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Sample records for metabolome annotation quality

  1. Quality assurance of metabolomics.

    PubMed

    Bouhifd, Mounir; Beger, Richard; Flynn, Thomas; Guo, Lining; Harris, Georgina; Hogberg, Helena; Kaddurah-Daouk, Rima; Kamp, Hennicke; Kleensang, Andre; Maertens, Alexandra; Odwin-DaCosta, Shelly; Pamies, David; Robertson, Donald; Smirnova, Lena; Sun, Jinchun; Zhao, Liang; Hartung, Thomas

    2015-01-01

    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.

  2. Quality of computationally inferred gene ontology annotations.

    PubMed

    Skunca, Nives; Altenhoff, Adrian; Dessimoz, Christophe

    2012-05-01

    Gene Ontology (GO) has established itself as the undisputed standard for protein function annotation. Most annotations are inferred electronically, i.e. without individual curator supervision, but they are widely considered unreliable. At the same time, we crucially depend on those automated annotations, as most newly sequenced genomes are non-model organisms. Here, we introduce a methodology to systematically and quantitatively evaluate electronic annotations. By exploiting changes in successive releases of the UniProt Gene Ontology Annotation database, we assessed the quality of electronic annotations in terms of specificity, reliability, and coverage. Overall, we not only found that electronic annotations have significantly improved in recent years, but also that their reliability now rivals that of annotations inferred by curators when they use evidence other than experiments from primary literature. This work provides the means to identify the subset of electronic annotations that can be relied upon-an important outcome given that >98% of all annotations are inferred without direct curation.

  3. Quality of Computationally Inferred Gene Ontology Annotations

    PubMed Central

    Škunca, Nives; Altenhoff, Adrian; Dessimoz, Christophe

    2012-01-01

    Gene Ontology (GO) has established itself as the undisputed standard for protein function annotation. Most annotations are inferred electronically, i.e. without individual curator supervision, but they are widely considered unreliable. At the same time, we crucially depend on those automated annotations, as most newly sequenced genomes are non-model organisms. Here, we introduce a methodology to systematically and quantitatively evaluate electronic annotations. By exploiting changes in successive releases of the UniProt Gene Ontology Annotation database, we assessed the quality of electronic annotations in terms of specificity, reliability, and coverage. Overall, we not only found that electronic annotations have significantly improved in recent years, but also that their reliability now rivals that of annotations inferred by curators when they use evidence other than experiments from primary literature. This work provides the means to identify the subset of electronic annotations that can be relied upon—an important outcome given that >98% of all annotations are inferred without direct curation. PMID:22693439

  4. Automated Annotation and Evaluation of In-Source Mass Spectra in GC/Atmospheric Pressure Chemical Ionization-MS-Based Metabolomics.

    PubMed

    Jaeger, Carsten; Hoffmann, Friederike; Schmitt, Clemens A; Lisec, Jan

    2016-10-04

    Gas chromatography using atmospheric pressure chemical ionization coupled to mass spectrometry (GC/APCI-MS) is an emerging metabolomics platform, providing much-enhanced capabilities for structural mass spectrometry as compared to traditional electron ionization (EI)-based techniques. To exploit the potential of GC/APCI-MS for more comprehensive metabolite annotation, a major bottleneck in metabolomics, we here present the novel R-based tool InterpretMSSpectrum assisting in the common task of annotating and evaluating in-source mass spectra as obtained from typical full-scan experiments. After passing a list of mass-intensity pairs, InterpretMSSpectrum locates the molecular ion (M0), fragment, and adduct peaks, calculates their most likely sum formula combination, and graphically summarizes results as an annotated mass spectrum. Using (modifiable) filter rules for the commonly used methoximated-trimethylsilylated (MeOx-TMS) derivatives, covering elemental composition, typical substructures, neutral losses, and adducts, InterpretMSSpectrum significantly reduces the number of sum formula candidates, minimizing manual effort for postprocessing candidate lists. We demonstrate the utility of InterpretMSSpectrum for 86 in-source spectra of derivatized standard compounds, in which rank-1 sum formula assignments were achieved in 84% of the cases, compared to only 63% when using mass and isotope information on the M0 alone. We further use, for the first time, automated annotation to evaluate the purity of pseudospectra generated by different metabolomics preprocessing tools, showing that automated annotation can serve as an integrative quality measure for peak picking/deconvolution methods. As an R package, InterpretMSSpectrum integrates flexibly into existing metabolomics pipelines and is freely available from CRAN ( https://cran.r-project.org/ ).

  5. Annotation of plant gene function via combined genomics, metabolomics and informatics.

    PubMed

    Tohge, Takayuki; Fernie, Alisdair R

    2012-06-17

    Given the ever expanding number of model plant species for which complete genome sequences are available and the abundance of bio-resources such as knockout mutants, wild accessions and advanced breeding populations, there is a rising burden for gene functional annotation. In this protocol, annotation of plant gene function using combined co-expression gene analysis, metabolomics and informatics is provided (Figure 1). This approach is based on the theory of using target genes of known function to allow the identification of non-annotated genes likely to be involved in a certain metabolic process, with the identification of target compounds via metabolomics. Strategies are put forward for applying this information on populations generated by both forward and reverse genetics approaches in spite of none of these are effortless. By corollary this approach can also be used as an approach to characterise unknown peaks representing new or specific secondary metabolites in the limited tissues, plant species or stress treatment, which is currently the important trial to understanding plant metabolism.

  6. ProbMetab: an R package for Bayesian probabilistic annotation of LC-MS-based metabolomics.

    PubMed

    Silva, Ricardo R; Jourdan, Fabien; Salvanha, Diego M; Letisse, Fabien; Jamin, Emilien L; Guidetti-Gonzalez, Simone; Labate, Carlos A; Vêncio, Ricardo Z N

    2014-05-01

    We present ProbMetab, an R package that promotes substantial improvement in automatic probabilistic liquid chromatography-mass spectrometry-based metabolome annotation. The inference engine core is based on a Bayesian model implemented to (i) allow diverse source of experimental data and metadata to be systematically incorporated into the model with alternative ways to calculate the likelihood function and (ii) allow sensitive selection of biologically meaningful biochemical reaction databases as Dirichlet-categorical prior distribution. Additionally, to ensure result interpretation by system biologists, we display the annotation in a network where observed mass peaks are connected if their candidate metabolites are substrate/product of known biochemical reactions. This graph can be overlaid with other graph-based analysis, such as partial correlation networks, in a visualization scheme exported to Cytoscape, with web and stand-alone versions.

  7. Educational Quality Indicators: Annotated Bibliography. Second Edition.

    ERIC Educational Resources Information Center

    Alberta Dept. of Education, Edmonton.

    This annotated bibliography of journal articles and documents on educational quality indicators contains approximately 230 entries arranged by the following topics: (1) indicator systems, including international, local/provincial/state, models, and national/federal systems; (2) interpretive framework (context, inputs, processes), including…

  8. Quality Management: An Annotated Bibliography.

    DTIC Science & Technology

    1986-06-01

    Garvin , D. A. (1983). Quality on the line. Harvard Business Review, 61( 5 ), 64-75. Key Terms: Case Histories...8217 ’. ," . ." . . .’ " . - "" , . . • " . ’ "" . - . I ’-4 * 0 Pavsidis, C. (1983). Zero defect programs thriving in Japan. b Quality Progress, 16( 5 ), 34-35. Key Terms: Approaches to QM/History of QM/SPC...1984). Quality Progress, 17(10), 32-37. Key Terms: Approaches to QM/SPC. Abstract: Feigenbaum , Juran, and Crosby

  9. ProbMetab: an R package for Bayesian probabilistic annotation of LC–MS-based metabolomics

    PubMed Central

    Silva, Ricardo R.; Jourdan, Fabien; Salvanha, Diego M.; Letisse, Fabien; Jamin, Emilien L.; Guidetti-Gonzalez, Simone; Labate, Carlos A.; Vêncio, Ricardo Z. N.

    2014-01-01

    Summary: We present ProbMetab, an R package that promotes substantial improvement in automatic probabilistic liquid chromatography–mass spectrometry-based metabolome annotation. The inference engine core is based on a Bayesian model implemented to (i) allow diverse source of experimental data and metadata to be systematically incorporated into the model with alternative ways to calculate the likelihood function and (ii) allow sensitive selection of biologically meaningful biochemical reaction databases as Dirichlet-categorical prior distribution. Additionally, to ensure result interpretation by system biologists, we display the annotation in a network where observed mass peaks are connected if their candidate metabolites are substrate/product of known biochemical reactions. This graph can be overlaid with other graph-based analysis, such as partial correlation networks, in a visualization scheme exported to Cytoscape, with web and stand-alone versions. Availability and implementation: ProbMetab was implemented in a modular manner to fit together with established upstream (xcms, CAMERA, AStream, mzMatch.R, etc) and downstream R package tools (GeneNet, RCytoscape, DiffCorr, etc). ProbMetab, along with extensive documentation and case studies, is freely available under GNU license at: http://labpib.fmrp.usp.br/methods/probmetab/. Contact: rvencio@usp.br Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24443383

  10. Annotated bibliography on forest practices legislation related to water quality

    Treesearch

    Neil K. Huyler; David McMath; Daphne Hewitt

    1999-01-01

    Includes annotated citations of literature on forest practices regulations related to all aspects of water quality protection. The bibliography is divided into three sections: 1) Water quality protection during timber harvesting; 2) Methods for assessing the costs and benefits of water quality protection; and 3) Effectiveness of regulatory programs in protecting water...

  11. Experimental Strategies for Functional Annotation and Metabolism Discovery: Targeted Screening of Solute Binding Proteins and Unbiased Panning of Metabolomes

    PubMed Central

    2015-01-01

    The rate at which genome sequencing data is accruing demands enhanced methods for functional annotation and metabolism discovery. Solute binding proteins (SBPs) facilitate the transport of the first reactant in a metabolic pathway, thereby constraining the regions of chemical space and the chemistries that must be considered for pathway reconstruction. We describe high-throughput protein production and differential scanning fluorimetry platforms, which enabled the screening of 158 SBPs against a 189 component library specifically tailored for this class of proteins. Like all screening efforts, this approach is limited by the practical constraints imposed by construction of the library, i.e., we can study only those metabolites that are known to exist and which can be made in sufficient quantities for experimentation. To move beyond these inherent limitations, we illustrate the promise of crystallographic- and mass spectrometric-based approaches for the unbiased use of entire metabolomes as screening libraries. Together, our approaches identified 40 new SBP ligands, generated experiment-based annotations for 2084 SBPs in 71 isofunctional clusters, and defined numerous metabolic pathways, including novel catabolic pathways for the utilization of ethanolamine as sole nitrogen source and the use of d-Ala-d-Ala as sole carbon source. These efforts begin to define an integrated strategy for realizing the full value of amassing genome sequence data. PMID:25540822

  12. Experimental Strategies for Functional Annotation and Metabolism Discovery: Targeted Screening of Solute Binding Proteins and Unbiased Panning of Metabolomes

    SciTech Connect

    Vetting, Matthew W.; Al-Obaidi, Nawar; Zhao, Suwen; San Francisco, Brian; Kim, Jungwook; Wichelecki, Daniel J.; Bouvier, Jason T.; Solbiati, Jose O.; Vu, Hoan; Zhang, Xinshuai; Rodionov, Dmitry A.; Love, James D.; Hillerich, Brandan S.; Seidel, Ronald D.; Quinn, Ronald J.; Osterman, Andrei L.; Cronan, John E.; Jacobson, Matthew P.; Gerlt, John A.; Almo, Steven C.

    2014-12-25

    The rate at which genome sequencing data is accruing demands enhanced methods for functional annotation and metabolism discovery. Solute binding proteins (SBPs) facilitate the transport of the first reactant in a metabolic pathway, thereby constraining the regions of chemical space and the chemistries that must be considered for pathway reconstruction. Here in this paper, we describe high-throughput protein production and differential scanning fluorimetry platforms, which enabled the screening of 158 SBPs against a 189 component library specifically tailored for this class of proteins. Like all screening efforts, this approach is limited by the practical constraints imposed by construction of the library, i.e., we can study only those metabolites that are known to exist and which can be made in sufficient quantities for experimentation. To move beyond these inherent limitations, we illustrate the promise of crystallographic- and mass spectrometric-based approaches for the unbiased use of entire metabolomes as screening libraries. Together, our approaches identified 40 new SBP ligands, generated experiment-based annotations for 2084 SBPs in 71 isofunctional clusters, and defined numerous metabolic pathways, including novel catabolic pathways for the utilization of ethanolamine as sole nitrogen source and the use of D-Ala-D-Ala as sole carbon source. These efforts begin to define an integrated strategy for realizing the full value of amassing genome sequence data.

  13. Experimental Strategies for Functional Annotation and Metabolism Discovery: Targeted Screening of Solute Binding Proteins and Unbiased Panning of Metabolomes

    DOE PAGES

    Vetting, Matthew W.; Al-Obaidi, Nawar; Zhao, Suwen; ...

    2014-12-25

    The rate at which genome sequencing data is accruing demands enhanced methods for functional annotation and metabolism discovery. Solute binding proteins (SBPs) facilitate the transport of the first reactant in a metabolic pathway, thereby constraining the regions of chemical space and the chemistries that must be considered for pathway reconstruction. Here in this paper, we describe high-throughput protein production and differential scanning fluorimetry platforms, which enabled the screening of 158 SBPs against a 189 component library specifically tailored for this class of proteins. Like all screening efforts, this approach is limited by the practical constraints imposed by construction of themore » library, i.e., we can study only those metabolites that are known to exist and which can be made in sufficient quantities for experimentation. To move beyond these inherent limitations, we illustrate the promise of crystallographic- and mass spectrometric-based approaches for the unbiased use of entire metabolomes as screening libraries. Together, our approaches identified 40 new SBP ligands, generated experiment-based annotations for 2084 SBPs in 71 isofunctional clusters, and defined numerous metabolic pathways, including novel catabolic pathways for the utilization of ethanolamine as sole nitrogen source and the use of D-Ala-D-Ala as sole carbon source. These efforts begin to define an integrated strategy for realizing the full value of amassing genome sequence data.« less

  14. Semi-automatic semantic annotation of PubMed queries: a study on quality, efficiency, satisfaction.

    PubMed

    Névéol, Aurélie; Islamaj Doğan, Rezarta; Lu, Zhiyong

    2011-04-01

    Information processing algorithms require significant amounts of annotated data for training and testing. The availability of such data is often hindered by the complexity and high cost of production. In this paper, we investigate the benefits of a state-of-the-art tool to help with the semantic annotation of a large set of biomedical queries. Seven annotators were recruited to annotate a set of 10,000 PubMed® queries with 16 biomedical and bibliographic categories. About half of the queries were annotated from scratch, while the other half were automatically pre-annotated and manually corrected. The impact of the automatic pre-annotations was assessed on several aspects of the task: time, number of actions, annotator satisfaction, inter-annotator agreement, quality and number of the resulting annotations. The analysis of annotation results showed that the number of required hand annotations is 28.9% less when using pre-annotated results from automatic tools. As a result, the overall annotation time was substantially lower when pre-annotations were used, while inter-annotator agreement was significantly higher. In addition, there was no statistically significant difference in the semantic distribution or number of annotations produced when pre-annotations were used. The annotated query corpus is freely available to the research community. This study shows that automatic pre-annotations are found helpful by most annotators. Our experience suggests using an automatic tool to assist large-scale manual annotation projects. This helps speed-up the annotation time and improve annotation consistency while maintaining high quality of the final annotations.

  15. Semi-automatic semantic annotation of PubMed Queries: a study on quality, efficiency, satisfaction

    PubMed Central

    Névéol, Aurélie; Islamaj-Doğan, Rezarta; Lu, Zhiyong

    2010-01-01

    Information processing algorithms require significant amounts of annotated data for training and testing. The availability of such data is often hindered by the complexity and high cost of production. In this paper, we investigate the benefits of a state-of-the-art tool to help with the semantic annotation of a large set of biomedical information queries. Seven annotators were recruited to annotate a set of 10,000 PubMed® queries with 16 biomedical and bibliographic categories. About half of the queries were annotated from scratch, while the other half were automatically pre-annotated and manually corrected. The impact of the automatic pre-annotations was assessed on several aspects of the task: time, number of actions, annotator satisfaction, inter-annotator agreement, quality and number of the resulting annotations. The analysis of annotation results showed that the number of required hand annotations is 28.9% less when using pre-annotated results from automatic tools. As a result, the overall annotation time was substantially lower when pre-annotations were used, while inter-annotator agreement was significantly higher. In addition, there was no statistically significant difference in the semantic distribution or number of annotations produced when pre-annotations were used. The annotated query corpus is freely available to the research community. This study shows that automatic pre-annotations are found helpful by most annotators. Our experience suggests using an automatic tool to assist large-scale manual annotation projects. This helps speed-up the annotation time and improve annotation consistency while maintaining high quality of the final annotations. PMID:21094696

  16. Toward better annotation in plant metabolomics: isolation and structure elucidation of 36 specialized metabolites from Oryza sativa (rice) by using MS/MS and NMR analyses.

    PubMed

    Yang, Zhigang; Nakabayashi, Ryo; Okazaki, Yozo; Mori, Tetsuya; Takamatsu, Satoshi; Kitanaka, Susumu; Kikuchi, Jun; Saito, Kazuki

    2014-01-01

    Metabolomics plays an important role in phytochemical genomics and crop breeding; however, metabolite annotation is a significant bottleneck in metabolomic studies. In particular, in liquid chromatography-mass spectrometry (MS)-based metabolomics, which has become a routine technology for the profiling of plant-specialized metabolites, a substantial number of metabolites detected as MS peaks are still not assigned properly to a single metabolite. Oryza sativa (rice) is one of the most important staple crops in the world. In the present study, we isolated and elucidated the structures of specialized metabolites from rice by using MS/MS and NMR. Thirty-six compounds, including five new flavonoids and eight rare flavonolignan isomers, were isolated from the rice leaves. The MS/MS spectral data of the isolated compounds, with a detailed interpretation of MS fragmentation data, will facilitate metabolite annotation of the related phytochemicals by enriching the public mass spectral data depositories, including the plant-specific MS/MS-based database, ReSpect.

  17. Automated LC-HRMS(/MS) approach for the annotation of fragment ions derived from stable isotope labeling-assisted untargeted metabolomics.

    PubMed

    Neumann, Nora K N; Lehner, Sylvia M; Kluger, Bernhard; Bueschl, Christoph; Sedelmaier, Karoline; Lemmens, Marc; Krska, Rudolf; Schuhmacher, Rainer

    2014-08-05

    Structure elucidation of biological compounds is still a major bottleneck of untargeted LC-HRMS approaches in metabolomics research. The aim of the present study was to combine stable isotope labeling and tandem mass spectrometry for the automated interpretation of the elemental composition of fragment ions and thereby facilitate the structural characterization of metabolites. The software tool FragExtract was developed and evaluated with LC-HRMS/MS spectra of both native (12)C- and uniformly (13)C (U-(13)C)-labeled analytical standards of 10 fungal substances in pure solvent and spiked into fungal culture filtrate of Fusarium graminearum respectively. Furthermore, the developed approach is exemplified with nine unknown biochemical compounds contained in F. graminearum samples derived from an untargeted metabolomics experiment. The mass difference between the corresponding fragment ions present in the MS/MS spectra of the native and U-(13)C-labeled compound enabled the assignment of the number of carbon atoms to each fragment signal and allowed the generation of meaningful putative molecular formulas for each fragment ion, which in turn also helped determine the elemental composition of the precursor ion. Compared to laborious manual analysis of the MS/MS spectra, the presented algorithm marks an important step toward efficient fragment signal elucidation and structure annotation of metabolites in future untargeted metabolomics studies. Moreover, as demonstrated for a fungal culture sample, FragExtract also assists the characterization of unknown metabolites, which are not contained in databases, and thus exhibits a significant contribution to untargeted metabolomics research.

  18. Metabolomic Quality Assessment of EDTA Plasma and Serum Samples.

    PubMed

    Malm, Linus; Tybring, Gunnel; Moritz, Thomas; Landin, Britta; Galli, Joakim

    2016-10-01

    Handling and processing of blood can significantly alter the molecular composition and consistency of biobank samples and can have a major impact on the identification of biomarkers. It is thus crucial to identify tools to determine the quality of samples to be used in biomarker discovery studies. In this study, a non-targeted gas chromatography/time-of-flight mass spectrometry (GC-TOFMS) metabolomic strategy was used with the aim of identifying quality markers for serum and plasma biobank collections lacking proper documentation of preanalytical handling. The effect of postcentrifugation delay was examined in serum stored in tubes with gel separation plugs and ethylenediaminetetraacetic acid (EDTA) plasma in tubes with or without gel separation plugs. The change in metabolic pattern was negligible in all sample types processed within 3 hours after centrifugation regardless of whether the samples were kept at 4°C or 22°C. After 8 and 24 hours postcentrifugation delay before aliquoting, there was a pronounced increase in the number of affected metabolites, as well as in the magnitude of the observed changes. No protective effect on the metabolites was observed in gel-separated EDTA plasma samples. In a separate series of experiments, lactate and glucose levels were determined in plasma to estimate the effect of precentrifugation delay. This separate experiment indicates that the lactate to glucose ratio may serve as a marker to identify samples with delayed time to centrifugation. Although our data from the untargeted GC-TOFMS analysis did not identify any specific markers, we conclude that plasma and serum metabolic profiles remain quite stable when plasma and serum are centrifuged and separated from the blood cells within 3 hours.

  19. Metabolomic Technologies for Improving the Quality of Food: Practice and Promise.

    PubMed

    Johanningsmeier, Suzanne D; Harris, G Keith; Klevorn, Claire M

    2016-01-01

    It is now well documented that the diet has a significant impact on human health and well-being. However, the complete set of small molecule metabolites present in foods that make up the human diet and the role of food production systems in altering this food metabolome are still largely unknown. Metabolomic platforms that rely on nuclear magnetic resonance (NMR) and mass spectrometry (MS) analytical technologies are being employed to study the impact of agricultural practices, processing, and storage on the global chemical composition of food; to identify novel bioactive compounds; and for authentication and region-of-origin classifications. This review provides an overview of the current terminology, analytical methods, and compounds associated with metabolomic studies, and provides insight into the application of metabolomics to generate new knowledge that enables us to produce, preserve, and distribute high-quality foods for health promotion.

  20. Automated LC-HRMS(/MS) Approach for the Annotation of Fragment Ions Derived from Stable Isotope Labeling-Assisted Untargeted Metabolomics

    PubMed Central

    2014-01-01

    Structure elucidation of biological compounds is still a major bottleneck of untargeted LC-HRMS approaches in metabolomics research. The aim of the present study was to combine stable isotope labeling and tandem mass spectrometry for the automated interpretation of the elemental composition of fragment ions and thereby facilitate the structural characterization of metabolites. The software tool FragExtract was developed and evaluated with LC-HRMS/MS spectra of both native 12C- and uniformly 13C (U-13C)-labeled analytical standards of 10 fungal substances in pure solvent and spiked into fungal culture filtrate of Fusarium graminearum respectively. Furthermore, the developed approach is exemplified with nine unknown biochemical compounds contained in F. graminearum samples derived from an untargeted metabolomics experiment. The mass difference between the corresponding fragment ions present in the MS/MS spectra of the native and U-13C-labeled compound enabled the assignment of the number of carbon atoms to each fragment signal and allowed the generation of meaningful putative molecular formulas for each fragment ion, which in turn also helped determine the elemental composition of the precursor ion. Compared to laborious manual analysis of the MS/MS spectra, the presented algorithm marks an important step toward efficient fragment signal elucidation and structure annotation of metabolites in future untargeted metabolomics studies. Moreover, as demonstrated for a fungal culture sample, FragExtract also assists the characterization of unknown metabolites, which are not contained in databases, and thus exhibits a significant contribution to untargeted metabolomics research. PMID:24965664

  1. Different Statistical Approaches to Investigate Porcine Muscle Metabolome Profiles to Highlight New Biomarkers for Pork Quality Assessment

    PubMed Central

    Welzenbach, Julia; Neuhoff, Christiane; Looft, Christian; Schellander, Karl; Tholen, Ernst; Große-Brinkhaus, Christine

    2016-01-01

    The aim of this study was to elucidate the underlying biochemical processes to identify potential key molecules of meat quality traits drip loss, pH of meat 1 h post-mortem (pH1), pH in meat 24 h post-mortem (pH24) and meat color. An untargeted metabolomics approach detected the profiles of 393 annotated and 1,600 unknown metabolites in 97 Duroc × Pietrain pigs. Despite obvious differences regarding the statistical approaches, the four applied methods, namely correlation analysis, principal component analysis, weighted network analysis (WNA) and random forest regression (RFR), revealed mainly concordant results. Our findings lead to the conclusion that meat quality traits pH1, pH24 and color are strongly influenced by processes of post-mortem energy metabolism like glycolysis and pentose phosphate pathway, whereas drip loss is significantly associated with metabolites of lipid metabolism. In case of drip loss, RFR was the most suitable method to identify reliable biomarkers and to predict the phenotype based on metabolites. On the other hand, WNA provides the best parameters to investigate the metabolite interactions and to clarify the complex molecular background of meat quality traits. In summary, it was possible to attain findings on the interaction of meat quality traits and their underlying biochemical processes. The detected key metabolites might be better indicators of meat quality especially of drip loss than the measured phenotype itself and potentially might be used as bio indicators. PMID:26919205

  2. Annotation of the Staphylococcus aureus Metabolome Using Liquid Chromatography Coupled to High-Resolution Mass Spectrometry and Application to the Study of Methicillin Resistance.

    PubMed

    Aros-Calt, Sandrine; Muller, Bruno H; Boudah, Samia; Ducruix, Céline; Gervasi, Gaspard; Junot, Christophe; Fenaille, François

    2015-11-06

    Staphylococcus aureus can cause a variety of severe disease patterns and can readily acquire antibiotic resistance; however, the mechanisms by which this commensal becomes a pathogen or develops antibiotic resistance are still poorly understood. Here we asked whether metabolomics can be used to distinguish bacterial strains with different antibiotic susceptibilities. Thus, an efficient and robust method was first thoroughly implemented to measure the intracellular metabolites of S. aureus in an unbiased and reproducible manner. We also placed special emphasis on metabolome coverage and annotation and used both hydrophilic interaction liquid chromatography and pentafluorophenyl-propyl columns coupled to high-resolution mass spectrometry in conjunction with our spectral database developed in-house to identify with high confidence as many meaningful S. aureus metabolites as possible. Overall, we were able to characterize up to 210 metabolites in S. aureus, which represents a substantial ∼50% improvement over previously published data. We then preliminarily compared the metabolic profiles of 10 clinically relevant methicillin-resistant and susceptible strains harvested at different time points during the exponential growth phase (without any antibiotic exposure). Interestingly, the resulting data revealed a distinct behavior of "slow-growing" resistant strains, which show modified levels of several precursors of peptidoglycan and capsular polysaccharide biosynthesis.

  3. Direct infusion mass spectrometry metabolomics dataset: a benchmark for data processing and quality control.

    PubMed

    Kirwan, Jennifer A; Weber, Ralf J M; Broadhurst, David I; Viant, Mark R

    2014-01-01

    Direct-infusion mass spectrometry (DIMS) metabolomics is an important approach for characterising molecular responses of organisms to disease, drugs and the environment. Increasingly large-scale metabolomics studies are being conducted, necessitating improvements in both bioanalytical and computational workflows to maintain data quality. This dataset represents a systematic evaluation of the reproducibility of a multi-batch DIMS metabolomics study of cardiac tissue extracts. It comprises of twenty biological samples (cow vs. sheep) that were analysed repeatedly, in 8 batches across 7 days, together with a concurrent set of quality control (QC) samples. Data are presented from each step of the workflow and are available in MetaboLights. The strength of the dataset is that intra- and inter-batch variation can be corrected using QC spectra and the quality of this correction assessed independently using the repeatedly-measured biological samples. Originally designed to test the efficacy of a batch-correction algorithm, it will enable others to evaluate novel data processing algorithms. Furthermore, this dataset serves as a benchmark for DIMS metabolomics, derived using best-practice workflows and rigorous quality assessment.

  4. Direct infusion mass spectrometry metabolomics dataset: a benchmark for data processing and quality control

    PubMed Central

    Kirwan, Jennifer A; Weber, Ralf J M; Broadhurst, David I; Viant, Mark R

    2014-01-01

    Direct-infusion mass spectrometry (DIMS) metabolomics is an important approach for characterising molecular responses of organisms to disease, drugs and the environment. Increasingly large-scale metabolomics studies are being conducted, necessitating improvements in both bioanalytical and computational workflows to maintain data quality. This dataset represents a systematic evaluation of the reproducibility of a multi-batch DIMS metabolomics study of cardiac tissue extracts. It comprises of twenty biological samples (cow vs. sheep) that were analysed repeatedly, in 8 batches across 7 days, together with a concurrent set of quality control (QC) samples. Data are presented from each step of the workflow and are available in MetaboLights. The strength of the dataset is that intra- and inter-batch variation can be corrected using QC spectra and the quality of this correction assessed independently using the repeatedly-measured biological samples. Originally designed to test the efficacy of a batch-correction algorithm, it will enable others to evaluate novel data processing algorithms. Furthermore, this dataset serves as a benchmark for DIMS metabolomics, derived using best-practice workflows and rigorous quality assessment. PMID:25977770

  5. A Novel Quality Measure and Correction Procedure for the Annotation of Microbial Translation Initiation Sites

    PubMed Central

    Overmars, Lex; Siezen, Roland J.; Francke, Christof

    2015-01-01

    The identification of translation initiation sites (TISs) constitutes an important aspect of sequence-based genome analysis. An erroneous TIS annotation can impair the identification of regulatory elements and N-terminal signal peptides, and also may flaw the determination of descent, for any particular gene. We have formulated a reference-free method to score the TIS annotation quality. The method is based on a comparison of the observed and expected distribution of all TISs in a particular genome given prior gene-calling. We have assessed the TIS annotations for all available NCBI RefSeq microbial genomes and found that approximately 87% is of appropriate quality, whereas 13% needs substantial improvement. We have analyzed a number of factors that could affect TIS annotation quality such as GC-content, taxonomy, the fraction of genes with a Shine-Dalgarno sequence and the year of publication. The analysis showed that only the first factor has a clear effect. We have then formulated a straightforward Principle Component Analysis-based TIS identification strategy to self-organize and score potential TISs. The strategy is independent of reference data and a priori calculations. A representative set of 277 genomes was subjected to the analysis and we found a clear increase in TIS annotation quality for the genomes with a low quality score. The PCA-based annotation was also compared with annotation with the current tool of reference, Prodigal. The comparison for the model genome of Escherichia coli K12 showed that both methods supplement each other and that prediction agreement can be used as an indicator of a correct TIS annotation. Importantly, the data suggest that the addition of a PCA-based strategy to a Prodigal prediction can be used to ‘flag’ TIS annotations for re-evaluation and in addition can be used to evaluate a given annotation in case a Prodigal annotation is lacking. PMID:26204119

  6. Implementation of a semi-automated strategy for the annotation of metabolomic fingerprints generated by liquid chromatography-high resolution mass spectrometry from biological samples.

    PubMed

    Courant, Frédérique; Royer, Anne-Lise; Chéreau, Sylvain; Morvan, Marie-Line; Monteau, Fabrice; Antignac, Jean-Philippe; Le Bizec, Bruno

    2012-11-07

    Metabolomics aims at detecting and semi-quantifying small molecular weight metabolites in biological samples in order to characterise the metabolic changes resulting from one or more given factors and/or to develop models based on diagnostic biomarker candidates. Nevertheless, whatever the objective of a metabolomic study, one critical step consists in the structural identification of mass spectrometric features revealed by statistical analysis and this remains a real challenge. Indeed, this requires both an understanding of the studied biological system, the correct use of various analytical information (retention time, molecular weight experimentally measured, isotopic golden rules, MS/MS fragment pattern interpretation…), or querying online databases. In gas chromatography-electro-ionisation (EI)-mass spectrometry, EI leads to a very reproducible fragmentation allowing establishment of universal EI mass spectra databases (for example, the NIST database -National Institute of Standards and Technology) and thus facilitates the identification step. Unfortunately, the situation is different when working with liquid chromatography-mass spectrometry (LC-MS) since atmospheric pressure ionisation exhibits high inter-instrument variability regarding fragmentation. Therefore, the constitution of LC-MS "in-house" spectral databases appears relevant in this context. The present study describes the procedure developed and applied to increment 133 and 130 metabolites in databanks dedicated to analyses performed with LC-HRMS in positive and negative electrospray ionisation, and the use of these databanks for annotating quickly untargeted metabolomics fingerprints. This study also describes the optimization of the parameters controlling the automatic processing in order to obtain a fast and reliable annotation of a maximum of organic compounds. This strategy was applied to bovine kidney samples collected from control animals or animals treated with steroid hormones. Thirty

  7. Automatic assessment of voice quality in the context of multiple annotations.

    PubMed

    Gil González, Julián; Álvarez, Mauricio A; Orozco, Álvaro A

    2015-01-01

    Approaches to evaluate voice quality include perceptual analysis, and acoustical analysis. Perceptual analysis is subjective and depends mostly on the ability of a specialist to assess a pathology, whereas acoustical analysis is objective, but highly relies on the quality of the so called annotations that the specialist assigns to the voice signal. The quality of the annotations for acoustical analysis depends heavily on the expertise and knowledge of the specialist. We face a scenario where we have annotations performed by several specialists with different levels of expertise and knowledge. Traditional pattern recognition methods employed in acoustical analysis are no longer applicable, since these methods are designed for scenarios where a "ground-truth" label is assigned by the specialist. In this paper, we apply recent developments in machine learning for taking into account multiple annotators for acoustical analysis of voice signals. For the classification step we compare two techniques, one of them based on Gaussian Processes for regression with multiple annotators, and the other is a multi-class Logistic Regression model that measures the annotator performance in terms of sensitivity and specificity. The performance of classifiers is assessed in terms of Cohen's Kappa index. Results show that the multi-annotator classification schemes have better performance when compared to techniques based on a traditional classifier where the true label is estimated from the multiple annotations available using majority voting.

  8. Application of Metabolomics to Quality Control of Natural Product Derived Medicines.

    PubMed

    Lee, Kyung-Min; Jeon, Jun-Yeong; Lee, Byeong-Ju; Lee, Hwanhui; Choi, Hyung-Kyoon

    2017-06-14

    Metabolomics has been used as a powerful tool for the analysis and quality assessment of the natural product (NP)-derived medicines. It is increasingly being used in the quality control and standardization of NP-derived medicines because they are composed of hundreds of natural compounds. The most common techniques that are used in metabolomics consist of NMR, GC-MS, and LC-MS in combination with multivariate statistical analyses including principal components analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). Currently, the quality control of the NP-derived medicines is usually conducted using HPLC and is specified by one or two indicators. To create a superior quality control framework and avoid adulterated drugs, it is necessary to be able to determine and establish standards based on multiple ingredients using metabolic profiling and fingerprinting. Therefore, the application of various analytical tools in the quality control of NP-derived medicines forms the major part of this review. Veregen(®) (Medigene AG, Planegg/Martinsried, Germany), which is the first botanical prescription drug approved by US Food and Drug Administration, is reviewed as an example that will hopefully provide future directions and perspectives on metabolomics technologies available for the quality control of NP-derived medicines.

  9. Effect of masticatory stimulation on the quantity and quality of saliva and the salivary metabolomic profile.

    PubMed

    Okuma, Nobuyuki; Saita, Makiko; Hoshi, Noriyuki; Soga, Tomoyoshi; Tomita, Masaru; Sugimoto, Masahiro; Kimoto, Katsuhiko

    2017-01-01

    This study characterized the changes in quality and quantity of saliva, and changes in the salivary metabolomic profile, to understand the effects of masticatory stimulation. Stimulated and unstimulated saliva samples were collected from 55 subjects and salivary hydrophilic metabolites were comprehensively quantified using capillary electrophoresis-time-of-flight mass spectrometry. In total, 137 metabolites were identified and quantified. The concentrations of 44 metabolites in stimulated saliva were significantly higher than those in unstimulated saliva. Pathway analysis identified the upregulation of the urea cycle and synthesis and degradation pathways of glycine, serine, cysteine and threonine in stimulated saliva. A principal component analysis revealed that the effect of masticatory stimulation on salivary metabolomic profiles was less dependent on sample population sex, age, and smoking. The concentrations of only 1 metabolite in unstimulated saliva, and of 3 metabolites stimulated saliva, showed significant correlation with salivary secretion volume, indicating that the salivary metabolomic profile and salivary secretion volume were independent factors. Masticatory stimulation affected not only salivary secretion volume, but also metabolite concentration patterns. A low correlation between the secretion volume and these patterns supports the conclusion that the salivary metabolomic profile may be a new indicator to characterize masticatory stimulation.

  10. Effect of masticatory stimulation on the quantity and quality of saliva and the salivary metabolomic profile

    PubMed Central

    Hoshi, Noriyuki; Soga, Tomoyoshi; Tomita, Masaru; Sugimoto, Masahiro; Kimoto, Katsuhiko

    2017-01-01

    Background This study characterized the changes in quality and quantity of saliva, and changes in the salivary metabolomic profile, to understand the effects of masticatory stimulation. Methods Stimulated and unstimulated saliva samples were collected from 55 subjects and salivary hydrophilic metabolites were comprehensively quantified using capillary electrophoresis-time-of-flight mass spectrometry. Results In total, 137 metabolites were identified and quantified. The concentrations of 44 metabolites in stimulated saliva were significantly higher than those in unstimulated saliva. Pathway analysis identified the upregulation of the urea cycle and synthesis and degradation pathways of glycine, serine, cysteine and threonine in stimulated saliva. A principal component analysis revealed that the effect of masticatory stimulation on salivary metabolomic profiles was less dependent on sample population sex, age, and smoking. The concentrations of only 1 metabolite in unstimulated saliva, and of 3 metabolites stimulated saliva, showed significant correlation with salivary secretion volume, indicating that the salivary metabolomic profile and salivary secretion volume were independent factors. Conclusions Masticatory stimulation affected not only salivary secretion volume, but also metabolite concentration patterns. A low correlation between the secretion volume and these patterns supports the conclusion that the salivary metabolomic profile may be a new indicator to characterize masticatory stimulation. PMID:28813487

  11. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm

    PubMed Central

    Kind, Tobias; Fiehn, Oliver

    2006-01-01

    Background Metabolomic studies are targeted at identifying and quantifying all metabolites in a given biological context. Among the tools used for metabolomic research, mass spectrometry is one of the most powerful tools. However, metabolomics by mass spectrometry always reveals a high number of unknown compounds which complicate in depth mechanistic or biochemical understanding. In principle, mass spectrometry can be utilized within strategies of de novo structure elucidation of small molecules, starting with the computation of the elemental composition of an unknown metabolite using accurate masses with errors <5 ppm (parts per million). However even with very high mass accuracy (<1 ppm) many chemically possible formulae are obtained in higher mass regions. In automatic routines an additional orthogonal filter therefore needs to be applied in order to reduce the number of potential elemental compositions. This report demonstrates the necessity of isotope abundance information by mathematical confirmation of the concept. Results High mass accuracy (<1 ppm) alone is not enough to exclude enough candidates with complex elemental compositions (C, H, N, S, O, P, and potentially F, Cl, Br and Si). Use of isotopic abundance patterns as a single further constraint removes >95% of false candidates. This orthogonal filter can condense several thousand candidates down to only a small number of molecular formulas. Example calculations for 10, 5, 3, 1 and 0.1 ppm mass accuracy are given. Corresponding software scripts can be downloaded from . A comparison of eight chemical databases revealed that PubChem and the Dictionary of Natural Products can be recommended for automatic queries using molecular formulae. Conclusion More than 1.6 million molecular formulae in the range 0–500 Da were generated in an exhaustive manner under strict observation of mathematical and chemical rules. Assuming that ion species are fully resolved (either by chromatography or by high resolution

  12. A high-quality annotated transcriptome of swine peripheral blood.

    PubMed

    Liu, Haibo; Smith, Timothy P L; Nonneman, Dan J; Dekkers, Jack C M; Tuggle, Christopher K

    2017-06-24

    High throughput gene expression profiling assays of peripheral blood are widely used in biomedicine, as well as in animal genetics and physiology research. Accurate, comprehensive, and precise interpretation of such high throughput assays relies on well-characterized reference genomes and/or transcriptomes. However, neither the reference genome nor the peripheral blood transcriptome of the pig have been sufficiently assembled and annotated to support such profiling assays in this emerging biomedical model organism. We aimed to assemble published and novel RNA-seq data to provide a comprehensive, well-annotated blood transcriptome for pigs by integrating a de novo assembly with a genome-guided assembly. A de novo and a genome-guided transcriptome of porcine whole peripheral blood was assembled with ~162 million pairs of paired-end and ~183 million single-end, trimmed and normalized Illumina RNA-seq reads (~6 billion initial reads from 146 RNA-seq libraries) from five independent studies by using the Trinity and Cufflinks software, respectively. We then removed putative transcripts (PTs) of low confidence from both assemblies and merged the remaining PTs into an integrated transcriptome consisting of 132,928 PTs, with 126,225 (~95%) PTs from the de novo assembly and more than 91% of PTs spliced. In the integrated transcriptome, ~90% and 63% of PTs had significant sequence similarity to sequences in the NCBI NT and NR databases, respectively; 68,754 (~52%) PTs were annotated with 15,965 unique gene ontology (GO) terms; and 7618 PTs annotated with Enzyme Commission codes were assigned to 134 pathways curated by the Kyoto Encyclopedia of Genes and Genomes (KEGG). Full exon-intron junctions of 17,528 PTs were validated by PacBio IsoSeq full-length cDNA reads from 3 other porcine tissues, NCBI pig RefSeq mRNAs and transcripts from Ensembl Sscrofa10.2 annotation. Completeness of the 5' termini of 37,569 PTs was validated by public cap analysis of gene expression (CAGE

  13. Analysis of Annotated Data Models for Improving Data Quality.

    PubMed

    Ulrich, Hannes; Kock-Schoppenhauer, Ann-Kristin; Andersen, Björn; Ingenerf, Josef

    2017-01-01

    The public Medical Data Models (MDM) portal with more than 9.000 annotated forms from clinical trials and other sources provides many research opportunities for the medical informatics community. It is mainly used to address the problem of heterogeneity by searching, mediating, reusing, and assessing data models, e. g. the semi-interactive curation of core data records in a special domain. Furthermore, it can be used as a benchmark for evaluating algorithms that create, transform, annotate, and analyse structured patient data. Using CDISC ODM for syntactically representing all data models in the MDM portal, there are semi-automatically added UMLS CUIs at several ODM levels like ItemGroupDef, ItemDef, or CodeList item. This can improve the interpretability and processability of the received information, but only if the coded information is correct and reliable. This raises the question how to assure that semantically similar datasets are also processed and classified similarly. In this work, a (semi-)automatic approach to analyse and assess items, questions, and data elements in clinical studies is described. The approach uses a hybrid evaluation process to rate and propose semantic annotations for under-specified trial items. The evaluation algorithm operates with the commonly used NLM MetaMap to provide UMLS support and corpus-based proposal algorithms to link datasets from the provided CDISC ODM item pool.

