PubMed

Diabetes and cardiovascular disease: let's push forward with translational research. Cardiovasc Diagn Ther. 2015 Oct;5(5):407-11 Authors: Paneni F, Costantino S Abstract Albeit advances in therapy have reduced morbidity and mortality in patients with diabetes, cardiovascular (CV) risk is far to be eradicated. This is partially due to the fact that breakthrough therapies have yet to be approved to counteract the atherosclerotic burden in this setting. Therefore, it is very important to understand the molecular mechanisms underpinning diabetes-related CV complications. Growing evidence is supporting the concept that translational research is perhaps the best approach to unveil novel insights into disease etiology and its link with CV phenotypes. The recent employment of high throughput "omics" (i.e., metabolomics, transcriptomics, proteomics) is a clinically relevant approach which may provide insightful interpretations of diabetes-related biological signals. The possibility to analyse thousands or more molecules simultaneously has given "omics" the ability to generate enormous quantities of data which may somehow offer a precious "window on the disease". In the present article, we critically discuss the importance of translational research in diabetes, including potential difficulties which may arise in the implementation and development of promising technologies from the laboratory to the marketplace. PMID: 26543828 [PubMed]

Production of hyperpolarized (13)CO2 from [1-(13)C]pyruvate in perfused liver does reflect total anaplerosis but is not a reliable biomarker of glucose production. Metabolomics. 2015 Oct;11(5):1144-1156 Authors: Moreno KX, Moore CL, Burgess SC, Sherry AD, Malloy CR, Merritt ME Abstract In liver, (13)CO2 can be generated from [1-(13)C] pyruvate via pyruvate dehydrogenase or anaplerotic entry of pyruvate into the TCA cycle followed by decarboxylation at phosphoenolpyruvate carboxykinase (PEPCK), the malic enzyme, isocitrate dehydrogenase, or α-ketoglutarate dehydrogenase. The purpose of this study was to determine the relative importance of these pathways in production of hyperpolarized (HP) (13)CO2 after administration of hyper-polarized pyruvate in livers supplied with a fatty acid plus substrates for gluconeogenesis. Isolated mouse livers were perfused with a mixture of thermally-polarized (13)C-enriched pyruvate, lactate and octanoate in various combinations prior to exposure to HP pyruvate. Under all perfusion conditions, HP malate, aspartate and fumarate were detected within ~ 3 s showing that HP [1-(13)C]pyruvate is rapidly converted to [1-(13)C]oxaloacetate which can subsequently produce HP (13)CO2 via decarboxylation at PEPCK. Measurements using HP [2-(13)C]pyruvate allowed the exclusion of reactions related to TCA cycle turnover as sources of HP (13)CO2. Direct measures of O2 consumption, ketone production, and glucose production by the intact liver combined with (13)C isotopomer analyses of tissue extracts yielded a comprehensive profile of metabolic flux in perfused liver. Together, these data show that, even though the majority of HP (13)CO2 derived from HP [1-(13)C]pyruvate in livers exposed to fatty acids reflects decarboxylation of [4-(13)C]oxaloacetate (PEPCK) or [4-(13)C]malate (malic enzyme), the intensity of the HP (13)CO2 signal is not proportional to glucose production because the amount of pyruvate returned to the TCA cycle via PEPCK and pyruvate kinase is variable, depending upon available substrates. PMID: 26543443 [PubMed - as supplied by publisher]

Calcified nodules on fingers in a primary hyperoxaluria type 2. Lancet Diabetes Endocrinol. 2015 Nov 2; Authors: Yamanouchi M, Ubara Y, Takayama T, Kuhara T, Takaichi K PMID: 26542998 [PubMed - as supplied by publisher]

