing metabolic profiling in response to anti-TNF treatments using plasma samples. The study highlighted two different metabolic profiles splitting good responders from non-responders. PMID: 27549132 [PubMed - in process]

Related Articles BCAT1 expression associates with ovarian cancer progression: possible implications in altered disease metabolism. Oncotarget. 2015 Oct 13;6(31):31522-43 Authors: Wang ZQ, Faddaoui A, Bachvarova M, Plante M, Gregoire J, Renaud MC, Sebastianelli A, Guillemette C, Gobeil S, Macdonald E, Vanderhyden B, Bachvarov D Abstract Previously, we have identified the branched chain amino-acid transaminase 1 (BCAT1) gene as notably hypomethylated in low-malignant potential (LMP) and high-grade (HG) serous epithelial ovarian tumors, compared to normal ovarian tissues. Here we show that BCAT1 is strongly overexpressed in both LMP and HG serous epithelial ovarian tumors, which probably correlates with its hypomethylated status. Knockdown of the BCAT1 expression in epithelial ovarian cancer (EOC) cells led to sharp decrease of cell proliferation, migration and invasion and inhibited cell cycle progression. BCAT1 silencing was associated with the suppression of numerous genes and pathways known previously to be implicated in ovarian tumorigenesis, and the induction of some tumor suppressor genes (TSGs). Moreover, BCAT1 suppression resulted in downregulation of numerous genes implicated in lipid production and protein synthesis, suggesting its important role in controlling EOC metabolism. Further metabolomic analyses were indicative for significant depletion of most amino acids and different phospho- and sphingolipids following BCAT1 knockdown. Finally, BCAT1 suppression led to significantly prolonged survival time in xenograft model of advanced peritoneal EOC. Taken together, our findings provide new insights about the functional role of BCAT1 in ovarian carcinogenesis and identify this transaminase as a novel EOC biomarker and putative EOC therapeutic target. PMID: 26372729 [PubMed - indexed for MEDLINE]

PCA as a practical indicator of OPLS-DA model reliability. Curr Metabolomics. 2016;4(2):97-103 Authors: Worley B, Powers R Abstract BACKGROUND: Principal Component Analysis (PCA) and Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) are powerful statistical modeling tools that provide insights into separations between experimental groups based on high-dimensional spectral measurements from NMR, MS or other analytical instrumentation. However, when used without validation, these tools may lead investigators to statistically unreliable conclusions. This danger is especially real for Partial Least Squares (PLS) and OPLS, which aggressively force separations between experimental groups. As a result, OPLS-DA is often used as an alternative method when PCA fails to expose group separation, but this practice is highly dangerous. Without rigorous validation, OPLS-DA can easily yield statistically unreliable group separation. METHODS: A Monte Carlo analysis of PCA group separations and OPLS-DA cross-validation metrics was performed on NMR datasets with statistically significant separations in scores-space. A linearly increasing amount of Gaussian noise was added to each data matrix followed by the construction and validation of PCA and OPLS-DA models. RESULTS: With increasing added noise, the PCA scores-space distance between groups rapidly decreased and the OPLS-DA cross-validation statistics simultaneously deteriorated. A decrease in correlation between the estimated loadings (added noise) and the true (original) loadings was also observed. While the validity of the OPLS-DA model diminished with increasing added noise, the group separation in scores-space remained basically unaffected. CONCLUSION: Supported by the results of Monte Carlo analyses of PCA group separations and OPLS-DA cross-validation metrics, we provide practical guidelines and cross-validatory recommendations for reliable inference from PCA and OPLS-DA models. PMID: 27547730 [PubMed - as supplied by publisher]

Discovery of A-type procyanidin dimers in yellow raspberries by untargeted metabolomics and correlation based data analysis. Metabolomics. 2016;12:144 Authors: Carvalho E, Franceschi P, Feller A, Herrera L, Palmieri L, Arapitsas P, Riccadonna S, Martens S Abstract INTRODUCTION: Raspberries are becoming increasingly popular due to their reported health beneficial properties. Despite the presence of only trace amounts of anthocyanins, yellow varieties seems to show similar or better effects in comparison to conventional raspberries. OBJECTIVES: The aim of this work is to characterize the metabolic differences between red and yellow berries, focussing on the compounds showing a higher concentration in yellow varieties. METHODS: The metabolomic profile of 13 red and 12 yellow raspberries (of different varieties, locations and collection dates) was determined by UPLC-TOF-MS. A novel approach based on Pearson correlation on the extracted ion chromatograms was implemented to extract the pseudospectra of the most relevant biomarkers from high energy LC-MS runs. The raw data will be made publicly available on MetaboLights (MTBLS333). RESULTS: Among the metabolites showing higher concentration in yellow raspberries it was possible to identify a series of compounds showing a pseudospectrum similar to that of A-type procyanidin polymers. The annotation of this group of compounds was confirmed by specific MS/MS experiments and performing standard injections. CONCLUSIONS: In berries lacking anthocyanins the polyphenol metabolism might be shifted to the formation of a novel class of A-type procyanidin polymers. PMID: 27547172 [PubMed - as supplied by publisher]

Renal cell carcinoma: a critical analysis of metabolomic biomarkers emerging from current model systems. Transl Res. 2016 Aug 2; Authors: Rodrigues D, Monteiro M, Jerónimo C, Henrique R, Belo L, de Lourdes Bastos M, de Pinho PG, Carvalho M Abstract Metabolomics, an emerging field of "omics" sciences, has caught wide scientific attention in the area of biomarker research for cancers in which early diagnostic biomarkers have the potential to greatly improve patient outcome, such as renal cell carcinoma (RCC). Metabolomic approaches have been successfully applied to various human RCC model systems, mostly ex vivo neoplastic renal tissues and biofluids (urine and serum) from patients with RCC. Importantly, in contrast to other cancers, only a few studies have addressed the RCC metabolome using cancer cell culture-based in vitro models. Herein, we first carried out a comprehensive review of current metabolomic data in RCC, with emphasis on metabolite disturbances and dysregulated metabolic pathways identified in each of these experimental models. We then critically analyzed the consistency of evidence in this field and whether metabolites found altered in tumor cell and tissue microenvironment are reflected in biofluids, which constitute the rationale underlying the translation of discovered metabolic biomarkers into noninvasive diagnostic tools. Finally, dominant metabolic pathways and promising metabolites as biomarkers for diagnosis and prognosis of RCC are outlined. PMID: 27546593 [PubMed - as supplied by publisher]