  14. Metabolomics in food science.

    PubMed

    Cevallos-Cevallos, Juan Manuel; Reyes-De-Corcuera, José Ignacio

    2012-01-01

    Metabolomics, the newest member of the omics techniques, has become an important tool in agriculture, pharmacy, and environmental sciences. Advances in compound extraction, separation, detection, identification, and data analysis have allowed metabolomics applications in food sciences including food processing, quality, and safety. This chapter discusses recent advances and applications of metabolomics in food science. Copyright © 2012 Elsevier Inc. All rights reserved.

  15. QCScreen: a software tool for data quality control in LC-HRMS based metabolomics.

    PubMed

    Simader, Alexandra Maria; Kluger, Bernhard; Neumann, Nora Katharina Nicole; Bueschl, Christoph; Lemmens, Marc; Lirk, Gerald; Krska, Rudolf; Schuhmacher, Rainer

    2015-10-24

    Metabolomics experiments often comprise large numbers of biological samples resulting in huge amounts of data. This data needs to be inspected for plausibility before data evaluation to detect putative sources of error e.g. retention time or mass accuracy shifts. Especially in liquid chromatography-high resolution mass spectrometry (LC-HRMS) based metabolomics research, proper quality control checks (e.g. for precision, signal drifts or offsets) are crucial prerequisites to achieve reliable and comparable results within and across experimental measurement sequences. Software tools can support this process. The software tool QCScreen was developed to offer a quick and easy data quality check of LC-HRMS derived data. It allows a flexible investigation and comparison of basic quality-related parameters within user-defined target features and the possibility to automatically evaluate multiple sample types within or across different measurement sequences in a short time. It offers a user-friendly interface that allows an easy selection of processing steps and parameter settings. The generated results include a coloured overview plot of data quality across all analysed samples and targets and, in addition, detailed illustrations of the stability and precision of the chromatographic separation, the mass accuracy and the detector sensitivity. The use of QCScreen is demonstrated with experimental data from metabolomics experiments using selected standard compounds in pure solvent. The application of the software identified problematic features, samples and analytical parameters and suggested which data files or compounds required closer manual inspection. QCScreen is an open source software tool which provides a useful basis for assessing the suitability of LC-HRMS data prior to time consuming, detailed data processing and subsequent statistical analysis. It accepts the generic mzXML format and thus can be used with many different LC-HRMS platforms to process both multiple

  16. Integration of high-content screening and untargeted metabolomics for comprehensive functional annotation of natural product libraries.

    PubMed

    Kurita, Kenji L; Glassey, Emerson; Linington, Roger G

    2015-09-29

    Traditional natural products discovery using a combination of live/dead screening followed by iterative bioassay-guided fractionation affords no information about compound structure or mode of action until late in the discovery process. This leads to high rates of rediscovery and low probabilities of finding compounds with unique biological and/or chemical properties. By integrating image-based phenotypic screening in HeLa cells with high-resolution untargeted metabolomics analysis, we have developed a new platform, termed Compound Activity Mapping, that is capable of directly predicting the identities and modes of action of bioactive constituents for any complex natural product extract library. This new tool can be used to rapidly identify novel bioactive constituents and provide predictions of compound modes of action directly from primary screening data. This approach inverts the natural products discovery process from the existing "grind and find" model to a targeted, hypothesis-driven discovery model where the chemical features and biological function of bioactive metabolites are known early in the screening workflow, and lead compounds can be rationally selected based on biological and/or chemical novelty. We demonstrate the utility of the Compound Activity Mapping platform by combining 10,977 mass spectral features and 58,032 biological measurements from a library of 234 natural products extracts and integrating these two datasets to identify 13 clusters of fractions containing 11 known compound families and four new compounds. Using Compound Activity Mapping we discovered the quinocinnolinomycins, a new family of natural products with a unique carbon skeleton that cause endoplasmic reticulum stress.

  17. Metabolomics as a Hypothesis-Generating Functional Genomics Tool for the Annotation of Arabidopsis thaliana Genes of “Unknown Function”

    PubMed Central

    Quanbeck, Stephanie M.; Brachova, Libuse; Campbell, Alexis A.; Guan, Xin; Perera, Ann; He, Kun; Rhee, Seung Y.; Bais, Preeti; Dickerson, Julie A.; Dixon, Philip; Wohlgemuth, Gert; Fiehn, Oliver; Barkan, Lenore; Lange, Iris; Lange, B. Markus; Lee, Insuk; Cortes, Diego; Salazar, Carolina; Shuman, Joel; Shulaev, Vladimir; Huhman, David V.; Sumner, Lloyd W.; Roth, Mary R.; Welti, Ruth; Ilarslan, Hilal; Wurtele, Eve S.; Nikolau, Basil J.

    2012-01-01

    Metabolomics is the methodology that identifies and measures global pools of small molecules (of less than about 1,000 Da) of a biological sample, which are collectively called the metabolome. Metabolomics can therefore reveal the metabolic outcome of a genetic or environmental perturbation of a metabolic regulatory network, and thus provide insights into the structure and regulation of that network. Because of the chemical complexity of the metabolome and limitations associated with individual analytical platforms for determining the metabolome, it is currently difficult to capture the complete metabolome of an organism or tissue, which is in contrast to genomics and transcriptomics. This paper describes the analysis of Arabidopsis metabolomics data sets acquired by a consortium that includes five analytical laboratories, bioinformaticists, and biostatisticians, which aims to develop and validate metabolomics as a hypothesis-generating functional genomics tool. The consortium is determining the metabolomes of Arabidopsis T-DNA mutant stocks, grown in standardized controlled environment optimized to minimize environmental impacts on the metabolomes. Metabolomics data were generated with seven analytical platforms, and the combined data is being provided to the research community to formulate initial hypotheses about genes of unknown function (GUFs). A public database (www.PlantMetabolomics.org) has been developed to provide the scientific community with access to the data along with tools to allow for its interactive analysis. Exemplary datasets are discussed to validate the approach, which illustrate how initial hypotheses can be generated from the consortium-produced metabolomics data, integrated with prior knowledge to provide a testable hypothesis concerning the functionality of GUFs. PMID:22645570

  18. Metabolomics Provides Quality Characterization of Commercial Gochujang (Fermented Pepper Paste).

    PubMed

    Lee, Gyu Min; Suh, Dong Ho; Jung, Eun Sung; Lee, Choong Hwan

    2016-07-15

    To identify the major factors contributing to the quality of commercial gochujang (fermented red pepper paste), metabolites were profiled by mass spectrometry. In principal component analysis, cereal type (wheat, brown rice, and white rice) and species of hot pepper (Capsicum annuum, C. annuum cv. Chung-yang, and C. frutescens) affected clustering patterns. Relative amino acid and citric acid levels were significantly higher in wheat gochujang than in rice gochujang. Sucrose, linoleic acid, oleic acid, and lysophospholipid levels were high in brown-rice gochujang, whereas glucose, maltose, and γ-aminobutyric acid levels were high in white-rice gochujang. The relative capsaicinoid and luteolin derivative contents in gochujang were affected by the hot pepper species used. Gochujang containing C. annuum cv. Chung-yang and C. frutescens showed high capsaicinoid levels. The luteolin derivative level was high in gochujang containing C. frutescens. These metabolite variations in commercial gochujang may be related to different physicochemical phenotypes and antioxidant activity.

  19. Early Learning: Program Quality in Early Childhood Education. Annotated Bibliography

    ERIC Educational Resources Information Center

    Hite, Jenny

    2014-01-01

    Overwhelmingly, research shows that program quality is a major determinant in the achievement gains for young children who participate in early education programs. Teacher quality, in particular, is closely related to positive educational outcomes for preschool participants. Research shows that children in programs whose lead and supporting…

  20. Early Learning: Program Quality in Early Childhood Education. Annotated Bibliography

    ERIC Educational Resources Information Center

    Hite, Jenny

    2014-01-01

    Overwhelmingly, research shows that program quality is a major determinant in the achievement gains for young children who participate in early education programs. Teacher quality, in particular, is closely related to positive educational outcomes for preschool participants. Research shows that children in programs whose lead and supporting…

  1. Framing Quality: Annotated Video-Based Portfolios of Classroom Practice by Pre-Service Teachers

    ERIC Educational Resources Information Center

    Joseph, Gail E.; Brennan, Carolyn

    2013-01-01

    In this paper we describe the use of peer learning teams creating annotated video-based portfolios to improve the quality of teacher-child interactions of undergraduate majors in early childhood and family studies. We used the intentional teaching framework (Hamre et al. in "Handbook of Early Education." Guilford Publications, New York,…

  2. Total Quality Management in Higher Education: From Assessment to Improvement. An Annotated Bibliography, Second Edition.

    ERIC Educational Resources Information Center

    Peterson, Marvin W.; And Others

    This publication is an annotated bibliography of articles and key organizational sources on Total Quality Management (TQM) in higher education. The list was developed through searches of local and national data bases including Education Resources Information Center (ERIC), Public Affairs Information System (PAIS), Wilson Indexes to Journal…

  3. Quality assessment of digital annotated ECG data from clinical trials by the FDA ECG Warehouse.

    PubMed

    Sarapa, Nenad

    2007-09-01

    The FDA mandates that digital electrocardiograms (ECGs) from 'thorough' QTc trials be submitted into the ECG Warehouse in Health Level 7 extended markup language format with annotated onset and offset points of waveforms. The FDA did not disclose the exact Warehouse metrics and minimal acceptable quality standards. The author describes the Warehouse scoring algorithms and metrics used by FDA, points out ways to improve FDA review and suggests Warehouse benefits for pharmaceutical sponsors. The Warehouse ranks individual ECGs according to their score for each quality metric and produces histogram distributions with Warehouse-specific thresholds that identify ECGs of questionable quality. Automatic Warehouse algorithms assess the quality of QT annotation and duration of manual QT measurement by the central ECG laboratory.

  4. Automatic ECG quality scoring methodology: mimicking human annotators.

    PubMed

    Johannesen, Lars; Galeotti, Loriano

    2012-09-01

    An algorithm to determine the quality of electrocardiograms (ECGs) can enable inexperienced nurses and paramedics to record ECGs of sufficient diagnostic quality. Previously, we proposed an algorithm for determining if ECG recordings are of acceptable quality, which was entered in the PhysioNet Challenge 2011. In the present work, we propose an improved two-step algorithm, which first rejects ECGs with macroscopic errors (signal absent, large voltage shifts or saturation) and subsequently quantifies the noise (baseline, powerline or muscular noise) on a continuous scale. The performance of the improved algorithm was evaluated using the PhysioNet Challenge database (1500 ECGs rated by humans for signal quality). We achieved a classification accuracy of 92.3% on the training set and 90.0% on the test set. The improved algorithm is capable of detecting ECGs with macroscopic errors and giving the user a score of the overall quality. This allows the user to assess the degree of noise and decide if it is acceptable depending on the purpose of the recording.

  5. Versatile annotation and publication quality visualization of protein complexes using POLYVIEW-3D.

    PubMed

    Porollo, Aleksey; Meller, Jaroslaw

    2007-08-29

    Macromolecular visualization as well as automated structural and functional annotation tools play an increasingly important role in the post-genomic era, contributing significantly towards the understanding of molecular systems and processes. For example, three dimensional (3D) models help in exploring protein active sites and functional hot spots that can be targeted in drug design. Automated annotation and visualization pipelines can also reveal other functionally important attributes of macromolecules. These goals are dependent on the availability of advanced tools that integrate better the existing databases, annotation servers and other resources with state-of-the-art rendering programs. We present a new tool for protein structure analysis, with the focus on annotation and visualization of protein complexes, which is an extension of our previously developed POLYVIEW web server. By integrating the web technology with state-of-the-art software for macromolecular visualization, such as the PyMol program, POLYVIEW-3D enables combining versatile structural and functional annotations with a simple web-based interface for creating publication quality structure rendering, as well as animated images for Powerpoint, web sites and other electronic resources. The service is platform independent and no plug-ins are required. Several examples of how POLYVIEW-3D can be used for structural and functional analysis in the context of protein-protein interactions are presented to illustrate the available annotation options. POLYVIEW-3D server features the PyMol image rendering that provides detailed and high quality presentation of macromolecular structures, with an easy to use web-based interface. POLYVIEW-3D also provides a wide array of options for automated structural and functional analysis of proteins and their complexes. Thus, the POLYVIEW-3D server may become an important resource for researches and educators in the fields of protein science and structural bioinformatics

  6. Told through the wine: A liquid chromatography-mass spectrometry interplatform comparison reveals the influence of the global approach on the final annotated metabolites in non-targeted metabolomics.

    PubMed

    Díaz, Ramon; Gallart-Ayala, Hector; Sancho, Juan V; Nuñez, Oscar; Zamora, Tatiana; Martins, Claudia P B; Hernández, Félix; Hernández-Cassou, Santiago; Saurina, Javier; Checa, Antonio

    2016-02-12

    This work focuses on the influence of the selected LC-HRMS platform on the final annotated compounds in non-targeted metabolomics. Two platforms that differed in columns, mobile phases, gradients, chromatographs, mass spectrometers (Orbitrap [Platform#1] and Q-TOF [Platform#2]), data processing and marker selection protocols were compared. A total of 42 wines samples from three different protected denomination of origin (PDO) were analyzed. At the feature level, good (O)PLS-DA models were obtained for both platforms (Q(2)[Platform#1]=0.89, 0.83 and 0.72; Q(2)[Platform#2]=0.86, 0.86 and 0.77 for Penedes, Ribera del Duero and Rioja wines respectively) with 100% correctly classified samples in all cases. At the annotated metabolite level, platforms proposed 9 and 8 annotated metabolites respectively which were identified by matching standards or the MS/MS spectra of the compounds. At this stage, there was no coincidence among platforms regarding the suggested metabolites. When screened on the raw data, 6 and 5 of these compounds were detected on the other platform with a similar trend. Some of the detected metabolites showed complimentary information when integrated on biological pathways. Through the use of some examples at the annotated metabolite level, possible explanations of this initial divergence on the results are presented. This work shows the complications that may arise on the comparison of non-targeted metabolomics platforms even when metabolite focused approaches are used in the identification. Copyright © 2016 Elsevier B.V. All rights reserved.

  7. Annotated Bibliography of Selected NPRDC Publications on Total Quality Management

    DTIC Science & Technology

    1990-12-01

    process deadly diseases of management, grated both with the leadership of improvement, the use of the management practices that repre- requirements for...34 t p a paith and the organization of work to that contribute to resistance to "deadly diseases on a par with deal with these "deadly diseases ...controlled by systems out- job characteristics (e.g., skill side of the chain of command The "total quality" concept variety, autonomy ) will result

  8. Metabolomics, Nutrition, and Potential Biomarkers of Food Quality, Intake, and Health Status.

    PubMed

    Sébédio, Jean-Louis

    Diet, dietary patterns, and other environmental factors such as exposure to toxins are playing an important role in the prevention/development of many diseases, like obesity, type 2 diabetes, and consequently on the health status of individuals. A major challenge nowadays is to identify novel biomarkers to detect as early as possible metabolic dysfunction and to predict evolution of health status in order to refine nutritional advices to specific population groups. Omics technologies such as genomics, transcriptomics, proteomics, and metabolomics coupled with statistical and bioinformatics tools have already shown great potential in this research field even if so far only few biomarkers have been validated. For the past two decades, important analytical techniques have been developed to detect as many metabolites as possible in human biofluids such as urine, blood, and saliva. In the field of food science and nutrition, many studies have been carried out for food authenticity, quality, and safety, as well as for food processing. Furthermore, metabolomic investigations have been carried out to discover new early biomarkers of metabolic dysfunction and predictive biomarkers of developing pathologies (obesity, metabolic syndrome, type-2 diabetes, etc.). Great emphasis is also placed in the development of methodologies to identify and validate biomarkers of nutrients exposure. © 2017 Elsevier Inc. All rights reserved.

  9. MAKER-P: a tool kit for the rapid creation, management, and quality control of plant genome annotations.

    PubMed

    Campbell, Michael S; Law, MeiYee; Holt, Carson; Stein, Joshua C; Moghe, Gaurav D; Hufnagel, David E; Lei, Jikai; Achawanantakun, Rujira; Jiao, Dian; Lawrence, Carolyn J; Ware, Doreen; Shiu, Shin-Han; Childs, Kevin L; Sun, Yanni; Jiang, Ning; Yandell, Mark

    2014-02-01

    We have optimized and extended the widely used annotation engine MAKER in order to better support plant genome annotation efforts. New features include better parallelization for large repeat-rich plant genomes, noncoding RNA annotation capabilities, and support for pseudogene identification. We have benchmarked the resulting software tool kit, MAKER-P, using the Arabidopsis (Arabidopsis thaliana) and maize (Zea mays) genomes. Here, we demonstrate the ability of the MAKER-P tool kit to automatically update, extend, and revise the Arabidopsis annotations in light of newly available data and to annotate pseudogenes and noncoding RNAs absent from The Arabidopsis Informatics Resource 10 build. Our results demonstrate that MAKER-P can be used to manage and improve the annotations of even Arabidopsis, perhaps the best-annotated plant genome. We have also installed and benchmarked MAKER-P on the Texas Advanced Computing Center. We show that this public resource can de novo annotate the entire Arabidopsis and maize genomes in less than 3 h and produce annotations of comparable quality to those of the current The Arabidopsis Information Resource 10 and maize V2 annotation builds.

  10. Filtered Push: Annotating Distributed Data for Quality Control and Fitness for Use Analysis

    NASA Astrophysics Data System (ADS)

    Morris, P. J.; Kelly, M. A.; Lowery, D. B.; Macklin, J. A.; Morris, R. A.; Tremonte, D.; Wang, Z.

    2009-12-01

    The single greatest problem with the federation of scientific data is the assessment of the quality and validity of the aggregated data in the context of particular research problems, that is, its fitness for use. There are three critical data quality issues in networks of distributed natural science collections data, as in all scientific data: identifying and correcting errors, maintaining currency, and assessing fitness for use. To this end, we have designed and implemented a prototype network in the domain of natural science collections. This prototype is built over the open source Map-Reduce platform Hadoop with a network client in the open source collections management system Specify 6. We call this network “Filtered Push” as, at its core, annotations are pushed from the network edges to relevant authoritative repositories, where humans and software filter the annotations before accepting them as changes to the authoritative data. The Filtered Push software is a domain-neutral framework for originating, distributing, and analyzing record-level annotations. Network participants can subscribe to notifications arising from ontology-based analyses of new annotations or of purpose-built queries against the network's global history of annotations. Quality and fitness for use of distributed natural science collections data can be addressed with Filtered Push software by implementing a network that allows data providers and consumers to define potential errors in data, develop metrics for those errors, specify workflows to analyze distributed data to detect potential errors, and to close the quality management cycle by providing a network architecture to pushing assertions about data quality such as corrections back to the curators of the participating data sets. Quality issues in distributed scientific data have several things in common: (1) Statements about data quality should be regarded as hypotheses about inconsistencies between perhaps several records, data

  11. Ranking Biomedical Annotations with Annotator's Semantic Relevancy

    PubMed Central

    2014-01-01

    Biomedical annotation is a common and affective artifact for researchers to discuss, show opinion, and share discoveries. It becomes increasing popular in many online research communities, and implies much useful information. Ranking biomedical annotations is a critical problem for data user to efficiently get information. As the annotator's knowledge about the annotated entity normally determines quality of the annotations, we evaluate the knowledge, that is, semantic relationship between them, in two ways. The first is extracting relational information from credible websites by mining association rules between an annotator and a biomedical entity. The second way is frequent pattern mining from historical annotations, which reveals common features of biomedical entities that an annotator can annotate with high quality. We propose a weighted and concept-extended RDF model to represent an annotator, a biomedical entity, and their background attributes and merge information from the two ways as the context of an annotator. Based on that, we present a method to rank the annotations by evaluating their correctness according to user's vote and the semantic relevancy between the annotator and the annotated entity. The experimental results show that the approach is applicable and efficient even when data set is large. PMID:24899918

  12. Ranking biomedical annotations with annotator's semantic relevancy.

    PubMed

    Wu, Aihua

    2014-01-01

    Biomedical annotation is a common and affective artifact for researchers to discuss, show opinion, and share discoveries. It becomes increasing popular in many online research communities, and implies much useful information. Ranking biomedical annotations is a critical problem for data user to efficiently get information. As the annotator's knowledge about the annotated entity normally determines quality of the annotations, we evaluate the knowledge, that is, semantic relationship between them, in two ways. The first is extracting relational information from credible websites by mining association rules between an annotator and a biomedical entity. The second way is frequent pattern mining from historical annotations, which reveals common features of biomedical entities that an annotator can annotate with high quality. We propose a weighted and concept-extended RDF model to represent an annotator, a biomedical entity, and their background attributes and merge information from the two ways as the context of an annotator. Based on that, we present a method to rank the annotations by evaluating their correctness according to user's vote and the semantic relevancy between the annotator and the annotated entity. The experimental results show that the approach is applicable and efficient even when data set is large.

  13. Annotated Bibliography: Understanding Ambulatory Care Practices in the Context of Patient Safety and Quality Improvement.

    PubMed

    Montano, Maria F; Mehdi, Harshal; Nash, David B

    2016-11-01

    The ambulatory care setting is an increasingly important component of the patient safety conversation. Inpatient safety is the primary focus of the vast majority of safety research and interventions, but the ambulatory setting is actually where most medical care is administered. Recent attention has shifted toward examining ambulatory care in order to implement better health care quality and safety practices. This annotated bibliography was created to analyze and augment the current literature on ambulatory care practices with regard to patient safety and quality improvement. By providing a thorough examination of current practices, potential improvement strategies in ambulatory care health care settings can be suggested. A better understanding of the myriad factors that influence delivery of patient care will catalyze future health care system development and implementation in the ambulatory setting.

  14. Quality evaluation and prediction of Citrullus lanatus by 1H NMR-based metabolomics and multivariate analysis.

    PubMed

    Tarachiwin, Lucksanaporn; Masako, Osawa; Fukusaki, Eiichiro

    2008-07-23

    (1)H NMR spectrometry in combination with multivariate analysis was considered to provide greater information on quality assessment over an ordinary sensory testing method due to its high reliability and high accuracy. The sensory quality evaluation of watermelon (Citrullus lanatus (Thunb.) Matsum. & Nakai) was carried out by means of (1)H NMR-based metabolomics. Multivariate analyses by partial least-squares projections to latent structures-discrimination analysis (PLS-DA) and PLS-regression offered extensive information for quality differentiation and quality evaluation, respectively. The impact of watermelon and rootstock cultivars on the sensory qualities of watermelon was determined on the basis of (1)H NMR metabolic fingerprinting and profiling. The significant metabolites contributing to the discrimination were also identified. A multivariate calibration model was successfully constructed by PLS-regression with extremely high reliability and accuracy. Thus, (1)H NMR-based metabolomics with multivariate analysis was considered to be one of the most suitable complementary techniques that could be applied to assess and predict the sensory quality of watermelons and other horticultural plants.

  15. metaX: a flexible and comprehensive software for processing metabolomics data.

    PubMed

    Wen, Bo; Mei, Zhanlong; Zeng, Chunwei; Liu, Siqi

    2017-03-21

    Non-targeted metabolomics based on mass spectrometry enables high-throughput profiling of the metabolites in a biological sample. The large amount of data generated from mass spectrometry requires intensive computational processing for annotation of mass spectra and identification of metabolites. Computational analysis tools that are fully integrated with multiple functions and are easily operated by users who lack extensive knowledge in programing are needed in this research field. We herein developed an R package, metaX, that is capable of end-to-end metabolomics data analysis through a set of interchangeable modules. Specifically, metaX provides several functions, such as peak picking and annotation, data quality assessment, missing value imputation, data normalization, univariate and multivariate statistics, power analysis and sample size estimation, receiver operating characteristic analysis, biomarker selection, pathway annotation, correlation network analysis, and metabolite identification. In addition, metaX offers a web-based interface ( http://metax.genomics.cn ) for data quality assessment and normalization method evaluation, and it generates an HTML-based report with a visualized interface. The metaX utilities were demonstrated with a published metabolomics dataset on a large scale. The software is available for operation as either a web-based graphical user interface (GUI) or in the form of command line functions. The package and the example reports are available at http://metax.genomics.cn/ . The pipeline of metaX is platform-independent and is easy to use for analysis of metabolomics data generated from mass spectrometry.

  16. Digital pathology and image analysis augment biospecimen annotation and biobank quality assurance harmonization.

    PubMed

    Wei, Bih-Rong; Simpson, R Mark

    2014-03-01

    Standardization of biorepository best practices will enhance the quality of translational biomedical research utilizing patient-derived biobank specimens. Harmonization of pathology quality assurance procedures for biobank accessions has lagged behind other avenues of biospecimen research and biobank development. Comprehension of the cellular content of biorepository specimens is important for discovery of tissue-specific clinically relevant biomarkers for diagnosis and treatment. While rapidly emerging technologies in molecular analyses and data mining create focus on appropriate measures for minimizing pre-analytic artifact-inducing variables, less attention gets paid to annotating the constituent makeup of biospecimens for more effective specimen selection by biobank clients. Both pre-analytic tissue processing and specimen composition influence acquisition of relevant macromolecules for downstream assays. Pathologist review of biorepository submissions, particularly tissues as part of quality assurance procedures, helps to ensure that the intended target cells are present and in sufficient quantity in accessioned specimens. This manual procedure can be tedious and subjective. Incorporating digital pathology into biobank quality assurance procedures, using automated pattern recognition morphometric image analysis to quantify tissue feature areas in digital whole slide images of tissue sections, can minimize variability and subjectivity associated with routine pathologic evaluations in biorepositories. Whole-slide images and pathologist-reviewed morphometric analyses can be provided to researchers to guide specimen selection. Harmonization of pathology quality assurance methods that minimize subjectivity and improve reproducibility among collections would facilitate research-relevant specimen selection by investigators and could facilitate information sharing in an integrated network approach to biobanking.

  17. Metabolomic technologies for improving the quality of food: Practice and promise

    USDA-ARS?s Scientific Manuscript database

    It is now well documented that the diet has a significant impact on human health and well-being. However, the complete set of small molecule metabolites present in foods that make up the human diet and the role of food production systems in altering this food metabolome are still largely unknown. Me...

  18. Microbial Metabolomics

    PubMed Central

    Tang, Jane

    2011-01-01

    Microbial metabolomics constitutes an integrated component of systems biology. By studying the complete set of metabolites within a microorganism and monitoring the global outcome of interactions between its development processes and the environment, metabolomics can potentially provide a more accurate snap shot of the actual physiological state of the cell. Recent advancement of technologies and post-genomic developments enable the study and analysis of metabolome. This unique contribution resulted in many scientific disciplines incorporating metabolomics as one of their “omics” platforms. This review focuses on metabolomics in microorganisms and utilizes selected topics to illustrate its impact on the understanding of systems microbiology. PMID:22379393

  19. Metabolomic analysis of the effect of shade treatment on the nutritional and sensory qualities of green tea.

    PubMed

    Lee, Lan-Sook; Choi, Ji Hea; Son, Nari; Kim, Sang-Hee; Park, Jong-Dae; Jang, Dae-Ja; Jeong, Yoonhwa; Kim, Hyun-Jin

    2013-01-16

    We analyzed metabolites from a 50% aqueous methanol extract of green teas treated with different shade periods (0, 15, 18, and 20 days) to investigate the effect of low light on their nutritional and sensory qualities. The shaded groups could be clearly distinguished from the control (0 day), and the 20 day group was separated from the 15 and 18 day groups. The shade treatment increased quercetin-galactosylrutinoside, kaempferol-glucosylrutinoside, epicatechin gallate, epigallocatechin gallate, tryptophan, phenylalanine, theanine, glutamine, glutamate, and caffeine levels but decreased quercetin-glucosylrutinoside, kaempferol-glucoside, gallocatechin, and epigallocatechin levels. Further studies on the nutritional benefits of these metabolites are needed. However, this result, along with the sensory evaluation and color measurement data, suggests that shade treatment improves the nutritional and sensory quality of green tea. Thus, we proposed a metabolomic pathway related to the effect of low light, which could elucidate the relationship between low light and tea quality.

  20. Microbial metabolomics: toward a platform with full metabolome coverage.

    PubMed

    van der Werf, Mariët J; Overkamp, Karin M; Muilwijk, Bas; Coulier, Leon; Hankemeier, Thomas

    2007-11-01

    Achieving metabolome data with satisfactory coverage is a formidable challenge in metabolomics because metabolites are a chemically highly diverse group of compounds. Here we present a strategy for the development of an advanced analytical platform that allows the comprehensive analysis of microbial metabolomes. Our approach started with in silico metabolome information from three microorganisms-Escherichia coli, Bacillus subtilis, and Saccharomyces cerevisiae-and resulted in a list of 905 different metabolites. Subsequently, these metabolites were classified based on their physicochemical properties, followed by the development of complementary gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry methods, each of which analyzes different metabolite classes. This metabolomics platform, consisting of six different analytical methods, was applied for the analysis of the metabolites for which commercial standards could be purchased (399 compounds). Of these 399 metabolites, 380 could be analyzed with the platform. To demonstrate the potential of this metabolomics platform, we report on its application to the analysis of the metabolome composition of mid-logarithmic E. coli cells grown on a mineral salts medium using glucose as the carbon source. Of the 431 peaks detected, 235 (=176 unique metabolites) could be identified. These include 61 metabolites that were not previously identified or annotated in existing E. coli databases.

  1. Metabolomic Profiling of Urine Samples from Mice Exposed to Protons Reveals Radiation Quality and Dose Specific Differences

    PubMed Central

    Laiakis, Evagelia C.; Trani, Daniela; Moon, Bo-Hyun; Strawn, Steven J.; Fornace, Albert J.

    2015-01-01

    As space travel is expanding to include private tourism and travel beyond low-Earth orbit, so is the risk of exposure to space radiation. Galactic cosmic rays and solar particle events have the potential to expose space travelers to significant doses of radiation that can lead to increased cancer risk and other adverse health consequences. Metabolomics has the potential to assess an individual’s risk by exploring the metabolic perturbations in a biofluid or tissue. In this study, C57BL/6 mice were exposed to 0.5 and 2 Gy of 1 GeV/nucleon of protons and the levels of metabolites were evaluated in urine at 4 h after radiation exposure through liquid chromatography coupled to time-of-flight mass spectrometry. Significant differences were identified in metabolites that map to the tricarboxylic acid (TCA) cycle and fatty acid metabolism, suggesting that energy metabolism is severely impacted after exposure to protons. Additionally, various pathways of amino acid metabolism (tryptophan, tyrosine, arginine and proline and phenylalanine) were affected with potential implications for DNA damage repair and cognitive impairment. Finally, presence of products of purine and pyrimidine metabolism points to direct DNA damage or increased apoptosis. Comparison of these metabolomic data to previously published data from our laboratory with gamma radiation strongly suggests a more pronounced effect on metabolism with protons. This is the first metabolomics study with space radiation in an easily accessible biofluid such as urine that further investigates and exemplifies the biological differences at early time points after exposure to different radiation qualities. PMID:25768838

  2. Metabolomic profiling of urine samples from mice exposed to protons reveals radiation quality and dose specific differences.

    PubMed

    Laiakis, Evagelia C; Trani, Daniela; Moon, Bo-Hyun; Strawn, Steven J; Fornace, Albert J

    2015-04-01

    As space travel is expanding to include private tourism and travel beyond low-Earth orbit, so is the risk of exposure to space radiation. Galactic cosmic rays and solar particle events have the potential to expose space travelers to significant doses of radiation that can lead to increased cancer risk and other adverse health consequences. Metabolomics has the potential to assess an individual's risk by exploring the metabolic perturbations in a biofluid or tissue. In this study, C57BL/6 mice were exposed to 0.5 and 2 Gy of 1 GeV/nucleon of protons and the levels of metabolites were evaluated in urine at 4 h after radiation exposure through liquid chromatography coupled to time-of-flight mass spectrometry. Significant differences were identified in metabolites that map to the tricarboxylic acid (TCA) cycle and fatty acid metabolism, suggesting that energy metabolism is severely impacted after exposure to protons. Additionally, various pathways of amino acid metabolism (tryptophan, tyrosine, arginine and proline and phenylalanine) were affected with potential implications for DNA damage repair and cognitive impairment. Finally, presence of products of purine and pyrimidine metabolism points to direct DNA damage or increased apoptosis. Comparison of these metabolomic data to previously published data from our laboratory with gamma radiation strongly suggests a more pronounced effect on metabolism with protons. This is the first metabolomics study with space radiation in an easily accessible biofluid such as urine that further investigates and exemplifies the biological differences at early time points after exposure to different radiation qualities.

  3. Utility of Metabolomics toward Assessing the Metabolic Basis of Quality Traits in Apple Fruit with an Emphasis on Antioxidants

    PubMed Central

    Cuthbertson, Daniel; Andrews, Preston K.; Reganold, John P.; Davies, Neal M.; Lange, B. Markus

    2012-01-01

    A gas chromatography–mass spectrometry approach was employed to evaluate the use of metabolite patterns to differentiate fruit from six commercially grown apple cultivars harvested in 2008. Principal component analysis (PCA) of apple fruit peel and flesh data indicated that individual cultivar replicates clustered together and were separated from all other cultivar samples. An independent metabolomics investigation with fruit harvested in 2003 confirmed the separate clustering of fruit from different cultivars. Further evidence for cultivar separation was obtained using a hierarchical clustering analysis. An evaluation of PCA component loadings revealed specific metabolite classes that contributed the most to each principal component, whereas a correlation analysis demonstrated that specific metabolites correlate directly with quality traits such as antioxidant activity, total phenolics, and total anthocyanins, which are important parameters in the selection of breeding germplasm. These data sets lay the foundation for elucidating the metabolic basis of commercially important fruit quality traits. PMID:22881116

  4. Quantitative performance of E-Scribe warehouse in detecting quality issues with digital annotated ECG data from healthy subjects.

    PubMed

    Sarapa, Nenad; Mortara, Justin L; Brown, Barry D; Isola, Lamberto; Badilini, Fabio

    2008-05-01

    The US Food and Drug Administration recommends submission of digital electrocardiograms in the standard HL7 XML format into the electrocardiogram warehouse to support preapproval review of new drug applications. The Food and Drug Administration scrutinizes electrocardiogram quality by viewing the annotated waveforms and scoring electrocardiogram quality by the warehouse algorithms. Part of the Food and Drug Administration warehouse is commercially available to sponsors as the E-Scribe Warehouse. The authors tested the performance of E-Scribe Warehouse algorithms by quantifying electrocardiogram acquisition quality, adherence to QT annotation protocol, and T-wave signal strength in 2 data sets: "reference" (104 digital electrocardiograms from a phase I study with sotalol in 26 healthy subjects with QT annotations by computer-assisted manual adjustment) and "test" (the same electrocardiograms with an intentionally introduced predefined number of quality issues). The E-Scribe Warehouse correctly detected differences between the 2 sets expected from the number and pattern of errors in the "test" set (except for 1 subject with QT misannotated in different leads of serial electrocardiograms) and confirmed the absence of differences where none was expected. E-Scribe Warehouse scores below the threshold value identified individual electrocardiograms with questionable T-wave signal strength. The E-Scribe Warehouse showed satisfactory performance in detecting electrocardiogram quality issues that may impair reliability of QTc assessment in clinical trials in healthy subjects.

  5. Evaluating Computational Gene Ontology Annotations.

    PubMed

    Škunca, Nives; Roberts, Richard J; Steffen, Martin

    2017-01-01

    Two avenues to understanding gene function are complementary and often overlapping: experimental work and computational prediction. While experimental annotation generally produces high-quality annotations, it is low throughput. Conversely, computational annotations have broad coverage, but the quality of annotations may be variable, and therefore evaluating the quality of computational annotations is a critical concern.In this chapter, we provide an overview of strategies to evaluate the quality of computational annotations. First, we discuss why evaluating quality in this setting is not trivial. We highlight the various issues that threaten to bias the evaluation of computational annotations, most of which stem from the incompleteness of biological databases. Second, we discuss solutions that address these issues, for example, targeted selection of new experimental annotations and leveraging the existing experimental annotations.

  6. MAKER-P: A Tool Kit for the Rapid Creation, Management, and Quality Control of Plant Genome Annotations1[W][OPEN

    PubMed Central

    Campbell, Michael S.; Law, MeiYee; Holt, Carson; Stein, Joshua C.; Moghe, Gaurav D.; Hufnagel, David E.; Lei, Jikai; Achawanantakun, Rujira; Jiao, Dian; Lawrence, Carolyn J.; Ware, Doreen; Shiu, Shin-Han; Childs, Kevin L.; Sun, Yanni; Jiang, Ning; Yandell, Mark

    2014-01-01

    We have optimized and extended the widely used annotation engine MAKER in order to better support plant genome annotation efforts. New features include better parallelization for large repeat-rich plant genomes, noncoding RNA annotation capabilities, and support for pseudogene identification. We have benchmarked the resulting software tool kit, MAKER-P, using the Arabidopsis (Arabidopsis thaliana) and maize (Zea mays) genomes. Here, we demonstrate the ability of the MAKER-P tool kit to automatically update, extend, and revise the Arabidopsis annotations in light of newly available data and to annotate pseudogenes and noncoding RNAs absent from The Arabidopsis Informatics Resource 10 build. Our results demonstrate that MAKER-P can be used to manage and improve the annotations of even Arabidopsis, perhaps the best-annotated plant genome. We have also installed and benchmarked MAKER-P on the Texas Advanced Computing Center. We show that this public resource can de novo annotate the entire Arabidopsis and maize genomes in less than 3 h and produce annotations of comparable quality to those of the current The Arabidopsis Information Resource 10 and maize V2 annotation builds. PMID:24306534

  7. Mining GO annotations for improving annotation consistency.

    PubMed

    Faria, Daniel; Schlicker, Andreas; Pesquita, Catia; Bastos, Hugo; Ferreira, António E N; Albrecht, Mario; Falcão, André O

    2012-01-01

    Despite the structure and objectivity provided by the Gene Ontology (GO), the annotation of proteins is a complex task that is subject to errors and inconsistencies. Electronically inferred annotations in particular are widely considered unreliable. However, given that manual curation of all GO annotations is unfeasible, it is imperative to improve the quality of electronically inferred annotations. In this work, we analyze the full GO molecular function annotation of UniProtKB proteins, and discuss some of the issues that affect their quality, focusing particularly on the lack of annotation consistency. Based on our analysis, we estimate that 64% of the UniProtKB proteins are incompletely annotated, and that inconsistent annotations affect 83% of the protein functions and at least 23% of the proteins. Additionally, we present and evaluate a data mining algorithm, based on the association rule learning methodology, for identifying implicit relationships between molecular function terms. The goal of this algorithm is to assist GO curators in updating GO and correcting and preventing inconsistent annotations. Our algorithm predicted 501 relationships with an estimated precision of 94%, whereas the basic association rule learning methodology predicted 12,352 relationships with a precision below 9%.