Lessons learned from metabolomics in cystic fibrosis. Mol Cell Pediatr. 2015 Dec;2(1):9 Authors: Muhlebach MS, Sha W Abstract Cystic fibrosis is a mono-genetic multi-system disease; however, respiratory manifestations cause the main morbidity and mortality where chronic bacterial infections lead to bronchiectasis and ultimately respiratory failure. Metabolomics allows a relatively complete snapshot of metabolic processes in a sample using different mass spectrometry methods. Sample types used for discovery of biomarkers or pathomechanisms in cystic fibrosis (CF) have included blood, respiratory secretions, and exhaled breath to date. Metabolomics has shown distinction of CF vs. non-CF for matrices of blood, exhaled breath, and respiratory epithelial cultures, each showing different pathways. Severity of lung disease has been addressed by studies in bronchoalveolar lavage and exhaled breath condensate showing separation by metabolites that the authors of each study related to inflammation; e.g., ethanol, acetone, purines. Lipidomics has been applied to blood and sputum samples showing associations with lung function and Pseudomonas aeruginosa infection status. Finally, studies of bacteria grown in vitro showed differences of bacterial metabolites to be associated with clinical parameters. Metabolomics, in the sense of global metabolomic profiling, is a powerful technique that has allowed discovery of pathways that had not previously been implicated in CF. These may include purines, mitochondrial pathways, and different aspects of glucose metabolism besides the known differences in lipid metabolism in CF. However, targeted studies to validate such potential metabolites and pathways of interest are necessary. Studies evaluating metabolites of bacterial origin are in their early stages. Thus further well-designed studies could be envisioned. PMID: 26542299 [PubMed]

Anticancer immunotherapy by CTLA-4 blockade relies on the gut microbiota. Science. 2015 Nov 5; Authors: Vétizou M, Pitt JM, Daillère R, Lepage P, Waldschmitt N, Flament C, Rusakiewicz S, Routy B, Roberti MP, Duong CP, Poirier-Colame V, Roux A, Becharef S, Formenti S, Golden E, Cording S, Eberl G, Schlitzer A, Ginhoux F, Mani S, Yamazaki T, Jacquelot N, Enot DP, Bérard M, Nigou J, Opolon P, Eggermont A, Woerther PL, Chachaty E, Chaput N, Robert C, Mateus C, Kroemer G, Raoult D, Boneca IG, Carbonnel F, Chamaillard M, Zitvogel L Abstract Antibodies targeting CTLA-4 have been successfully used as cancer immunotherapy. We find that the antitumor effects of CTLA-4 blockade depend on distinct Bacteroides species. In mice and patients, T cell responses specific for B. thetaiotaomicron or B. fragilis were associated with the efficacy of CTLA-4 blockade. Tumors in antibiotic-treated or germ-free mice did not respond to CTLA blockade. This defect was overcome by gavage with B. fragilis, or by immunization with B. fragilis polysaccharides, or by adoptive transfer of B. fragilis-specific T cells. Fecal microbial transplantation from humans to mice confirmed that anti-CTLA-4 treatment of melanoma patients favored the outgrowth of B. fragilis with anticancer properties. This study reveals a key role for Bacteroidales in the immunostimulatory effects of CTLA-4 blockade. PMID: 26541610 [PubMed - as supplied by publisher]

Changes in the NMR Metabolic Profile of Live Human Neuron-Like SH-SY5Y Cells Exposed to Interferon-α2. J Neuroimmune Pharmacol. 2015 Nov 5; Authors: Valeria R, Luisa S, Adele M, Stefania B, Fabio T, Nicoletta B, Carmine PM, Silvia A Abstract Interferon (IFN)-α2 is an extensively therapeutically used pro-inflammatory cytokine. Though its efficacy in controlling viral replication and tumor cells proliferation, administration of IFN-α2 is often associated with the development of central side effects. Magnetic resonance spectroscopy studies have demonstrated that IFN-α2 administration affects brain metabolism, however the exact nature of this effect is not completely known. We hypothesized that IFN-α2 can affect metabolic activity of human neuron-like SH-SY5Y cells which possess many characteristics of neurons and represent one of the most used models for studying mechanisms involved in neurotoxicity or neuroprotection. To test our hypothesis we have characterized the metabolic signature of live SH-SY5Y, and their conditioned media, after 24 and 72 h of exposure to vehicle or IFN-α2 (100 ng/ml) by using High Resolution-Magic Angle Spinning (HR-MAS) Nuclear Magnetic Resonance (NMR) spectroscopy. Our results revealed that 1) the use of HR-MAS NMR is ideally suitable for the characterization of the metabolic profile of live cells and their conditioned media without extraction procedures; and 2) a 72 h exposure to IFN-α2 increases the level of metabolites involved in maintaining energetic (including creatine and lactate) and osmotic (such as myo-inositol, scyllo-inositol, taurine and glycerophosphorylcholine) balances in neuron-like cells and of metabolic waste products (namely lactate, ethanol and acetate), glycine and glutamine in their growth media. These results may contribute to gain more knowledge about the IFN-α2 induced effect on the brain and support the interpretation of magnetic resonance spectroscopy studies performed in humans. PMID: 26541470 [PubMed - as supplied by publisher]