  8. A Systematic Bioinformatics Approach to Identify High Quality Mass Spectrometry Data and Functionally Annotate Proteins and Proteomes.

    PubMed

    Islam, Mohammad Tawhidul; Mohamedali, Abidali; Ahn, Seong Beom; Nawar, Ishmam; Baker, Mark S; Ranganathan, Shoba

    2017-01-01

    In the past decade, proteomics and mass spectrometry have taken tremendous strides forward, particularly in the life sciences, spurred on by rapid advances in technology resulting in generation and conglomeration of vast amounts of data. Though this has led to tremendous advancements in biology, the interpretation of the data poses serious challenges for many practitioners due to the immense size and complexity of the data. Furthermore, the lack of annotation means that a potential gold mine of relevant biological information may be hiding within this data. We present here a simple and intuitive workflow for the research community to investigate and mine this data, not only to extract relevant data but also to segregate usable, quality data to develop hypotheses for investigation and validation. We apply an MS evidence workflow for verifying peptides of proteins from one's own data as well as publicly available databases. We then integrate a suite of freely available bioinformatics analysis and annotation software tools to identify homologues and map putative functional signatures, gene ontology and biochemical pathways. We also provide an example of the functional annotation of missing proteins in human chromosome 7 data from the NeXtProt database, where no evidence is available at the proteomic, antibody, or structural levels. We give examples of protocols, tools and detailed flowcharts that can be extended or tailored to interpret and annotate the proteome of any novel organism.

  9. Workflow4Metabolomics: a collaborative research infrastructure for computational metabolomics.

    PubMed

    Giacomoni, Franck; Le Corguillé, Gildas; Monsoor, Misharl; Landi, Marion; Pericard, Pierre; Pétéra, Mélanie; Duperier, Christophe; Tremblay-Franco, Marie; Martin, Jean-François; Jacob, Daniel; Goulitquer, Sophie; Thévenot, Etienne A; Caron, Christophe

    2015-05-01

    The complex, rapidly evolving field of computational metabolomics calls for collaborative infrastructures where the large volume of new algorithms for data pre-processing, statistical analysis and annotation can be readily integrated whatever the language, evaluated on reference datasets and chained to build ad hoc workflows for users. We have developed Workflow4Metabolomics (W4M), the first fully open-source and collaborative online platform for computational metabolomics. W4M is a virtual research environment built upon the Galaxy web-based platform technology. It enables ergonomic integration, exchange and running of individual modules and workflows. Alternatively, the whole W4M framework and computational tools can be downloaded as a virtual machine for local installation. http://workflow4metabolomics.org homepage enables users to open a private account and access the infrastructure. W4M is developed and maintained by the French Bioinformatics Institute (IFB) and the French Metabolomics and Fluxomics Infrastructure (MetaboHUB). contact@workflow4metabolomics.org. © The Author 2014. Published by Oxford University Press.

  10. Metabolomics by Gas Chromatography-Mass Spectrometry: the combination of targeted and untargeted profiling

    PubMed Central

    Fiehn, Oliver

    2016-01-01

    Gas chromatography-mass spectrometry (GC-MS)-based metabolomics is ideal for identifying and quantitating small molecular metabolites (<650 daltons), including small acids, alcohols, hydroxyl acids, amino acids, sugars, fatty acids, sterols, catecholamines, drugs, and toxins, often using chemical derivatization to make these compounds volatile enough for gas chromatography. This unit shows that on GC-MS- based metabolomics easily allows integrating targeted assays for absolute quantification of specific metabolites with untargeted metabolomics to discover novel compounds. Complemented by database annotations using large spectral libraries and validated, standardized standard operating procedures, GC-MS can identify and semi-quantify over 200 compounds per study in human body fluids (e.g., plasma, urine or stool) samples. Deconvolution software enables detection of more than 300 additional unidentified signals that can be annotated through accurate mass instruments with appropriate data processing workflows, similar to liquid chromatography-MS untargeted profiling (LC-MS). Hence, GC-MS is a mature technology that not only uses classic detectors (‘quadrupole’) but also target mass spectrometers (‘triple quadrupole’) and accurate mass instruments (‘quadrupole-time of flight’). This unit covers the following aspects of GC-MS-based metabolomics: (i) sample preparation from mammalian samples, (ii) acquisition of data, (iii) quality control, and (iv) data processing. PMID:27038389

  11. Semantic Annotation of Mutable Data

    PubMed Central

    Morris, Robert A.; Dou, Lei; Hanken, James; Kelly, Maureen; Lowery, David B.; Ludäscher, Bertram; Macklin, James A.; Morris, Paul J.

    2013-01-01

    Electronic annotation of scientific data is very similar to annotation of documents. Both types of annotation amplify the original object, add related knowledge to it, and dispute or support assertions in it. In each case, annotation is a framework for discourse about the original object, and, in each case, an annotation needs to clearly identify its scope and its own terminology. However, electronic annotation of data differs from annotation of documents: the content of the annotations, including expectations and supporting evidence, is more often shared among members of networks. Any consequent actions taken by the holders of the annotated data could be shared as well. But even those current annotation systems that admit data as their subject often make it difficult or impossible to annotate at fine-enough granularity to use the results in this way for data quality control. We address these kinds of issues by offering simple extensions to an existing annotation ontology and describe how the results support an interest-based distribution of annotations. We are using the result to design and deploy a platform that supports annotation services overlaid on networks of distributed data, with particular application to data quality control. Our initial instance supports a set of natural science collection metadata services. An important application is the support for data quality control and provision of missing data. A previous proof of concept demonstrated such use based on data annotations modeled with XML-Schema. PMID:24223697

  12. Metabolomics as a Powerful Tool for Molecular Quality Assessment of the Fish Sparus aurata

    PubMed Central

    Picone, Gianfranco; Engelsen, Søren Balling; Savorani, Francesco; Testi, Silvia; Badiani, Anna; Capozzi, Francesco

    2011-01-01

    The molecular profiles of perchloric acid solutions extracted from the flesh of Sparus aurata fish specimens, produced according to different aquaculture systems, have been investigated. The 1H-NMR spectra of aqueous extracts are indicative of differences in the metabolite content of fish reared under different conditions that are already distinguishable at their capture, and substantially maintain the same differences in their molecular profiles after sixteen days of storage under ice. The fish metabolic profiles are studied by top-down chemometric analysis. The results of this exploratory investigation show that the fish metabolome accurately reflects the rearing conditions. The level of many metabolites co-vary with the rearing conditions and a few metabolites are quantified including glycogen (stress indicator), histidine, alanine and glycine which all display significant changes dependent on the aquaculture system and on the storage times. PMID:22254093

  13. Single-Cell Metabolomics.

    PubMed

    Emara, Samy; Amer, Sara; Ali, Ahmed; Abouleila, Yasmine; Oga, April; Masujima, Tsutomu

    2017-01-01

    The dynamics of a cell is always changing. Cells move, divide, communicate, adapt, and are always reacting to their surroundings non-synchronously. Currently, single-cell metabolomics has become the leading field in understanding the phenotypical variations between them, but sample volumes, low analyte concentrations, and validating gentle sample techniques have proven great barriers toward achieving accurate and complete metabolomics profiling. Certainly, advanced technologies such as nanodevices and microfluidic arrays are making great progress, and analytical techniques, such as matrix-assisted laser desorption ionization (MALDI), are gaining popularity with high-throughput methodology. Nevertheless, live single-cell mass spectrometry (LCSMS) values the sample quality and precision, turning once theoretical speculation into present-day applications in a variety of fields, including those of medicine, pharmaceutical, and agricultural industries. While there is still room for much improvement, it is clear that the metabolomics field is progressing toward analysis and discoveries at the single-cell level.

  14. Ecology and Environmental Quality, A Selected and Annotated Bibliography for Biologists and Earth Scientists.

    ERIC Educational Resources Information Center

    Watkins, Jessie B.

    This is a selected and annotated bibliography compiled and published by the Syracuse University Libraries and specifically designed for those seeking information regarding the biological aspects of air, land, and water pollution, as well as information concerning geographic and geologic facets of the biosphere. No attempt has been made to compile…

  15. Tools and databases of the KOMICS web portal for preprocessing, mining, and dissemination of metabolomics data.

    PubMed

    Sakurai, Nozomu; Ara, Takeshi; Enomoto, Mitsuo; Motegi, Takeshi; Morishita, Yoshihiko; Kurabayashi, Atsushi; Iijima, Yoko; Ogata, Yoshiyuki; Nakajima, Daisuke; Suzuki, Hideyuki; Shibata, Daisuke

    2014-01-01

    A metabolome--the collection of comprehensive quantitative data on metabolites in an organism--has been increasingly utilized for applications such as data-intensive systems biology, disease diagnostics, biomarker discovery, and assessment of food quality. A considerable number of tools and databases have been developed to date for the analysis of data generated by various combinations of chromatography and mass spectrometry. We report here a web portal named KOMICS (The Kazusa Metabolomics Portal), where the tools and databases that we developed are available for free to academic users. KOMICS includes the tools and databases for preprocessing, mining, visualization, and publication of metabolomics data. Improvements in the annotation of unknown metabolites and dissemination of comprehensive metabolomic data are the primary aims behind the development of this portal. For this purpose, PowerGet and FragmentAlign include a manual curation function for the results of metabolite feature alignments. A metadata-specific wiki-based database, Metabolonote, functions as a hub of web resources related to the submitters' work. This feature is expected to increase citation of the submitters' work, thereby promoting data publication. As an example of the practical use of KOMICS, a workflow for a study on Jatropha curcas is presented. The tools and databases available at KOMICS should contribute to enhanced production, interpretation, and utilization of metabolomic Big Data.

  16. Metabolomic profiling and sensorial quality of 'Golden Delicious', 'Liberty', 'Santana', and 'Topaz' apples grown using organic and integrated production systems.

    PubMed

    Vanzo, Andreja; Jenko, Mojca; Vrhovsek, Urska; Stopar, Matej

    2013-07-03

    Apple quality was investigated in the scab-resistant 'Liberty', 'Santana', and 'Topaz' cultivars and the scab-susceptible 'Golden Delicious' cultivar. Trees subjected to the same crop load were cultivated using either an organic (ORG) or an integrated production (IP) system. Physicochemical properties, phenolic content, and sensorial quality of fruit from both systems were compared. There were no significant differences in fruit mass, starch, and total soluble solid content (the latter was higher in ORG 'Liberty') between ORG and IP fruit, whereas significantly higher flesh firmness was found in ORG fruit (except no difference in 'Golden Delicious'). Significantly higher total phenolic content in ORG fruit was found in 'Golden Delicious', whereas differences in other cultivars were not significant. Targeted metabolomic profiling of multiple classes of phenolics confirmed the impact of the production system on the 'Golden Delicious' phenolic profile as higher levels of 4-hydroxybenzoic acid, neo- and chlorogenic acids, phloridzin, procyanidin B2+B4, -3-O-glucoside and -3-O-galactoside of quercetin, kaempferol-3-O-rutinoside, and rutin being found in ORG fruit. The results obtained suggested that scab resistance influenced the phenolic biosynthesis in relation to the agricultural system. Sensorial evaluation indicated significantly better flavor (except for 'Topaz') and better appearance of IP fruit.

  17. Evaluation of the Nutritional Quality of Chinese Kale (Brassica alboglabra Bailey) Using UHPLC-Quadrupole-Orbitrap MS/MS-Based Metabolomics.

    PubMed

    Wang, Ya-Qin; Hu, Li-Ping; Liu, Guang-Min; Zhang, De-Shuang; He, Hong-Ju

    2017-07-27

    Chinese kale (Brassica alboglabra Bailey) is a widely consumed vegetable which is rich in antioxidants and anticarcinogenic compounds. Herein, we used an untargeted ultra-high-performance liquid chromatography (UHPLC)-Quadrupole-Orbitrap MS/MS-based metabolomics strategy to study the nutrient profiles of Chinese kale. Seven Chinese kale cultivars and three different edible parts were evaluated, and amino acids, sugars, organic acids, glucosinolates and phenolic compounds were analysed simultaneously. We found that two cultivars, a purple-stem cultivar W1 and a yellow-flower cultivar Y1, had more health-promoting compounds than others. The multivariate statistical analysis results showed that gluconapin was the most important contributor for discriminating both cultivars and edible parts. The purple-stem cultivar W1 had higher levels of some phenolic acids and flavonoids than the green stem cultivars. Compared to stems and leaves, the inflorescences contained more amino acids, glucosinolates and most of the phenolic acids. Meanwhile, the stems had the least amounts of phenolic compounds among the organs tested. Metabolomics is a powerful approach for the comprehensive understanding of vegetable nutritional quality. The results provide the basis for future metabolomics-guided breeding and nutritional quality improvement.

  18. Elemental metabolomics.

    PubMed

    Zhang, Ping; Georgiou, Constantinos A; Brusic, Vladimir

    2017-01-10

    Elemental metabolomics is quantification and characterization of total concentration of chemical elements in biological samples and monitoring of their changes. Recent advances in inductively coupled plasma mass spectrometry have enabled simultaneous measurement of concentrations of > 70 elements in biological samples. In living organisms, elements interact and compete with each other for absorption and molecular interactions. They also interact with proteins and nucleotide sequences. These interactions modulate enzymatic activities and are critical for many molecular and cellular functions. Testing for concentration of > 40 elements in blood, other bodily fluids and tissues is now in routine use in advanced medical laboratories. In this article, we define the basic concepts of elemental metabolomics, summarize standards and workflows, and propose minimum information for reporting the results of an elemental metabolomics experiment. Major statistical and informatics tools for elemental metabolomics are reviewed, and examples of applications are discussed. Elemental metabolomics is emerging as an important new technology with applications in medical diagnostics, nutrition, agriculture, food science, environmental science and multiplicity of other areas. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  19. The Human Urine Metabolome

    PubMed Central

    Bouatra, Souhaila; Aziat, Farid; Mandal, Rupasri; Guo, An Chi; Wilson, Michael R.; Knox, Craig; Bjorndahl, Trent C.; Krishnamurthy, Ramanarayan; Saleem, Fozia; Liu, Philip; Dame, Zerihun T.; Poelzer, Jenna; Huynh, Jessica; Yallou, Faizath S.; Psychogios, Nick; Dong, Edison; Bogumil, Ralf; Roehring, Cornelia; Wishart, David S.

    2013-01-01

    Urine has long been a “favored” biofluid among metabolomics researchers. It is sterile, easy-to-obtain in large volumes, largely free from interfering proteins or lipids and chemically complex. However, this chemical complexity has also made urine a particularly difficult substrate to fully understand. As a biological waste material, urine typically contains metabolic breakdown products from a wide range of foods, drinks, drugs, environmental contaminants, endogenous waste metabolites and bacterial by-products. Many of these compounds are poorly characterized and poorly understood. In an effort to improve our understanding of this biofluid we have undertaken a comprehensive, quantitative, metabolome-wide characterization of human urine. This involved both computer-aided literature mining and comprehensive, quantitative experimental assessment/validation. The experimental portion employed NMR spectroscopy, gas chromatography mass spectrometry (GC-MS), direct flow injection mass spectrometry (DFI/LC-MS/MS), inductively coupled plasma mass spectrometry (ICP-MS) and high performance liquid chromatography (HPLC) experiments performed on multiple human urine samples. This multi-platform metabolomic analysis allowed us to identify 445 and quantify 378 unique urine metabolites or metabolite species. The different analytical platforms were able to identify (quantify) a total of: 209 (209) by NMR, 179 (85) by GC-MS, 127 (127) by DFI/LC-MS/MS, 40 (40) by ICP-MS and 10 (10) by HPLC. Our use of multiple metabolomics platforms and technologies allowed us to identify several previously unknown urine metabolites and to substantially enhance the level of metabolome coverage. It also allowed us to critically assess the relative strengths and weaknesses of different platforms or technologies. The literature review led to the identification and annotation of another 2206 urinary compounds and was used to help guide the subsequent experimental studies. An online database containing

  20. Recent advances of metabolomics in plant biotechnology.

    PubMed

    Okazaki, Yozo; Saito, Kazuki

    2012-01-01

    Biotechnology, including genetic modification, is a very important approach to regulate the production of particular metabolites in plants to improve their adaptation to environmental stress, to improve food quality, and to increase crop yield. Unfortunately, these approaches do not necessarily lead to the expected results due to the highly complex mechanisms underlying metabolic regulation in plants. In this context, metabolomics plays a key role in plant molecular biotechnology, where plant cells are modified by the expression of engineered genes, because we can obtain information on the metabolic status of cells via a snapshot of their metabolome. Although metabolome analysis could be used to evaluate the effect of foreign genes and understand the metabolic state of cells, there is no single analytical method for metabolomics because of the wide range of chemicals synthesized in plants. Here, we describe the basic analytical advancements in plant metabolomics and bioinformatics and the application of metabolomics to the biological study of plants.

  1. Metabolomic Analysis of Three Mollicute Species

    PubMed Central

    Vanyushkina, Anna A.; Fisunov, Gleb Y.; Gorbachev, Alexey Y.; Kamashev, Dmitri E.; Govorun, Vadim M.

    2014-01-01

    We present a systematic study of three bacterial species that belong to the class Mollicutes, the smallest and simplest bacteria, Spiroplasma melliferum, Mycoplasma gallisepticum, and Acholeplasma laidlawii. To understand the difference in the basic principles of metabolism regulation and adaptation to environmental conditions in the three species, we analyzed the metabolome of these bacteria. Metabolic pathways were reconstructed using the proteogenomic annotation data provided by our lab. The results of metabolome, proteome and genome profiling suggest a fundamental difference in the adaptation of the three closely related Mollicute species to stress conditions. As the transaldolase is not annotated in Mollicutes, we propose variants of the pentose phosphate pathway catalyzed by annotated enzymes for three species. For metabolite detection we employed high performance liquid chromatography coupled with mass spectrometry. We used liquid chromatography method - hydrophilic interaction chromatography with silica column - as it effectively separates highly polar cellular metabolites prior to their detection by mass spectrometer. PMID:24595068

  2. Metabolomics by Gas Chromatography-Mass Spectrometry: Combined Targeted and Untargeted Profiling.

    PubMed

    Fiehn, Oliver

    2016-04-01

    Gas chromatography-mass spectrometry (GC-MS)-based metabolomics is ideal for identifying and quantitating small-molecule metabolites (<650 Da), including small acids, alcohols, hydroxyl acids, amino acids, sugars, fatty acids, sterols, catecholamines, drugs, and toxins, often using chemical derivatization to make these compounds sufficiently volatile for gas chromatography. This unit shows how GC-MS-based metabolomics allows integration of targeted assays for absolute quantification of specific metabolites with untargeted metabolomics to discover novel compounds. Complemented by database annotations using large spectral libraries and validated standard operating procedures, GC-MS can identify and semiquantify over 200 compounds from human body fluids (e.g., plasma, urine, or stool) per study. Deconvolution software enables detection of more than 300 additional unidentified signals that can be annotated through accurate mass instruments with appropriate data processing workflows, similar to untargeted profiling using liquid chromatography-mass spectrometry. GC-MS is a mature technology that uses not only classic detectors (quadrupole) but also target mass spectrometers (triple quadrupole) and accurate mass instruments (quadrupole-time of flight). This unit covers sample preparation from mammalian samples, data acquisition, quality control, and data processing. Copyright © 2016 John Wiley & Sons, Inc.

  3. Tools and Databases of the KOMICS Web Portal for Preprocessing, Mining, and Dissemination of Metabolomics Data

    PubMed Central

    Enomoto, Mitsuo; Morishita, Yoshihiko; Kurabayashi, Atsushi; Iijima, Yoko; Ogata, Yoshiyuki; Nakajima, Daisuke; Suzuki, Hideyuki; Shibata, Daisuke

    2014-01-01

    A metabolome—the collection of comprehensive quantitative data on metabolites in an organism—has been increasingly utilized for applications such as data-intensive systems biology, disease diagnostics, biomarker discovery, and assessment of food quality. A considerable number of tools and databases have been developed to date for the analysis of data generated by various combinations of chromatography and mass spectrometry. We report here a web portal named KOMICS (The Kazusa Metabolomics Portal), where the tools and databases that we developed are available for free to academic users. KOMICS includes the tools and databases for preprocessing, mining, visualization, and publication of metabolomics data. Improvements in the annotation of unknown metabolites and dissemination of comprehensive metabolomic data are the primary aims behind the development of this portal. For this purpose, PowerGet and FragmentAlign include a manual curation function for the results of metabolite feature alignments. A metadata-specific wiki-based database, Metabolonote, functions as a hub of web resources related to the submitters' work. This feature is expected to increase citation of the submitters' work, thereby promoting data publication. As an example of the practical use of KOMICS, a workflow for a study on Jatropha curcas is presented. The tools and databases available at KOMICS should contribute to enhanced production, interpretation, and utilization of metabolomic Big Data. PMID:24949426

  4. Automated update, revision, and quality control of the maize genome annotations using MAKER-P improves the B73 RefGen_v3 gene models and identifies new genes

    USDA-ARS?s Scientific Manuscript database

    The large size and relative complexity of many plant genomes make creation, quality control, and dissemination of high-quality gene structure annotations challenging. In response, we have developed MAKER-P, a fast and easy-to-use genome annotation engine for plants. Here, we report the use of MAKER-...

  5. Automated Update, Revision, and Quality Control of the Maize Genome Annotations Using MAKER-P Improves the B73 RefGen_v3 Gene Models and Identifies New Genes1[OPEN

    PubMed Central

    Law, MeiYee; Childs, Kevin L.; Campbell, Michael S.; Stein, Joshua C.; Olson, Andrew J.; Holt, Carson; Panchy, Nicholas; Lei, Jikai; Jiao, Dian; Andorf, Carson M.; Lawrence, Carolyn J.; Ware, Doreen; Shiu, Shin-Han; Sun, Yanni; Jiang, Ning; Yandell, Mark

    2015-01-01

    The large size and relative complexity of many plant genomes make creation, quality control, and dissemination of high-quality gene structure annotations challenging. In response, we have developed MAKER-P, a fast and easy-to-use genome annotation engine for plants. Here, we report the use of MAKER-P to update and revise the maize (Zea mays) B73 RefGen_v3 annotation build (5b+) in less than 3 h using the iPlant Cyberinfrastructure. MAKER-P identified and annotated 4,466 additional, well-supported protein-coding genes not present in the 5b+ annotation build, added additional untranslated regions to 1,393 5b+ gene models, identified 2,647 5b+ gene models that lack any supporting evidence (despite the use of large and diverse evidence data sets), identified 104,215 pseudogene fragments, and created an additional 2,522 noncoding gene annotations. We also describe a method for de novo training of MAKER-P for the annotation of newly sequenced grass genomes. Collectively, these results lead to the 6a maize genome annotation and demonstrate the utility of MAKER-P for rapid annotation, management, and quality control of grasses and other difficult-to-annotate plant genomes. PMID:25384563

  6. Automated update, revision, and quality control of the maize genome annotations using MAKER-P improves the B73 RefGen_v3 gene models and identifies new genes.

    PubMed

    Law, MeiYee; Childs, Kevin L; Campbell, Michael S; Stein, Joshua C; Olson, Andrew J; Holt, Carson; Panchy, Nicholas; Lei, Jikai; Jiao, Dian; Andorf, Carson M; Lawrence, Carolyn J; Ware, Doreen; Shiu, Shin-Han; Sun, Yanni; Jiang, Ning; Yandell, Mark

    2015-01-01

    The large size and relative complexity of many plant genomes make creation, quality control, and dissemination of high-quality gene structure annotations challenging. In response, we have developed MAKER-P, a fast and easy-to-use genome annotation engine for plants. Here, we report the use of MAKER-P to update and revise the maize (Zea mays) B73 RefGen_v3 annotation build (5b+) in less than 3 h using the iPlant Cyberinfrastructure. MAKER-P identified and annotated 4,466 additional, well-supported protein-coding genes not present in the 5b+ annotation build, added additional untranslated regions to 1,393 5b+ gene models, identified 2,647 5b+ gene models that lack any supporting evidence (despite the use of large and diverse evidence data sets), identified 104,215 pseudogene fragments, and created an additional 2,522 noncoding gene annotations. We also describe a method for de novo training of MAKER-P for the annotation of newly sequenced grass genomes. Collectively, these results lead to the 6a maize genome annotation and demonstrate the utility of MAKER-P for rapid annotation, management, and quality control of grasses and other difficult-to-annotate plant genomes. © 2015 American Society of Plant Biologists. All Rights Reserved.

  7. Managing for Organizational Quality-Theory and Implementation: An Annotated Bibliography

    DTIC Science & Technology

    1990-06-01

    improvement. Garvin, D. A. (September-October 1983). Quality on the line. Harvad Business Review . kj(5), 64-75. Key words: U.S. competitive position...Southern California School of Business Administration Harold H. Rosen Navy Personnel Research and Development Center Reviewed by Linda M. Doherty...new industrial America. Scientific American, 16Q(6), 39-47. I-1 Garvin, D. A. (1983). Quality on the line. Harvard Business Review .1(5), 64-75. 1-1

  8. Metabolomic Analyses Reveal Distinct Change of Metabolites and Quality of Green Tea during the Short Duration of a Single Spring Season.

    PubMed

    Liu, Jianwei; Zhang, Qunfeng; Liu, Meiya; Ma, Lifeng; Shi, Yuanzhi; Ruan, Jianyun

    2016-04-27

    The sensory quality of green tea changes greatly within a single spring season, but the mechanism is not clearly elucidated. Young shoots of the early, middle, and late spring season were subjected to metabolite profiling using gas chromatography-time-of-flight mass spectrometry (TOF/MS) and ultraperformance liquid chromatography-quadrupole-TOF/MS. Multivariate analyses revealed largely different metabolite phenotypes in young shoots among different periods. The contents of amino acids decreased, whereas carbohydrates, flavonoids and their glycosides, tricarboxylic acid cycle, and photorespiration pathways were strongly reinforced in the late spring season, which were well reflected in the sensory quality of made teas. Metabolomic analyses further demonstrated distinct variations of metabolite phenotypes in mature leaves. The results suggested that the fluctuation of green tea quality in the spring season was caused by changes of metabolite phenotypes in young shoots, which was likely related to the remobilization of carbon and nitrogen reserves from mature leaves.

  9. Adaptation and Recommendation Techniques to Improve the Quality of Annotations and the Relevance of Resources in Web 2.0 and Semantic Web-Based Applications

    NASA Astrophysics Data System (ADS)

    Torre, Ilaria

    The Web 2.0 and the Semantic Web represent different forms of evolution of the first-generation Web, and both of them enrich Web resources with semantic annotations. Recommendation and personalization of Web resources is another trend that becomes more and more important with the growth of information, and both the Web 2.0 and the Semantic Web are deeply connected to it. The objective of this paper is to analyze the contribution of recommendation and adaptation techniques to these paradigms and to investigate if these techniques can be used as a bridge for their integration. More specifically, the paper will focus on the contribution of adaptation and recommendation techniques to improve the quality of annotations in the Web 2.0, Semantic Web, and mixed approaches and the relevance of annotated resources that are retrieved or filtered to users.

  10. YMDB: the Yeast Metabolome Database

    PubMed Central

    Jewison, Timothy; Knox, Craig; Neveu, Vanessa; Djoumbou, Yannick; Guo, An Chi; Lee, Jacqueline; Liu, Philip; Mandal, Rupasri; Krishnamurthy, Ram; Sinelnikov, Igor; Wilson, Michael; Wishart, David S.

    2012-01-01

    The Yeast Metabolome Database (YMDB, http://www.ymdb.ca) is a richly annotated ‘metabolomic’ database containing detailed information about the metabolome of Saccharomyces cerevisiae. Modeled closely after the Human Metabolome Database, the YMDB contains >2000 metabolites with links to 995 different genes/proteins, including enzymes and transporters. The information in YMDB has been gathered from hundreds of books, journal articles and electronic databases. In addition to its comprehensive literature-derived data, the YMDB also contains an extensive collection of experimental intracellular and extracellular metabolite concentration data compiled from detailed Mass Spectrometry (MS) and Nuclear Magnetic Resonance (NMR) metabolomic analyses performed in our lab. This is further supplemented with thousands of NMR and MS spectra collected on pure, reference yeast metabolites. Each metabolite entry in the YMDB contains an average of 80 separate data fields including comprehensive compound description, names and synonyms, structural information, physico-chemical data, reference NMR and MS spectra, intracellular/extracellular concentrations, growth conditions and substrates, pathway information, enzyme data, gene/protein sequence data, as well as numerous hyperlinks to images, references and other public databases. Extensive searching, relational querying and data browsing tools are also provided that support text, chemical structure, spectral, molecular weight and gene/protein sequence queries. Because of S. cervesiae's importance as a model organism for biologists and as a biofactory for industry, we believe this kind of database could have considerable appeal not only to metabolomics researchers, but also to yeast biologists, systems biologists, the industrial fermentation industry, as well as the beer, wine and spirit industry. PMID:22064855

  11. PLS/OPLS models in metabolomics: the impact of permutation of dataset rows on the K-fold cross-validation quality parameters.

    PubMed

    Triba, Mohamed N; Le Moyec, Laurence; Amathieu, Roland; Goossens, Corentine; Bouchemal, Nadia; Nahon, Pierre; Rutledge, Douglas N; Savarin, Philippe

    2015-01-01

    Among all the software packages available for discriminant analyses based on projection to latent structures (PLS-DA) or orthogonal projection to latent structures (OPLS-DA), SIMCA (Umetrics, Umeå Sweden) is the more widely used in the metabolomics field. SIMCA proposes many parameters or tests to assess the quality of the computed model (the number of significant components, R2, Q2, pCV-ANOVA, and the permutation test). Significance thresholds for these parameters are strongly application-dependent. Concerning the Q2 parameter, a significance threshold of 0.5 is generally admitted. However, during the last few years, many PLS-DA/OPLS-DA models built using SIMCA have been published with Q2 values lower than 0.5. The purpose of this opinion note is to point out that, in some circumstances frequently encountered in metabolomics, the values of these parameters strongly depend on the individuals that constitute the validation subsets. As a result of the way in which the software selects members of the calibration and validation subsets, a simple permutation of dataset rows can, in several cases, lead to contradictory conclusions about the significance of the models when a K-fold cross-validation is used. We believe that, when Q2 values lower than 0.5 are obtained, SIMCA users should at least verify that the quality parameters are stable towards permutation of the rows in their dataset.

  12. Plant metabolomics is not ripe for environmental risk assessment.

    PubMed

    Hall, Robert D; de Maagd, Ruud A

    2014-08-01

    Metabolomics separates and detects small molecules and helps determine the composition of plant materials. This makes it appear to be a possible contributor to environmental risk assessment (ERA) of transgenic plants. Here we argue that, despite important advances in the technology, limited annotation and our limited knowledge of the role of metabolites in plant-environment interactions means that metabolomics is not yet ripe for ERA. Copyright © 2014 Elsevier Ltd. All rights reserved.

  13. Quality Assurance for Alcohol, Drug Abuse, and Mental Health Services: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Towery, O. B.; And Others

    This is a comprehensive bibliography for all those in the alcohol, drug abuse and mental health fields who are developing and implementing programs for assuring quality in the services they provide. A major problem is the newness of the language and the unfamilarity with procedures required by the government and others seeking accountability from…

  14. Metabolomics-Inspired Insight into Developmental, Environmental and Genetic Aspects of Tomato Fruit Chemical Composition and Quality.

    PubMed

    Tohge, Takayuki; Fernie, Alisdair R

    2015-09-01

    Tomato was one of the first plant species to be evaluated using metabolomics and remains one of the best characterized, with tomato fruit being both an important source of nutrition in the human diet and a valuable model system for the development of fleshy fruits. Additionally, given the broad habitat range of members of the tomato clade and the extensive use of exotic germplasm in tomato genetic research, it represents an excellent genetic model system for understanding both metabolism per se and the importance of various metabolites in conferring stress tolerance. This review summarizes technical approaches used to characterize the tomato metabolome to date and details insights into metabolic pathway structure and regulation that have been obtained via analysis of tissue samples taken under different developmental or environmental circumstance as well as following genetic perturbation. Particular attention is paid to compounds of importance for nutrition or the shelf-life of tomatoes. We propose furthermore how metabolomics information can be coupled to the burgeoning wealth of genome sequence data from the tomato clade to enhance further our understanding of (i) the shifts in metabolic regulation occurring during development and (ii) specialization of metabolism within the tomato clade as a consequence of either adaptive evolution or domestication.

  15. Untargeted metabolomics of fresh and heat treatment Tiger nut (Cyperus esculentus L.) milks reveals further insight into food quality and nutrition.

    PubMed

    Rubert, Josep; Monforte, Andoni; Hurkova, Kamila; Pérez-Martínez, Gaspar; Blesa, Jesús; Navarro, José L; Stranka, Milena; Soriano, José Miguel; Hajslova, Jana

    2017-09-08

    Tiger nut (Cyperus esculentus L.) is a crop traditionally grown in Valencia Region (Spain) and other temperate and tropical regions in the world, where its tubers are commonly consumed as tiger nut milk (horchata). Because of their nutritive potential and original taste, these products are beginning to spread internationally and, as consequence, analytical procedures to assess nutritional profiles, quality control issues are acquiring increasing relevance. The main objective of this study was to use an advance analytical method and chemometrics tools to determine if the ultra-high temperature (UHT) treatment necessary to extend the shelf life of tiger nut milk would affect the profile of nutrients when compared to fresh product. A cold solvent extraction followed by liquid chromatography coupled with high resolution mass spectrometry (UHPLC-HRMS) was used. Datasets obtained from UHT and fresh tiger nut milk data were analyzed through an untargeted metabolomics approach to compare chemical patterns, highlighting differences in citric acid esters of mono- diglycerides (CITREM) and monoacylglycerol (MAG) used as emulsifiers of UHT products, and a remarkably higher abundance of biotin, phosphatidic acid (PA) and L-arginine in fresh products. These results showed that untargeted metabolomics through high resolution tandem mass spectrometry allowed fine differences between food products to be found, therefore, the nutrient lost caused by UHT treatment was clearly discerned. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Validation of a two-step quality control approach for a large-scale human urine metabolomic study conducted in seven experimental batches with LC/QTOF-MS.

    PubMed

    Demetrowitsch, Tobias J; Petersen, Beate; Keppler, Julia K; Koch, Andreas; Schreiber, Stefan; Laudes, Matthias; Schwarz, Karin

    2015-01-01

    After his study of food science at the Rheinische Friedrich-Wilhelms University of Bonn, Tobias J Demetrowitsch obtained his doctoral degree in the research field of metabolomics at the Christian-Albrechts-University of Kiel. The present paper is part of his doctoral thesis and describes an extended strategy to evaluate and verify complex or large-scale experiments and data sets. Large-scale studies result in high sample numbers, requiring the analysis of samples in different batches. So far, the verification of such LC-MS-based metabolomics studies is difficult. Common approaches have not provided a reliable validation procedure to date. This article shows a novel verification process for a large-scale human urine study (analyzed by a LC/QToF-MS system) using a two-step validation procedure. The first step comprises a targeted approach that aims to examine and exclude statistical outliers. The second step consists of a principle component analysis, with the aim of a tight cluster of all quality controls and a second for all volunteer samples. The applied study design provides a reliable two-step validation procedure for large-scale studies and additionally contains an inhouse verification procedure.

  17. RATT: Rapid Annotation Transfer Tool

    PubMed Central

    Otto, Thomas D.; Dillon, Gary P.; Degrave, Wim S.; Berriman, Matthew

    2011-01-01

    Second-generation sequencing technologies have made large-scale sequencing projects commonplace. However, making use of these datasets often requires gene function to be ascribed genome wide. Although tool development has kept pace with the changes in sequence production, for tasks such as mapping, de novo assembly or visualization, genome annotation remains a challenge. We have developed a method to rapidly provide accurate annotation for new genomes using previously annotated genomes as a reference. The method, implemented in a tool called RATT (Rapid Annotation Transfer Tool), transfers annotations from a high-quality reference to a new genome on the basis of conserved synteny. We demonstrate that a Mycobacterium tuberculosis genome or a single 2.5 Mb chromosome from a malaria parasite can be annotated in less than five minutes with only modest computational resources. RATT is available at http://ratt.sourceforge.net. PMID:21306991

  18. Integrated metabolomic and transcriptome analyses reveal finishing forage affects metabolic pathways related to beef quality and animal welfare

    PubMed Central

    Carrillo, José A.; He, Yanghua; Li, Yaokun; Liu, Jianan; Erdman, Richard A.; Sonstegard, Tad S.; Song, Jiuzhou

    2016-01-01

    Beef represents a major dietary component and source of protein in many countries. With an increasing demand for beef, the industry is currently undergoing changes towards naturally produced beef. However, the true differences between the feeding systems, especially the biochemical and nutritional aspects, are still unclear. Using transcriptome and metabolome profiles, we identified biological pathways related to the differences between grass- and grain-fed Angus steers. In the latissimus dorsi muscle, we have recognized 241 differentially expressed genes (FDR < 0.1). The metabolome examinations of muscle and blood revealed 163 and 179 altered compounds in each tissue (P < 0.05), respectively. Accordingly, alterations in glucose metabolism, divergences in free fatty acids and carnitine conjugated lipid levels, and altered β-oxidation have been observed. The anti-inflammatory n3 polyunsaturated fatty acids are enriched in grass finished beef, while higher levels of n6 PUFAs in grain finished animals may promote inflammation and oxidative stress. Furthermore, grass-fed animals produce tender beef with lower total fat and a higher omega3/omega6 ratio than grain-fed ones, which could potentially benefit consumer health. Most importantly, blood cortisol levels strongly indicate that grass-fed animals may experience less stress than the grain-fed individuals. These results will provide deeper insights into the merits and mechanisms of muscle development. PMID:27185157

  19. Marky: a tool supporting annotation consistency in multi-user and iterative document annotation projects.

    PubMed

    Pérez-Pérez, Martín; Glez-Peña, Daniel; Fdez-Riverola, Florentino; Lourenço, Anália

    2015-02-01

    Document annotation is a key task in the development of Text Mining methods and applications. High quality annotated corpora are invaluable, but their preparation requires a considerable amount of resources and time. Although the existing annotation tools offer good user interaction interfaces to domain experts, project management and quality control abilities are still limited. Therefore, the current work introduces Marky, a new Web-based document annotation tool equipped to manage multi-user and iterative projects, and to evaluate annotation quality throughout the project life cycle. At the core, Marky is a Web application based on the open source CakePHP framework. User interface relies on HTML5 and CSS3 technologies. Rangy library assists in browser-independent implementation of common DOM range and selection tasks, and Ajax and JQuery technologies are used to enhance user-system interaction. Marky grants solid management of inter- and intra-annotator work. Most notably, its annotation tracking system supports systematic and on-demand agreement analysis and annotation amendment. Each annotator may work over documents as usual, but all the annotations made are saved by the tracking system and may be further compared. So, the project administrator is able to evaluate annotation consistency among annotators and across rounds of annotation, while annotators are able to reject or amend subsets of annotations made in previous rounds. As a side effect, the tracking system minimises resource and time consumption. Marky is a novel environment for managing multi-user and iterative document annotation projects. Compared to other tools, Marky offers a similar visually intuitive annotation experience while providing unique means to minimise annotation effort and enforce annotation quality, and therefore corpus consistency. Marky is freely available for non-commercial use at http://sing.ei.uvigo.es/marky. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  20. Annotated Videography.

    ERIC Educational Resources Information Center

    United States Holocaust Memorial Museum, Washington, DC.

    This annotated list of 43 videotapes recommended for classroom use addresses various themes for teaching about the Holocaust, including: (1) overviews of the Holocaust; (2) life before the Holocaust; (3) propaganda; (4) racism, anti-Semitism; (5) "enemies of the state"; (6) ghettos; (7) camps; (8) genocide; (9) rescue; (10) resistance;…

  1. Genome Annotation and Curation Using MAKER and MAKER-P

    PubMed Central

    Campbell, Michael S.; Holt, Carson; Moore, Barry; Yandell, Mark

    2014-01-01

    This unit describes how to use the genome annotation and curation tools MAKER and MAKER-P to annotate protein coding and non-coding RNA genes in newly assembled genomes, update/combine legacy annotations in light of new evidence, add quality metrics to annotations from other pipelines, and map existing annotations to a new assembly. MAKER and MAKER-P can rapidly annotate genomes of any size, and scale to match available computational resources. PMID:25501943

  2. MAKER-P: a tool-kit for the creation, management, and quality control of plant genome annotations

    USDA-ARS?s Scientific Manuscript database

    We have optimized and extended the widely used annotation-engine MAKER for use on plant genomes. We have benchmarked the resulting software, MAKER-P, using the A. thaliana genome and the TAIR10 gene models. Here we demonstrate the ability of the MAKER-P toolkit to generate de novo repeat databases, ...

  3. Annotated Bibliography of 100 Quality Books of Multicultural Literature for Children in Grades K-6 (1990-1996).

    ERIC Educational Resources Information Center

    Donoghue, Mildred R.

    This annotated bibliography of contemporary multicultural books for children is divided into sections on: (1) non-fiction, biography (12 citations); (2) non-fiction, information (18 citations); (3) contemporary realistic fiction (14 citations); (4) folklore (11 citations); (5) historical fiction (11 citations); (6) modern fantasy (10 citations);…

  4. Metabolomics for laboratory diagnostics.

    PubMed

    Bujak, Renata; Struck-Lewicka, Wiktoria; Markuszewski, Michał J; Kaliszan, Roman

    2015-09-10

    Metabolomics is an emerging approach in a systems biology field. Due to continuous development in advanced analytical techniques and in bioinformatics, metabolomics has been extensively applied as a novel, holistic diagnostic tool in clinical and biomedical studies. Metabolome's measurement, as a chemical reflection of a current phenotype of a particular biological system, is nowadays frequently implemented to understand pathophysiological processes involved in disease progression as well as to search for new diagnostic or prognostic biomarkers of various organism's disorders. In this review, we discussed the research strategies and analytical platforms commonly applied in the metabolomics studies. The applications of the metabolomics in laboratory diagnostics in the last 5 years were also reviewed according to the type of biological sample used in the metabolome's analysis. We also discussed some limitations and further improvements which should be considered taking in mind potential applications of metabolomic research and practice. Copyright © 2014 Elsevier B.V. All rights reserved.

  5. Evaluating plant immunity using mass spectrometry-based metabolomics workflows

    PubMed Central

    Heuberger, Adam L.; Robison, Faith M.; Lyons, Sarah Marie A.; Broeckling, Corey D.; Prenni, Jessica E.

    2014-01-01

    Metabolic processes in plants are key components of physiological and biochemical disease resistance. Metabolomics, the analysis of a broad range of small molecule compounds in a biological system, has been used to provide a systems-wide overview of plant metabolism associated with defense responses. Plant immunity has been examined using multiple metabolomics workflows that vary in methods of detection, annotation, and interpretation, and the choice of workflow can significantly impact the conclusions inferred from a metabolomics investigation. The broad range of metabolites involved in plant defense often requires multiple chemical detection platforms and implementation of a non-targeted approach. A review of the current literature reveals a wide range of workflows that are currently used in plant metabolomics, and new methods for analyzing and reporting mass spectrometry (MS) data can improve the ability to translate investigative findings among different plant-pathogen systems. PMID:25009545

  6. Gene Ontology annotations and resources.

    PubMed

    Blake, J A; Dolan, M; Drabkin, H; Hill, D P; Li, Ni; Sitnikov, D; Bridges, S; Burgess, S; Buza, T; McCarthy, F; Peddinti, D; Pillai, L; Carbon, S; Dietze, H; Ireland, A; Lewis, S E; Mungall, C J; Gaudet, P; Chrisholm, R L; Fey, P; Kibbe, W A; Basu, S; Siegele, D A; McIntosh, B K; Renfro, D P; Zweifel, A E; Hu, J C; Brown, N H; Tweedie, S; Alam-Faruque, Y; Apweiler, R; Auchinchloss, A; Axelsen, K; Bely, B; Blatter, M -C; Bonilla, C; Bouguerleret, L; Boutet, E; Breuza, L; Bridge, A; Chan, W M; Chavali, G; Coudert, E; Dimmer, E; Estreicher, A; Famiglietti, L; Feuermann, M; Gos, A; Gruaz-Gumowski, N; Hieta, R; Hinz, C; Hulo, C; Huntley, R; James, J; Jungo, F; Keller, G; Laiho, K; Legge, D; Lemercier, P; Lieberherr, D; Magrane, M; Martin, M J; Masson, P; Mutowo-Muellenet, P; O'Donovan, C; Pedruzzi, I; Pichler, K; Poggioli, D; Porras Millán, P; Poux, S; Rivoire, C; Roechert, B; Sawford, T; Schneider, M; Stutz, A; Sundaram, S; Tognolli, M; Xenarios, I; Foulgar, R; Lomax, J; Roncaglia, P; Khodiyar, V K; Lovering, R C; Talmud, P J; Chibucos, M; Giglio, M Gwinn; Chang, H -Y; Hunter, S; McAnulla, C; Mitchell, A; Sangrador, A; Stephan, R; Harris, M A; Oliver, S G; Rutherford, K; Wood, V; Bahler, J; Lock, A; Kersey, P J; McDowall, D M; Staines, D M; Dwinell, M; Shimoyama, M; Laulederkind, S; Hayman, T; Wang, S -J; Petri, V; Lowry, T; D'Eustachio, P; Matthews, L; Balakrishnan, R; Binkley, G; Cherry, J M; Costanzo, M C; Dwight, S S; Engel, S R; Fisk, D G; Hitz, B C; Hong, E L; Karra, K; Miyasato, S R; Nash, R S; Park, J; Skrzypek, M S; Weng, S; Wong, E D; Berardini, T Z; Huala, E; Mi, H; Thomas, P D; Chan, J; Kishore, R; Sternberg, P; Van Auken, K; Howe, D; Westerfield, M

    2013-01-01

    The Gene Ontology (GO) Consortium (GOC, http://www.geneontology.org) is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies. Over the past year, the GOC has implemented several processes to increase the quantity, quality and specificity of GO annotations. First, the number of manual, literature-based annotations has grown at an increasing rate. Second, as a result of a new 'phylogenetic annotation' process, manually reviewed, homology-based annotations are becoming available for a broad range of species. Third, the quality of GO annotations has been improved through a streamlined process for, and automated quality checks of, GO annotations deposited by different annotation groups. Fourth, the consistency and correctness of the ontology itself has increased by using automated reasoning tools. Finally, the GO has been expanded not only to cover new areas of biology through focused interaction with experts, but also to capture greater specificity in all areas of the ontology using tools for adding new combinatorial terms. The GOC works closely with other ontology developers to support integrated use of terminologies. The GOC supports its user community through the use of e-mail lists, social media and web-based resources.

  7. Corpus annotation for mining biomedical events from literature.

    PubMed

    Kim, Jin-Dong; Ohta, Tomoko; Tsujii, Jun'ichi

    2008-01-08

    Advanced Text Mining (TM) such as semantic enrichment of papers, event or relation extraction, and intelligent Question Answering have increasingly attracted attention in the bio-medical domain. For such attempts to succeed, text annotation from the biological point of view is indispensable. However, due to the complexity of the task, semantic annotation has never been tried on a large scale, apart from relatively simple term annotation. We have completed a new type of semantic annotation, event annotation, which is an addition to the existing annotations in the GENIA corpus. The corpus has already been annotated with POS (Parts of Speech), syntactic trees, terms, etc. The new annotation was made on half of the GENIA corpus, consisting of 1,000 Medline abstracts. It contains 9,372 sentences in which 36,114 events are identified. The major challenges during event annotation were (1) to design a scheme of annotation which meets specific requirements of text annotation, (2) to achieve biology-oriented annotation which reflect biologists' interpretation of text, and (3) to ensure the homogeneity of annotation quality across annotators. To meet these challenges, we introduced new concepts such as Single-facet Annotation and Semantic Typing, which have collectively contributed to successful completion of a large scale annotation. The resulting event-annotated corpus is the largest and one of the best in quality among similar annotation efforts. We expect it to become a valuable resource for NLP (Natural Language Processing)-based TM in the bio-medical domain.

  8. Metabolomics and Epidemiology Working Group

    Cancer.gov

    The Metabolomics and Epidemiology (MetEpi) Working Group promotes metabolomics analyses in population-based studies, as well as advancement in the field of metabolomics for broader biomedical and public health research.

  9. Assisted annotation of medical free text using RapTAT.

    PubMed

    Gobbel, Glenn T; Garvin, Jennifer; Reeves, Ruth; Cronin, Robert M; Heavirland, Julia; Williams, Jenifer; Weaver, Allison; Jayaramaraja, Shrimalini; Giuse, Dario; Speroff, Theodore; Brown, Steven H; Xu, Hua; Matheny, Michael E

    2014-01-01

    To determine whether assisted annotation using interactive training can reduce the time required to annotate a clinical document corpus without introducing bias. A tool, RapTAT, was designed to assist annotation by iteratively pre-annotating probable phrases of interest within a document, presenting the annotations to a reviewer for correction, and then using the corrected annotations for further machine learning-based training before pre-annotating subsequent documents. Annotators reviewed 404 clinical notes either manually or using RapTAT assistance for concepts related to quality of care during heart failure treatment. Notes were divided into 20 batches of 19-21 documents for iterative annotation and training. The number of correct RapTAT pre-annotations increased significantly and annotation time per batch decreased by ~50% over the course of annotation. Annotation rate increased from batch to batch for assisted but not manual reviewers. Pre-annotation F-measure increased from 0.5 to 0.6 to >0.80 (relative to both assisted reviewer and reference annotations) over the first three batches and more slowly thereafter. Overall inter-annotator agreement was significantly higher between RapTAT-assisted reviewers (0.89) than between manual reviewers (0.85). The tool reduced workload by decreasing the number of annotations needing to be added and helping reviewers to annotate at an increased rate. Agreement between the pre-annotations and reference standard, and agreement between the pre-annotations and assisted annotations, were similar throughout the annotation process, which suggests that pre-annotation did not introduce bias. Pre-annotations generated by a tool capable of interactive training can reduce the time required to create an annotated document corpus by up to 50%. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  10. Assisted annotation of medical free text using RapTAT

    PubMed Central

    Gobbel, Glenn T; Garvin, Jennifer; Reeves, Ruth; Cronin, Robert M; Heavirland, Julia; Williams, Jenifer; Weaver, Allison; Jayaramaraja, Shrimalini; Giuse, Dario; Speroff, Theodore; Brown, Steven H; Xu, Hua; Matheny, Michael E

    2014-01-01

    Objective To determine whether assisted annotation using interactive training can reduce the time required to annotate a clinical document corpus without introducing bias. Materials and methods A tool, RapTAT, was designed to assist annotation by iteratively pre-annotating probable phrases of interest within a document, presenting the annotations to a reviewer for correction, and then using the corrected annotations for further machine learning-based training before pre-annotating subsequent documents. Annotators reviewed 404 clinical notes either manually or using RapTAT assistance for concepts related to quality of care during heart failure treatment. Notes were divided into 20 batches of 19–21 documents for iterative annotation and training. Results The number of correct RapTAT pre-annotations increased significantly and annotation time per batch decreased by ∼50% over the course of annotation. Annotation rate increased from batch to batch for assisted but not manual reviewers. Pre-annotation F-measure increased from 0.5 to 0.6 to >0.80 (relative to both assisted reviewer and reference annotations) over the first three batches and more slowly thereafter. Overall inter-annotator agreement was significantly higher between RapTAT-assisted reviewers (0.89) than between manual reviewers (0.85). Discussion The tool reduced workload by decreasing the number of annotations needing to be added and helping reviewers to annotate at an increased rate. Agreement between the pre-annotations and reference standard, and agreement between the pre-annotations and assisted annotations, were similar throughout the annotation process, which suggests that pre-annotation did not introduce bias. Conclusions Pre-annotations generated by a tool capable of interactive training can reduce the time required to create an annotated document corpus by up to 50%. PMID:24431336

  11. GC/MS based metabolomics: development of a data mining system for metabolite identification by using soft independent modeling of class analogy (SIMCA)

    PubMed Central

    2011-01-01

    Background The goal of metabolomics analyses is a comprehensive and systematic understanding of all metabolites in biological samples. Many useful platforms have been developed to achieve this goal. Gas chromatography coupled to mass spectrometry (GC/MS) is a well-established analytical method in metabolomics study, and 200 to 500 peaks are routinely observed with one biological sample. However, only ~100 metabolites can be identified, and the remaining peaks are left as "unknowns". Result We present an algorithm that acquires more extensive metabolite information. Pearson's product-moment correlation coefficient and the Soft Independent Modeling of Class Analogy (SIMCA) method were combined to automatically identify and annotate unknown peaks, which tend to be missed in routine studies that employ manual processing. Conclusions Our data mining system can offer a wealth of metabolite information quickly and easily, and it provides new insights, particularly into food quality evaluation and prediction. PMID:21542920

  12. ALLocator: An Interactive Web Platform for the Analysis of Metabolomic LC-ESI-MS Datasets, Enabling Semi-Automated, User-Revised Compound Annotation and Mass Isotopomer Ratio Analysis

    PubMed Central

    Persicke, Marcus; Albaum, Stefan P.; Kalinowski, Jörn; Goesmann, Alexander; Niehaus, Karsten; Nattkemper, Tim W.

    2014-01-01

    Adduct formation, fragmentation events and matrix effects impose special challenges to the identification and quantitation of metabolites in LC-ESI-MS datasets. An important step in compound identification is the deconvolution of mass signals. During this processing step, peaks representing adducts, fragments, and isotopologues of the same analyte are allocated to a distinct group, in order to separate peaks from coeluting compounds. From these peak groups, neutral masses and pseudo spectra are derived and used for metabolite identification via mass decomposition and database matching. Quantitation of metabolites is hampered by matrix effects and nonlinear responses in LC-ESI-MS measurements. A common approach to correct for these effects is the addition of a U-13C-labeled internal standard and the calculation of mass isotopomer ratios for each metabolite. Here we present a new web-platform for the analysis of LC-ESI-MS experiments. ALLocator covers the workflow from raw data processing to metabolite identification and mass isotopomer ratio analysis. The integrated processing pipeline for spectra deconvolution “ALLocatorSD” generates pseudo spectra and automatically identifies peaks emerging from the U-13C-labeled internal standard. Information from the latter improves mass decomposition and annotation of neutral losses. ALLocator provides an interactive and dynamic interface to explore and enhance the results in depth. Pseudo spectra of identified metabolites can be stored in user- and method-specific reference lists that can be applied on succeeding datasets. The potential of the software is exemplified in an experiment, in which abundance fold-changes of metabolites of the l-arginine biosynthesis in C. glutamicum type strain ATCC 13032 and l-arginine producing strain ATCC 21831 are compared. Furthermore, the capability for detection and annotation of uncommon large neutral losses is shown by the identification of (γ-)glutamyl dipeptides in the same strains

  13. Cancer Metabolomics and the Human Metabolome Database

    PubMed Central

    Wishart, David S.; Mandal, Rupasri; Stanislaus, Avalyn; Ramirez-Gaona, Miguel

    2016-01-01

    The application of metabolomics towards cancer research has led to a renewed appreciation of metabolism in cancer development and progression. It has also led to the discovery of metabolite cancer biomarkers and the identification of a number of novel cancer causing metabolites. The rapid growth of metabolomics in cancer research is also leading to challenges. In particular, with so many cancer-associate metabolites being identified, it is often difficult to keep track of which compounds are associated with which cancers. It is also challenging to track down information on the specific pathways that particular metabolites, drugs or drug metabolites may be affecting. Even more frustrating are the difficulties associated with identifying metabolites from NMR or MS spectra. Fortunately, a number of metabolomics databases are emerging that are designed to address these challenges. One such database is the Human Metabolome Database (HMDB). The HMDB is currently the world’s largest and most comprehensive, organism-specific metabolomics database. It contains more than 40,000 metabolite entries, thousands of metabolite concentrations, >700 metabolic and disease-associated pathways, as well as information on dozens of cancer biomarkers. This review is intended to provide a brief summary of the HMDB and to offer some guidance on how it can be used in metabolomic studies of cancer. PMID:26950159

  14. Cancer Metabolomics and the Human Metabolome Database.

    PubMed

    Wishart, David S; Mandal, Rupasri; Stanislaus, Avalyn; Ramirez-Gaona, Miguel

    2016-03-02

    The application of metabolomics towards cancer research has led to a renewed appreciation of metabolism in cancer development and progression. It has also led to the discovery of metabolite cancer biomarkers and the identification of a number of novel cancer causing metabolites. The rapid growth of metabolomics in cancer research is also leading to challenges. In particular, with so many cancer-associate metabolites being identified, it is often difficult to keep track of which compounds are associated with which cancers. It is also challenging to track down information on the specific pathways that particular metabolites, drugs or drug metabolites may be affecting. Even more frustrating are the difficulties associated with identifying metabolites from NMR or MS spectra. Fortunately, a number of metabolomics databases are emerging that are designed to address these challenges. One such database is the Human Metabolome Database (HMDB). The HMDB is currently the world's largest and most comprehensive, organism-specific metabolomics database. It contains more than 40,000 metabolite entries, thousands of metabolite concentrations, >700 metabolic and disease-associated pathways, as well as information on dozens of cancer biomarkers. This review is intended to provide a brief summary of the HMDB and to offer some guidance on how it can be used in metabolomic studies of cancer.

  15. Gene Ontology Annotations and Resources

    PubMed Central

    2013-01-01

    The Gene Ontology (GO) Consortium (GOC, http://www.geneontology.org) is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies. Over the past year, the GOC has implemented several processes to increase the quantity, quality and specificity of GO annotations. First, the number of manual, literature-based annotations has grown at an increasing rate. Second, as a result of a new ‘phylogenetic annotation’ process, manually reviewed, homology-based annotations are becoming available for a broad range of species. Third, the quality of GO annotations has been improved through a streamlined process for, and automated quality checks of, GO annotations deposited by different annotation groups. Fourth, the consistency and correctness of the ontology itself has increased by using automated reasoning tools. Finally, the GO has been expanded not only to cover new areas of biology through focused interaction with experts, but also to capture greater specificity in all areas of the ontology using tools for adding new combinatorial terms. The GOC works closely with other ontology developers to support integrated use of terminologies. The GOC supports its user community through the use of e-mail lists, social media and web-based resources. PMID:23161678

  16. Likelihood-based gene annotations for gap filling and quality assessment in genome-scale metabolic models

    DOE PAGES

    Benedict, Matthew N.; Mundy, Michael B.; Henry, Christopher S.; ...

    2014-10-16

    Genome-scale metabolic models provide a powerful means to harness information from genomes to deepen biological insights. With exponentially increasing sequencing capacity, there is an enormous need for automated reconstruction techniques that can provide more accurate models in a short time frame. Current methods for automated metabolic network reconstruction rely on gene and reaction annotations to build draft metabolic networks and algorithms to fill gaps in these networks. However, automated reconstruction is hampered by database inconsistencies, incorrect annotations, and gap filling largely without considering genomic information. Here we develop an approach for applying genomic information to predict alternative functions for genesmore » and estimate their likelihoods from sequence homology. We show that computed likelihood values were significantly higher for annotations found in manually curated metabolic networks than those that were not. We then apply these alternative functional predictions to estimate reaction likelihoods, which are used in a new gap filling approach called likelihood-based gap filling to predict more genomically consistent solutions. To validate the likelihood-based gap filling approach, we applied it to models where essential pathways were removed, finding that likelihood-based gap filling identified more biologically relevant solutions than parsimony-based gap filling approaches. We also demonstrate that models gap filled using likelihood-based gap filling provide greater coverage and genomic consistency with metabolic gene functions compared to parsimony-based approaches. Interestingly, despite these findings, we found that likelihoods did not significantly affect consistency of gap filled models with Biolog and knockout lethality data. This indicates that the phenotype data alone cannot necessarily be used to discriminate between alternative solutions for gap filling and therefore, that the use of other information is necessary

  17. Likelihood-based gene annotations for gap filling and quality assessment in genome-scale metabolic models

    SciTech Connect

    Benedict, Matthew N.; Mundy, Michael B.; Henry, Christopher S.; Chia, Nicholas; Price, Nathan D.; Maranas, Costas D.

    2014-10-16

    Genome-scale metabolic models provide a powerful means to harness information from genomes to deepen biological insights. With exponentially increasing sequencing capacity, there is an enormous need for automated reconstruction techniques that can provide more accurate models in a short time frame. Current methods for automated metabolic network reconstruction rely on gene and reaction annotations to build draft metabolic networks and algorithms to fill gaps in these networks. However, automated reconstruction is hampered by database inconsistencies, incorrect annotations, and gap filling largely without considering genomic information. Here we develop an approach for applying genomic information to predict alternative functions for genes and estimate their likelihoods from sequence homology. We show that computed likelihood values were significantly higher for annotations found in manually curated metabolic networks than those that were not. We then apply these alternative functional predictions to estimate reaction likelihoods, which are used in a new gap filling approach called likelihood-based gap filling to predict more genomically consistent solutions. To validate the likelihood-based gap filling approach, we applied it to models where essential pathways were removed, finding that likelihood-based gap filling identified more biologically relevant solutions than parsimony-based gap filling approaches. We also demonstrate that models gap filled using likelihood-based gap filling provide greater coverage and genomic consistency with metabolic gene functions compared to parsimony-based approaches. Interestingly, despite these findings, we found that likelihoods did not significantly affect consistency of gap filled models with Biolog and knockout lethality data. This indicates that the phenotype data alone cannot necessarily be used to discriminate between alternative solutions for gap filling and therefore, that the use of other information is necessary to

  18. Likelihood-based gene annotations for gap filling and quality assessment in genome-scale metabolic models.

    PubMed

    Benedict, Matthew N; Mundy, Michael B; Henry, Christopher S; Chia, Nicholas; Price, Nathan D

    2014-10-01

    Genome-scale metabolic models provide a powerful means to harness information from genomes to deepen biological insights. With exponentially increasing sequencing capacity, there is an enormous need for automated reconstruction techniques that can provide more accurate models in a short time frame. Current methods for automated metabolic network reconstruction rely on gene and reaction annotations to build draft metabolic networks and algorithms to fill gaps in these networks. However, automated reconstruction is hampered by database inconsistencies, incorrect annotations, and gap filling largely without considering genomic information. Here we develop an approach for applying genomic information to predict alternative functions for genes and estimate their likelihoods from sequence homology. We show that computed likelihood values were significantly higher for annotations found in manually curated metabolic networks than those that were not. We then apply these alternative functional predictions to estimate reaction likelihoods, which are used in a new gap filling approach called likelihood-based gap filling to predict more genomically consistent solutions. To validate the likelihood-based gap filling approach, we applied it to models where essential pathways were removed, finding that likelihood-based gap filling identified more biologically relevant solutions than parsimony-based gap filling approaches. We also demonstrate that models gap filled using likelihood-based gap filling provide greater coverage and genomic consistency with metabolic gene functions compared to parsimony-based approaches. Interestingly, despite these findings, we found that likelihoods did not significantly affect consistency of gap filled models with Biolog and knockout lethality data. This indicates that the phenotype data alone cannot necessarily be used to discriminate between alternative solutions for gap filling and therefore, that the use of other information is necessary to

  19. Metabolomics: A Primer.

    PubMed

    Liu, Xiaojing; Locasale, Jason W

    2017-04-01

    Metabolomics generates a profile of small molecules that are derived from cellular metabolism and can directly reflect the outcome of complex networks of biochemical reactions, thus providing insights into multiple aspects of cellular physiology. Technological advances have enabled rapid and increasingly expansive data acquisition with samples as small as single cells; however, substantial challenges in the field remain. In this primer we provide an overview of metabolomics, especially mass spectrometry (MS)-based metabolomics, which uses liquid chromatography (LC) for separation, and discuss its utilities and limitations. We identify and discuss several areas at the frontier of metabolomics. Our goal is to give the reader a sense of what might be accomplished when conducting a metabolomics experiment, now and in the near future.

  20. Metabolomics in hypertension.

    PubMed

    Nikolic, Sonja B; Sharman, James E; Adams, Murray J; Edwards, Lindsay M

    2014-06-01

    Hypertension is the most prevalent chronic medical condition and a major risk factor for cardiovascular morbidity and mortality. In the majority of hypertensive cases, the underlying cause of hypertension cannot be easily identified because of the heterogeneous, polygenic and multi-factorial nature of hypertension. Metabolomics is a relatively new field of research that has been used to evaluate metabolic perturbations associated with disease, identify disease biomarkers and to both assess and predict drug safety and efficacy. Metabolomics has been increasingly used to characterize risk factors for cardiovascular disease, including hypertension, and it appears to have significant potential for uncovering mechanisms of this complex disease. This review details the analytical techniques, pre-analytical steps and study designs used in metabolomics studies, as well as the emerging role for metabolomics in gaining mechanistic insights into the development of hypertension. Suggestions as to the future direction for metabolomics research in the field of hypertension are also proposed.

  1. MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments.

    PubMed

    Franceschi, Pietro; Mylonas, Roman; Shahaf, Nir; Scholz, Matthias; Arapitsas, Panagiotis; Masuero, Domenico; Weingart, Georg; Carlin, Silvia; Vrhovsek, Urska; Mattivi, Fulvio; Wehrens, Ron

    2014-01-01

    Due to their sensitivity and speed, mass-spectrometry based analytical technologies are widely used to in metabolomics to characterize biological phenomena. To address issues like metadata organization, quality assessment, data processing, data storage, and, finally, submission to public repositories, bioinformatic pipelines of a non-interactive nature are often employed, complementing the interactive software used for initial inspection and visualization of the data. These pipelines often are created as open-source software allowing the complete and exhaustive documentation of each step, ensuring the reproducibility of the analysis of extensive and often expensive experiments. In this paper, we will review the major steps which constitute such a data processing pipeline, discussing them in the context of an open-source software for untargeted MS-based metabolomics experiments recently developed at our institute. The software has been developed by integrating our metaMS R package with a user-friendly web-based application written in Grails. MetaMS takes care of data pre-processing and annotation, while the interface deals with the creation of the sample lists, the organization of the data storage, and the generation of survey plots for quality assessment. Experimental and biological metadata are stored in the ISA-Tab format making the proposed pipeline fully integrated with the Metabolights framework.

  2. TriAnnot: A Versatile and High Performance Pipeline for the Automated Annotation of Plant Genomes

    PubMed Central

    Leroy, Philippe; Guilhot, Nicolas; Sakai, Hiroaki; Bernard, Aurélien; Choulet, Frédéric; Theil, Sébastien; Reboux, Sébastien; Amano, Naoki; Flutre, Timothée; Pelegrin, Céline; Ohyanagi, Hajime; Seidel, Michael; Giacomoni, Franck; Reichstadt, Mathieu; Alaux, Michael; Gicquello, Emmanuelle; Legeai, Fabrice; Cerutti, Lorenzo; Numa, Hisataka; Tanaka, Tsuyoshi; Mayer, Klaus; Itoh, Takeshi; Quesneville, Hadi; Feuillet, Catherine

    2012-01-01

    In support of the international effort to obtain a reference sequence of the bread wheat genome and to provide plant communities dealing with large and complex genomes with a versatile, easy-to-use online automated tool for annotation, we have developed the TriAnnot pipeline. Its modular architecture allows for the annotation and masking of transposable elements, the structural, and functional annotation of protein-coding genes with an evidence-based quality indexing, and the identification of conserved non-coding sequences and molecular markers. The TriAnnot pipeline is parallelized on a 712 CPU computing cluster that can run a 1-Gb sequence annotation in less than 5 days. It is accessible through a web interface for small scale analyses or through a server for large scale annotations. The performance of TriAnnot was evaluated in terms of sensitivity, specificity, and general fitness using curated reference sequence sets from rice and wheat. In less than 8 h, TriAnnot was able to predict more than 83% of the 3,748 CDS from rice chromosome 1 with a fitness of 67.4%. On a set of 12 reference Mb-sized contigs from wheat chromosome 3B, TriAnnot predicted and annotated 93.3% of the genes among which 54% were perfectly identified in accordance with the reference annotation. It also allowed the curation of 12 genes based on new biological evidences, increasing the percentage of perfect gene prediction to 63%. TriAnnot systematically showed a higher fitness than other annotation pipelines that are not improved for wheat. As it is easily adaptable to the annotation of other plant genomes, TriAnnot should become a useful resource for the annotation of large and complex genomes in the future. PMID:22645565

  3. Error Analysis and Propagation in Metabolomics Data Analysis.

    PubMed

    Moseley, Hunter N B

    2013-01-01

    Error analysis plays a fundamental role in describing the uncertainty in experimental results. It has several fundamental uses in metabolomics including experimental design, quality control of experiments, the selection of appropriate statistical methods, and the determination of uncertainty in results. Furthermore, the importance of error analysis has grown with the increasing number, complexity, and heterogeneity of measurements characteristic of 'omics research. The increase in data complexity is particularly problematic for metabolomics, which has more heterogeneity than other omics technologies due to the much wider range of molecular entities detected and measured. This review introduces the fundamental concepts of error analysis as they apply to a wide range of metabolomics experimental designs and it discusses current methodologies for determining the propagation of uncertainty in appropriate metabolomics data analysis. These methodologies include analytical derivation and approximation techniques, Monte Carlo error analysis, and error analysis in metabolic inverse problems. Current limitations of each methodology with respect to metabolomics data analysis are also discussed.

  4. Metabolomics in chemical ecology.

    PubMed

    Kuhlisch, Constanze; Pohnert, Georg

    2015-07-01

    Chemical ecology elucidates the nature and role of natural products as mediators of organismal interactions. The emerging techniques that can be summarized under the concept of metabolomics provide new opportunities to study such environmentally relevant signaling molecules. Especially comparative tools in metabolomics enable the identification of compounds that are regulated during interaction situations and that might play a role as e.g. pheromones, allelochemicals or in induced and activated defenses. This approach helps overcoming limitations of traditional bioassay-guided structure elucidation approaches. But the power of metabolomics is not limited to the comparison of metabolic profiles of interacting partners. Especially the link to other -omics techniques helps to unravel not only the compounds in question but the entire biosynthetic and genetic re-wiring, required for an ecological response. This review comprehensively highlights successful applications of metabolomics in chemical ecology and discusses existing limitations of these novel techniques. It focuses on recent developments in comparative metabolomics and discusses the use of metabolomics in the systems biology of organismal interactions. It also outlines the potential of large metabolomics initiatives for model organisms in the field of chemical ecology.

  5. The Human Serum Metabolome

    PubMed Central

    Psychogios, Nikolaos; Hau, David D.; Peng, Jun; Guo, An Chi; Mandal, Rupasri; Bouatra, Souhaila; Sinelnikov, Igor; Krishnamurthy, Ramanarayan; Eisner, Roman; Gautam, Bijaya; Young, Nelson; Xia, Jianguo; Knox, Craig; Dong, Edison; Huang, Paul; Hollander, Zsuzsanna; Pedersen, Theresa L.; Smith, Steven R.; Bamforth, Fiona; Greiner, Russ; McManus, Bruce; Newman, John W.; Goodfriend, Theodore; Wishart, David S.

    2011-01-01

    Continuing improvements in analytical technology along with an increased interest in performing comprehensive, quantitative metabolic profiling, is leading to increased interest pressures within the metabolomics community to develop centralized metabolite reference resources for certain clinically important biofluids, such as cerebrospinal fluid, urine and blood. As part of an ongoing effort to systematically characterize the human metabolome through the Human Metabolome Project, we have undertaken the task of characterizing the human serum metabolome. In doing so, we have combined targeted and non-targeted NMR, GC-MS and LC-MS methods with computer-aided literature mining to identify and quantify a comprehensive, if not absolutely complete, set of metabolites commonly detected and quantified (with today's technology) in the human serum metabolome. Our use of multiple metabolomics platforms and technologies allowed us to substantially enhance the level of metabolome coverage while critically assessing the relative strengths and weaknesses of these platforms or technologies. Tables containing the complete set of 4229 confirmed and highly probable human serum compounds, their concentrations, related literature references and links to their known disease associations are freely available at http://www.serummetabolome.ca. PMID:21359215

  6. Considerations when choosing a genetic model organism for metabolomics studies.

    PubMed

    Reed, Laura K; Baer, Charles F; Edison, Arthur S

    2017-02-01

    Model organisms are important in many areas of chemical biology. In metabolomics, model organisms can provide excellent samples for methods development as well as the foundation of comparative phylometabolomics, which will become possible as metabolomics applications expand. Comparative studies of conserved and unique metabolic pathways will help in the annotation of metabolites as well as provide important new targets of investigation in biology and biomedicine. However, most chemical biologists are not familiar with genetics, which needs to be considered when choosing a model organism. In this review we summarize the strengths and weaknesses of several genetic systems, including natural isolates, recombinant inbred lines, and genetic mutations. We also discuss methods to detect targets of selection on the metabolome.

  7. Training in metabolomics research. I. Designing the experiment, collecting and extracting samples and generating metabolomics data

    PubMed Central

    Barnes, Stephen; Benton, H. Paul; Casazza, Krista; Cooper, Sara J.; Cui, Xiangqin; Du, Xiuxia; Engler, Jeffrey; Kabarowski, Janusz H.; Li, Shuzhao; Pathmasiri, Wimal; Prasain, Jeevan K.; Renfrow, Matthew B.; Tiwari, Hemant K.

    2016-01-01

    The study of metabolism has had a long history. Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. The National Institutes of Health Common Fund Metabolomics Program was established in 2012 to stimulate interest in the approaches and technologies of metabolomics. To deliver one of the program’s goals, the University of Alabama at Birmingham has hosted an annual 4-day short course in metabolomics for faculty, postdoctoral fellows and graduate students from national and international institutions. This paper is the first part of a summary of the training materials presented in the course to be used as a resource for all those embarking on metabolomics research. PMID:27434804

  8. Metabolomics and malaria biology

    PubMed Central

    Lakshmanan, Viswanathan; Rhee, Kyu Y.; Daily, Johanna P.

    2010-01-01

    Metabolomics has ushered in a novel and multi-disciplinary realm in biological research. It has provided researchers with a platform to combine powerful biochemical, statistical, computational, and bioinformatics techniques to delve into the mysteries of biology and disease. The application of metabolomics to study malaria parasites represents a major advance in our approach towards gaining a more comprehensive perspective on parasite biology and disease etiology. This review attempts to highlight some of the important aspects of the field of metabolomics, and its ongoing and potential future applications to malaria research. PMID:20970461

  9. Enhanced acylcarnitine annotation in high-resolution mass spectrometry data: fragmentation analysis for the classification and annotation of acylcarnitines.

    PubMed

    van der Hooft, Justin J J; Ridder, Lars; Barrett, Michael P; Burgess, Karl E V

    2015-01-01

    Metabolite annotation and identification are primary challenges in untargeted metabolomics experiments. Rigorous workflows for reliable annotation of mass features with chemical structures or compound classes are needed to enhance the power of untargeted mass spectrometry. High-resolution mass spectrometry considerably improves the confidence in assigning elemental formulas to mass features in comparison to nominal mass spectrometry, and embedding of fragmentation methods enables more reliable metabolite annotations and facilitates metabolite classification. However, the analysis of mass fragmentation spectra can be a time-consuming step and requires expert knowledge. This study demonstrates how characteristic fragmentations, specific to compound classes, can be used to systematically analyze their presence in complex biological extracts like urine that have undergone untargeted mass spectrometry combined with data dependent or targeted fragmentation. Human urine extracts were analyzed using normal phase liquid chromatography (hydrophilic interaction chromatography) coupled to an Ion Trap-Orbitrap hybrid instrument. Subsequently, mass chromatograms and collision-induced dissociation and higher-energy collisional dissociation (HCD) fragments were annotated using the freely available MAGMa software. Acylcarnitines play a central role in energy metabolism by transporting fatty acids into the mitochondrial matrix. By filtering on a combination of a mass fragment and neutral loss designed based on the MAGMa fragment annotations, we were able to classify and annotate 50 acylcarnitines in human urine extracts, based on high-resolution mass spectrometry HCD fragmentation spectra at different energies for all of them. Of these annotated acylcarnitines, 31 are not described in HMDB yet and for only 4 annotated acylcarnitines the fragmentation spectra could be matched to reference spectra. Therefore, we conclude that the use of mass fragmentation filters within the context of

  10. Enhanced Acylcarnitine Annotation in High-Resolution Mass Spectrometry Data: Fragmentation Analysis for the Classification and Annotation of Acylcarnitines

    PubMed Central

    van der Hooft, Justin J. J.; Ridder, Lars; Barrett, Michael P.; Burgess, Karl E. V.

    2015-01-01

    Metabolite annotation and identification are primary challenges in untargeted metabolomics experiments. Rigorous workflows for reliable annotation of mass features with chemical structures or compound classes are needed to enhance the power of untargeted mass spectrometry. High-resolution mass spectrometry considerably improves the confidence in assigning elemental formulas to mass features in comparison to nominal mass spectrometry, and embedding of fragmentation methods enables more reliable metabolite annotations and facilitates metabolite classification. However, the analysis of mass fragmentation spectra can be a time-consuming step and requires expert knowledge. This study demonstrates how characteristic fragmentations, specific to compound classes, can be used to systematically analyze their presence in complex biological extracts like urine that have undergone untargeted mass spectrometry combined with data dependent or targeted fragmentation. Human urine extracts were analyzed using normal phase liquid chromatography (hydrophilic interaction chromatography) coupled to an Ion Trap-Orbitrap hybrid instrument. Subsequently, mass chromatograms and collision-induced dissociation and higher-energy collisional dissociation (HCD) fragments were annotated using the freely available MAGMa software1. Acylcarnitines play a central role in energy metabolism by transporting fatty acids into the mitochondrial matrix. By filtering on a combination of a mass fragment and neutral loss designed based on the MAGMa fragment annotations, we were able to classify and annotate 50 acylcarnitines in human urine extracts, based on high-resolution mass spectrometry HCD fragmentation spectra at different energies for all of them. Of these annotated acylcarnitines, 31 are not described in HMDB yet and for only 4 annotated acylcarnitines the fragmentation spectra could be matched to reference spectra. Therefore, we conclude that the use of mass fragmentation filters within the context

  11. Metabolomics and protozoan parasites.

    PubMed

    Paget, Timothy; Haroune, Nicolas; Bagchi, Sushmita; Jarroll, Edward

    2013-06-01

    In this review, we examine the state-of-the-art technologies (gas and liquid chromatography, mass spectroscopy and nuclear magnetic resonance, etc.) in the well-established area of metabolomics especially as they relate to protozoan parasites.

  12. Metabolomics in dyslipidemia.

    PubMed

    Chen, Hua; Miao, Hua; Feng, Ya-Long; Zhao, Ying-Yong; Lin, Rui-Chao

    2014-01-01

    Hyperlipidemia is an important public health problem with increased incidence and prevalence worldwide. Current clinical biomarkers, triglyceride, total cholesterol, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol lack the necessary specificity and sensitivity and only increase significantly after serious dyslipidemia. Therefore, sensitive biomarkers are needed for hyperlipidemia. Hyperlipidemia-specific biomarkers would improve clinical diagnosis and therapeutic treatment at early disease stages. The aim of metabolomics is to identify untargeted and global small-molecule metabolite profiles from cells, biofluids, and tissues. This method offers the potential for a holistic approach to improve disease diagnoses and our understanding of underlying pathologic mechanisms. This review summarizes analytical techniques, data collection and analysis for metabolomics, and metabolomics in hyperlipidemia animal models and clinical studies. Mechanisms of hypolipemia and antilipemic drug therapy are also discussed. Metabolomics provides a new opportunity to gain insight into metabolic profiling and pathophysiologic mechanisms of hyperlipidemia.

  13. The human serum metabolome

    USDA-ARS?s Scientific Manuscript database

    Continuing improvements in analytical technology along with an increased interest in performing comprehensive, quantitative metabolic profiling, is leading to increased interest pressures within the metabolomics community to develop centralized metabolite reference resources for certain clinically i...

  14. Optimized experimental workflow for tandem mass spectrometry molecular networking in metabolomics.

    PubMed

    Olivon, Florent; Roussi, Fanny; Litaudon, Marc; Touboul, David

    2017-07-31

    New omics sciences generate massive amounts of data, requiring to be sorted, curated, and statistically analyzed by dedicated software. Data-dependent acquisition mode including inclusion and exclusion rules for tandem mass spectrometry is routinely used to perform such analyses. While acquisition parameters are well described for proteomics, no general rule is currently available to generate reliable metabolomic data for molecular networking analysis on the Global Natural Product Social Molecular Networking platform (GNPS). Following on from an exploration of key parameters influencing the quality of molecular networks, universal optimal acquisition conditions for metabolomic studies are suggested in the present paper. The benefit of data pre-clustering before initiating large datasets for GNPS analyses is also demonstrated. Moreover, an efficient workflow dedicated to Agilent Technologies instruments is described, making the dereplication process easier by unambiguously distinguishing isobaric isomers eluted at different retention times, annotating the molecular networks with chemical formulas, and giving access to semi-quantitative data. This specific workflow foreshadows future developments of the GNPS platform.

  15. From classical taxonomy to genome and metabolome: towards comprehensive quality standards for medicinal herb raw materials and extracts.

    PubMed

    Govindaraghavan, Suresh; Hennell, James R; Sucher, Nikolaus J

    2012-09-01

    Fundamental to herbal medicine quality is the use of 'authentic' medicinal herb species. Species, however, 'represent more or less arbitrary and subjective man-made units'. Against this background, we discuss, with illustrative examples, the importance of defining species boundaries by accommodating both the fixed (shared) diagnostic and varying (within-species) traits in medicinal herb populations. We emphasize the role of taxonomy, floristic information and genomic profiling in authenticating medicinal herb species, in addition to the need to include within species phytochemical profile variations while developing herbal extract identification protocols. We outline the application of species-specific genomic and phytochemical markers, chemoprofiling and chemometrics as additional tools to develop qualifying herbal extract references. We list the diagnostic traits available subsequent to each step during the medicinal herb extract manufacturing process and delineate limits to qualification of extract references. Copyright © 2012 Elsevier B.V. All rights reserved.