The Cooperative Health Research in South Tyrol (CHRIS) study: rationale, objectives, and preliminary results. J Transl Med. 2015;13(1):348 Authors: Pattaro C, Gögele M, Mascalzoni D, Melotti R, Schwienbacher C, De Grandi A, Foco L, D'Elia Y, Linder B, Fuchsberger C, Minelli C, Egger C, Kofink LS, Zanigni S, Schäfer T, Facheris MF, Smárason SV, Rossini A, Hicks AA, Weiss H, Pramstaller PP Abstract The Cooperative Health Research In South Tyrol (CHRIS) study is a population-based study with a longitudinal lookout to investigate the genetic and molecular basis of age-related common chronic conditions and their interaction with life style and environment in the general population. All adults of the middle and upper Vinschgau/Val Venosta are invited, while 10,000 participants are anticipated by mid-2017. Family participation is encouraged for complete pedigree reconstruction and disease inheritance mapping. After a pilot study on the compliance with a paperless assessment mode, computer-assisted interviews have been implemented to screen for conditions of the cardiovascular, endocrine, metabolic, genitourinary, nervous, behavioral, and cognitive system. Fat intake, cardiac health, and tremor are assessed instrumentally. Nutrient intake, physical activity, and life-course smoking are measured semi-quantitatively. Participants are phenotyped for 73 blood and urine parameters and 60 aliquots per participant are biobanked (cryo-preserved urine, DNA, and whole and fractionated blood). Through liquid-chromatography mass-spectrometry analysis, metabolite profiling of the mitochondrial function is assessed. Samples are genotyped on 1 million variants with the Illumina HumanOmniExpressExome array and the first data release including 4570 fully phenotyped and genotyped samples is now available for analysis. Participants' follow-up is foreseen 6 years after the first visit. The target population is characterized by long-term social stability and homogeneous environment which should both favor the identification of enriched genetic variants. The CHRIS cohort is a valuable resource to assess the contribution of genomics, metabolomics, and environmental factors to human health and disease. It is awaited that this will result in the identification of novel molecular targets for disease prevention and treatment. PMID: 26541195 [PubMed - in process]

Related Articles Characterization of T Antigens, Including Middle T and Alternative T, Expressed by the Human Polyomavirus Associated with Trichodysplasia Spinulosa. J Virol. 2015 Sep;89(18):9427-39 Authors: van der Meijden E, Kazem S, Dargel CA, van Vuren N, Hensbergen PJ, Feltkamp MC Abstract UNLABELLED: The polyomavirus tumor (T) antigens play crucial roles in viral replication, transcription, and cellular transformation. They are encoded by partially overlapping open reading frames (ORFs) located in the early region through alternative mRNA splicing. The T expression pattern of the trichodysplasia spinulosa-associated polyomavirus (TSPyV) has not been established yet, hampering further study of its pathogenic mechanisms and taxonomic relationship. Here, we characterized TSPyV T antigen expression in human cell lines transfected with the TSPyV early region. Sequencing of T antigen-encoded reverse transcription-PCR (RT-PCR) products revealed three splice donor and acceptor sites creating six mRNA splice products that potentially encode the antigens small T (ST), middle T (MT), large T (LT), tiny T, 21kT, and alternative T (ALTO). Except for 21kT, these splice products were also detected in skin of TSPyV-infected patients. At least three splice products were confirmed by Northern blotting, likely encoding LT, MT, ST, 21kT, and ALTO. Protein expression was demonstrated for LT, ALTO, and possibly MT, with LT detected in the nucleus and ALTO in the cytoplasm of transfected cells. Splice site and start codon mutations indicated that ALTO is encoded by the same splice product that encodes LT and uses internal start codons for initiation. The genuineness of ALTO was indicated by the identification of acetylated N-terminal ALTO peptides by mass spectrometry. Summarizing, TSPyV exhibits an expression pattern characterized by both MT and ALTO expression, combining features of rodent and human polyomaviruses. This unique expression pattern provides important leads for further study of polyomavirus-related disease and for an understanding of polyomavirus evolution. IMPORTANCE: The human trichodysplasia spinulosa-associated polyomavirus (TSPyV) is distinguished among polyomaviruses for combining productive infection with cell-transforming properties. In the research presented here, we further substantiate this unique position by indicating expression of both middle T antigen (MT) and alternative T antigen (ALTO) in TSPyV. So far, none of the human polyomaviruses was shown to express MT, which is considered the most important viral oncoprotein of rodent polyomaviruses. Coexpression of ALTO and MT, which involves a conserved, recently recognized overlapping ORF subject to positive selection, has not been observed before for any polyomavirus. As a result of our findings, this study provides valuable new insights into polyomavirus T gene use and expression. Obviously, these insights will be instrumental in further study and gaining an understanding of TSPyV pathogenicity. More importantly, however, they provide important leads with regard to the interrelationship, functionality, and evolution of polyomaviruses as a whole, indicating that TSPyV is a suitable model virus to study these entities further. PMID: 26136575 [PubMed - indexed for MEDLINE]