  16. Evaluating the effects of machine pre-annotation and an interactive annotation interface on manual de-identification of clinical text.

    PubMed

    South, Brett R; Mowery, Danielle; Suo, Ying; Leng, Jianwei; Ferrández, Óscar; Meystre, Stephane M; Chapman, Wendy W

    2014-08-01

    The Health Insurance Portability and Accountability Act (HIPAA) Safe Harbor method requires removal of 18 types of protected health information (PHI) from clinical documents to be considered "de-identified" prior to use for research purposes. Human review of PHI elements from a large corpus of clinical documents can be tedious and error-prone. Indeed, multiple annotators may be required to consistently redact information that represents each PHI class. Automated de-identification has the potential to improve annotation quality and reduce annotation time. For instance, using machine-assisted annotation by combining de-identification system outputs used as pre-annotations and an interactive annotation interface to provide annotators with PHI annotations for "curation" rather than manual annotation from "scratch" on raw clinical documents. In order to assess whether machine-assisted annotation improves the reliability and accuracy of the reference standard quality and reduces annotation effort, we conducted an annotation experiment. In this annotation study, we assessed the generalizability of the VA Consortium for Healthcare Informatics Research (CHIR) annotation schema and guidelines applied to a corpus of publicly available clinical documents called MTSamples. Specifically, our goals were to (1) characterize a heterogeneous corpus of clinical documents manually annotated for risk-ranked PHI and other annotation types (clinical eponyms and person relations), (2) evaluate how well annotators apply the CHIR schema to the heterogeneous corpus, (3) compare whether machine-assisted annotation (experiment) improves annotation quality and reduces annotation time compared to manual annotation (control), and (4) assess the change in quality of reference standard coverage with each added annotator's annotations.

  17. COnsortium of METabolomics Studies (COMETS)

    Cancer.gov

    The COnsortium of METabolomics Studies (COMETS) is an extramural-intramural partnership that promotes collaboration among prospective cohort studies that follow participants for a range of outcomes and perform metabolomic profiling of individuals.

  18. Metabolomics of temperature stress.

    PubMed

    Guy, Charles; Kaplan, Fatma; Kopka, Joachim; Selbig, Joachim; Hincha, Dirk K

    2008-02-01

    Plants possess inducible tolerance mechanisms that extend the temperature range for survival during acute temperature stress. The inducible mechanisms of cold acclimation and acquired thermotolerance involve highly complex processes. These include perception and signal transduction of non-optimal temperatures or their physical consequences on cellular components that program extensive modification of the transcriptome, proteome, metabolome and composition and physical structure of the cytoplasm, membranes and cell walls. Therefore, a systems biology approach will be necessary to advance the understanding of plant stress responses and tolerance mechanisms. One promise of systems biology is that it will greatly enhance our understanding of individual and collective functions and thereby provide a more holistic view of plant stress responses. Past studies have found that several metabolites that could functionally contribute to induced stress tolerance have been associated with stress responses. Recent metabolite-profiling studies have refocused attention on these and other potentially important components found in the 'temperature-stress metabolome'. These metabolomic studies have demonstrated that active reconfiguration of the metabolome is regulated in part by changes in gene expression initiated by temperature-stress-activated signaling and stress-related transcription factors. One aspect of metabolism that is consistent across all of the temperature-stress metabolomic studies to date is the prominent role of central carbohydrate metabolism, which seems to be a major feature of the reprogramming of the metabolome during temperature stress. Future metabolomic studies of plant temperature-stress responses should reveal additional metabolic pathways that have important functions in temperature-stress tolerance mechanisms.

  19. Corpus annotation for mining biomedical events from literature

    PubMed Central

    Kim, Jin-Dong; Ohta, Tomoko; Tsujii, Jun'ichi

    2008-01-01

    Background Advanced Text Mining (TM) such as semantic enrichment of papers, event or relation extraction, and intelligent Question Answering have increasingly attracted attention in the bio-medical domain. For such attempts to succeed, text annotation from the biological point of view is indispensable. However, due to the complexity of the task, semantic annotation has never been tried on a large scale, apart from relatively simple term annotation. Results We have completed a new type of semantic annotation, event annotation, which is an addition to the existing annotations in the GENIA corpus. The corpus has already been annotated with POS (Parts of Speech), syntactic trees, terms, etc. The new annotation was made on half of the GENIA corpus, consisting of 1,000 Medline abstracts. It contains 9,372 sentences in which 36,114 events are identified. The major challenges during event annotation were (1) to design a scheme of annotation which meets specific requirements of text annotation, (2) to achieve biology-oriented annotation which reflect biologists' interpretation of text, and (3) to ensure the homogeneity of annotation quality across annotators. To meet these challenges, we introduced new concepts such as Single-facet Annotation and Semantic Typing, which have collectively contributed to successful completion of a large scale annotation. Conclusion The resulting event-annotated corpus is the largest and one of the best in quality among similar annotation efforts. We expect it to become a valuable resource for NLP (Natural Language Processing)-based TM in the bio-medical domain. PMID:18182099

  20. Training in metabolomics research. II. Processing and statistical analysis of metabolomics data, metabolite identification, pathway analysis, applications of metabolomics and its future

    PubMed Central

    Barnes, Stephen; Benton, H. Paul; Casazza, Krista; Cooper, Sara; Cui, Xiangqin; Du, Xiuxia; Engler, Jeffrey; Kabarowski, Janusz H.; Li, Shuzhao; Pathmasiri, Wimal; Prasain, Jeevan K.; Renfrow, Matthew B.; Tiwari, Hemant K.

    2017-01-01

    Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites, and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. This second part of a comprehensive description of the methods of metabolomics focuses on data analysis, emerging methods in metabolomics and the future of this discipline. PMID:28239968

  1. Bacterial genome annotation.

    PubMed

    Beckloff, Nicholas; Starkenburg, Shawn; Freitas, Tracey; Chain, Patrick

    2012-01-01

    Annotation of prokaryotic sequences can be separated into structural and functional annotation. Structural annotation is dependent on algorithmic interrogation of experimental evidence to discover the physical characteristics of a gene. This is done in an effort to construct accurate gene models, so understanding function or evolution of genes among organisms is not impeded. Functional annotation is dependent on sequence similarity to other known genes or proteins in an effort to assess the function of the gene. Combining structural and functional annotation across genomes in a comparative manner promotes higher levels of accurate annotation as well as an advanced understanding of genome evolution. As the availability of bacterial sequences increases and annotation methods improve, the value of comparative annotation will increase.

  2. Improving the quality of biomarker candidates in untargeted metabolomics via peak table-based alignment of comprehensive two-dimensional gas chromatography-mass spectrometry data

    PubMed Central

    Bean, Heather D.; Hill, Jane E.; Dimandja, Jean-Marie D.

    2015-01-01

    The potential of high-resolution analytical technologies like GC×GC/TOF MS in untargeted metabolomics and biomarker discovery has been limited by the development of fully automated software that can efficiently align and extract information from multiple chromatographic data sets. In this work we report the first investigation on a peak-by-peak basis of the chromatographic factors that impact GC×GC data alignment. A representative set of 16 compounds of different chromatographic characteristics were followed through the alignment of 63 GC×GC chromatograms. We found that varying the mass spectral match parameter had a significant influence on the alignment for poorly- resolved peaks, especially those at the extremes of the detector linear range, and no influence on well- chromatographed peaks. Therefore, optimized chromatography is required for proper GC×GC data alignment. Based on these observations, a workflow is presented for the conservative selection of biomarker candidates from untargeted metabolomics analyses. PMID:25857541

  3. Clinical Metabolomics and Glaucoma.

    PubMed

    Barbosa-Breda, João; Himmelreich, Uwe; Ghesquière, Bart; Rocha-Sousa, Amândio; Stalmans, Ingeborg

    2017-09-01

    Glaucoma is one of the leading causes of irreversible blindness worldwide. However, there are no biomarkers that accurately help clinicians perform an early diagnosis or detect patients with a high risk of progression. Metabolomics is the study of all metabolites in an organism, and it has the potential to provide a biomarker. This review summarizes the findings of metabolomics in glaucoma patients and explains why this field is promising for new research. We identified published studies that focused on metabolomics and ophthalmology. After providing an overview of metabolomics in ophthalmology, we focused on human glaucoma studies. Five studies have been conducted in glaucoma patients and all compared patients to healthy controls. Using mass spectrometry, significant differences were found in blood plasma in the metabolic pathways that involve palmitoylcarnitine, sphingolipids, vitamin D-related compounds, and steroid precursors. For nuclear magnetic resonance spectroscopy, a high glutamine-glutamate/creatine ratio was found in the vitreous and lateral geniculate body; no differences were detected in the optic radiations, and a lower N-acetylaspartate/choline ratio was observed in the geniculocalcarine and striate areas. Metabolomics can move glaucoma care towards a personalized approach and provide new knowledge concerning the pathophysiology of glaucoma, which can lead to new therapeutic options. © 2017 S. Karger AG, Basel.

  4. Establishing Substantial Equivalence: Metabolomics

    NASA Astrophysics Data System (ADS)

    Beale, Michael H.; Ward, Jane L.; Baker, John M.

    Modern ‘metabolomic’ methods allow us to compare levels of many structurally diverse compounds in an automated fashion across a large number of samples. This technology is ideally suited to screening of populations of plants, including trials where the aim is the determination of unintended effects introduced by GM. A number of metabolomic methods have been devised for the determination of substantial equivalence. We have developed a methodology, using [1H]-NMR fingerprinting, for metabolomic screening of plants and have applied it to the study of substantial equivalence of field-grown GM wheat. We describe here the principles and detail of that protocol as applied to the analysis of flour generated from field plots of wheat. Particular emphasis is given to the downstream data processing and comparison of spectra by multivariate analysis, from which conclusions regarding metabolome changes due to the GM can be assessed against the background of natural variation due to environment.

  5. Metabolomics of Diabetic Retinopathy.

    PubMed

    Liew, Gerald; Lei, Zhou; Tan, Gavin; Joachim, Nichole; Ho, I-Van; Wong, Tien Y; Mitchell, Paul; Gopinath, Bamini; Crossett, Ben

    2017-09-23

    Metabolomics is the study of dysregulated metabolites in biological materials. We reviewed the use of the technique to elucidate the genetic and environmental factors that contribute to the development of diabetic retinopathy. With regard to metabolomic studies of diabetic retinopathy, the field remains in its infancy with few studies published to date and little replication of results. Vitreous and serum samples are the main tissues examined, and dysregulation in pathways such as the pentose phosphate pathway, arginine to proline pathway, polyol pathway, and ascorbic acidic pathways have been reported. Few studies have examined the metabolomic underpinnings of diabetic retinopathy. Further research is required to replicate findings to date and determine longitudinal associations with disease.

  6. Metabolomics for Plant Improvement: Status and Prospects

    PubMed Central

    Kumar, Rakesh; Bohra, Abhishek; Pandey, Arun K.; Pandey, Manish K.; Kumar, Anirudh

    2017-01-01

    Post-genomics era has witnessed the development of cutting-edge technologies that have offered cost-efficient and high-throughput ways for molecular characterization of the function of a cell or organism. Large-scale metabolite profiling assays have allowed researchers to access the global data sets of metabolites and the corresponding metabolic pathways in an unprecedented way. Recent efforts in metabolomics have been directed to improve the quality along with a major focus on yield related traits. Importantly, an integration of metabolomics with other approaches such as quantitative genetics, transcriptomics and genetic modification has established its immense relevance to plant improvement. An effective combination of these modern approaches guides researchers to pinpoint the functional gene(s) and the characterization of massive metabolites, in order to prioritize the candidate genes for downstream analyses and ultimately, offering trait specific markers to improve commercially important traits. This in turn will improve the ability of a plant breeder by allowing him to make more informed decisions. Given this, the present review captures the significant leads gained in the past decade in the field of plant metabolomics accompanied by a brief discussion on the current contribution and the future scope of metabolomics to accelerate plant improvement. PMID:28824660

  7. Metabolomics in childhood diabetes

    PubMed Central

    Frohnert, Brigitte I; Rewers, Marian J

    2015-01-01

    Recent increases in the incidence of both type 1 (T1D) and type 2 diabetes (T2D) in children and adolescents point to the importance of environmental factors in the development of these diseases. Metabolomic analysis explores the integrated response of the organism to environmental changes. Metabolic profiling can identify biomarkers that are predictive of disease incidence and development, potentially providing insight into disease pathogenesis. This review provides an overview of the role of metabolomic analysis in diabetes research and summarizes recent research relating to the development of T1D and T2D in children. PMID:26420304

  8. Metabolomic strategies for the identification of new enzyme functions and metabolic pathways

    PubMed Central

    Prosser, Gareth A; Larrouy-Maumus, Gerald; de Carvalho, Luiz Pedro S

    2014-01-01

    Recent technological advances in accurate mass spectrometry and data analysis have revolutionized metabolomics experimentation. Activity-based and global metabolomic profiling methods allow simultaneous and rapid screening of hundreds of metabolites from a variety of chemical classes, making them useful tools for the discovery of novel enzymatic activities and metabolic pathways. By using the metabolome of the relevant organism or close species, these methods capitalize on biological relevance, avoiding the assignment of artificial and non-physiological functions. This review discusses state-of-the-art metabolomic approaches and highlights recent examples of their use for enzyme annotation, discovery of new metabolic pathways, and gene assignment of orphan metabolic activities across diverse biological sources. PMID:24829223

  9. Yeast metabolomics: sample preparation for a GC/MS-based analysis.

    PubMed

    Carneiro, Sónia; Pereira, Rui; Rocha, Isabel

    2014-01-01

    Metabolome sample preparation is one of the key factors in metabolomics analyses. The quality of the metabolome data will depend on the suitability of the experimental procedures to the cellular system (e.g., yeast cells) and the analytical performance. Here, we summarize a protocol for metabolome analysis of yeast cells using gas chromatography-mass spectrometry (GC-MS). First, the main phases of a metabolomics analysis are identified: sample preparation, metabolite extraction, and analysis. We also provide an overview on different methods used to quench samples and extract intracellular metabolites from yeast cells. This protocol provides a detailed description of a GC-MS-based analysis of yeast metabolome, in particular for metabolites containing amino and/or carboxyl groups, which represent most of the compounds participating in the central carbon metabolism.

  10. Dynamic multimedia annotation tool

    NASA Astrophysics Data System (ADS)

    Pfund, Thomas; Marchand-Maillet, Stephane

    2001-12-01

    Annotating image collections is crucial for different multimedia applications. Not only this provides an alternative access to visual information but it is a critical step to perform the evaluation of content-based image retrieval systems. Annotation is a tedious task so that there is a real need for developing tools that lighten the work of annotators. The tool should be flexible and offer customization so as to make the annotator the most comfortable. It should also automate the most tasks as possible. In this paper, we present a still image annotation tool that has been developed with the aim of being flexible and adaptive. The principle is to create a set of dynamic web pages that are an interface to a SQL database. The keyword set is fixed and every image receives from concurrent annotators a set of keywords along with time stamps and annotator Ids. Each annotator has the possibility of going back and forth within the collection and its previous annotations. He is helped by a number of search services and customization options. An administrative section allows the supervisor to control the parameter of the annotation, including the keyword set, given via an XML structure. The architecture of the tool is made flexible so as to accommodate further options through its development.

  11. The evolution of the natural killer complex; a comparison between mammals using new high-quality genome assemblies and targeted annotation.

    PubMed

    Schwartz, John C; Gibson, Mark S; Heimeier, Dorothea; Koren, Sergey; Phillippy, Adam M; Bickhart, Derek M; Smith, Timothy P L; Medrano, Juan F; Hammond, John A

    2017-04-01

    Natural killer (NK) cells are a diverse population of lymphocytes with a range of biological roles including essential immune functions. NK cell diversity is in part created by the differential expression of cell surface receptors which modulate activation and function, including multiple subfamilies of C-type lectin receptors encoded within the NK complex (NKC). Little is known about the gene content of the NKC beyond rodent and primate lineages, other than it appears to be extremely variable between mammalian groups. We compared the NKC structure between mammalian species using new high-quality draft genome assemblies for cattle and goat; re-annotated sheep, pig, and horse genome assemblies; and the published human, rat, and mouse lemur NKC. The major NKC genes are largely in the equivalent positions in all eight species, with significant independent expansions and deletions between species, allowing us to propose a model for NKC evolution during mammalian radiation. The ruminant species, cattle and goats, have independently evolved a second KLRC locus flanked by KLRA and KLRJ, and a novel KLRH-like gene has acquired an activating tail. This novel gene has duplicated several times within cattle, while other activating receptor genes have been selectively disrupted. Targeted genome enrichment in cattle identified varying levels of allelic polymorphism between the NKC genes concentrated in the predicted extracellular ligand-binding domains. This novel recombination and allelic polymorphism is consistent with NKC evolution under balancing selection, suggesting that this diversity influences individual immune responses and may impact on differential outcomes of pathogen infection and vaccination.

  12. Computational Metabolomics: A Framework for the Million Metabolome

    PubMed Central

    Uppal, Karan; Walker, Douglas I.; Liu, Ken; Li, Shuzhao; Go, Young-Mi; Jones, Dean P.

    2017-01-01

    “Sola dosis facit venenum.” These words of Paracelsus, “the dose makes the poison”, can lead to a cavalier attitude concerning potential toxicities of the vast array of low abundance environmental chemicals to which humans are exposed. Exposome research teaches that 80–85% of human disease is linked to environmental exposures. The human exposome is estimated to include >400,000 environmental chemicals, most of which are uncharacterized with regard to human health. In fact, mass spectrometry measures >200,000 m/z features (ions) in microliter volumes derived from human samples; most are unidentified. This crystallizes a grand challenge for chemical research in toxicology: to develop reliable and affordable analytical methods to understand health impacts of the extensive human chemical experience. To this end, there appears to be no choice but to abandon the limitations of measuring one chemical at a time. The present review looks at progress in computational metabolomics to provide probability based annotation linking ions to known chemicals and serve as a foundation for unambiguous designation of unidentified ions for toxicologic study. We review methods to characterize ions in terms of accurate mass m/z, chromatographic retention time, correlation of adduct, isotopic and fragment forms, association with metabolic pathways and measurement of collision-induced dissociation products, collision cross section, and chirality. Such information can support a largely unambiguous system for documenting unidentified ions in environmental surveillance and human biomonitoring. Assembly of this data would provide a resource to characterize and understand health risks of the array of low-abundance chemicals to which humans are exposed. PMID:27629808

  13. Effects of boiling duration in processing of White Paeony Root on its overall quality evaluated by ultra-high performance liquid chromatography quadrupole/time-of-flight mass spectrometry based metabolomics analysis and high performance liquid chromatography quantification.

    PubMed

    Ming, Kong; Xu, Jun; Liu, Huan-Huan; Xu, Jin-Di; Li, Xiu-Yang; Lu, Min; Wang, Chun-Ru; Chen, Hu-Biao; Li, Song-Lin

    2017-01-01

    Boiling processing is commonly used in post-harvest handling of White Paeony Root (WPR), in order to whiten the herbal materials and preserve the bright color, since such WPR is empirically considered to possess a higher quality. The present study was designed to investigate whether and how the boiling processing affects overall quality of WPR. First, an ultra-high performance liquid chromatography quadrupole/time-of-flight mass spectrometry-based metabolomics approach coupled with multivariate statistical analysis was developed to compare the holistic quality of boiled and un-boiled WPR samples. Second, ten major components in WPR samples boiled for different durations were quantitatively determined using high performance liquid chromatography to further explore the effects of boiling time on the holistic quality of WPR, meanwhile the appearance of the processed herbal materials was observed. The results suggested that the boiling processing conspicuously affected the holistic quality of WPR by simultaneously and inconsistently altering the chemical compositions and that short-time boiling processing between 2 and 10 min could both make the WPR bright-colored and improve the contents of major bioactive components, which were not achieved either without boiling or with prolonged boiling. In conclusion, short-term boiling (2-10 min) is recommended for post-harvest handling of WPR. Copyright © 2017 China Pharmaceutical University. Published by Elsevier B.V. All rights reserved.

  14. Development and Evaluation of an Automated Annotation Pipeline and cDNA Annotation System

    PubMed Central

    Kasukawa, Takeya; Furuno, Masaaki; Nikaido, Itoshi; Bono, Hidemasa; Hume, David A.; Bult, Carol; Hill, David P.; Baldarelli, Richard; Gough, Julian; Kanapin, Alexander; Matsuda, Hideo; Schriml, Lynn M.; Hayashizaki, Yoshihide; Okazaki, Yasushi; Quackenbush, John

    2003-01-01

    Manual curation has long been held to be the “gold standard” for functional annotation of DNA sequence. Our experience with the annotation of more than 20,000 full-length cDNA sequences revealed problems with this approach, including inaccurate and inconsistent assignment of gene names, as well as many good assignments that were difficult to reproduce using only computational methods. For the FANTOM2 annotation of more than 60,000 cDNA clones, we developed a number of methods and tools to circumvent some of these problems, including an automated annotation pipeline that provides high-quality preliminary annotation for each sequence by introducing an “uninformative filter” that eliminates uninformative annotations, controlled vocabularies to accurately reflect both the functional assignments and the evidence supporting them, and a highly refined, Web-based manual annotation tool that allows users to view a wide array of sequence analyses and to assign gene names and putative functions using a consistent nomenclature. The ultimate utility of our approach is reflected in the low rate of reassignment of automated assignments by manual curation. Based on these results, we propose a new standard for large-scale annotation, in which the initial automated annotations are manually investigated and then computational methods are iteratively modified and improved based on the results of manual curation. PMID:12819153

  15. Concept annotation in the CRAFT corpus

    PubMed Central

    2012-01-01

    Background Manually annotated corpora are critical for the training and evaluation of automated methods to identify concepts in biomedical text. Results This paper presents the concept annotations of the Colorado Richly Annotated Full-Text (CRAFT) Corpus, a collection of 97 full-length, open-access biomedical journal articles that have been annotated both semantically and syntactically to serve as a research resource for the biomedical natural-language-processing (NLP) community. CRAFT identifies all mentions of nearly all concepts from nine prominent biomedical ontologies and terminologies: the Cell Type Ontology, the Chemical Entities of Biological Interest ontology, the NCBI Taxonomy, the Protein Ontology, the Sequence Ontology, the entries of the Entrez Gene database, and the three subontologies of the Gene Ontology. The first public release includes the annotations for 67 of the 97 articles, reserving two sets of 15 articles for future text-mining competitions (after which these too will be released). Concept annotations were created based on a single set of guidelines, which has enabled us to achieve consistently high interannotator agreement. Conclusions As the initial 67-article release contains more than 560,000 tokens (and the full set more than 790,000 tokens), our corpus is among the largest gold-standard annotated biomedical corpora. Unlike most others, the journal articles that comprise the corpus are drawn from diverse biomedical disciplines and are marked up in their entirety. Additionally, with a concept-annotation count of nearly 100,000 in the 67-article subset (and more than 140,000 in the full collection), the scale of conceptual markup is also among the largest of comparable corpora. The concept annotations of the CRAFT Corpus have the potential to significantly advance biomedical text mining by providing a high-quality gold standard for NLP systems. The corpus, annotation guidelines, and other associated resources are freely available at http

  16. Computing human image annotation.

    PubMed

    Channin, David S; Mongkolwat, Pattanasak; Kleper, Vladimir; Rubin, Daniel L

    2009-01-01

    An image annotation is the explanatory or descriptive information about the pixel data of an image that is generated by a human (or machine) observer. An image markup is the graphical symbols placed over the image to depict an annotation. In the majority of current, clinical and research imaging practice, markup is captured in proprietary formats and annotations are referenced only in free text radiology reports. This makes these annotations difficult to query, retrieve and compute upon, hampering their integration into other data mining and analysis efforts. This paper describes the National Cancer Institute's Cancer Biomedical Informatics Grid's (caBIG) Annotation and Image Markup (AIM) project, focusing on how to use AIM to query for annotations. The AIM project delivers an information model for image annotation and markup. The model uses controlled terminologies for important concepts. All of the classes and attributes of the model have been harmonized with the other models and common data elements in use at the National Cancer Institute. The project also delivers XML schemata necessary to instantiate AIMs in XML as well as a software application for translating AIM XML into DICOM S/R and HL7 CDA. Large collections of AIM annotations can be built and then queried as Grid or Web services. Using the tools of the AIM project, image annotations and their markup can be captured and stored in human and machine readable formats. This enables the inclusion of human image observation and inference as part of larger data mining and analysis activities.

  17. Galileo Reader and Annotator

    NASA Astrophysics Data System (ADS)

    Besomi, O.

    2011-06-01

    In his readings, Galileo made frequent use of annotations. Here, I will offer a general glance at them by discussing the case of the annotations to the Libra astronomica published in 1619 by Orazio Grassi, a Jesuit mathematician of the Collegio Romano. The annotations directly reflect Galileo's reaction to Grassi's book in a heated debate between the two astronomers. Galileo and Grassi had opposite ideas about the nature of the comets, which resulted in different scientific and theological implications. The annotations represent the starting point for Galileo's reply to the Libra, namely Il Saggiatore, which was published four years later and dedicated to the new pope Urban VIII.

  18. AnnotCompute: annotation-based exploration and meta-analysis of genomics experiments

    PubMed Central

    Zheng, Jie; Stoyanovich, Julia; Manduchi, Elisabetta; Liu, Junmin; Stoeckert, Christian J.

    2011-01-01

    The ever-increasing scale of biological data sets, particularly those arising in the context of high-throughput technologies, requires the development of rich data exploration tools. In this article, we present AnnotCompute, an information discovery platform for repositories of functional genomics experiments such as ArrayExpress. Our system leverages semantic annotations of functional genomics experiments with controlled vocabulary and ontology terms, such as those from the MGED Ontology, to compute conceptual dissimilarities between pairs of experiments. These dissimilarities are then used to support two types of exploratory analysis—clustering and query-by-example. We show that our proposed dissimilarity measures correspond to a user's intuition about conceptual dissimilarity, and can be used to support effective query-by-example. We also evaluate the quality of clustering based on these measures. While AnnotCompute can support a richer data exploration experience, its effectiveness is limited in some cases, due to the quality of available annotations. Nonetheless, tools such as AnnotCompute may provide an incentive for richer annotations of experiments. Code is available for download at http://www.cbil.upenn.edu/downloads/AnnotCompute. Database URL: http://www.cbil.upenn.edu/annotCompute/ PMID:22190598

  19. Siderophore biosynthesis coordinately modulated the virulence-associated interactive metabolome of uropathogenic Escherichia coli and human urine

    PubMed Central

    Su, Qiao; Guan, Tianbing; Lv, Haitao

    2016-01-01

    Uropathogenic Escherichia coli (UPEC) growth in women’s bladders during urinary tract infection (UTI) incurs substantial chemical exchange, termed the “interactive metabolome”, which primarily accounts for the metabolic costs (utilized metabolome) and metabolic donations (excreted metabolome) between UPEC and human urine. Here, we attempted to identify the individualized interactive metabolome between UPEC and human urine. We were able to distinguish UPEC from non-UPEC by employing a combination of metabolomics and genetics. Our results revealed that the interactive metabolome between UPEC and human urine was markedly different from that between non-UPEC and human urine, and that UPEC triggered much stronger perturbations in the interactive metabolome in human urine. Furthermore, siderophore biosynthesis coordinately modulated the individualized interactive metabolome, which we found to be a critical component of UPEC virulence. The individualized virulence-associated interactive metabolome contained 31 different metabolites and 17 central metabolic pathways that were annotated to host these different metabolites, including energetic metabolism, amino acid metabolism, and gut microbe metabolism. Changes in the activities of these pathways mechanistically pinpointed the virulent capability of siderophore biosynthesis. Together, our findings provide novel insights into UPEC virulence, and we propose that siderophores are potential targets for further discovery of drugs to treat UPEC-induced UTI. PMID:27076285

  20. A new exploration of licorice metabolome.

    PubMed

    Rizzato, Giovanni; Scalabrin, Elisa; Radaelli, Marta; Capodaglio, Gabriele; Piccolo, Oreste

    2017-04-15

    The roots and rhizomes of licorice plants (genus Glycyrrhiza L.) are commercially employed, after processing, in confectionery production or as sweetening and flavouring agents in the food, tobacco and beer industries. G. glabra, G. inflata and G. uralensis are the most significant licorice species, often indistinctly used for different productions. Licorice properties are directly related to its chemical composition, which determines the commercial values and the quality of the derived products. In order to better understand the characteristics and properties of each species, a chemical characterization of three species of licorice (G. glabra, G. inflata, G. uralensis) is proposed, through an untargeted metabolomic approach and using high-resolution mass spectrometry. The statistical analysis reveals new possible markers for the analyzed species, and provides a reliable identification of a high number of metabolites, contributing to the characterization of Glycyrrhiza metabolome.

  1. Maize - GO annotation methods, evaluation, and review (Maize-GAMER)

    USDA-ARS?s Scientific Manuscript database

    Making a genome sequence accessible and useful involves three basic steps: genome assembly, structural annotation, and functional annotation. The quality of data generated at each step influences the accuracy of inferences that can be made, with high-quality analyses produce better datasets resultin...

  2. Metabolomics in agriculture.

    PubMed

    Nadella, K D; Marla, Soma S; Kumar, P Ananda

    2012-04-01

    Metabolome refers to the complete set of metabolites synthesized through a series of multiple enzymatic steps from various biochemical pathways processing the information encrypted in the plant genome. Knowledge about synthesis and regulation of various plant metabolic substances has improved substantially with availability of Omics data originating from sequencing of plant genomes. Metabolic profiling of crops is increasingly becoming popular in assessing plant phenotypes and genetic diversity. Metabolic compositional changes vividly reflect the changes occurring during plant growth, development, and in response to stress. Hence, study of plant metabolic pathways, the interconnections between them in context of systems biology is increasingly becoming popular in identification of candidate genes. The present article reviews recent developments in analysis of plant metabolomics, available bioinformatics techniques and databases employed for comparative pathway analysis, metabolic QTLs, and their application in plants.

  3. Annotated Humanities Programs.

    ERIC Educational Resources Information Center

    Adler, Richard R.; Applebee, Arthur

    The humanities programs offered in 1968 by 227 United States secondary schools are listed alphabetically by state, including almost 100 new programs not annotated in the 1967 listing (see TE 000 224). Each annotation presents a brief description of the approach to study used in the particular humanities course (e.g., American Studies, Culture…

  4. SEED Software Annotations.

    ERIC Educational Resources Information Center

    Bethke, Dee; And Others

    This document provides a composite index of the first five sets of software annotations produced by Project SEED. The software has been indexed by title, subject area, and grade level, and it covers sets of annotations distributed in September 1986, April 1987, September 1987, November 1987, and February 1988. The date column in the index…

  5. Metabolomics in asthma.

    PubMed

    Luxon, Bruce A

    2014-01-01

    Asthma and airway inflammation are responses to infectious stimuli and the mechanisms of how they are mediated, whether by the innate or adaptive immune response systems, are complex and results in a broad spectrum of possible metabolic products. In principle, a syndrome such as asthma should have a characteristic temporal-spatial metabolic signature indicative of its current state and the constituents that caused it. Generally, the term metabolomics refers to the quantitative analysis of sets of small compounds from biological samples with molecular masses less than 1 kDa so unambiguous identification can be difficult and usually requires sophisticated instrumentation. The practical success of clinical metabolomics will largely hinge on a few key issues such as the ability to capture a readily available biofluid that can be analyzed to identify metabolite biomarkers with the required sensitivity and specificity in a cost-effective manner in a clinical setting. In this chapter, we review the current state of the metabolomics of asthma and airway inflammation with a focus on the different methods and instrumentation being used for the discovery of biomarkers in research and their future translation into the clinic as diagnostic aids for the choice of patient-specific therapies.

  6. Metabolomics and human nutrition.

    PubMed

    Primrose, Sandy; Draper, John; Elsom, Rachel; Kirkpatrick, Verity; Mathers, John C; Seal, Chris; Beckmann, Manfred; Haldar, Sumanto; Beattie, John H; Lodge, John K; Jenab, Mazda; Keun, Hector; Scalbert, Augustin

    2011-04-01

    The present report summarises a workshop convened by the UK Food Standards Agency (Agency) on 25 March 2010 to discuss the current Agency's funded research on the use of metabolomics technologies in human nutrition research. The objectives of this workshop were to review progress to date, to identify technical challenges and ways of overcoming them, and to discuss future research priorities and the application of metabolomics in public health nutrition research and surveys. Results from studies nearing completion showed that by using carefully designed dietary and sampling regimens, it is possible to identify novel biomarkers of food intake that could not have been predicted from current knowledge of food composition. These findings provide proof-of-principle that the metabolomics approach can be used to develop new putative biomarkers of dietary intake. The next steps will be to validate these putative biomarkers, to develop rapid and inexpensive assays for biomarkers of food intake of high public health relevance, and to test their utility in population cohort studies and dietary surveys.

  7. Cadec: A corpus of adverse drug event annotations.

    PubMed

    Karimi, Sarvnaz; Metke-Jimenez, Alejandro; Kemp, Madonna; Wang, Chen

    2015-06-01

    CSIRO Adverse Drug Event Corpus (Cadec) is a new rich annotated corpus of medical forum posts on patient-reported Adverse Drug Events (ADEs). The corpus is sourced from posts on social media, and contains text that is largely written in colloquial language and often deviates from formal English grammar and punctuation rules. Annotations contain mentions of concepts such as drugs, adverse effects, symptoms, and diseases linked to their corresponding concepts in controlled vocabularies, i.e., SNOMED Clinical Terms and MedDRA. The quality of the annotations is ensured by annotation guidelines, multi-stage annotations, measuring inter-annotator agreement, and final review of the annotations by a clinical terminologist. This corpus is useful for studies in the area of information extraction, or more generally text mining, from social media to detect possible adverse drug reactions from direct patient reports. The corpus is publicly available at https://data.csiro.au.(1).

  8. Expansion of DSSTox: Leveraging public data to create a semantic cheminformatics resource with quality annotations for support of U.S. EPA applications. (American Chemical Society)

    EPA Science Inventory

    The expansion of chemical-bioassay data in the public domain is a boon to science; however, the difficulty in establishing accurate linkages from CAS registry number (CASRN) to structure, or for properly annotating names and synonyms for a particular structure is well known. DSS...

  9. Expansion of DSSTox: Leveraging public data to create a semantic cheminformatics resource with quality annotations for support of U.S. EPA applications. (American Chemical Society)

    EPA Science Inventory

    The expansion of chemical-bioassay data in the public domain is a boon to science; however, the difficulty in establishing accurate linkages from CAS registry number (CASRN) to structure, or for properly annotating names and synonyms for a particular structure is well known. DSS...

  10. WormBase: Annotating many nematode genomes.

    PubMed

    Howe, Kevin; Davis, Paul; Paulini, Michael; Tuli, Mary Ann; Williams, Gary; Yook, Karen; Durbin, Richard; Kersey, Paul; Sternberg, Paul W

    2012-01-01

    WormBase (www.wormbase.org) has been serving the scientific community for over 11 years as the central repository for genomic and genetic information for the soil nematode Caenorhabditis elegans. The resource has evolved from its beginnings as a database housing the genomic sequence and genetic and physical maps of a single species, and now represents the breadth and diversity of nematode research, currently serving genome sequence and annotation for around 20 nematodes. In this article, we focus on WormBase's role of genome sequence annotation, describing how we annotate and integrate data from a growing collection of nematode species and strains. We also review our approaches to sequence curation, and discuss the impact on annotation quality of large functional genomics projects such as modENCODE.

  11. Livestock metabolomics and the livestock metabolome: A systematic review

    PubMed Central

    Guo, An Chi; Sajed, Tanvir; Steele, Michael A.; Plastow, Graham S.; Wishart, David S.

    2017-01-01

    Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular “omics” approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production). A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs). These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at http://www.lmdb.ca). The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed. PMID:28531195

  12. Livestock metabolomics and the livestock metabolome: A systematic review.

    PubMed

    Goldansaz, Seyed Ali; Guo, An Chi; Sajed, Tanvir; Steele, Michael A; Plastow, Graham S; Wishart, David S

    2017-01-01

    Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular "omics" approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production). A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs). These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at http://www.lmdb.ca). The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed.

  13. Prokaryotic Contig Annotation Pipeline Server: Web Application for a Prokaryotic Genome Annotation Pipeline Based on the Shiny App Package.

    PubMed

    Park, Byeonghyeok; Baek, Min-Jeong; Min, Byoungnam; Choi, In-Geol

    2017-09-01

    Genome annotation is a primary step in genomic research. To establish a light and portable prokaryotic genome annotation pipeline for use in individual laboratories, we developed a Shiny app package designated as "P-CAPS" (Prokaryotic Contig Annotation Pipeline Server). The package is composed of R and Python scripts that integrate publicly available annotation programs into a server application. P-CAPS is not only a browser-based interactive application but also a distributable Shiny app package that can be installed on any personal computer. The final annotation is provided in various standard formats and is summarized in an R markdown document. Annotation can be visualized and examined with a public genome browser. A benchmark test showed that the annotation quality and completeness of P-CAPS were reliable and compatible with those of currently available public pipelines.

  14. Plant Metabolomics: An Indispensable System Biology Tool for Plant Science.

    PubMed

    Hong, Jun; Yang, Litao; Zhang, Dabing; Shi, Jianxin

    2016-06-01

    As genomes of many plant species have been sequenced, demand for functional genomics has dramatically accelerated the improvement of other omics including metabolomics. Despite a large amount of metabolites still remaining to be identified, metabolomics has contributed significantly not only to the understanding of plant physiology and biology from the view of small chemical molecules that reflect the end point of biological activities, but also in past decades to the attempts to improve plant behavior under both normal and stressed conditions. Hereby, we summarize the current knowledge on the genetic and biochemical mechanisms underlying plant growth, development, and stress responses, focusing further on the contributions of metabolomics to practical applications in crop quality improvement and food safety assessment, as well as plant metabolic engineering. We also highlight the current challenges and future perspectives in this inspiring area, with the aim to stimulate further studies leading to better crop improvement of yield and quality.

  15. Integrated metabolomics and phytochemical genomics approaches for studies on rice.

    PubMed

    Okazaki, Yozo; Saito, Kazuki

    2016-01-01

    Metabolomics is widely employed to monitor the cellular metabolic state and assess the quality of plant-derived foodstuffs because it can be used to manage datasets that include a wide range of metabolites in their analytical samples. In this review, we discuss metabolomics research on rice in order to elucidate the overall regulation of the metabolism as it is related to the growth and mechanisms of adaptation to genetic modifications and environmental stresses such as fungal infections, submergence, and oxidative stress. We also focus on phytochemical genomics studies based on a combination of metabolomics and quantitative trait locus (QTL) mapping techniques. In addition to starch, rice produces many metabolites that also serve as nutrients for human consumers. The outcomes of recent phytochemical genomics studies of diverse natural rice resources suggest there is potential for using further effective breeding strategies to improve the quality of ingredients in rice grains.

  16. MetaboLights: An Open-Access Database Repository for Metabolomics Data.

    PubMed

    Kale, Namrata S; Haug, Kenneth; Conesa, Pablo; Jayseelan, Kalaivani; Moreno, Pablo; Rocca-Serra, Philippe; Nainala, Venkata Chandrasekhar; Spicer, Rachel A; Williams, Mark; Li, Xuefei; Salek, Reza M; Griffin, Julian L; Steinbeck, Christoph

    2016-03-24

    MetaboLights is the first general purpose, open-access database repository for cross-platform and cross-species metabolomics research at the European Bioinformatics Institute (EMBL-EBI). Based upon the open-source ISA framework, MetaboLights provides Metabolomics Standard Initiative (MSI) compliant metadata and raw experimental data associated with metabolomics experiments. Users can upload their study datasets into the MetaboLights Repository. These studies are then automatically assigned a stable and unique identifier (e.g., MTBLS1) that can be used for publication reference. The MetaboLights Reference Layer associates metabolites with metabolomics studies in the archive and is extensively annotated with data fields such as structural and chemical information, NMR and MS spectra, target species, metabolic pathways, and reactions. The database is manually curated with no specific release schedules. MetaboLights is also recommended by journals for metabolomics data deposition. This unit provides a guide to using MetaboLights, downloading experimental data, and depositing metabolomics datasets using user-friendly submission tools. Copyright © 2016 John Wiley & Sons, Inc.

  17. Metabolomics protocols for filamentous fungi.

    PubMed

    Gummer, Joel P A; Krill, Christian; Du Fall, Lauren; Waters, Ormonde D C; Trengove, Robert D; Oliver, Richard P; Solomon, Peter S

    2012-01-01

    Proteomics and transcriptomics are established functional genomics tools commonly used to study filamentous fungi. Metabolomics has recently emerged as another option to complement existing techniques and provide detailed information on metabolic regulation and secondary metabolism. Here, we describe broad generic protocols that can be used to undertake metabolomics studies in filamentous fungi.

  18. Metabolite Profiling in the Pursuit of Biomarkers for IVF Outcome: The Case for Metabolomics Studies

    PubMed Central

    McRae, C.; Sharma, V.; Fisher, J.

    2013-01-01

    Background. This paper presents the literature on biomarkers of in vitro fertilisation (IVF) outcome, demonstrating the progression of these studies towards metabolite profiling, specifically metabolomics. The need for more, and improved, metabolomics studies in the field of assisted conception is discussed. Methods. Searches were performed on ISI Web of Knowledge SM for literature associated with biomarkers of oocyte and embryo quality, and biomarkers of IVF outcome in embryo culture medium, follicular fluid (FF), and blood plasma in female mammals. Results. Metabolomics in the field of female reproduction is still in its infancy. Metabolomics investigations of embryo culture medium for embryo selection have been the most common, but only within the last five years. Only in 2012 has the first metabolomics investigation of FF for biomarkers of oocyte quality been reported. The only metabolomics studies of human blood plasma in this context have been aimed at identifying women with polycystic ovary syndrome (PCOS). Conclusions. Metabolomics is becoming more established in the field of assisted conception, but the studies performed so far have been preliminary and not all potential applications have yet been explored. With further improved metabolomics studies, the possibility of identifying a method for predicting IVF outcome may become a reality. PMID:25763388

  19. Biological insights through nontargeted metabolomics.

    PubMed

    Sévin, Daniel C; Kuehne, Andreas; Zamboni, Nicola; Sauer, Uwe

    2015-08-01

    Metabolomics is increasingly employed to investigate metabolism and its reciprocal crosstalk with cellular signaling and regulation. In recent years, several nontargeted metabolomics methods providing substantial metabolome coverage have been developed. Here, we review and compare the contributions of traditional targeted and nontargeted metabolomics in advancing different research areas ranging from biotechnology to human health. Although some studies demonstrated the power of nontargeted profiling in generating unexpected and yet highly important insights, we found that most mechanistic links were still revealed by hypothesis-driven targeted methods. Novel computational approaches for formal interpretation of complex metabolic patterns and integration of complementary molecular layers are required to tap the full potential of nontargeted metabolomics for data-driven, discovery-oriented research and rapidly nucleating novel biological insights. Copyright © 2014 Elsevier Ltd. All rights reserved.

  20. Genome-enabled plant metabolomics.

    PubMed

    Tohge, Takayuki; de Souza, Leonardo Perez; Fernie, Alisdair R

    2014-09-01

    The grand challenge currently facing metabolomics is that of comprehensitivity whilst next generation sequencing and advanced proteomics methods now allow almost complete and at least 50% coverage of their respective target molecules, metabolomics platforms at best offer coverage of just 10% of the small molecule complement of the cell. Here we discuss the use of genome sequence information as an enabling tool for peak identity and for translational metabolomics. Whilst we argue that genome information is not sufficient to compute the size of a species metabolome it is highly useful in predicting the occurrence of a wide range of common metabolites. Furthermore, we describe how via gene functional analysis in model species the identity of unknown metabolite peaks can be resolved. Taken together these examples suggest that genome sequence information is current (and likely will remain), a highly effective tool in peak elucidation in mass spectral metabolomics strategies. Copyright © 2014 Elsevier B.V. All rights reserved.

  1. MASS SPECTROMETRY-BASED METABOLOMICS

    PubMed Central

    Dettmer, Katja; Aronov, Pavel A.; Hammock, Bruce D.

    2007-01-01

    This review presents an overview of the dynamically developing field of mass spectrometry-based metabolomics. Metabolomics aims at the comprehensive and quantitative analysis of wide arrays of metabolites in biological samples. These numerous analytes have very diverse physico-chemical properties and occur at different abundance levels. Consequently, comprehensive metabolomics investigations are primarily a challenge for analytical chemistry and specifically mass spectrometry has vast potential as a tool for this type of investigation. Metabolomics require special approaches for sample preparation, separation, and mass spectrometric analysis. Current examples of those approaches are described in this review. It primarily focuses on metabolic fingerprinting, a technique that analyzes all detectable analytes in a given sample with subsequent classification of samples and identification of differentially expressed metabolites, which define the sample classes. To perform this complex task, data analysis tools, metabolite libraries, and databases are required. Therefore, recent advances in metabolomics bioinformatics are also discussed. PMID:16921475

  2. The GOA database: Gene Ontology annotation updates for 2015

    PubMed Central

    Huntley, Rachael P.; Sawford, Tony; Mutowo-Meullenet, Prudence; Shypitsyna, Aleksandra; Bonilla, Carlos; Martin, Maria J.; O'Donovan, Claire

    2015-01-01

    The Gene Ontology Annotation (GOA) resource (http://www.ebi.ac.uk/GOA) provides evidence-based Gene Ontology (GO) annotations to proteins in the UniProt Knowledgebase (UniProtKB). Manual annotations provided by UniProt curators are supplemented by manual and automatic annotations from model organism databases and specialist annotation groups. GOA currently supplies 368 million GO annotations to almost 54 million proteins in more than 480 000 taxonomic groups. The resource now provides annotations to five times the number of proteins it did 4 years ago. As a member of the GO Consortium, we adhere to the most up-to-date Consortium-agreed annotation guidelines via the use of quality control checks that ensures that the GOA resource supplies high-quality functional information to proteins from a wide range of species. Annotations from GOA are freely available and are accessible through a powerful web browser as well as a variety of annotation file formats. PMID:25378336

  3. MyPro: A seamless pipeline for automated prokaryotic genome assembly and annotation

    PubMed Central

    Liao, Yu-Chieh; Lin, Hsin-Hung; Sabharwal, Amarpreet; Haase, Elaine M.; Scannapieco, Frank A.

    2016-01-01

    MyPro is a software pipeline for high-quality prokaryotic genome assembly and annotation. It was validated on 18 oral streptococcal strains to produce submission-ready, annotated draft genomes. MyPro installed as a virtual machine and supported by updated databases will enable biologists to perform quality prokaryotic genome assembly and annotation with ease. PMID:25911337

  4. MyPro: A seamless pipeline for automated prokaryotic genome assembly and annotation.

    PubMed

    Liao, Yu-Chieh; Lin, Hsin-Hung; Sabharwal, Amarpreet; Haase, Elaine M; Scannapieco, Frank A

    2015-06-01

    MyPro is a software pipeline for high-quality prokaryotic genome assembly and annotation. It was validated on 18 oral streptococcal strains to produce submission-ready, annotated draft genomes. MyPro installed as a virtual machine and supported by updated databases will enable biologists to perform quality prokaryotic genome assembly and annotation with ease.

  5. AnnotCompute: annotation-based exploration and meta-analysis of genomics experiments.

    PubMed

    Zheng, Jie; Stoyanovich, Julia; Manduchi, Elisabetta; Liu, Junmin; Stoeckert, Christian J

    2011-01-01

    The ever-increasing scale of biological data sets, particularly those arising in the context of high-throughput technologies, requires the development of rich data exploration tools. In this article, we present AnnotCompute, an information discovery platform for repositories of functional genomics experiments such as ArrayExpress. Our system leverages semantic annotations of functional genomics experiments with controlled vocabulary and ontology terms, such as those from the MGED Ontology, to compute conceptual dissimilarities between pairs of experiments. These dissimilarities are then used to support two types of exploratory analysis-clustering and query-by-example. We show that our proposed dissimilarity measures correspond to a user's intuition about conceptual dissimilarity, and can be used to support effective query-by-example. We also evaluate the quality of clustering based on these measures. While AnnotCompute can support a richer data exploration experience, its effectiveness is limited in some cases, due to the quality of available annotations. Nonetheless, tools such as AnnotCompute may provide an incentive for richer annotations of experiments. Database URL: http://www.cbil.upenn.edu/annotCompute/

  6. Influence of different processing times on the quality of Polygoni Multiflora Radix by metabolomics based on ultra high performance liquid chromatography with quadrupole time-of-flight mass spectrometry.

    PubMed

    Yu, Xie-An; Ge, Ai-Hua; Zhang, Lu; Li, Jin; An, Mingrui; Cao, Jun; He, Jun; Gao, Xiu-Mei; Chang, Yan-Xu

    2017-03-20

    A metabolomics method based on ultra high performance liquid chromatography with quadrupole time-of-flight mass spectrometry was developed to evaluate the influence of processing times on the quality of raw and processed Polygoni Multiflora Radix. Principal component analysis and partial least squares discriminant analysis was used to screen the potential maker metabolites that were contributed to the quality changes. Then these marker metabolites were selected as variables in Fisher's discriminant analysis to establish the models that were used to distinguish the raw and processed Polygoni Multiflora Radix in the markets. Additionally, 36 compounds were identified. 12 raw Polygoni Multiflora Radix samples and 23 processed Polygoni Multiflora Radix samples were distinguished. The results showed that the 12 raw Polygoni Multiflora Radix samples belonged to the group of processing time of 0 h, and two processed Polygoni Multiflora Radix samples were part of the group of processing times of 4 h, 12 samples belonged to group of processing times of 8 to 16 h, and nine samples were the group of processing times of 24 to 48 h. The results demonstrated that the method could provide scientific support for the processing standardization of Polygoni Multiflora Radix. This article is protected by copyright. All rights reserved.

  7. An annotated energy bibliography

    NASA Technical Reports Server (NTRS)

    Blow, S. J.

    1979-01-01

    Comprehensive annotated compilation of books, journals, periodicals, and reports on energy and energy related topics, contains approximately 10,0000 tehcnical and nontechnical references from bibliographic and other sources dated January 1975 through May 1977.

  8. An annotated energy bibliography

    NASA Technical Reports Server (NTRS)

    Blow, S. J.

    1979-01-01

    Comprehensive annotated compilation of books, journals, periodicals, and reports on energy and energy related topics, contains approximately 10,0000 tehcnical and nontechnical references from bibliographic and other sources dated January 1975 through May 1977.

  9. Rapid volatile metabolomics and genomics in large strawberry populations segregating for aroma

    USDA-ARS?s Scientific Manuscript database

    Volatile organic compounds (VOCs) in strawberry (Fragaria spp.) represent a large portion of the fruit secondary metabolome, and contribute significantly to aroma, flavor, disease resistance, pest resistance and overall fruit quality. Understanding the basis for volatile compound biosynthesis and it...

  10. Metabolomics for salinity research.

    PubMed

    Roessner, Ute; Beckles, Diane M

    2012-01-01

    Soil salinity devastates agriculture. It reduces crop yields and makes arable land unsuitable for later use. Many species have evolved highly efficient strategies to sense, transduce, and build up tolerance to high salinity and even sensitive species have endogenous mechanism for coping with this stress. These underlying physiological and metabolic mechanisms can be unraveled using metabolomics. Here we describe detailed protocols of how to extract polar metabolites for analysis using GC-MS and LC-MS. We also touch briefly on considerations that should be taken into account when designing the experiment and how the resulting data may be analyzed and visualized in a biological context.

  11. A metabolomic approach to quality determination and authentication of raw plant material in the fragrance field. Iris rhizomes: a case study.

    PubMed

    Masson, Jerome; Liberto, Erica; Brevard, Hugues; Bicchi, Carlo; Rubiolo, Patrizia

    2014-11-14

    This study aimed to discriminate 22 samples of commercial Iris rhizomes (orris root) by species and origin (Iris germanica (Morocco), I. albicans (Morocco), I. pallida (Morocco), I. pallida (China), I. pallida (Italy)) by applying a strategy derived from those adopted in metabolomics. The specimens' fingerprints from conventional analysis methods (LC-UV and/or LC-MS) were unable to provide clear discrimination. A strategy combining UHPLC/TOF-HRMS, in positive and negative modes, with multivariate statistical methods was therefore applied. Exact mass/retention time (EMRT) pairs obtained by UHPLC-TOF/HRMS were successfully submitted to statistical processing by principal component analysis (PCA), partial least square discriminant analysis (PLS-DA), and then orthogonal partial least square-discriminant analysis (OPLS-DA), to extract the discriminating EMRT pairs through their trend views. 146 EMRT pairs were selected on the basis of their trend views, because they significantly varied, and 104 of them were included to discriminate between species and origins. 32 of them were tentatively identified as discriminating markers (flavonoids, isoflavonoids, triterpenoids, benzophenone derivatives and related glycosides …) from the reference database created on the basis of Iris genus components reported in the literature: eight of them specific for I. albicans, four for I. germanica, five for I. pallida (Italy), five for I. pallida (China), and ten for I. pallida (Morocco). The reliability of this strategy was confirmed by identifying species and origin of two unknown samples submitted to the same analytical procedure.

  12. Strategy for comparative untargeted metabolomics reveals honey markers of different floral and geographic origins using ultrahigh-performance liquid chromatography-hybrid quadrupole-orbitrap mass spectrometry.

    PubMed

    Li, Yi; Jin, Yue; Yang, Shupeng; Zhang, Wenwen; Zhang, Jinzhen; Zhao, Wen; Chen, Lanzhen; Wen, Yaqin; Zhang, Yongxin; Lu, Kaizhi; Zhang, Yaping; Zhou, Jinhui; Yang, Shuming

    2017-05-26

    Honey discrimination based on floral and geographic origins is limited by the ability to determine reliable markers because developing hypothetical substances in advance considerably limits the throughput of metabolomics studies. Here, we present a novel approach to screen and elucidate honey markers based on comparative untargeted metabolomics using ultrahigh-performance liquid chromatography-hybrid quadrupole-orbitrap mass spectrometry (UHPLC-Q-Orbitrap). To reduce metabolite information losses during sample preparation, the honey samples were dissolved in water and centrifuged to remove insoluble particles prior to UHPLC-Q-Orbitrap analysis in positive and negative electrospray ionization modes. The data were pretreated using background subtraction, chromatographic peak extraction, normalization, transformation and scaling to remove interferences from unwanted biases and variance in the experimental data. The pretreated data were further processed using principal component analysis (PCA) and a three-stage approach (t-test, volcano plot and variable importance in projection (VIP) plot) to ensure marker authenticity. A correlation between the molecular and fragment ions with a mass accuracy of less than 1.0ppm was used to annotate and elucidate the marker structures, and the marker responses in real samples were used to confirm the effectiveness of the honey discrimination. Moreover, we evaluated the data quality using blank and quality control (QC) samples based on PCA clustering, retention times, normalized levels and peak areas. This strategy will help guide standardized, comparative untargeted metabolomics studies of honey and other agro-products from different floral and geographic origins. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. JGI Plant Genomics Gene Annotation Pipeline

    SciTech Connect

    Shu, Shengqiang; Rokhsar, Dan; Goodstein, David; Hayes, David; Mitros, Therese

    2014-07-14

    Plant genomes vary in size and are highly complex with a high amount of repeats, genome duplication and tandem duplication. Gene encodes a wealth of information useful in studying organism and it is critical to have high quality and stable gene annotation. Thanks to advancement of sequencing technology, many plant species genomes have been sequenced and transcriptomes are also sequenced. To use these vastly large amounts of sequence data to make gene annotation or re-annotation in a timely fashion, an automatic pipeline is needed. JGI plant genomics gene annotation pipeline, called integrated gene call (IGC), is our effort toward this aim with aid of a RNA-seq transcriptome assembly pipeline. It utilizes several gene predictors based on homolog peptides and transcript ORFs. See Methods for detail. Here we present genome annotation of JGI flagship green plants produced by this pipeline plus Arabidopsis and rice except for chlamy which is done by a third party. The genome annotations of these species and others are used in our gene family build pipeline and accessible via JGI Phytozome portal whose URL and front page snapshot are shown below.

  14. An Introduction to Genome Annotation.

    PubMed

    Campbell, Michael S; Yandell, Mark

    2015-12-17

    Genome projects have evolved from large international undertakings to tractable endeavors for a single lab. Accurate genome annotation is critical for successful genomic, genetic, and molecular biology experiments. These annotations can be generated using a number of approaches and available software tools. This unit describes methods for genome annotation and a number of software tools commonly used in gene annotation.

  15. An integrated computational pipeline and database to support whole-genome sequence annotation.

    PubMed

    Mungall, C J; Misra, S; Berman, B P; Carlson, J; Frise, E; Harris, N; Marshall, B; Shu, S; Kaminker, J S; Prochnik, S E; Smith, C D; Smith, E; Tupy, J L; Wiel, C; Rubin, G M; Lewis, S E

    2002-01-01

    We describe here our experience in annotating the Drosophila melanogaster genome sequence, in the course of which we developed several new open-source software tools and a database schema to support large-scale genome annotation. We have developed these into an integrated and reusable software system for whole-genome annotation. The key contributions to overall annotation quality are the marshalling of high-quality sequences for alignments and the design of a system with an adaptable and expandable flexible architecture.

  16. Omic Relief for the Biotically Stressed: Metabolomics of Plant Biotic Interactions.

    PubMed

    Tenenboim, Hezi; Brotman, Yariv

    2016-09-01

    Many aspects of the way plants protect themselves against pathogen attack, or react upon such an attack, are realized by metabolites. The ambitious aim of metabolomics, namely the identification and annotation of the entire cellular metabolome, still poses a considerable challenge due to the high diversity of the metabolites in the cell. Recent advances in analytical methods and data analysis have resulted in improved sensitivity, accuracy, and capacity, allowing the analysis of several hundreds or even thousands of compounds within one sample. Investigators have only recently begun to acknowledge and harness the power of metabolomics to elucidate key questions in the study of plant biotic interactions; we review trends and developments in the field.

  17. Using fragmentation trees and mass spectral trees for identifying unknown compounds in metabolomics

    PubMed Central

    Vaniya, Arpana

    2015-01-01

    Identification of unknown metabolites is the bottleneck in advancing metabolomics, leaving interpretation of metabolomics results ambiguous. The chemical diversity of metabolism is vast, making structure identification arduous and time consuming. Currently, comprehensive analysis of mass spectra in metabolomics is limited to library matching, but tandem mass spectral libraries are small compared to the large number of compounds found in the biosphere, including xenobiotics. Resolving this bottleneck requires richer data acquisition and better computational tools. Multi-stage mass spectrometry (MSn) trees show promise to aid in this regard. Fragmentation trees explore the fragmentation process, generate fragmentation rules and aid in sub-structure identification, while mass spectral trees delineate the dependencies in multi-stage MS of collision-induced dissociations. This review covers advancements over the past 10 years as a tool for metabolite identification, including algorithms, software and databases used to build and to implement fragmentation trees and mass spectral annotations. PMID:26213431

  18. Nuclear magnetic resonance metabolomics of iron deficiency in soybean leaves

    USDA-ARS?s Scientific Manuscript database

    Iron (Fe) deficiency is an important agricultural concern leading to lower yields and crop quality. A better understanding of the condition, at the metabolome level, could contribute to the design of strategies to ameliorate Fe deficiency problems. Fe-sufficient and Fe-deficient soybean leaf extract...

  19. Metabolomic Profiling in Perinatal Asphyxia: A Promising New Field

    PubMed Central

    Denihan, Niamh M.; Boylan, Geraldine B.; Murray, Deirdre M.

    2015-01-01

    Metabolomics, the latest “omic” technology, is defined as the comprehensive study of all low molecular weight biochemicals, “metabolites” present in an organism. As a systems biology approach, metabolomics has huge potential to progress our understanding of perinatal asphyxia and neonatal hypoxic-ischaemic encephalopathy, by uniquely detecting rapid biochemical pathway alterations in response to the hypoxic environment. The study of metabolomic biomarkers in the immediate neonatal period is not a trivial task and requires a number of specific considerations, unique to this disease and population. Recruiting a clearly defined cohort requires standardised multicentre recruitment with broad inclusion criteria and the participation of a range of multidisciplinary staff. Minimally invasive biospecimen collection is a priority for biomarker discovery. Umbilical cord blood presents an ideal medium as large volumes can be easily extracted and stored and the sample is not confounded by postnatal disease progression. Pristine biobanking and phenotyping are essential to ensure the validity of metabolomic findings. This paper provides an overview of the current state of the art in the field of metabolomics in perinatal asphyxia and neonatal hypoxic-ischaemic encephalopathy. We detail the considerations required to ensure high quality sampling and analysis, to support scientific progression in this important field. PMID:25802843

  20. The Progress of Metabolomics Study in Traditional Chinese Medicine Research.

    PubMed

    Wang, Pengcheng; Wang, Qiuhong; Yang, Bingyou; Zhao, Shan; Kuang, Haixue

    2015-01-01

    Traditional Chinese medicine (TCM) has played important roles in health protection and disease treatment for thousands of years in China and has gained the gradual acceptance of the international community. However, many intricate issues, which cannot be explained by traditional methods, still remain, thus, new ideas and technologies are needed. As an emerging system biology technology, the holistic view adopted by metabolomics is similar to that of TCM, which allows us to investigate TCM with complicated conditions and multiple factors in depth. In this paper, we tried to give a timely and comprehensive update about the methodology progression of metabolomics, as well as its applications, in different fields of TCM studies including quality control, processing, safety and efficacy evaluation. The herbs investigated by metabolomics were selected for detailed examination, including Anemarrhena asphodeloides Bunge, Atractylodes macrocephala Kidd, Pinellia ternate, etc.; furthermore, some valuable results have been obtained and summarized. In conclusion, although the study of metabolomics is at the early phase and requires further scrutiny and validation, it still provides bright prospects to dissect the synergistic action of multiple components from TCM. Overall, with the further development of analytical techniques, especially multi-analysis techniques, we expect that metabolomics will greatly promote TCM research and the establishment of international standards, which is beneficial to TCM modernization.

  1. Error Analysis and Propagation in Metabolomics Data Analysis

    PubMed Central

    Moseley, Hunter N.B.

    2013-01-01

    Error analysis plays a fundamental role in describing the uncertainty in experimental results. It has several fundamental uses in metabolomics including experimental design, quality control of experiments, the selection of appropriate statistical methods, and the determination of uncertainty in results. Furthermore, the importance of error analysis has grown with the increasing number, complexity, and heterogeneity of measurements characteristic of ‘omics research. The increase in data complexity is particularly problematic for metabolomics, which has more heterogeneity than other omics technologies due to the much wider range of molecular entities detected and measured. This review introduces the fundamental concepts of error analysis as they apply to a wide range of metabolomics experimental designs and it discusses current methodologies for determining the propagation of uncertainty in appropriate metabolomics data analysis. These methodologies include analytical derivation and approximation techniques, Monte Carlo error analysis, and error analysis in metabolic inverse problems. Current limitations of each methodology with respect to metabolomics data analysis are also discussed. PMID:23667718

  2. Metabolomics of genetically modified crops.

    PubMed

    Simó, Carolina; Ibáñez, Clara; Valdés, Alberto; Cifuentes, Alejandro; García-Cañas, Virginia

    2014-10-20

    Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs) making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not) the substantial equivalence and occurrence of unintended changes resulting from genetic transformation. This review provides insight into recent progress in metabolomics studies on transgenic crops focusing mainly in papers published in the last decade.

  3. Metabolomics of Genetically Modified Crops

    PubMed Central

    Simó, Carolina; Ibáñez, Clara; Valdés, Alberto; Cifuentes, Alejandro; García-Cañas, Virginia

    2014-01-01

    Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs) making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not) the substantial equivalence and occurrence of unintended changes resulting from genetic transformation. This review provides insight into recent progress in metabolomics studies on transgenic crops focusing mainly in papers published in the last decade. PMID:25334064

  4. Metabolomics in diabetes.

    PubMed

    Zhang, Ai-hua; Qiu, Shi; Xu, Hong-ying; Sun, Hui; Wang, Xi-jun

    2014-02-15

    Characterization of metabolic changes is key to early detection, treatment, and understanding molecular mechanisms of diabetes. Diabetes represents one of the most important global health problems. Approximately 90% of diabetics have type 2 diabetes. Identification of effective screening markers is critical for early treatment and intervention that can delay and/or prevent complications associated with this chronic disease. Fortunately, metabolomics has introduced new insights into the pathology of diabetes as well as to predict disease onset and revealed new biomarkers to improve diagnostics in a range of diseases. Small-molecule metabolites have an important role in biological systems and represent attractive candidates to understand T2D phenotypes. Characteristic patterns of metabolites can be revealed that broaden our understanding of T2D disorder. This technique-driven review aims to demystify the mechanisms of T2D, to provide updates on the applications of metabolomics in addressing T2D with a focus on metabolites based biomarker discovery. Copyright © 2013 Elsevier B.V. All rights reserved.

  5. Metabolomics in diabetic complications.

    PubMed

    Filla, Laura A; Edwards, James L

    2016-04-01

    With a global prevalence of 9%, diabetes is the direct cause of millions of deaths each year and is quickly becoming a health crisis. Major long-term complications of diabetes arise from persistent oxidative stress and dysfunction in multiple metabolic pathways. The most serious complications involve vascular damage and include cardiovascular disease as well as microvascular disorders such as nephropathy, neuropathy, and retinopathy. Current clinical analyses like glycated hemoglobin and plasma glucose measurements hold some value as prognostic indicators of the severity of complications, but investigations into the underlying pathophysiology are still lacking. Advancements in biotechnology hold the key to uncovering new pathways and establishing therapeutic targets. Metabolomics, the study of small endogenous molecules, is a powerful toolset for studying pathophysiological processes and has been used to elucidate metabolic signatures of diabetes in various biological systems. Current challenges in the field involve correlating these biomarkers to specific complications to provide a better prediction of future risk and disease progression. This review will highlight the progress that has been made in the field of metabolomics including technological advancements, the identification of potential biomarkers, and metabolic pathways relevant to macro- and microvascular diabetic complications.

  6. A metabolomics guided exploration of marine natural product chemical space

    PubMed Central

    Floros, Dimitrios J.

    2017-01-01

    Introduction Natural products from culture collections have enormous impact in advancing discovery programs for metabolites of biotechnological importance. These discovery efforts rely on the metabolomic characterization of strain collections. Objective Many emerging approaches compare metabolomic profiles of such collections, but few enable the analysis and prioritization of thousands of samples from diverse organisms while delivering chemistry specific read outs. Method In this work we utilize untargeted LC–MS/MS based metabolomics together with molecular networking to Result This approach annotated 76 molecular families (a spectral match rate of 28 %), including clinically and biotechnologically important molecules such as valinomycin, actinomycin D, and desferrioxamine E. Targeting a molecular family produced primarily by one microorganism led to the isolation and structure elucidation of two new molecules designated maridric acids A and B. Conclusion Molecular networking guided exploration of large culture collections allows for rapid dereplication of know molecules and can highlight producers of uniques metabolites. These methods, together with large culture collections and growing databases, allow for data driven strain prioritization with a focus on novel chemistries. PMID:28819353

  7. A metabolomics guided exploration of marine natural product chemical space.

    PubMed

    Floros, Dimitrios J; Jensen, Paul R; Dorrestein, Pieter C; Koyama, Nobuhiro

    2016-09-01

    Natural products from culture collections have enormous impact in advancing discovery programs for metabolites of biotechnological importance. These discovery efforts rely on the metabolomic characterization of strain collections. Many emerging approaches compare metabolomic profiles of such collections, but few enable the analysis and prioritization of thousands of samples from diverse organisms while delivering chemistry specific read outs. In this work we utilize untargeted LC-MS/MS based metabolomics together with molecular networking to. This approach annotated 76 molecular families (a spectral match rate of 28 %), including clinically and biotechnologically important molecules such as valinomycin, actinomycin D, and desferrioxamine E. Targeting a molecular family produced primarily by one microorganism led to the isolation and structure elucidation of two new molecules designated maridric acids A and B. Molecular networking guided exploration of large culture collections allows for rapid dereplication of know molecules and can highlight producers of uniques metabolites. These methods, together with large culture collections and growing databases, allow for data driven strain prioritization with a focus on novel chemistries.

  8. Solving the Problem: Genome Annotation Standards before the Data Deluge

    PubMed Central

    Klimke, William; O'Donovan, Claire; White, Owen; Brister, J. Rodney; Clark, Karen; Fedorov, Boris; Mizrachi, Ilene; Pruitt, Kim D.; Tatusova, Tatiana

    2011-01-01

    The promise of genome sequencing was that the vast undiscovered country would be mapped out by comparison of the multitude of sequences available and would aid researchers in deciphering the role of each gene in every organism. Researchers recognize that there is a need for high quality data. However, different annotation procedures, numerous databases, and a diminishing percentage of experimentally determined gene functions have resulted in a spectrum of annotation quality. NCBI in collaboration with sequencing centers, archival databases, and researchers, has developed the first international annotation standards, a fundamental step in ensuring that high quality complete prokaryotic genomes are available as gold standard references. Highlights include the development of annotation assessment tools, community acceptance of protein naming standards, comparison of annotation resources to provide consistent annotation, and improved tracking of the evidence used to generate a particular annotation. The development of a set of minimal standards, including the requirement for annotated complete prokaryotic genomes to contain a full set of ribosomal RNAs, transfer RNAs, and proteins encoding core conserved functions, is an historic milestone. The use of these standards in existing genomes and future submissions will increase the quality of databases, enabling researchers to make accurate biological discoveries. PMID:22180819

  9. A Novel Approach to Semantic and Coreference Annotation at LLNL

    SciTech Connect

    Firpo, M

    2005-02-04

    A case is made for the importance of high quality semantic and coreference annotation. The challenges of providing such annotation are described. Asperger's Syndrome is introduced, and the connections are drawn between the needs of text annotation and the abilities of persons with Asperger's Syndrome to meet those needs. Finally, a pilot program is recommended wherein semantic annotation is performed by people with Asperger's Syndrome. The primary points embodied in this paper are as follows: (1) Document annotation is essential to the Natural Language Processing (NLP) projects at Lawrence Livermore National Laboratory (LLNL); (2) LLNL does not currently have a system in place to meet its need for text annotation; (3) Text annotation is challenging for a variety of reasons, many related to its very rote nature; (4) Persons with Asperger's Syndrome are particularly skilled at rote verbal tasks, and behavioral experts agree that they would excel at text annotation; and (6) A pilot study is recommend in which two to three people with Asperger's Syndrome annotate documents and then the quality and throughput of their work is evaluated relative to that of their neuro-typical peers.

  10. Algal functional annotation tool

    SciTech Connect

    2012-07-12

    Abstract BACKGROUND: Progress in genome sequencing is proceeding at an exponential pace, and several new algal genomes are becoming available every year. One of the challenges facing the community is the association of protein sequences encoded in the genomes with biological function. While most genome assembly projects generate annotations for predicted protein sequences, they are usually limited and integrate functional terms from a limited number of databases. Another challenge is the use of annotations to interpret large lists of 'interesting' genes generated by genome-scale datasets. Previously, these gene lists had to be analyzed across several independent biological databases, often on a gene-by-gene basis. In contrast, several annotation databases, such as DAVID, integrate data from multiple functional databases and reveal underlying biological themes of large gene lists. While several such databases have been constructed for animals, none is currently available for the study of algae. Due to renewed interest in algae as potential sources of biofuels and the emergence of multiple algal genome sequences, a significant need has arisen for such a database to process the growing compendiums of algal genomic data. DESCRIPTION: The Algal Functional Annotation Tool is a web-based comprehensive analysis suite integrating annotation data from several pathway, ontology, and protein family databases. The current version provides annotation for the model alga Chlamydomonas reinhardtii, and in the future will include additional genomes. The site allows users to interpret large gene lists by identifying associated functional terms, and their enrichment. Additionally, expression data for several experimental conditions were compiled and analyzed to provide an expression-based enrichment search. A tool to search for functionally-related genes based on gene expression across these conditions is also provided. Other features include dynamic visualization of genes on KEGG

  11. High-throughput discovery metabolomics.

    PubMed

    Fuhrer, Tobias; Zamboni, Nicola

    2015-02-01

    Non-targeted metabolomics by mass spectrometry has established as the method of choice for investigating metabolic phenotypes in basic and applied research. Compared to other omics, metabolomics provides broad scope and yet direct information on the integrated cellular response with low demand in material and sample preparation. These features render non-targeted metabolomics ideally suited for large scale screens and discovery. Here we review the achievements and potential in high-throughput, non-targeted metabolomics. We found that routine and precise analysis of thousands of small molecular features in thousands of complex samples per day and instrument is already reality, and ongoing developments in microfluidics and integrated interfaces will likely further boost throughput in the next few years. Copyright © 2014 Elsevier Ltd. All rights reserved.

  12. Human Genome Annotation

    NASA Astrophysics Data System (ADS)

    Gerstein, Mark

    A central problem for 21st century science is annotating the human genome and making this annotation useful for the interpretation of personal genomes. My talk will focus on annotating the 99% of the genome that does not code for canonical genes, concentrating on intergenic features such as structural variants (SVs), pseudogenes (protein fossils), binding sites, and novel transcribed RNAs (ncRNAs). In particular, I will describe how we identify regulatory sites and variable blocks (SVs) based on processing next-generation sequencing experiments. I will further explain how we cluster together groups of sites to create larger annotations. Next, I will discuss a comprehensive pseudogene identification pipeline, which has enabled us to identify >10K pseudogenes in the genome and analyze their distribution with respect to age, protein family, and chromosomal location. Throughout, I will try to introduce some of the computational algorithms and approaches that are required for genome annotation. Much of this work has been carried out in the framework of the ENCODE, modENCODE, and 1000 genomes projects.

  13. Create, run, share, publish, and reference your LC-MS, FIA-MS, GC-MS, and NMR data analysis workflows with the Workflow4Metabolomics 3.0 Galaxy online infrastructure for metabolomics.

    PubMed

    Guitton, Yann; Tremblay-Franco, Marie; Le Corguillé, Gildas; Martin, Jean-François; Pétéra, Mélanie; Roger-Mele, Pierrick; Delabrière, Alexis; Goulitquer, Sophie; Monsoor, Misharl; Duperier, Christophe; Canlet, Cécile; Servien, Rémi; Tardivel, Patrick; Caron, Christophe; Giacomoni, Franck; Thévenot, Etienne A

    2017-07-12

    Metabolomics is a key approach in modern functional genomics and systems biology. Due to the complexity of metabolomics data, the variety of experimental designs, and the multiplicity of bioinformatics tools, providing experimenters with a simple and efficient resource to conduct comprehensive and rigorous analysis of their data is of utmost importance. In 2014, we launched the Workflow4Metabolomics (W4M; http://workflow4metabolomics.org) online infrastructure for metabolomics built on the Galaxy environment, which offers user-friendly features to build and run data analysis workflows including preprocessing, statistical analysis, and annotation steps. Here we present the new W4M 3.0 release, which contains twice as many tools as the first version, and provides two features which are, to our knowledge, unique among online resources. First, data from the four major metabolomics technologies (i.e., LC-MS, FIA-MS, GC-MS, and NMR) can be analyzed on a single platform. By using three studies in human physiology, alga evolution, and animal toxicology, we demonstrate how the 40 available tools can be easily combined to address biological issues. Second, the full analysis (including the workflow, the parameter values, the input data and output results) can be referenced with a permanent digital object identifier (DOI). Publication of data analyses is of major importance for robust and reproducible science. Furthermore, the publicly shared workflows are of high-value for e-learning and training. The Workflow4Metabolomics 3.0 e-infrastructure thus not only offers a unique online environment for analysis of data from the main metabolomics technologies, but it is also the first reference repository for metabolomics workflows. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Algal functional annotation tool

    SciTech Connect

    Lopez, D.; Casero, D.; Cokus, S. J.; Merchant, S. S.; Pellegrini, M.

    2012-07-01

    The Algal Functional Annotation Tool is a web-based comprehensive analysis suite integrating annotation data from several pathway, ontology, and protein family databases. The current version provides annotation for the model alga Chlamydomonas reinhardtii, and in the future will include additional genomes. The site allows users to interpret large gene lists by identifying associated functional terms, and their enrichment. Additionally, expression data for several experimental conditions were compiled and analyzed to provide an expression-based enrichment search. A tool to search for functionally-related genes based on gene expression across these conditions is also provided. Other features include dynamic visualization of genes on KEGG pathway maps and batch gene identifier conversion.

  15. Re-Annotator: Annotation Pipeline for Microarray Probe Sequences.

    PubMed

    Arloth, Janine; Bader, Daniel M; Röh, Simone; Altmann, Andre

    2015-01-01

    Microarray technologies are established approaches for high throughput gene expression, methylation and genotyping analysis. An accurate mapping of the array probes is essential to generate reliable biological findings. However, manufacturers of the microarray platforms typically provide incomplete and outdated annotation tables, which often rely on older genome and transcriptome versions that differ substantially from up-to-date sequence databases. Here, we present the Re-Annotator, a re-annotation pipeline for microarray probe sequences. It is primarily designed for gene expression microarrays but can also be adapted to other types of microarrays. The Re-Annotator uses a custom-built mRNA reference database to identify the positions of gene expression array probe sequences. We applied Re-Annotator to the Illumina Human-HT12 v4 microarray platform and found that about one quarter (25%) of the probes differed from the manufacturer's annotation. In further computational experiments on experimental gene expression data, we compared Re-Annotator to another probe re-annotation tool, ReMOAT, and found that Re-Annotator provided an improved re-annotation of microarray probes. A thorough re-annotation of probe information is crucial to any microarray analysis. The Re-Annotator pipeline is freely available at http://sourceforge.net/projects/reannotator along with re-annotated files for Illumina microarrays HumanHT-12 v3/v4 and MouseRef-8 v2.

  16. Injectors and Annotations

    NASA Technical Reports Server (NTRS)

    Filman, Robert E.

    2004-01-01

    In a previous paper, we presented the Object Infrastructure Framework. The goal of that system is to simplify the creation of distributed applications. The primary claim of that work is that non-functional 'ilities' could be achieved by controlling and manipulating the communications between components, thereby simplifying the development of distributed systems. A secondary element of that paper is to argue for extending the conventional distributed objects model in two important ways: 1) The ability to insert injectors (filters, wrappers) into the communication path between components; 2) The ability to annotate communications with additional information, and to propagate these annotations through an application. Here we express the descriptions of that paper.

  17. Ultrafast Polyphenol Metabolomics of Red Wines Using MicroLC-MS/MS.

    PubMed

    Ma, Yan; Tanaka, Nobuo; Vaniya, Arpana; Kind, Tobias; Fiehn, Oliver

    2016-01-20

    The taste and quality of red wine are determined by its highly complex mixture of polyphenols and many other metabolites. No single method can fully cover the full metabolome, but even for polyphenols and related compounds, current methods proved inadequate. We optimized liquid chromatography resolution and sensitivity using 1 mm i.d. columns with microLC pumps and compared data-dependent to data-independent (SWATH) MS/MS acquisitions. A high-throughput microLC-MS method was developed with a 4 min gradient at 0.05 mL/min flow rate on a Kinetex C18 column and Sciex TripleTOF mass spectrometry. Using the novel software MS-DIAL, we structurally annotated 264 compounds including 165 polyphenols in six commercial red wines by accurate mass MS/MS matching. As proof of concept, multivariate statistics revealed the difference in the metabolite profiles of the six red wines, and regression analysis linked the polyphenol contents to the taste of the red wines.

  18. Omics data management and annotation.

    PubMed

    Harel, Arye; Dalah, Irina; Pietrokovski, Shmuel; Safran, Marilyn; Lancet, Doron

    2011-01-01

    Technological Omics breakthroughs, including next generation sequencing, bring avalanches of data which need to undergo effective data management to ensure integrity, security, and maximal knowledge-gleaning. Data management system requirements include flexible input formats, diverse data entry mechanisms and views, user friendliness, attention to standards, hardware and software platform definition, as well as robustness. Relevant solutions elaborated by the scientific community include Laboratory Information Management Systems (LIMS) and standardization protocols facilitating data sharing and managing. In project planning, special consideration has to be made when choosing relevant Omics annotation sources, since many of them overlap and require sophisticated integration heuristics. The data modeling step defines and categorizes the data into objects (e.g., genes, articles, disorders) and creates an application flow. A data storage/warehouse mechanism must be selected, such as file-based systems and relational databases, the latter typically used for larger projects. Omics project life cycle considerations must include the definition and deployment of new versions, incorporating either full or partial updates. Finally, quality assurance (QA) procedures must validate data and feature integrity, as well as system performance expectations. We illustrate these data management principles with examples from the life cycle of the GeneCards Omics project (http://www.genecards.org), a comprehensive, widely used compendium of annotative information about human genes. For example, the GeneCards infrastructure has recently been changed from text files to a relational database, enabling better organization and views of the growing data. Omics data handling benefits from the wealth of Web-based information, the vast amount of public domain software, increasingly affordable hardware, and effective use of data management and annotation principles as outlined in this chapter.

  19. Atmospheric vs. anaerobic processing of metabolome samples for the metabolite profiling of a strict anaerobic bacterium, Clostridium acetobutylicum.