Related Articles Characterization of ampicillin-stressed proteomics and development of a direct method for detecting drug-binding proteins in Edwardsiella tarda. J Proteomics. 2015 Feb 26;116:97-105 Authors: Liu XJ, Zhu WC, Su YB, Guo C, Zeng ZH, Zhu H, Li H, Peng XX Abstract UNLABELLED: Antibiotic-resistant Edwardsiella tarda poses a severe challenge to aquaculture. An understanding for antibiotic-resistant mechanisms is crucial to control the disease. The present study characterizes E. tarda ampicillin-stressed proteome and shows the importance of energy metabolism including the TCA cycle and glycolysis/gluconeogenesis in the antibiotic resistance. Further combination with antibiotic measurement develops a new method for identification of antibiotic-binding proteins out of differential abundances of proteins and results in determination of ETAE_0175 and ETAE_3367 as ampicillin-binding proteins in E. tarda. Genes of the two proteins are cloned and recombinant proteins are purified for validation of antibiotic-binding capability. Results show that higher binding capability is detected in ETAE_3367 than ETAE_0175. Out of the two proteins, ETAE_3367 is first reported here to be an antibiotic-binding protein, while ETAE_0175 homology in other bacteria has been shown to bind with other antibiotics. Bioinformatics analysis shows that ETAE_3367 may closely interact with aceF and sucA belonging to the TCA cycle and glycolysis/gluconeogenesis, respectively. These results indicate that energy metabolism contributes to ampicillin resistance in E. tarda and a new method to identify antibiotic-binding proteins is developed. These findings highlight the way to an understanding of antibiotic-resistant mechanisms in content of antibiotic-binding proteins. BIOLOGICAL SIGNIFICANCE: Our data characterizes Edwardsiella tarda ampicillin-stressed proteome and shows the importance of energy metabolism including the TCA cycle and glycolysis/gluconeogenesis in the antibiotic resistance. Furthermore, a new method based 2-DE proteomics is developed for identification of antibiotic-binding proteins, which results in determination of ETAE_0175 and ETAE_3367 as ampicillin-binding proteins in E. tarda. ETAE_3367 is closely interacted with proteins of the TCA cycle and glycolysis/gluconeogenesis, suggesting the drug-resistant mechanism. PMID: 25596334 [PubMed - indexed for MEDLINE]

18 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 2015/11/06PubMed comprises more than 24 million 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.

Molecular Regulation of Circadian Rhythms by Polyamines. Cell Metab. 2015 Nov 3;22(5):757-758 Authors: Galluzzi L, Pietrocola F, Kroemer G Abstract In this issue of Cell Metabolism, Zwighaft and colleagues (Zwighaft et al., 2015) describe a novel mechanism through which intracellular polyamines regulate circadian rhythms. These findings are significant, as they add yet another layer of complexity to the interplay between environmental, dietary, and organismal factors in the molecular control of daily behavioral oscillations. PMID: 26536485 [PubMed - as supplied by publisher]

Quality assurance of metabolomics. ALTEX. 2015;32(4):319-326 Authors: Bouhifd M, Beger R, Flynn T, Guo L, Harris G, Hogberg H, Kaddurah-Daouk R, Kamp H, Kleensang A, Maertens A, Odwin-DaCosta S, Pamies D, Robertson D, Smirnova L, Sun J, Zhao L, Hartung T Abstract Metabolomics promises a holistic phenotypic characterization of biological responses to toxicants. This technology is based on advanced chemical analytical tools with reasonable throughput, including mass-spectroscopy and NMR. Quality assurance, however - from experimental design, sample preparation, metabolite identification, to bioinformatics data-mining - is urgently needed to assure both quality of metabolomics data and reproducibility of biological models. In contrast to microarray-based transcriptomics, where consensus on quality assurance and reporting standards has been fostered over the last two decades, quality assurance of metabolomics is only now emerging. Regulatory use in safety sciences, and even proper scientific use of these technologies, demand quality assurance. In an effort to promote this discussion, an expert workshop discussed the quality assurance needs of metabolomics. The goals for this workshop were 1) to consider the challenges associated with metabolomics as an emerging science, with an emphasis on its application in toxicology and 2) to identify the key issues to be addressed in order to establish and implement quality assurance procedures in metabolomics-based toxicology. Consensus has still to be achieved regarding best practices to make sure sound, useful, and relevant information is derived from these new tools. PMID: 26536290 [PubMed - as supplied by publisher]

Abnormal metabolites related to bone marrow failure in aplastic anemia patients. Genet Mol Res. 2015;14(4):13709-13718 Authors: Zhong P, Zhang J, Cui X Abstract Metabolomics is the identification and quantitation of small molecules that are involved in metabolic reactions. Liquid chromatography-mass spectrometry (LC-MS) has enjoyed growing popularity as the platform for metabolomic studies due to high throughput, soft ionization, and good coverage of metabolites. Serum metabolites of aplastic anemia (AA) patients and healthy controls were investigated using LC-MS. A wavelet-based method was utilized to find and align LC-MS peaks. Principal component analysis, partial least squares discriminant analysis, and optimized potential for liquid simulations were used to identify differences in metabolite levels, and to reveal useful biomarkers. Thirty-two metabolites that were significantly altered were detected. Of these metabolites, 23 were successfully identified. In AA patients, metabolites involved amino acid biosynthesis, aminoacyl-tRNA biosynthesis, and ATP-binding cassette transporters were higher than normal, while the levels of metabolites involved in TCA cycles were lower than normal. These changes may be the primary cause or result of bone marrow failure in patients with AA. PMID: 26535686 [PubMed - as supplied by publisher]

Identification of Reliable Components in Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS): a Data-Driven Approach across Metabolic Processes. Sci Rep. 2015;5:15710 Authors: Motegi H, Tsuboi Y, Saga A, Kagami T, Inoue M, Toki H, Minowa O, Noda T, Kikuchi J Abstract There is an increasing need to use multivariate statistical methods for understanding biological functions, identifying the mechanisms of diseases, and exploring biomarkers. In addition to classical analyses such as hierarchical cluster analysis, principal component analysis, and partial least squares discriminant analysis, various multivariate strategies, including independent component analysis, non-negative matrix factorization, and multivariate curve resolution, have recently been proposed. However, determining the number of components is problematic. Despite the proposal of several different methods, no satisfactory approach has yet been reported. To resolve this problem, we implemented a new idea: classifying a component as "reliable" or "unreliable" based on the reproducibility of its appearance, regardless of the number of components in the calculation. Using the clustering method for classification, we applied this idea to multivariate curve resolution-alternating least squares (MCR-ALS). Comparisons between conventional and modified methods applied to proton nuclear magnetic resonance ((1)H-NMR) spectral datasets derived from known standard mixtures and biological mixtures (urine and feces of mice) revealed that more plausible results are obtained by the modified method. In particular, clusters containing little information were detected with reliability. This strategy, named "cluster-aided MCR-ALS," will facilitate the attainment of more reliable results in the metabolomics datasets. PMID: 26531245 [PubMed - in process]