    PubMed

    Lee, Sang-Hyun; Kim, Sooah; Kwon, Min-A; Jung, Young Hoon; Shin, Yong-An; Kim, Kyoung Heon

    2014-12-01

    Well-established metabolome sample preparation is a prerequisite for reliable metabolomic data. For metabolome sampling of a Gram-positive strict anaerobe, Clostridium acetobutylicum, fast filtration and metabolite extraction with acetonitrile/methanol/water (2:2:1, v/v) at -20°C under anaerobic conditions has been commonly used. This anaerobic metabolite processing method is laborious and time-consuming since it is conducted in an anaerobic chamber. Also, there have not been any systematic method evaluation and development of metabolome sample preparation for strict anaerobes and Gram-positive bacteria. In this study, metabolome sampling and extraction methods were rigorously evaluated and optimized for C. acetobutylicum by using gas chromatography/time-of-flight mass spectrometry-based metabolomics, in which a total of 116 metabolites were identified. When comparing the atmospheric (i.e., in air) and anaerobic (i.e., in an anaerobic chamber) processing of metabolome sample preparation, there was no significant difference in the quality and quantity of the metabolomic data. For metabolite extraction, pure methanol at -20°C was a better solvent than acetonitrile/methanol/water (2:2:1, v/v/v) at -20°C that is frequently used for C. acetobutylicum, and metabolite profiles were significantly different depending on extraction solvents. This is the first evaluation of metabolite sample preparation under aerobic processing conditions for an anaerobe. This method could be applied conveniently, efficiently, and reliably to metabolome analysis for strict anaerobes in air.

  20. Gene and alternative splicing annotation with AIR

    PubMed Central

    Florea, Liliana; Di Francesco, Valentina; Miller, Jason; Turner, Russell; Yao, Alison; Harris, Michael; Walenz, Brian; Mobarry, Clark; Merkulov, Gennady V.; Charlab, Rosane; Dew, Ian; Deng, Zuoming; Istrail, Sorin; Li, Peter; Sutton, Granger

    2005-01-01

    Designing effective and accurate tools for identifying the functional and structural elements in a genome remains at the frontier of genome annotation owing to incompleteness and inaccuracy of the data, limitations in the computational models, and shifting paradigms in genomics, such as alternative splicing. We present a methodology for the automated annotation of genes and their alternatively spliced mRNA transcripts based on existing cDNA and protein sequence evidence from the same species or projected from a related species using syntenic mapping information. At the core of the method is the splice graph, a compact representation of a gene, its exons, introns, and alternatively spliced isoforms. The putative transcripts are enumerated from the graph and assigned confidence scores based on the strength of sequence evidence, and a subset of the high-scoring candidates are selected and promoted into the annotation. The method is highly selective, eliminating the unlikely candidates while retaining 98% of the high-quality mRNA evidence in well-formed transcripts, and produces annotation that is measurably more accurate than some evidence-based gene sets. The process is fast, accurate, and fully automated, and combines the traditionally distinct gene annotation and alternative splicing detection processes in a comprehensive and systematic way, thus considerably aiding in the ensuing manual curation efforts. PMID:15632090

  1. Gene and alternative splicing annotation with AIR.

    PubMed

    Florea, Liliana; Di Francesco, Valentina; Miller, Jason; Turner, Russell; Yao, Alison; Harris, Michael; Walenz, Brian; Mobarry, Clark; Merkulov, Gennady V; Charlab, Rosane; Dew, Ian; Deng, Zuoming; Istrail, Sorin; Li, Peter; Sutton, Granger

    2005-01-01

    Designing effective and accurate tools for identifying the functional and structural elements in a genome remains at the frontier of genome annotation owing to incompleteness and inaccuracy of the data, limitations in the computational models, and shifting paradigms in genomics, such as alternative splicing. We present a methodology for the automated annotation of genes and their alternatively spliced mRNA transcripts based on existing cDNA and protein sequence evidence from the same species or projected from a related species using syntenic mapping information. At the core of the method is the splice graph, a compact representation of a gene, its exons, introns, and alternatively spliced isoforms. The putative transcripts are enumerated from the graph and assigned confidence scores based on the strength of sequence evidence, and a subset of the high-scoring candidates are selected and promoted into the annotation. The method is highly selective, eliminating the unlikely candidates while retaining 98% of the high-quality mRNA evidence in well-formed transcripts, and produces annotation that is measurably more accurate than some evidence-based gene sets. The process is fast, accurate, and fully automated, and combines the traditionally distinct gene annotation and alternative splicing detection processes in a comprehensive and systematic way, thus considerably aiding in the ensuing manual curation efforts.

  2. Modeling loosely annotated images using both given and imagined annotations

    NASA Astrophysics Data System (ADS)

    Tang, Hong; Boujemaa, Nozha; Chen, Yunhao; Deng, Lei

    2011-12-01

    In this paper, we present an approach to learn latent semantic analysis models from loosely annotated images for automatic image annotation and indexing. The given annotation in training images is loose due to: 1. ambiguous correspondences between visual features and annotated keywords; 2. incomplete lists of annotated keywords. The second reason motivates us to enrich the incomplete annotation in a simple way before learning a topic model. In particular, some ``imagined'' keywords are poured into the incomplete annotation through measuring similarity between keywords in terms of their co-occurrence. Then, both given and imagined annotations are employed to learn probabilistic topic models for automatically annotating new images. We conduct experiments on two image databases (i.e., Corel and ESP) coupled with their loose annotations, and compare the proposed method with state-of-the-art discrete annotation methods. The proposed method improves word-driven probability latent semantic analysis (PLSA-words) up to a comparable performance with the best discrete annotation method, while a merit of PLSA-words is still kept, i.e., a wider semantic range.

  3. Cheating. An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Wildemuth, Barbara M., Comp.

    This 89-item, annotated bibliography was compiled to provide access to research and discussions of cheating and, specifically, cheating on tests. It is not limited to any educational level, nor is it confined to any specific curriculum area. Two data bases were searched by computer, and a library search was conducted. A computer search of the…

  4. Automated Microbial Genome Annotation

    SciTech Connect

    Land, Miriam

    2009-05-29

    Miriam Land of the DOE Joint Genome Institute at Oak Ridge National Laboratory gives a talk on the current state and future challenges of moving toward automated microbial genome annotation at the "Sequencing, Finishing, Analysis in the Future" meeting in Santa Fe, NM

  5. Annotation: The Savant Syndrome

    ERIC Educational Resources Information Center

    Heaton, Pamela; Wallace, Gregory L.

    2004-01-01

    Background: Whilst interest has focused on the origin and nature of the savant syndrome for over a century, it is only within the past two decades that empirical group studies have been carried out. Methods: The following annotation briefly reviews relevant research and also attempts to address outstanding issues in this research area.…

  6. Ghostwriting: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Simmons, Donald B.

    Drawn from communication journals, historical and news magazines, business and industrial magazines, political science and world affairs journals, general interest periodicals, and literary and political review magazines, the approximately 90 entries in this annotated bibliography discuss ghostwriting as practiced through the ages and reveal the…

  7. Annotated Bibliography. First Edition.

    ERIC Educational Resources Information Center

    Haring, Norris G.

    An annotated bibliography which presents approximately 300 references from 1951 to 1973 on the education of severely/profoundly handicapped persons. Citations are grouped alphabetically by author's name within the following categories: characteristics and treatment, gross motor development, sensory and motor development, physical therapy for the…

  8. Ghostwriting: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Simmons, Donald B.

    Drawn from communication journals, historical and news magazines, business and industrial magazines, political science and world affairs journals, general interest periodicals, and literary and political review magazines, the approximately 90 entries in this annotated bibliography discuss ghostwriting as practiced through the ages and reveal the…

  9. Geothermal wetlands: an annotated bibliography of pertinent literature

    SciTech Connect

    Stanley, N.E.; Thurow, T.L.; Russell, B.F.; Sullivan, J.F.

    1980-05-01

    This annotated bibliography covers the following topics: algae, wetland ecosystems; institutional aspects; macrophytes - general, production rates, and mineral absorption; trace metal absorption; wetland soils; water quality; and other aspects of marsh ecosystems. (MHR)

  10. Application of a Smartphone Metabolomics Platform to the Authentication of Schisandra sinensis.

    PubMed

    Kwon, Hyuk Nam; Phan, Hong-Duc; Xu, Wen Jun; Ko, Yoon-Joo; Park, Sunghyouk

    2016-05-01

    Herbal medicines have been used for a long time all around the world. Since the quality of herbal preparations depends on the source of herbal materials, there has been a strong need to develop methods to correctly identify the origin of materials. To develop a smartphone metabolomics platform as a simpler and low-cost alternative for the identification of herbal material source. Schisandra sinensis extracts from Korea and China were prepared. The visible spectra of all samples were measured by a smartphone spectrometer platform. This platform included all the necessary measures built-in for the metabolomics research: data acquisition, processing, chemometric analysis and visualisation of the results. The result of the smartphone metabolomics platform was compared to that of NMR-based metabolomics, suggesting the feasibility of smartphone platform in metabolomics research. The smartphone metabolomics platform gave similar results to the NMR method, showing good separation between Korean and Chinese materials and correct predictability for all test samples. With its accuracy and advantages of affordability, user-friendliness, and portability, the smartphone metabolomics platform could be applied to the authentication of other medicinal plants. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  11. Metabolomics in plant environmental physiology.

    PubMed

    Brunetti, Cecilia; George, Rachel M; Tattini, Massimiliano; Field, Katie; Davey, Matthew P

    2013-10-01

    Changes in plant metabolism are at the heart of plant developmental processes, underpinning many of the ways in which plants respond to the environment. As such, the comprehensive study of plant metabolism, or metabolomics, is highly valuable in identifying phenotypic effects of abiotic and biotic stresses on plants. When study is in reference to analysing samples that are relevant to environmental or ecologically based hypotheses, it is termed 'environmental metabolomics'. The emergence of environmental metabolomics as one of the latest of the omics technologies has been one of the most critically important recent developments in plant physiology. Its applications broach the entire landscape of plant ecology, from the understanding of plant plasticity and adaptation through to community composition and even genetic modification in crops. The multitude of novel studies published utilizing metabolomics methods employ a variety of techniques, from the initial stages of tissue sampling, through to sample preservation, transportation, and analysis. This review introduces the concept and applications of plant environmental metabolomics as an ecologically important investigative tool. It examines the main techniques used in situ within field sites, with particular reference to sampling and processing, and those more appropriate for use in laboratory-based settings with emphasis on secondary metabolite analysis.

  12. MeMo: a hybrid SQL/XML approach to metabolomic data management for functional genomics.

    PubMed

    Spasić, Irena; Dunn, Warwick B; Velarde, Giles; Tseng, Andy; Jenkins, Helen; Hardy, Nigel; Oliver, Stephen G; Kell, Douglas B

    2006-06-05

    The genome sequencing projects have shown our limited knowledge regarding gene function, e.g. S. cerevisiae has 5-6,000 genes of which nearly 1,000 have an uncertain function. Their gross influence on the behaviour of the cell can be observed using large-scale metabolomic studies. The metabolomic data produced need to be structured and annotated in a machine-usable form to facilitate the exploration of the hidden links between the genes and their functions. MeMo is a formal model for representing metabolomic data and the associated metadata. Two predominant platforms (SQL and XML) are used to encode the model. MeMo has been implemented as a relational database using a hybrid approach combining the advantages of the two technologies. It represents a practical solution for handling the sheer volume and complexity of the metabolomic data effectively and efficiently. The MeMo model and the associated software are available at http://dbkgroup.org/memo/. The maturity of relational database technology is used to support efficient data processing. The scalability and self-descriptiveness of XML are used to simplify the relational schema and facilitate the extensibility of the model necessitated by the creation of new experimental techniques. Special consideration is given to data integration issues as part of the systems biology agenda. MeMo has been physically integrated and cross-linked to related metabolomic and genomic databases. Semantic integration with other relevant databases has been supported through ontological annotation. Compatibility with other data formats is supported by automatic conversion.

  13. MeMo: a hybrid SQL/XML approach to metabolomic data management for functional genomics

    PubMed Central

    Spasić, Irena; Dunn, Warwick B; Velarde, Giles; Tseng, Andy; Jenkins, Helen; Hardy, Nigel; Oliver, Stephen G; Kell, Douglas B

    2006-01-01

    Background The genome sequencing projects have shown our limited knowledge regarding gene function, e.g. S. cerevisiae has 5–6,000 genes of which nearly 1,000 have an uncertain function. Their gross influence on the behaviour of the cell can be observed using large-scale metabolomic studies. The metabolomic data produced need to be structured and annotated in a machine-usable form to facilitate the exploration of the hidden links between the genes and their functions. Description MeMo is a formal model for representing metabolomic data and the associated metadata. Two predominant platforms (SQL and XML) are used to encode the model. MeMo has been implemented as a relational database using a hybrid approach combining the advantages of the two technologies. It represents a practical solution for handling the sheer volume and complexity of the metabolomic data effectively and efficiently. The MeMo model and the associated software are available at . Conclusion The maturity of relational database technology is used to support efficient data processing. The scalability and self-descriptiveness of XML are used to simplify the relational schema and facilitate the extensibility of the model necessitated by the creation of new experimental techniques. Special consideration is given to data integration issues as part of the systems biology agenda. MeMo has been physically integrated and cross-linked to related metabolomic and genomic databases. Semantic integration with other relevant databases has been supported through ontological annotation. Compatibility with other data formats is supported by automatic conversion. PMID:16753052

  14. Apollo: a sequence annotation editor.

    PubMed

    Lewis, S E; Searle, S M J; Harris, N; Gibson, M; Lyer, V; Richter, J; Wiel, C; Bayraktaroglu, L; Birney, E; Crosby, M A; Kaminker, J S; Matthews, B B; Prochnik, S E; Smithy, C D; Tupy, J L; Rubin, G M; Misra, S; Mungall, C J; Clamp, M E

    2002-01-01

    The well-established inaccuracy of purely computational methods for annotating genome sequences necessitates an interactive tool to allow biological experts to refine these approximations by viewing and independently evaluating the data supporting each annotation. Apollo was developed to meet this need, enabling curators to inspect genome annotations closely and edit them. FlyBase biologists successfully used Apollo to annotate the Drosophila melanogaster genome and it is increasingly being used as a starting point for the development of customized annotation editing tools for other genome projects.

  15. Food metabolomics: from farm to human.

    PubMed

    Kim, Sooah; Kim, Jungyeon; Yun, Eun Ju; Kim, Kyoung Heon

    2016-02-01

    Metabolomics, one of the latest components in the suite of systems biology, has been used to understand the metabolism and physiology of living systems, including microorganisms, plants, animals and humans. Food metabolomics can be defined as the application of metabolomics in food systems, including food resources, food processing and diet for humans. The study of food metabolomics has increased gradually in the recent years, because food systems are directly related to nutrition and human health. This review describes the recent trends and applications of metabolomics to food systems, from farm to human, including food resource production, industrial food processing and food intake by humans. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Metabolomics in diabetes, a review.

    PubMed

    Pallares-Méndez, Rigoberto; Aguilar-Salinas, Carlos A; Cruz-Bautista, Ivette; Del Bosque-Plata, Laura

    2016-01-01

    Metabolomics is a promising approach for the identification of chemical compounds that serve for early detection, diagnosis, prediction of therapeutic response and prognosis of disease. Moreover, metabolomics has shown to increase the diagnostic threshold and prediction of type 2 diabetes. Evidence suggests that branched-chain amino acids, acylcarnitines and aromatic amino acids may play an early role on insulin resistance, exposing defects on amino acid metabolism, β-oxidation, and tricarboxylic acid cycle. This review aims to provide a panoramic view of the metabolic shifts that antecede or follow type 2 diabetes. Key messages BCAAs, AAAs and acylcarnitines are strongly associated with early insulin resistance. Diabetes risk prediction has been improved when adding metabolomic markers of dysglycemia to standard clinical and biochemical factors.

  17. GSV Annotated Bibliography

    SciTech Connect

    Roberts, Randy S.; Pope, Paul A.; Jiang, Ming; Trucano, Timothy G.; Aragon, Cecilia R.; Ni, Kevin; Wei, Thomas; Chilton, Lawrence K.; Bakel, Alan

    2011-06-14

    The following annotated bibliography was developed as part of the Geospatial Algorithm Veri cation and Validation (GSV) project for the Simulation, Algorithms and Modeling program of NA-22. Veri cation and Validation of geospatial image analysis algorithms covers a wide range of technologies. Papers in the bibliography are thus organized into the following ve topic areas: Image processing and analysis, usability and validation of geospatial image analysis algorithms, image distance measures, scene modeling and image rendering, and transportation simulation models.

  18. Rethinking Mass Spectrometry-Based Small Molecule Identification Strategies in Metabolomics.

    PubMed

    Matsuda, Fumio

    2014-01-01

    The CASMI 2013 (Critical Assessment of Small Molecule Identification 2013, http://casmi-contest.org/) contest was held to systematically evaluate strategies used for mass spectrometry-based identification of small molecules. The results of the contest highlight that, because of the extensive efforts made towards the construction of databases and search tools, database-assisted small molecule identification can now automatically annotate some metabolite signals found in the metabolome data. In this commentary, the current state of metabolite annotation is compared with that of transcriptomics and proteomics. The comparison suggested that certain limitations in the metabolite annotation process need to be addressed, such as (i) the completeness of the database, (ii) the conversion between raw data and structure, (iii) the one-to-one correspondence between measured data and correct search results, and (iv) the false discovery rate in database search results.

  19. Metabolomic quality control of commercial Asian ginseng, and cultivated and wild American ginseng using (1)H NMR and multi-step PCA.

    PubMed

    Zhao, Huiying; Xu, Jin; Ghebrezadik, Helen; Hylands, Peter J

    2015-10-10

    Ginseng, mainly Asian ginseng and American ginseng, is the most widely consumed herbal product in the world . However, the existing quality control method is not adequate: adulteration is often seen in the market. In this study, 31 batches of ginseng from Chinese stores were analyzed using (1)H NMR metabolite profiles together with multi-step principal component analysis. The most abundant metabolites, sugars, were excluded from the NMR spectra after the first principal component analysis, in order to reveal differences contributed by less abundant metabolites. For the first time, robust, distinctive and representative differences of Asian ginseng from American ginseng were found and the key metabolites responsible were identified as sucrose, glucose, arginine, choline, and 2-oxoglutarate and malate. Differences between wild and cultivated ginseng were identified as ginsenosides. A substitute cultivated American ginseng was noticed. These results demonstrated that the combination of (1)H NMR and PCA is effective in quality control of ginseng.

  20. The RAST Server: Rapid Annotations using Subsystems Technology

    PubMed Central

    Aziz, Ramy K; Bartels, Daniela; Best, Aaron A; DeJongh, Matthew; Disz, Terrence; Edwards, Robert A; Formsma, Kevin; Gerdes, Svetlana; Glass, Elizabeth M; Kubal, Michael; Meyer, Folker; Olsen, Gary J; Olson, Robert; Osterman, Andrei L; Overbeek, Ross A; McNeil, Leslie K; Paarmann, Daniel; Paczian, Tobias; Parrello, Bruce; Pusch, Gordon D; Reich, Claudia; Stevens, Rick; Vassieva, Olga; Vonstein, Veronika; Wilke, Andreas; Zagnitko, Olga

    2008-01-01

    Background The number of prokaryotic genome sequences becoming available is growing steadily and is growing faster than our ability to accurately annotate them. Description We describe a fully automated service for annotating bacterial and archaeal genomes. The service identifies protein-encoding, rRNA and tRNA genes, assigns functions to the genes, predicts which subsystems are represented in the genome, uses this information to reconstruct the metabolic network and makes the output easily downloadable for the user. In addition, the annotated genome can be browsed in an environment that supports comparative analysis with the annotated genomes maintained in the SEED environment. The service normally makes the annotated genome available within 12–24 hours of submission, but ultimately the quality of such a service will be judged in terms of accuracy, consistency, and completeness of the produced annotations. We summarize our attempts to address these issues and discuss plans for incrementally enhancing the service. Conclusion By providing accurate, rapid annotation freely to the community we have created an important community resource. The service has now been utilized by over 120 external users annotating over 350 distinct genomes. PMID:18261238

  1. The RAST server : rapid annotations using subsystems technology.

    SciTech Connect

    Aziz, R. K.; Bartels, D.; Best, A. A.; DeJongh, M.; Disz, T.; Edwards, R. A.; Formsma, K.; Gerdes, S.; Glass, E. M.; Kubal, M.; Meyer, F.; Olsen, G. J.; Olson, R.; Osterman, A. L.; Overbeek, R. A.; McNeil, L. K.; Paarmann, D.; Paczian, T.; Parrello, B.; Pusch, G. D.; Reich, C.; Stevens, R.; Vassieva, O.; Vonstein, V.; Wilke, A.; Zagnitko, O.; Mathematics and Computer Science; Fellowship for Interpretation of Genomes; Univ. of Chicago; Univ. of Illinois; The Burnham Inst.; Hope Coll.; Univ. of Tenn.; Cairo Univ.

    2008-02-08

    The number of prokaryotic genome sequences becoming available is growing steadily and is growing faster than our ability to accurately annotate them. We describe a fully automated service for annotating bacterial and archaeal genomes. The service identifies protein-encoding, rRNA and tRNA genes, assigns functions to the genes, predicts which subsystems are represented in the genome, uses this information to reconstruct the metabolic network and makes the output easily downloadable for the user. In addition, the annotated genome can be browsed in an environment that supports comparative analysis with the annotated genomes maintained in the SEED environment. The service normally makes the annotated genome available within 12-24 hours of submission, but ultimately the quality of such a service will be judged in terms of accuracy, consistency, and completeness of the produced annotations. We summarize our attempts to address these issues and discuss plans for incrementally enhancing the service. By providing accurate, rapid annotation freely to the community we have created an important community resource. The service has now been utilized by over 120 external users annotating over 350 distinct genomes.

  2. Methods used to increase the comprehensive coverage of urinary and plasma metabolomes by MS.

    PubMed

    Chen, Yanhua; Xu, Jing; Zhang, Ruiping; Abliz, Zeper

    2016-05-01

    Metabolomics, focusing on comprehensive analysis of all the metabolites in a biological system, provides a direct signature of biochemical activity. Using emerging technologies in MS, it is possible to simultaneously and rapidly analyze thousands of metabolites. However, due to the chemical and physical diversity of metabolites, it is difficult to acquire a comprehensive and reliable profiling of the whole metabolome. Here, we summarize the state of the art in metabolomics research, focusing on efforts to provide a more comprehensive metabolome coverage via improvements in two fundamental processes: sample preparation and MS analysis. Additionally, the reliable analysis is also highlighted via the combinations of multiple methods (e.g., targeted and untargeted approaches), and analytical quality control and calibration methods.

  3. Metabolomics of medicinal plants: the importance of multivariate analysis of analytical chemistry data.

    PubMed

    Okada, Taketo; Afendi, Farit Mochamad; Altaf-Ul-Amin, Md; Takahashi, Hiroki; Nakamura, Kensuke; Kanaya, Shigehiko

    2010-09-01

    Metabolomics, the comprehensive and global analysis of diverse metabolites produced in cells and organisms, has greatly expanded metabolite fingerprinting and profiling as well as the selection and identification of marker metabolites. The methodology typically employs multivariate analysis to statistically process the massive amount of analytical chemistry data resulting from high-throughput and simultaneous metabolite analysis. Although the technology of plant metabolomics has mainly developed with other post-genomics in systems biology and functional genomics, it is independently applied to the evaluation of the qualities of medicinal plants, based on the diversity of metabolite fingerprints resulting from multivariate analysis of non-targeted or widely targeted metabolite analysis. One advantage of applying metabolomics is that medicinal plants are evaluated based not only on the limited number of metabolites that are pharmacologically important chemicals, but also on the fingerprints of minor metabolites and bioactive chemicals. In particular, score plot and loading plot analyses e.g. principal component analysis (PCA), partial-least-squares discriminant analysis (PLS-DA), and discrimination map analysis such as batch-learning self-organizing map (BL-SOM) analysis, are often employed for the reduction of a metabolite fingerprint and the classification of analyzed samples. Based on recent studies, we now understand that metabolomics can be an effective approach for comprehensive evaluation of the qualities of medicinal plants. In this review, we describe practical cases in which metabolomic study was performed on medicinal plants, and discuss the utility of metabolomics for this research field, with focus on multivariate analysis.

  4. The MetaboLights repository: curation challenges in metabolomics.

    PubMed

    Salek, Reza M; Haug, Kenneth; Conesa, Pablo; Hastings, Janna; Williams, Mark; Mahendraker, Tejasvi; Maguire, Eamonn; González-Beltrán, Alejandra N; Rocca-Serra, Philippe; Sansone, Susanna-Assunta; Steinbeck, Christoph

    2013-01-01

    MetaboLights is the first general-purpose open-access curated repository for metabolomic studies, their raw experimental data and associated metadata, maintained by one of the major open-access data providers in molecular biology. Increases in the number of depositions, number of samples per study and the file size of data submitted to MetaboLights present a challenge for the objective of ensuring high-quality and standardized data in the context of diverse metabolomic workflows and data representations. Here, we describe the MetaboLights curation pipeline, its challenges and its practical application in quality control of complex data depositions. Database URL: http://www.ebi.ac.uk/metabolights.

  5. The MetaboLights repository: curation challenges in metabolomics

    PubMed Central

    Salek, Reza M.; Haug, Kenneth; Conesa, Pablo; Hastings, Janna; Williams, Mark; Mahendraker, Tejasvi; Maguire, Eamonn; González-Beltrán, Alejandra N.; Rocca-Serra, Philippe; Sansone, Susanna-Assunta; Steinbeck, Christoph

    2013-01-01

    MetaboLights is the first general-purpose open-access curated repository for metabolomic studies, their raw experimental data and associated metadata, maintained by one of the major open-access data providers in molecular biology. Increases in the number of depositions, number of samples per study and the file size of data submitted to MetaboLights present a challenge for the objective of ensuring high-quality and standardized data in the context of diverse metabolomic workflows and data representations. Here, we describe the MetaboLights curation pipeline, its challenges and its practical application in quality control of complex data depositions. Database URL: http://www.ebi.ac.uk/metabolights PMID:23630246

  6. COordination of Standards in MetabOlomicS (COSMOS): facilitating integrated metabolomics data access.

    PubMed

    Salek, Reza M; Neumann, Steffen; Schober, Daniel; Hummel, Jan; Billiau, Kenny; Kopka, Joachim; Correa, Elon; Reijmers, Theo; Rosato, Antonio; Tenori, Leonardo; Turano, Paola; Marin, Silvia; Deborde, Catherine; Jacob, Daniel; Rolin, Dominique; Dartigues, Benjamin; Conesa, Pablo; Haug, Kenneth; Rocca-Serra, Philippe; O'Hagan, Steve; Hao, Jie; van Vliet, Michael; Sysi-Aho, Marko; Ludwig, Christian; Bouwman, Jildau; Cascante, Marta; Ebbels, Timothy; Griffin, Julian L; Moing, Annick; Nikolski, Macha; Oresic, Matej; Sansone, Susanna-Assunta; Viant, Mark R; Goodacre, Royston; Günther, Ulrich L; Hankemeier, Thomas; Luchinat, Claudio; Walther, Dirk; Steinbeck, Christoph

    Metabolomics has become a crucial phenotyping technique in a range of research fields including medicine, the life sciences, biotechnology and the environmental sciences. This necessitates the transfer of experimental information between research groups, as well as potentially to publishers and funders. After the initial efforts of the metabolomics standards initiative, minimum reporting standards were proposed which included the concepts for metabolomics databases. Built by the community, standards and infrastructure for metabolomics are still needed to allow storage, exchange, comparison and re-utilization of metabolomics data. The Framework Programme 7 EU Initiative 'coordination of standards in metabolomics' (COSMOS) is developing a robust data infrastructure and exchange standards for metabolomics data and metadata. This is to support workflows for a broad range of metabolomics applications within the European metabolomics community and the wider metabolomics and biomedical communities' participation. Here we announce our concepts and efforts asking for re-engagement of the metabolomics community, academics and industry, journal publishers, software and hardware vendors, as well as those interested in standardisation worldwide (addressing missing metabolomics ontologies, complex-metadata capturing and XML based open source data exchange format), to join and work towards updating and implementing metabolomics standards.

  7. The effectiveness of annotated (vs. non-annotated) digital pathology slides as a teaching tool during dermatology and pathology residencies.

    PubMed

    Marsch, Amanda F; Espiritu, Baltazar; Groth, John; Hutchens, Kelli A

    2014-06-01

    With today's technology, paraffin-embedded, hematoxylin & eosin-stained pathology slides can be scanned to generate high quality virtual slides. Using proprietary software, digital images can also be annotated with arrows, circles and boxes to highlight certain diagnostic features. Previous studies assessing digital microscopy as a teaching tool did not involve the annotation of digital images. The objective of this study was to compare the effectiveness of annotated digital pathology slides versus non-annotated digital pathology slides as a teaching tool during dermatology and pathology residencies. A study group composed of 31 dermatology and pathology residents was asked to complete an online pre-quiz consisting of 20 multiple choice style questions, each associated with a static digital pathology image. After completion, participants were given access to an online tutorial composed of digitally annotated pathology slides and subsequently asked to complete a post-quiz. A control group of 12 residents completed a non-annotated version of the tutorial. Nearly all participants in the study group improved their quiz score, with an average improvement of 17%, versus only 3% (P = 0.005) in the control group. These results support the notion that annotated digital pathology slides are superior to non-annotated slides for the purpose of resident education. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  8. Considerations to improve functional annotations in biological databases.

    PubMed

    Benítez-Páez, Alfonso

    2009-12-01

    Despite the great effort to design efficient systems allowing the electronic indexation of information concerning genes, proteins, structures, and interactions published daily in scientific journals, some problems are still observed in specific tasks such as functional annotation. The annotation of function is a critical issue for bioinformatic routines, such as for instance, in functional genomics and the further prediction of unknown protein function, which are highly dependent of the quality of existing annotations. Some information management systems evolve to efficiently incorporate information from large-scale projects, but often, annotation of single records from the literature is difficult and slow. In this short report, functional characterizations of a representative sample of the entire set of uncharacterized proteins from Escherichia coli K12 was compiled from Swiss-Prot, PubMed, and EcoCyc and demonstrate a functional annotation deficit in biological databases. Some issues are postulated as causes of the lack of annotation, and different solutions are evaluated and proposed to avoid them. The hope is that as a consequence of these observations, there will be new impetus to improve the speed and quality of functional annotation and ultimately provide updated, reliable information to the scientific community.

  9. Vitamins, metabolomics, and prostate cancer.

    PubMed

    Mondul, Alison M; Weinstein, Stephanie J; Albanes, Demetrius

    2017-06-01

    How micronutrients might influence risk of developing adenocarcinoma of the prostate has been the focus of a large body of research (especially regarding vitamins E, A, and D). Metabolomic profiling has the potential to discover molecular species relevant to prostate cancer etiology, early detection, and prevention, and may help elucidate the biologic mechanisms through which vitamins influence prostate cancer risk. Prostate cancer risk data related to vitamins E, A, and D and metabolomic profiling from clinical, cohort, and nested case-control studies, along with randomized controlled trials, are examined and summarized, along with recent metabolomic data of the vitamin phenotypes. Higher vitamin E serologic status is associated with lower prostate cancer risk, and vitamin E genetic variant data support this. By contrast, controlled vitamin E supplementation trials have had mixed results based on differing designs and dosages. Beta-carotene supplementation (in smokers) and higher circulating retinol and 25-hydroxy-vitamin D concentrations appear related to elevated prostate cancer risk. Our prospective metabolomic profiling of fasting serum collected 1-20 years prior to clinical diagnoses found reduced lipid and energy/TCA cycle metabolites, including inositol-1-phosphate, lysolipids, alpha-ketoglutarate, and citrate, significantly associated with lower risk of aggressive disease. Several active leads exist regarding the role of micronutrients and metabolites in prostate cancer carcinogenesis and risk. How vitamins D and A may adversely impact risk, and whether low-dose vitamin E supplementation remains a viable preventive approach, require further study.

  10. Brain Injury Alters Volatile Metabolome.

    PubMed

    Kimball, Bruce A; Cohen, Akiva S; Gordon, Amy R; Opiekun, Maryanne; Martin, Talia; Elkind, Jaclynn; Lundström, Johan N; Beauchamp, Gary K

    2016-06-01

    Chemical signals arising from body secretions and excretions communicate information about health status as have been reported in a range of animal models of disease. A potential common pathway for diseases to alter chemical signals is via activation of immune function-which is known to be intimately involved in modulation of chemical signals in several species. Based on our prior findings that both immunization and inflammation alter volatile body odors, we hypothesized that injury accompanied by inflammation might correspondingly modify the volatile metabolome to create a signature endophenotype. In particular, we investigated alteration of the volatile metabolome as a result of traumatic brain injury. Here, we demonstrate that mice could be trained in a behavioral assay to discriminate mouse models subjected to lateral fluid percussion injury from appropriate surgical sham controls on the basis of volatile urinary metabolites. Chemical analyses of the urine samples similarly demonstrated that brain injury altered urine volatile profiles. Behavioral and chemical analyses further indicated that alteration of the volatile metabolome induced by brain injury and alteration resulting from lipopolysaccharide-associated inflammation were not synonymous. Monitoring of alterations in the volatile metabolome may be a useful tool for rapid brain trauma diagnosis and for monitoring recovery. Published by Oxford University Press on behalf of US Government 2016.

  11. Brain Injury Alters Volatile Metabolome

    PubMed Central

    Cohen, Akiva S.; Gordon, Amy R.; Opiekun, Maryanne; Martin, Talia; Elkind, Jaclynn; Lundström, Johan N.; Beauchamp, Gary K.

    2016-01-01

    Chemical signals arising from body secretions and excretions communicate information about health status as have been reported in a range of animal models of disease. A potential common pathway for diseases to alter chemical signals is via activation of immune function—which is known to be intimately involved in modulation of chemical signals in several species. Based on our prior findings that both immunization and inflammation alter volatile body odors, we hypothesized that injury accompanied by inflammation might correspondingly modify the volatile metabolome to create a signature endophenotype. In particular, we investigated alteration of the volatile metabolome as a result of traumatic brain injury. Here, we demonstrate that mice could be trained in a behavioral assay to discriminate mouse models subjected to lateral fluid percussion injury from appropriate surgical sham controls on the basis of volatile urinary metabolites. Chemical analyses of the urine samples similarly demonstrated that brain injury altered urine volatile profiles. Behavioral and chemical analyses further indicated that alteration of the volatile metabolome induced by brain injury and alteration resulting from lipopolysaccharide-associated inflammation were not synonymous. Monitoring of alterations in the volatile metabolome may be a useful tool for rapid brain trauma diagnosis and for monitoring recovery. PMID:26926034

  12. Statistical mechanics of ontology based annotations

    NASA Astrophysics Data System (ADS)

    Hoyle, David C.; Brass, Andrew

    2016-01-01

    We present a statistical mechanical theory of the process of annotating an object with terms selected from an ontology. The term selection process is formulated as an ideal lattice gas model, but in a highly structured inhomogeneous field. The model enables us to explain patterns recently observed in real-world annotation data sets, in terms of the underlying graph structure of the ontology. By relating the external field strengths to the information content of each node in the ontology graph, the statistical mechanical model also allows us to propose a number of practical metrics for assessing the quality of both the ontology, and the annotations that arise from its use. Using the statistical mechanical formalism we also study an ensemble of ontologies of differing size and complexity; an analysis not readily performed using real data alone. Focusing on regular tree ontology graphs we uncover a rich set of scaling laws describing the growth in the optimal ontology size as the number of objects being annotated increases. In doing so we provide a further possible measure for assessment of ontologies.

  13. Mulligan Concept manual therapy: standardizing annotation.

    PubMed

    McDowell, Jillian Marie; Johnson, Gillian Margaret; Hetherington, Barbara Helen

    2014-10-01

    Quality technique documentation is integral to the practice of manual therapy, ensuring uniform application and reproducibility of treatment. Manual therapy techniques are described by annotations utilizing a range of acronyms, abbreviations and universal terminology based on biomechanical and anatomical concepts. The various combinations of therapist and patient generated forces utilized in a variety of weight-bearing positions, which are synonymous with Mulligan Concept, challenge practitioners existing annotational skills. An annotation framework with recording rules adapted to the Mulligan Concept is proposed in which the abbreviations incorporate established manual therapy tenets and are detailed in the following sequence of; starting position, side, joint/s, method of application, glide/s, Mulligan technique, movement (or function), whether an assistant is used, overpressure (and by whom) and numbers of repetitions or time and sets. Therapist or patient application of overpressure and utilization of treatment belts or manual techniques must be recorded to capture the complete description. The adoption of the Mulligan Concept annotation framework in this way for documentation purposes will provide uniformity and clarity of information transfer for the future purposes of teaching, clinical practice and audit for its practitioners.

  14. SNAD: Sequence Name Annotation-based Designer.

    PubMed

    Sidorov, Igor A; Reshetov, Denis A; Gorbalenya, Alexander E

    2009-08-14

    A growing diversity of biological data is tagged with unique identifiers (UIDs) associated with polynucleotides and proteins to ensure efficient computer-mediated data storage, maintenance, and processing. These identifiers, which are not informative for most people, are often substituted by biologically meaningful names in various presentations to facilitate utilization and dissemination of sequence-based knowledge. This substitution is commonly done manually that may be a tedious exercise prone to mistakes and omissions. Here we introduce SNAD (Sequence Name Annotation-based Designer) that mediates automatic conversion of sequence UIDs (associated with multiple alignment or phylogenetic tree, or supplied as plain text list) into biologically meaningful names and acronyms. This conversion is directed by precompiled or user-defined templates that exploit wealth of annotation available in cognate entries of external databases. Using examples, we demonstrate how this tool can be used to generate names for practical purposes, particularly in virology. A tool for controllable annotation-based conversion of sequence UIDs into biologically meaningful names and acronyms has been developed and placed into service, fostering links between quality of sequence annotation, and efficiency of communication and knowledge dissemination among researchers.

  15. Metabolomics-Driven Nutraceutical Evaluation of Diverse Green Tea Cultivars

    PubMed Central

    Ida, Megumi; Kosaka, Reia; Miura, Daisuke; Wariishi, Hiroyuki; Maeda-Yamamoto, Mari; Nesumi, Atsushi; Saito, Takeshi; Kanda, Tomomasa; Yamada, Koji; Tachibana, Hirofumi

    2011-01-01

    Background Green tea has various health promotion effects. Although there are numerous tea cultivars, little is known about the differences in their nutraceutical properties. Metabolic profiling techniques can provide information on the relationship between the metabolome and factors such as phenotype or quality. Here, we performed metabolomic analyses to explore the relationship between the metabolome and health-promoting attributes (bioactivity) of diverse Japanese green tea cultivars. Methodology/Principal Findings We investigated the ability of leaf extracts from 43 Japanese green tea cultivars to inhibit thrombin-induced phosphorylation of myosin regulatory light chain (MRLC) in human umbilical vein endothelial cells (HUVECs). This thrombin-induced phosphorylation is a potential hallmark of vascular endothelial dysfunction. Among the tested cultivars, Cha Chuukanbohon Nou-6 (Nou-6) and Sunrouge (SR) strongly inhibited MRLC phosphorylation. To evaluate the bioactivity of green tea cultivars using a metabolomics approach, the metabolite profiles of all tea extracts were determined by high-performance liquid chromatography-mass spectrometry (LC-MS). Multivariate statistical analyses, principal component analysis (PCA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA), revealed differences among green tea cultivars with respect to their ability to inhibit MRLC phosphorylation. In the SR cultivar, polyphenols were associated with its unique metabolic profile and its bioactivity. In addition, using partial least-squares (PLS) regression analysis, we succeeded in constructing a reliable bioactivity-prediction model to predict the inhibitory effect of tea cultivars based on their metabolome. This model was based on certain identified metabolites that were associated with bioactivity. When added to an extract from the non-bioactive cultivar Yabukita, several metabolites enriched in SR were able to transform the extract into a bioactive extract

  16. Solar Tutorial and Annotation Resource (STAR)

    NASA Astrophysics Data System (ADS)

    Showalter, C.; Rex, R.; Hurlburt, N. E.; Zita, E. J.

    2009-12-01

    We have written a software suite designed to facilitate solar data analysis by scientists, students, and the public, anticipating enormous datasets from future instruments. Our “STAR" suite includes an interactive learning section explaining 15 classes of solar events. Users learn software tools that exploit humans’ superior ability (over computers) to identify many events. Annotation tools include time slice generation to quantify loop oscillations, the interpolation of event shapes using natural cubic splines (for loops, sigmoids, and filaments) and closed cubic splines (for coronal holes). Learning these tools in an environment where examples are provided prepares new users to comfortably utilize annotation software with new data. Upon completion of our tutorial, users are presented with media of various solar events and asked to identify and annotate the images, to test their mastery of the system. Goals of the project include public input into the data analysis of very large datasets from future solar satellites, and increased public interest and knowledge about the Sun. In 2010, the Solar Dynamics Observatory (SDO) will be launched into orbit. SDO’s advancements in solar telescope technology will generate a terabyte per day of high-quality data, requiring innovation in data management. While major projects develop automated feature recognition software, so that computers can complete much of the initial event tagging and analysis, still, that software cannot annotate features such as sigmoids, coronal magnetic loops, coronal dimming, etc., due to large amounts of data concentrated in relatively small areas. Previously, solar physicists manually annotated these features, but with the imminent influx of data it is unrealistic to expect specialized researchers to examine every image that computers cannot fully process. A new approach is needed to efficiently process these data. Providing analysis tools and data access to students and the public have proven

  17. The Ensembl gene annotation system

    PubMed Central

    Aken, Bronwen L.; Ayling, Sarah; Barrell, Daniel; Clarke, Laura; Curwen, Valery; Fairley, Susan; Fernandez Banet, Julio; Billis, Konstantinos; García Girón, Carlos; Hourlier, Thibaut; Howe, Kevin; Kähäri, Andreas; Kokocinski, Felix; Martin, Fergal J.; Murphy, Daniel N.; Nag, Rishi; Ruffier, Magali; Schuster, Michael; Tang, Y. Amy; Vogel, Jan-Hinnerk; White, Simon; Zadissa, Amonida; Flicek, Paul

    2016-01-01

    The Ensembl gene annotation system has been used to annotate over 70 different vertebrate species across a wide range of genome projects. Furthermore, it generates the automatic alignment-based annotation for the human and mouse GENCODE gene sets. The system is based on the alignment of biological sequences, including cDNAs, proteins and RNA-seq reads, to the target genome in order to construct candidate transcript models. Careful assessment and filtering of these candidate transcripts ultimately leads to the final gene set, which is made available on the Ensembl website. Here, we describe the annotation process in detail. Database URL: http://www.ensembl.org/index.html PMID:27337980

  18. Phylogenetic molecular function annotation

    NASA Astrophysics Data System (ADS)

    Engelhardt, Barbara E.; Jordan, Michael I.; Repo, Susanna T.; Brenner, Steven E.