Nutrition recommendations and science: next parallel steps. J Sci Food Agric. 2015 Sep 29; Authors: Fogelholm M Abstract This article examines nutrition recommendations in relation to developments in nutrition science. Combining data on the genome, metabolome and microbiota is likely to open possibilities for personalized nutrition planning, but we are still far from practical applications. However, even these new steps are unlikely to challenge the role and importance of population-based nutrition recommendations as a tool to promote dietary patterns, policies and public health. Developments in science could help in deriving more benefits from nutrition recommendations. For instance, improved accuracy of dietary intake assessment is needed both for surveillance and for understanding the quantitative interplay between diet and health. Applying metabolomics together with food diaries or questionnaires, and also modern technologies such as digital photography, are potentially interesting methods in this respect. Research on consumer behaviour, attitudes and policy interventions, such as taxation of unhealthy foods and nutrition labelling, are needed to gain more insight into how to change eating behaviour for better health at the population level. © 2015 Society of Chemical Industry. PMID: 26531226 [PubMed - as supplied by publisher]

Metabolomic and Gene Expression Profiles Exhibit Modular Genetic and Dietary Structure Linking Metabolic Syndrome Phenotypes in Drosophila. G3 (Bethesda). 2015 Nov 3; Authors: Williams S, Dew-Budd K, Davis K, Anderson J, Bishop R, Freeman K, Davis D, Bray K, Perkins L, Hubickey J, Reed LK Abstract Genetic and environmental factors influence complex disease in humans, such as Metabolic Syndrome (MetS), and Drosophila melanogaster serves as an excellent model in which to test these factors experimentally. Here we explore the modularity of endophenotypes with an in-depth reanalysis of a previous study by Reed et al., where we raised twenty wildtype genetic lines of Drosophila larvae on four diets and measured gross phenotypes of body weight, total sugar, and total triglycerides, as well as the endophenotypes of metabolomic and whole genome expression profiles. We then perform new gene expression experiments to test for conservation of phenotype-expression correlations across different diets and populations. We find that transcript levels correlated with gross phenotypes were enriched for puparial adhesion, metamorphosis, and central energy metabolism functions. The specific metabolites L-DOPA, N- arachidonoyl dopamine make physiological links between the gross phenotypes across diets, while leucine and isoleucine thus exhibit genotype-by-diet interactions. Between diets, we find low conservation of the endophenotypes that correlate with the gross phenotypes. Through the follow-up expression study, we found that transcript-trait correlations are well conserved across populations raised on a familiar diet, but on a novel diet, the transcript-trait correlations are no longer conserved. Thus, physiological canalization of metabolic phenotypes breaks down in a novel environment exposing cryptic variation. We cannot predict the physiological basis of disease in a perturbing environment from profiles observed in the ancestral environment. This study demonstrates that variation for disease traits within a population is acquired through a multitude of physiological mechanisms, some of which transcend genetic and environmental influences, and others that are specific to an individual's genetic and environmental context. PMID: 26530416 [PubMed - as supplied by publisher]

The Role of Metabolomics in the Study of Cancer Biomarkers and in the Development of Diagnostic Tools. Adv Exp Med Biol. 2015;867:41-57 Authors: Trezzi JP, Vlassis N, Hiller K Abstract This chapter introduces the emerging field of metabolomics and its application in the context of cancer biomarker research. Taking advantage of modern high-throughput technologies, and enhanced computational power, metabolomics has a high potential for cancer biomarker identification and the development of diagnostic tools. This chapter describes current metabolomics technologies used in cancer research, starting with metabolomics sample preparation, elaborating on current analytical methodologies for metabolomics measurement and introducing existing software for data analysis. The last part of this chapter deals with the statistical analysis of very large metabolomics datasets and their relevance for cancer biomarker identification. PMID: 26530359 [PubMed - in process]

Global Detection and Semi-quantification of Fritillaria Alkaloids in Fritillariae Ussuriensis Bulbus by a Non-targeted Multiple Reaction Monitoring Approach. J Sep Sci. 2015 Nov 4; Authors: Wang L, Yao ZP, Li P, Chen SB, So PK, Shi ZQ, Hu B, Liu LF, Xin GZ Abstract Methods based on triple quadrupole tandem mass spectrometry have been widely used and reported as highly selective and sensitive methods for quantifying substances of herbal medicines. However, most of them were limited to targeted components, due to the difficulties to optimize the multiple reaction monitoring transitions without authentic standards. This study proposed a novel strategy for non-targeted optimization of multiple reaction monitoring method based on the diagnostic ion guided family classifications, tandem mass spectrometry database establishment, and transitions and collision energy screening. Applying this strategy, 59 Fritillaria alkaloids in Fritillariae ussuriensis bulbus have been classified, and 51 of these Fritillaria alkaloids were successfully detected by the optimal multiple reaction monitoring method. For semi-quantification, the easy-to-get Fritillaria alkaloids of each type, such as verticinone for cevanine type and peimisine for jervine type, were used as the reference standards to calibrate the other Fritillaria alkaloids in the same type. The method was demonstrated good linearity (R(2) > 0.998) with satisfactory accuracy and precision, and the lower limit of quantifications of verticinone and peimisine were estimated to be 0.076 and 0.216 pg, respectively. In addition, the results suggested that the proposed strategy might obtained high quality metabolomics data in discrimination of Fritillaria unibracteata and Fritillaria ussuriensis. This article is protected by copyright. All rights reserved. PMID: 26530331 [PubMed - as supplied by publisher]

Related Articles An integrated analysis for determining the geographical origin of medicinal herbs using ICP-AES/ICP-MS and (1)H NMR analysis. Food Chem. 2014 Oct 15;161:168-75 Authors: Kwon YK, Bong YS, Lee KS, Hwang GS Abstract ICP-MS and (1)H NMR are commonly used to determine the geographical origin of food and crops. In this study, data from multielemental analysis performed by ICP-AES/ICP-MS and metabolomic data obtained from (1)H NMR were integrated to improve the reliability of determining the geographical origin of medicinal herbs. Astragalus membranaceus and Paeonia albiflora with different origins in Korea and China were analysed by (1)H NMR and ICP-AES/ICP-MS, and an integrated multivariate analysis was performed to characterise the differences between their origins. Four classification methods were applied: linear discriminant analysis (LDA), k-nearest neighbour classification (KNN), support vector machines (SVM), and partial least squares-discriminant analysis (PLS-DA). Results were compared using leave-one-out cross-validation and external validation. The integration of multielemental and metabolomic data was more suitable for determining geographical origin than the use of each individual data set alone. The integration of the two analytical techniques allowed diverse environmental factors such as climate and geology, to be considered. Our study suggests that an appropriate integration of different types of analytical data is useful for determining the geographical origin of food and crops with a high degree of reliability. PMID: 24837936 [PubMed - indexed for MEDLINE]

Related Articles A powerful methodological approach combining headspace solid phase microextraction, mass spectrometry and multivariate analysis for profiling the volatile metabolomic pattern of beer starting raw materials. Food Chem. 2014 Oct 1;160:266-80 Authors: Gonçalves JL, Figueira JA, Rodrigues FP, Ornelas LP, Branco RN, Silva CL, Câmara JS Abstract The volatile metabolomic patterns from different raw materials commonly used in beer production, namely barley, corn and hop-derived products - such as hop pellets, hop essential oil from Saaz variety and tetra-hydro isomerized hop extract (tetra hop), were established using a suitable analytical procedure based on dynamic headspace solid-phase microextraction (HS-SPME) followed by thermal desorption gas chromatography-quadrupole mass spectrometry detection (GC-qMS). Some SPME extraction parameters were optimized. The best results, in terms of maximum signal recorded and number of isolated metabolites, were obtained with a 50/30 μm DVB/CAR/PDMS coating fiber at 40 °C for 30 min. A set of 152 volatile metabolites comprising ketones (27), sesquiterpenes (26), monoterpenes (19), aliphatic esters (19), higher alcohols (15), aldehydes (11), furan compounds (11), aliphatic fatty acids (9), aliphatic hydrocarbons (8), sulphur compounds (5) and nitrogen compounds (2) were positively identified. Each raw material showed a specific volatile metabolomic profile. Monoterpenes in hop essential oil and corn, sesquiterpenes in hop pellets, ketones in tetra hop and aldehydes and sulphur compounds in barley were the predominant chemical families in the targeted beer raw materials. β-Myrcene was the most dominant volatile metabolite in hop essential oil, hop pellets and corn samples while, in barley, the predominant volatile metabolites were dimethyl sulphide and 3-methylbutanal and, in tetra hop, 6-methyl-2-pentanone and 4-methyl-2-pentanone. Principal component analysis (PCA) showed natural sample grouping among beer raw materials. PMID: 24799238 [PubMed - indexed for MEDLINE]