    2009-07-01

    It is now easier to discover thousands of protein sequences in a new microbial genome than it is to biochemically characterize the specific activity of a single protein of unknown function. The molecular functions of protein sequences have typically been predicted using homology-based computational methods, which rely on the principle that homologous proteins share a similar function. However, some protein families include groups of proteins with different molecular functions. A phylogenetic approach for predicting molecular function (sometimes called "phylogenomics") is an effective means to predict protein molecular function. These methods incorporate functional evidence from all members of a family that have functional characterizations using the evolutionary history of the protein family to make robust predictions for the uncharacterized proteins. However, they are often difficult to apply on a genome-wide scale because of the time-consuming step of reconstructing the phylogenies of each protein to be annotated. Our automated approach for function annotation using phylogeny, the SIFTER (Statistical Inference of Function Through Evolutionary Relationships) methodology, uses a statistical graphical model to compute the probabilities of molecular functions for unannotated proteins. Our benchmark tests showed that SIFTER provides accurate functional predictions on various protein families, outperforming other available methods.

  19. Annotation: the savant syndrome.

    PubMed

    Heaton, Pamela; Wallace, Gregory L

    2004-07-01

    Whilst interest has focused on the origin and nature of the savant syndrome for over a century, it is only within the past two decades that empirical group studies have been carried out. The following annotation briefly reviews relevant research and also attempts to address outstanding issues in this research area. Traditionally, savants have been defined as intellectually impaired individuals who nevertheless display exceptional skills within specific domains. However, within the extant literature, cases of savants with developmental and other clinical disorders, but with average intellectual functioning, are increasingly reported. We thus propose that focus should diverge away from IQ scores to encompass discrepancies between functional impairments and unexpected skills. It has long been observed that savant skills are more prevalent in individuals with autism than in those with other disorders. Therefore, in this annotation we seek to explore the parameters of the savant syndrome by considering these skills within the context of neuropsychological accounts of autism. A striking finding amongst those with savant skills, but without the diagnosis of autism, is the presence of cognitive features and behavioural traits associated with the disorder. We thus conclude that autism (or autistic traits) and savant skills are inextricably linked and we should therefore look to autism in our quest to solve the puzzle of the savant syndrome. Copyright 2004 Association for Child Psychology and Psychiatry

  20. Visualizing GO Annotations.

    PubMed

    Supek, Fran; Škunca, Nives

    2017-01-01

    Contemporary techniques in biology produce readouts for large numbers of genes simultaneously, the typical example being differential gene expression measurements. Moreover, those genes are often richly annotated using GO terms that describe gene function and that can be used to summarize the results of the genome-scale experiments. However, making sense of such GO enrichment analyses may be challenging. For instance, overrepresented GO functions in a set of differentially expressed genes are typically output as a flat list, a format not adequate to capture the complexities of the hierarchical structure of the GO annotation labels.In this chapter, we survey various methods to visualize large, difficult-to-interpret lists of GO terms. We catalog their availability-Web-based or standalone, the main principles they employ in summarizing large lists of GO terms, and the visualization styles they support. These brief commentaries on each software are intended as a helpful inventory, rather than comprehensive descriptions of the underlying algorithms. Instead, we show examples of their use and suggest that the choice of an appropriate visualization tool may be crucial to the utility of GO in biological discovery.

  1. LC-MS-based metabolomics: an update.

    PubMed

    Fang, Zhong-Ze; Gonzalez, Frank J

    2014-08-01

    Liquid chromatography-mass spectrometry (LC-MS)-based metabolomics can have a major impact in multiple research fields, especially when combined with other technologies, such as stable isotope tracers and genetically modified mice. This review highlights recent applications of metabolomic technology in the study of xenobiotic metabolism and toxicity, and the understanding of disease pathogenesis and therapeutics. Metabolomics has been employed to study metabolism of noscapine, an aryl hydrocarbon receptor antagonist, and to determine the mechanisms of liver toxicities of rifampicin and isoniazid, trichloroethylene, and gemfibrozil. Metabolomics-based insights into the pathogenesis of inflammatory bowel disease, alcohol-induced liver diseases, non-alcoholic steatohepatitis, and farnesoid X receptor signaling pathway-based therapeutic target discovery will also be discussed. Limitations in metabolomics technology such as sample preparation and lack of LC-MS databases and metabolite standards, need to be resolved in order to improve and broaden the application of metabolomic studies.

  2. NoGOA: predicting noisy GO annotations using evidences and sparse representation.

    PubMed

    Yu, Guoxian; Lu, Chang; Wang, Jun

    2017-07-21

    Gene Ontology (GO) is a community effort to represent functional features of gene products. GO annotations (GOA) provide functional associations between GO terms and gene products. Due to resources limitation, only a small portion of annotations are manually checked by curators, and the others are electronically inferred. Although quality control techniques have been applied to ensure the quality of annotations, the community consistently report that there are still considerable noisy (or incorrect) annotations. Given the wide application of annotations, however, how to identify noisy annotations is an important but yet seldom studied open problem. We introduce a novel approach called NoGOA to predict noisy annotations. NoGOA applies sparse representation on the gene-term association matrix to reduce the impact of noisy annotations, and takes advantage of sparse representation coefficients to measure the semantic similarity between genes. Secondly, it preliminarily predicts noisy annotations of a gene based on aggregated votes from semantic neighborhood genes of that gene. Next, NoGOA estimates the ratio of noisy annotations for each evidence code based on direct annotations in GOA files archived on different periods, and then weights entries of the association matrix via estimated ratios and propagates weights to ancestors of direct annotations using GO hierarchy. Finally, it integrates evidence-weighted association matrix and aggregated votes to predict noisy annotations. Experiments on archived GOA files of six model species (H. sapiens, A. thaliana, S. cerevisiae, G. gallus, B. Taurus and M. musculus) demonstrate that NoGOA achieves significantly better results than other related methods and removing noisy annotations improves the performance of gene function prediction. The comparative study justifies the effectiveness of integrating evidence codes with sparse representation for predicting noisy GO annotations. Codes and datasets are available at http://mlda.swu.edu.cn/codes.php?name=NoGOA .

  3. Managing Development Projects: A Selected, Annotated Bibliography. Annotated Bibliography #5.

    ERIC Educational Resources Information Center

    Chuenyane, Zachariah; And Others

    A selected annotated bibliography on managing development projects, intended for rural development practitioners, highlights items that outline some pressing issues and concerns confronting those involved in rural development in general and rural project management in particular. A section of annotated entries lists 21 publications on project…

  4. Bovine Genome Database: supporting community annotation and analysis of the Bos taurus genome

    PubMed Central

    2010-01-01

    Background A goal of the Bovine Genome Database (BGD; http://BovineGenome.org) has been to support the Bovine Genome Sequencing and Analysis Consortium (BGSAC) in the annotation and analysis of the bovine genome. We were faced with several challenges, including the need to maintain consistent quality despite diversity in annotation expertise in the research community, the need to maintain consistent data formats, and the need to minimize the potential duplication of annotation effort. With new sequencing technologies allowing many more eukaryotic genomes to be sequenced, the demand for collaborative annotation is likely to increase. Here we present our approach, challenges and solutions facilitating a large distributed annotation project. Results and Discussion BGD has provided annotation tools that supported 147 members of the BGSAC in contributing 3,871 gene models over a fifteen-week period, and these annotations have been integrated into the bovine Official Gene Set. Our approach has been to provide an annotation system, which includes a BLAST site, multiple genome browsers, an annotation portal, and the Apollo Annotation Editor configured to connect directly to our Chado database. In addition to implementing and integrating components of the annotation system, we have performed computational analyses to create gene evidence tracks and a consensus gene set, which can be viewed on individual gene pages at BGD. Conclusions We have provided annotation tools that alleviate challenges associated with distributed annotation. Our system provides a consistent set of data to all annotators and eliminates the need for annotators to format data. Involving the bovine research community in genome annotation has allowed us to leverage expertise in various areas of bovine biology to provide biological insight into the genome sequence. PMID:21092105

  5. NoisyGOA: Noisy GO annotations prediction using taxonomic and semantic similarity.

    PubMed

    Lu, Chang; Wang, Jun; Zhang, Zili; Yang, Pengyi; Yu, Guoxian

    2016-12-01

    Gene Ontology (GO) provides GO annotations (GOA) that associate gene products with GO terms that summarize their cellular, molecular and functional aspects in the context of biological pathways. GO Consortium (GOC) resorts to various quality assurances to ensure the correctness of annotations. Due to resources limitations, only a small portion of annotations are manually added/checked by GO curators, and a large portion of available annotations are computationally inferred. While computationally inferred annotations provide greater coverage of known genes, they may also introduce annotation errors (noise) that could mislead the interpretation of the gene functions and their roles in cellular and biological processes. In this paper, we investigate how to identify noisy annotations, a rarely addressed problem, and propose a novel approach called NoisyGOA. NoisyGOA first measures taxonomic similarity between ontological terms using the GO hierarchy and semantic similarity between genes. Next, it leverages the taxonomic similarity and semantic similarity to predict noisy annotations. We compare NoisyGOA with other alternative methods on identifying noisy annotations under different simulated cases of noisy annotations, and on archived GO annotations. NoisyGOA achieved higher accuracy than other alternative methods in comparison. These results demonstrated both taxonomic similarity and semantic similarity contribute to the identification of noisy annotations. Our study shows that annotation errors are predictable and removing noisy annotations improves the performance of gene function prediction. This study can prompt the community to study methods for removing inaccurate annotations, a critical step for annotating gene and pathway functions. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. Widowed Persons Service: Selected Annotated Bibliography.

    ERIC Educational Resources Information Center

    Bressler, Dawn, Comp.; And Others

    This document presents an annotated bibliography of books and articles on topics relevant to widowhood. These annotations are included: (1) 21 annotations on the grief process; (2) 11 annotations on personal observations about widowhood; (3) 16 annotations on practical problems surrounding widowhood, including legal and financial problems and job…

  7. MEETING: Chlamydomonas Annotation Jamboree - October 2003

    SciTech Connect

    Grossman, Arthur R

    2007-04-13

    Shotgun sequencing of the nuclear genome of Chlamydomonas reinhardtii (Chlamydomonas throughout) was performed at an approximate 10X coverage by JGI. Roughly half of the genome is now contained on 26 scaffolds, all of which are at least 1.6 Mb, and the coverage of the genome is ~95%. There are now over 200,000 cDNA sequence reads that we have generated as part of the Chlamydomonas genome project (Grossman, 2003; Shrager et al., 2003; Grossman et al. 2007; Merchant et al., 2007); other sequences have also been generated by the Kasuza sequence group (Asamizu et al., 1999; Asamizu et al., 2000) or individual laboratories that have focused on specific genes. Shrager et al. (2003) placed the reads into distinct contigs (an assemblage of reads with overlapping nucleotide sequences), and contigs that group together as part of the same genes have been designated ACEs (assembly of contigs generated from EST information). All of the reads have also been mapped to the Chlamydomonas nuclear genome and the cDNAs and their corresponding genomic sequences have been reassembled, and the resulting assemblage is called an ACEG (an Assembly of contiguous EST sequences supported by genomic sequence) (Jain et al., 2007). Most of the unique genes or ACEGs are also represented by gene models that have been generated by the Joint Genome Institute (JGI, Walnut Creek, CA). These gene models have been placed onto the DNA scaffolds and are presented as a track on the Chlamydomonas genome browser associated with the genome portal (http://genome.jgi-psf.org/Chlre3/Chlre3.home.html). Ultimately, the meeting grant awarded by DOE has helped enormously in the development of an annotation pipeline (a set of guidelines used in the annotation of genes) and resulted in high quality annotation of over 4,000 genes; the annotators were from both Europe and the USA. Some of the people who led the annotation initiative were Arthur Grossman, Olivier Vallon, and Sabeeha Merchant (with many individual

  8. Beyond the paradigm: Combining mass spectrometry and nuclear magnetic resonance for metabolomics.

    PubMed

    Marshall, Darrell D; Powers, Robert

    2017-05-01

    Metabolomics is undergoing tremendous growth and is being employed to solve a diversity of biological problems from environmental issues to the identification of biomarkers for human diseases. Nuclear magnetic resonance (NMR) and mass spectrometry (MS) are the analytical tools that are routinely, but separately, used to obtain metabolomics data sets due to their versatility, accessibility, and unique strengths. NMR requires minimal sample handling without the need for chromatography, is easily quantitative, and provides multiple means of metabolite identification, but is limited to detecting the most abundant metabolites (⩾1μM). Conversely, mass spectrometry has the ability to measure metabolites at very low concentrations (femtomolar to attomolar) and has a higher resolution (∼10(3)-10(4)) and dynamic range (∼10(3)-10(4)), but quantitation is a challenge and sample complexity may limit metabolite detection because of ion suppression. Consequently, liquid chromatography (LC) or gas chromatography (GC) is commonly employed in conjunction with MS, but this may lead to other sources of error. As a result, NMR and mass spectrometry are highly complementary, and combining the two techniques is likely to improve the overall quality of a study and enhance the coverage of the metabolome. While the majority of metabolomic studies use a single analytical source, there is a growing appreciation of the inherent value of combining NMR and MS for metabolomics. An overview of the current state of utilizing both NMR and MS for metabolomics will be presented. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Advances in metabolome information retrieval: turning chemistry into biology. Part II: biological information recovery.

    PubMed

    Tebani, Abdellah; Afonso, Carlos; Bekri, Soumeya

    2017-08-25

    This work reports the second part of a review intending to give the state of the art of major metabolic phenotyping strategies. It particularly deals with inherent advantages and limits regarding data analysis issues and biological information retrieval tools along with translational challenges. This Part starts with introducing the main data preprocessing strategies of the different metabolomics data. Then, it describes the main data analysis techniques including univariate and multivariate aspects. It also addresses the challenges related to metabolite annotation and characterization. Finally, functional analysis including pathway and network strategies are discussed. The last section of this review is devoted to practical considerations and current challenges and pathways to bring metabolomics into clinical environments.

  10. System-Level and Granger Network Analysis of Integrated Proteomic and Metabolomic Dynamics Identifies Key Points of Grape Berry Development at the Interface of Primary and Secondary Metabolism

    PubMed Central

    Wang, Lei; Sun, Xiaoliang; Weiszmann, Jakob; Weckwerth, Wolfram

    2017-01-01

    Grapevine is a fruit crop with worldwide economic importance. The grape berry undergoes complex biochemical changes from fruit set until ripening. This ripening process and production processes define the wine quality. Thus, a thorough understanding of berry ripening is crucial for the prediction of wine quality. For a systemic analysis of grape berry development we applied mass spectrometry based platforms to analyse the metabolome and proteome of Early Campbell at 12 stages covering major developmental phases. Primary metabolites involved in central carbon metabolism, such as sugars, organic acids and amino acids together with various bioactive secondary metabolites like flavonols, flavan-3-ols and anthocyanins were annotated and quantified. At the same time, the proteomic analysis revealed the protein dynamics of the developing grape berries. Multivariate statistical analysis of the integrated metabolomic and proteomic dataset revealed the growth trajectory and corresponding metabolites and proteins contributing most to the specific developmental process. K-means clustering analysis revealed 12 highly specific clusters of co-regulated metabolites and proteins. Granger causality network analysis allowed for the identification of time-shift correlations between metabolite-metabolite, protein- protein and protein-metabolite pairs which is especially interesting for the understanding of developmental processes. The integration of metabolite and protein dynamics with their corresponding biochemical pathways revealed an energy-linked metabolism before veraison with high abundances of amino acids and accumulation of organic acids, followed by protein and secondary metabolite synthesis. Anthocyanins were strongly accumulated after veraison whereas other flavonoids were in higher abundance at early developmental stages and decreased during the grape berry developmental processes. A comparison of the anthocyanin profile of Early Campbell to other cultivars revealed

  11. Metabolomics in Toxicology and Preclinical Research

    PubMed Central

    Ramirez, Tzutzuy; Daneshian, Mardas; Kamp, Hennicke; Bois, Frederic Y.; Clench, Malcolm R.; Coen, Muireann; Donley, Beth; Fischer, Steven M.; Ekman, Drew R.; Fabian, Eric; Guillou, Claude; Heuer, Joachim; Hogberg, Helena T.; Jungnickel, Harald; Keun, Hector C.; Krennrich, Gerhard; Krupp, Eckart; Luch, Andreas; Noor, Fozia; Peter, Erik; Riefke, Bjoern; Seymour, Mark; Skinner, Nigel; Smirnova, Lena; Verheij, Elwin; Wagner, Silvia; Hartung, Thomas; van Ravenzwaay, Bennard; Leist, Marcel

    2013-01-01

    Summary Metabolomics, the comprehensive analysis of metabolites in a biological system, provides detailed information about the biochemical/physiological status of a biological system, and about the changes caused by chemicals. Metabolomics analysis is used in many fields, ranging from the analysis of the physiological status of genetically modified organisms in safety science to the evaluation of human health conditions. In toxicology, metabolomics is the -omics discipline that is most closely related to classical knowledge of disturbed biochemical pathways. It allows rapid identification of the potential targets of a hazardous compound. It can give information on target organs and often can help to improve our understanding regarding the mode-of-action of a given compound. Such insights aid the discovery of biomarkers that either indicate pathophysiological conditions or help the monitoring of the efficacy of drug therapies. The first toxicological applications of metabolomics were for mechanistic research, but different ways to use the technology in a regulatory context are being explored. Ideally, further progress in that direction will position the metabolomics approach to address the challenges of toxicology of the 21st century. To address these issues, scientists from academia, industry, and regulatory bodies came together in a workshop to discuss the current status of applied metabolomics and its potential in the safety assessment of compounds. We report here on the conclusions of three working groups addressing questions regarding 1) metabolomics for in vitro studies 2) the appropriate use of metabolomics in systems toxicology, and 3) use of metabolomics in a regulatory context. PMID:23665807

  12. Genix: a new online automated pipeline for bacterial genome annotation.

    PubMed

    Kremer, Frederico Schmitt; Eslabão, Marcus Redü; Dellagostin, Odir Antônio; Pinto, Luciano da Silva

    2016-12-01

    Next-generation sequencing has significantly reduced the cost of genome-sequencing projects, resulting in an expressive increase in the availability of genomic data in public databases. The cheaper and easier is to sequence new genomes, the more accurate the annotation steps have to be to avoid both the loss of information and the accumulation of erroneous features that may affect the accuracy of further analysis. In the case of bacteria genomes, a range of web annotation software has been developed; however, many applications have yet to incorporate the steps required to improve their result, including the removal of false-positive/spurious and a more complete identification of non-coding features. We present Genix, a new web-based bacterial genome annotation pipeline. A comparison of the results generated by Genix for four reference genomes against those generated by other annotation tools indicated that our pipeline is able to provide results that are closer to the reference genome annotation, with a smaller amount of false-positive proteins and missing functional annotated proteins. Additionally, the metrics obtained by Genix were slightly better than those obtained by Prokka, a state-of-art standalone annotation system. Our results indicate that Genix is a useful tool that is able to provide a more refined result, and may be a user-friendly way to obtain high-quality results.

  13. Metabolomic biomarkers in diabetic kidney diseases--A systematic review.

    PubMed

    Zhang, Yumin; Zhang, Siwen; Wang, Guixia

    2015-01-01

    Diabetic kidney disease (DKD) is generally characterized by increasing albuminuria in diabetic patients; however, few biomarkers are available to facilitate early diagnosis of this disease. The application of metabolomics has shown promises addressing this need. In this review, we conducted a search about metabolomic biomarkers in DKD patients through MEDLINE, EMBASE, and Cochrane Database up to the end of March, 2015. 12 eligible studies were selected and evaluated subsequently through the use of QUADOMICS, a quality assessment tool. 7 of the 12 included studies were classified as 'high quality'. We also recorded specific study characteristics including participants' characteristics, metabolomic techniques, sample types, and significantly altered metabolites between DKD and control groups. Products of lipid metabolisms including esterified and non-esterified fatty acids, carnitines, phospholipids and metabolites involved in branch-chained amino acids and aromatic amino acids metabolisms were frequently affected biomarkers of DKD. Other differential metabolites were also found, while some of their associations with DKD were unclear. Further more studies are required to test these findings in larger, diverse ethnic populations with elaborate study designs, and finally we could translate them into the benefits of DKD patients.

  14. Morphosyntactic Annotation of CHILDES Transcripts

    ERIC Educational Resources Information Center

    Sagae, Kenji; Davis, Eric; Lavie, Alon; MacWhinney, Brian; Wintner, Shuly

    2010-01-01

    Corpora of child language are essential for research in child language acquisition and psycholinguistics. Linguistic annotation of the corpora provides researchers with better means for exploring the development of grammatical constructions and their usage. We describe a project whose goal is to annotate the English section of the CHILDES database…

  15. An Annotated Bibliography on Children.

    ERIC Educational Resources Information Center

    Bureau of Libraries and Educational Technology (DHEW/OE), Washington, DC.

    This annotated bibliography is a highly selective list of materials published in the last five years on the major problems, trends, methodologies and achievements in the field of child development. It contains annotated references to approximately 500 books, periodicals, technical reports, government documents, legislative materials, professional…

  16. Drug Education: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Mathieson, Moira B.

    This bibliography consists of a total of 215 entries dealing with drug education, including curriculum guides, and drawn from documents in the ERIC system. There are two sections, the first containing 130 annotated citations of documents and journal articles, and the second containing 85 citations of journal articles without annotations, but with…

  17. Metabolomics Insights Into Pathophysiological Mechanisms of Interstitial Cystitis

    PubMed Central

    Fiehn, Oliver

    2014-01-01

    Interstitial cystitis (IC), also known as painful bladder syndrome or bladder pain syndrome, is a chronic lower urinary tract syndrome characterized by pelvic pain, urinary urgency, and increased urinary frequency in the absence of bacterial infection or identifiable clinicopathology. IC can lead to long-term adverse effects on the patient's quality of life. Therefore, early diagnosis and better understanding of the mechanisms underlying IC are needed. Metabolomic studies of biofluids have become a powerful method for assessing disease mechanisms and biomarker discovery, which potentially address these important clinical needs. However, limited intensive metabolic profiles have been elucidated in IC. The article is a short review on metabolomic analyses that provide a unique fingerprint of IC with a focus on its use in determining a potential diagnostic biomarker associated with symptoms, a response predictor of therapy, and a prognostic marker. PMID:25279237

  18. Metabolomic Profiling of 13 Diatom Cultures and Their Adaptation to Nitrate-Limited Growth Conditions

    PubMed Central

    Bromke, Mariusz A.; Sabir, Jamal S.; Alfassi, Fahad A.; Hajarah, Nahid H.; Kabli, Saleh A.; Al-Malki, Abdulrahman L.; Ashworth, Matt P.; Méret, Michaël; Jansen, Robert K.; Willmitzer, Lothar

    2015-01-01

    Diatoms are very efficient in their use of available nutrients. Changes in nutrient availability influence the metabolism and the composition of the cell constituents. Since diatoms are valuable candidates to search for oil producing algae, measurements of diatom-produced compounds can be very useful for biotechnology. In order to explore the diversity of lipophilic compounds produced by diatoms, we describe the results from an analysis of 13 diatom strains. With the help of a lipidomics platform, which combines an UPLC separation with a high resolution/high mass accuracy mass spectrometer, we were able to measure and annotate 142 lipid species. Out of these, 32 were present in all 13 cultures. The annotated lipid features belong to six classes of glycerolipids. The data obtained from the measurements were used to create lipidomic profiles. The metabolomic overview of analysed cultures is amended by the measurement of 96 polar compounds. To further increase the lipid diversity and gain insight into metabolomic adaptation to nitrogen limitation, diatoms were cultured in media with high and low concentrations of nitrate. The growth in nitrogen-deplete or nitrogen-replete conditions affects metabolite accumulation but has no major influence on the species-specific metabolomic profile. Thus, the genetic component is stronger in determining metabolic patterns than nitrogen levels. Therefore, lipid profiling is powerful enough to be used as a molecular fingerprint for diatom cultures. Furthermore, an increase of triacylglycerol (TAG) accumulation was observed in low nitrogen samples, although this trend was not consistent across all 13 diatom strains. Overall, our results expand the current understanding of metabolomics diversity in diatoms and confirm their potential value for producing lipids for either bioenergy or as feed stock. PMID:26440112

  19. Multi-Platform Metabolomic Analyses of Ergosterol-Induced Dynamic Changes in Nicotiana tabacum Cells

    PubMed Central

    Tugizimana, Fidele; Steenkamp, Paul A.; Piater, Lizelle A.; Dubery, Ian A.

    2014-01-01

    Metabolomics is providing new dimensions into understanding the intracellular adaptive responses in plants to external stimuli. In this study, a multi-technology-metabolomic approach was used to investigate the effect of the fungal sterol, ergosterol, on the metabolome of cultured tobacco cells. Cell suspensions were treated with different concentrations (0–1000 nM) of ergosterol and incubated for different time periods (0–24 h). Intracellular metabolites were extracted with two methods: a selective dispersive liquid-liquid micro-extraction and a general methanol extraction. Chromatographic techniques (GC-FID, GC-MS, GC×GC-TOF-MS, UHPLC-MS) and 1H NMR spectroscopy were used for quantitative and qualitative analyses. Multivariate data analyses (PCA and OPLS-DA models) were used to extract interpretable information from the multidimensional data generated from the analytical techniques. The results showed that ergosterol triggered differential changes in the metabolome of the cells, leading to variation in the biosynthesis of secondary metabolites. PCA scores plots revealed dose- and time-dependent metabolic variations, with optimal treatment conditions being found to be 300 nM ergosterol and an 18 h incubation period. The observed ergosterol-induced metabolic changes were correlated with changes in defence-related metabolites. The ‘defensome’ involved increases in terpenoid metabolites with five antimicrobial compounds (the bicyclic sesquiterpenoid phytoalexins: phytuberin, solavetivone, capsidiol, lubimin and rishitin) and other metabolites (abscisic acid and phytosterols) putatively identified. In addition, various phenylpropanoid precursors, cinnamic acid derivatives and - conjugates, coumarins and lignin monomers were annotated. These annotated metabolites revealed a dynamic reprogramming of metabolic networks that are functionally correlated, with a high complexity in their regulation. PMID:24498209

  20. Metabolomic Profiling of 13 Diatom Cultures and Their Adaptation to Nitrate-Limited Growth Conditions.

    PubMed

    Bromke, Mariusz A; Sabir, Jamal S; Alfassi, Fahad A; Hajarah, Nahid H; Kabli, Saleh A; Al-Malki, Abdulrahman L; Ashworth, Matt P; Méret, Michaël; Jansen, Robert K; Willmitzer, Lothar

    2015-01-01

    Diatoms are very efficient in their use of available nutrients. Changes in nutrient availability influence the metabolism and the composition of the cell constituents. Since diatoms are valuable candidates to search for oil producing algae, measurements of diatom-produced compounds can be very useful for biotechnology. In order to explore the diversity of lipophilic compounds produced by diatoms, we describe the results from an analysis of 13 diatom strains. With the help of a lipidomics platform, which combines an UPLC separation with a high resolution/high mass accuracy mass spectrometer, we were able to measure and annotate 142 lipid species. Out of these, 32 were present in all 13 cultures. The annotated lipid features belong to six classes of glycerolipids. The data obtained from the measurements were used to create lipidomic profiles. The metabolomic overview of analysed cultures is amended by the measurement of 96 polar compounds. To further increase the lipid diversity and gain insight into metabolomic adaptation to nitrogen limitation, diatoms were cultured in media with high and low concentrations of nitrate. The growth in nitrogen-deplete or nitrogen-replete conditions affects metabolite accumulation but has no major influence on the species-specific metabolomic profile. Thus, the genetic component is stronger in determining metabolic patterns than nitrogen levels. Therefore, lipid profiling is powerful enough to be used as a molecular fingerprint for diatom cultures. Furthermore, an increase of triacylglycerol (TAG) accumulation was observed in low nitrogen samples, although this trend was not consistent across all 13 diatom strains. Overall, our results expand the current understanding of metabolomics diversity in diatoms and confirm their potential value for producing lipids for either bioenergy or as feed stock.

  1. Metabolome-ionome-biomass interactions

    PubMed Central

    Sanchez, Diego H; Redestig, Henning; Krämer, Ute; Udvardi, Michael K

    2008-01-01

    Long-term exposure of plants to saline soil results in mineral ion imbalance, altered metabolism and reduced growth. Currently, the interaction between ion content and plant metabolism under salt-stress is poorly understood. Here we present a multivariate correlation study on the metabolome, ionome and biomass changes of Lotus japonicus challenged by salt stress. Using latent variable models, we show that increasing salinity leads to reproducible changes of metabolite, ion and nutrient pools. Strong correlations between the metabolome and the ionome or biomass may allow one to estimate the degree of salt stress experienced by a plant based on metabolite profiles. Despite the apparently high predictive power of the models, it remains to be investigated whether such metabolite profiles of non- or moderately-stressed plants can be used by breeding programs as ideal ideotypes for the selection of enhanced salt-tolerant genotypes. PMID:19704810

  2. Metabolomics for plant stress response.

    PubMed

    Shulaev, Vladimir; Cortes, Diego; Miller, Gad; Mittler, Ron

    2008-02-01

    Stress in plants could be defined as any change in growth condition(s) that disrupts metabolic homeostasis and requires an adjustment of metabolic pathways in a process that is usually referred to as acclimation. Metabolomics could contribute significantly to the study of stress biology in plants and other organisms by identifying different compounds, such as by-products of stress metabolism, stress signal transduction molecules or molecules that are part of the acclimation response of plants. These could be further tested by direct measurements, correlated with changes in transcriptome and proteome expression and confirmed by mutant analysis. In this review, we will discuss recent application of metabolomics and system biology to the area of plant stress response. We will describe approaches such as metabolic profiling and metabolic fingerprinting as well as combination of different 'omics' platforms to achieve a holistic view of the plant response stress and conduct detailed pathway analysis.

  3. Progress toward single cell metabolomics

    PubMed Central

    Rubakhin, Stanislav S.; Lanni, Eric J.; Sweedler, Jonathan V.

    2012-01-01

    The metabolome refers to the entire set of small molecules, or metabolites, within a biological sample. These molecules are involved in many fundamental intracellular functions and reflect the cell’s physiological condition. The ability to detect and identify metabolites and determine and monitor their amounts at the single cell level enables an exciting range of studies of biological variation and functional heterogeneity between cells, even within a presumably homogenous cell population. Significant progress has been made in the development and application of bioanalytical tools for single cell metabolomics based on mass spectrometry, microfluidics, and capillary separations. Remarkable improvements in the sensitivity, specificity, and throughput of these approaches enable investigation of multiple metabolites simultaneously in a range of individual cell samples. PMID:23246232

  4. Morphosyntactic annotation of CHILDES transcripts*

    PubMed Central

    SAGAE, KENJI; DAVIS, ERIC; LAVIE, ALON; MACWHINNEY, BRIAN; WINTNER, SHULY

    2014-01-01

    Corpora of child language are essential for research in child language acquisition and psycholinguistics. Linguistic annotation of the corpora provides researchers with better means for exploring the development of grammatical constructions and their usage. We describe a project whose goal is to annotate the English section of the CHILDES database with grammatical relations in the form of labeled dependency structures. We have produced a corpus of over 18,800 utterances (approximately 65,000 words) with manually curated gold-standard grammatical relation annotations. Using this corpus, we have developed a highly accurate data-driven parser for the English CHILDES data, which we used to automatically annotate the remainder of the English section of CHILDES. We have also extended the parser to Spanish, and are currently working on supporting more languages. The parser and the manually and automatically annotated data are freely available for research purposes. PMID:20334720

  5. Model and Interoperability using Meta Data Annotations

    NASA Astrophysics Data System (ADS)

    David, O.

    2011-12-01

    modeling components are not directly bound to framework by the use of specific APIs and/or data types they can more easily be reused both within the framework as well as outside. While providing all those capabilities, a significant reduction in the size of the model source code was achieved. To support the benefit of annotations for a modeler, studies were conducted to evaluate the effectiveness of an annotation based framework approach with other modeling frameworks and libraries, a framework-invasiveness study was conducted to evaluate the effects of framework design on model code quality. A typical hydrological model was implemented across several modeling frameworks and several software metrics were collected. The metrics selected were measures of non-invasive design methods for modeling frameworks from a software engineering perspective. It appears that the use of annotations positively impacts several software quality measures. Experience to date has demonstrated the multi-purpose value of using annotations. Annotations are also a feasible and practical method to enable interoperability among models and modeling frameworks.

  6. Is the Juice Worth the Squeeze? Costs and Benefits of Multiple Human Annotators for Clinical Text De-identification

    PubMed Central

    Carrell, D. S.; Cronkite, D. J.; Malin, B. A.; Aberdeen, J. S.; Hirschman, L.

    2016-01-01

    Summary Background Clinical text contains valuable information but must be de-identified before it can be used for secondary purposes. Accurate annotation of personally identifiable information (PII) is essential to the development of automated de-identification systems and to manual redaction of PII. Yet the accuracy of annotations may vary considerably across individual annotators and annotation is costly. As such, the marginal benefit of incorporating additional annotators has not been well characterized. Objectives This study models the costs and benefits of incorporating increasing numbers of independent human annotators to identify the instances of PII in a corpus. We used a corpus with gold standard annotations to evaluate the performance of teams of annotators of increasing size. Methods Four annotators independently identified PII in a 100-document corpus consisting of randomly selected clinical notes from Family Practice clinics in a large integrated health care system. These annotations were pooled and validated to generate a gold standard corpus for evaluation. Results Recall rates for all PII types ranged from 0.90 to 0.98 for individual annotators to 0.998 to 1.0 for teams of three, when measured against the gold standard. Median cost per PII instance discovered during corpus annotation ranged from $0.71 for an individual annotator to $377 for annotations discovered only by a fourth annotator. Conclusions Incorporating a second annotator into a PII annotation process reduces unredacted PII and improves the quality of annotations to 0.99 recall, yielding clear benefit at reasonable cost; the cost advantages of annotation teams larger than two diminish rapidly. PMID:27405787

  7. Is the Juice Worth the Squeeze? Costs and Benefits of Multiple Human Annotators for Clinical Text De-identification.

    PubMed

    Carrell, David S; Cronkite, David J; Malin, Bradley A; Aberdeen, John S; Hirschman, Lynette

    2016-08-05

    Clinical text contains valuable information but must be de-identified before it can be used for secondary purposes. Accurate annotation of personally identifiable information (PII) is essential to the development of automated de-identification systems and to manual redaction of PII. Yet the accuracy of annotations may vary considerably across individual annotators and annotation is costly. As such, the marginal benefit of incorporating additional annotators has not been well characterized. This study models the costs and benefits of incorporating increasing numbers of independent human annotators to identify the instances of PII in a corpus. We used a corpus with gold standard annotations to evaluate the performance of teams of annotators of increasing size. Four annotators independently identified PII in a 100-document corpus consisting of randomly selected clinical notes from Family Practice clinics in a large integrated health care system. These annotations were pooled and validated to generate a gold standard corpus for evaluation. Recall rates for all PII types ranged from 0.90 to 0.98 for individual annotators to 0.998 to 1.0 for teams of three, when meas-ured against the gold standard. Median cost per PII instance discovered during corpus annotation ranged from $ 0.71 for an individual annotator to $ 377 for annotations discovered only by a fourth annotator. Incorporating a second annotator into a PII annotation process reduces unredacted PII and improves the quality of annotations to 0.99 recall, yielding clear benefit at reasonable cost; the cost advantages of annotation teams larger than two diminish rapidly.

  8. Metabolomic signature of brain cancer.

    PubMed

    Pandey, Renu; Caflisch, Laura; Lodi, Alessia; Brenner, Andrew J; Tiziani, Stefano

    2017-06-15

    Despite advances in surgery and adjuvant therapy, brain tumors represent one of the leading causes of cancer-related mortality and morbidity in both adults and children. Gliomas constitute about 60% of all cerebral tumors, showing varying degrees of malignancy. They are difficult to treat due to dismal prognosis and limited therapeutics. Metabolomics is the untargeted and targeted analyses of endogenous and exogenous small molecules, which charact erizes the phenotype of an individual. This emerging "omics" science provides functional readouts of cellular activity that contribute greatly to the understanding of cancer biology including brain tumor biology. Metabolites are highly informative as a direct signature of biochemical activity; therefore, metabolite profiling has become a promising approach for clinical diagnostics and prognostics. The metabolic alterations are well-recognized as one of the key hallmarks in monitoring disease progression, therapy, and revealing new molecular targets for effective therapeutic intervention. Taking advantage of the latest high-throughput analytical technologies, that is, nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), metabolomics is now a promising field for precision medicine and drug discovery. In the present report, we review the application of metabolomics and in vivo metabolic profiling in the context of adult gliomas and paediatric brain tumors. Analytical platforms such as high-resolution (HR) NMR, in vivo magnetic resonance spectroscopic imaging and high- and low-resolution MS are discussed. Moreover, the relevance of metabolic studies in the development of new therapeutic strategies for treatment of gliomas are reviewed. © 2017 Wiley Periodicals, Inc.

  9. Applications of metabolomics in agriculture.

    PubMed

    Dixon, Richard A; Gang, David R; Charlton, Adrian J; Fiehn, Oliver; Kuiper, Harry A; Reynolds, Tracey L; Tjeerdema, Ronald S; Jeffery, Elizabeth H; German, J Bruce; Ridley, William P; Seiber, James N

    2006-11-29

    Biological systems are exceedingly complex. The unraveling of the genome in plants and humans revealed fewer than the anticipated number of genes. Therefore, other processes such as the regulation of gene expression, the action of gene products, and the metabolic networks resulting from catalytic proteins must make fundamental contributions to the remarkable diversity inherent in living systems. Metabolomics is a relatively new approach aimed at improved understanding of these metabolic networks and the subsequent biochemical composition of plants and other biological organisms. Analytical tools within metabolomics including mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy can profile the impact of time, stress, nutritional status, and environmental perturbation on hundreds of metabolites simultaneously resulting in massive, complex data sets. This information, in combination with transcriptomics and proteomics, has the potential to generate a more complete picture of the composition of food and feed products, to optimize crop trait development, and to enhance diet and health. Selected presentations from an American Chemical Society symposium held in March 2005 have been assembled to highlight the emerging application of metabolomics in agriculture.

  10. An integrated computational pipeline and database to support whole-genome sequence annotation

    PubMed Central

    Mungall, CJ; Misra, S; Berman, BP; Carlson, J; Frise, E; Harris, N; Marshall, B; Shu, S; Kaminker, JS; Prochnik, SE; Smith, CD; Smith, E; Tupy, JL; Wiel, C; Rubin, GM; Lewis, SE

    2002-01-01

    We describe here our experience in annotating the Drosophila melanogaster genome sequence, in the course of which we developed several new open-source software tools and a database schema to support large-scale genome annotation. We have developed these into an integrated and reusable software system for whole-genome annotation. The key contributions to overall annotation quality are the marshalling of high-quality sequences for alignments and the design of a system with an adaptable and expandable flexible architecture. PMID:12537570

  11. Annotation of the Drosophila melanogaster euchromatic genome: a systematic review

    PubMed Central

    Misra, Sima; Crosby, Madeline A; Mungall, Christopher J; Matthews, Beverley B; Campbell, Kathryn S; Hradecky, Pavel; Huang, Yanmei; Kaminker, Joshua S; Millburn, Gillian H; Prochnik, Simon E; Smith, Christopher D; Tupy, Jonathan L; Whitfield, Eleanor J; Bayraktaroglu, Leyla; Berman, Benjamin P; Bettencourt, Brian R; Celniker, Susan E; de Grey, Aubrey DNJ; Drysdale, Rachel A; Harris, Nomi L; Richter, John; Russo, Susan; Schroeder, Andrew J; Shu, ShengQiang; Stapleton, Mark; Yamada, Chihiro; Ashburner, Michael; Gelbart, William M; Rubin, Gerald M; Lewis, Suzanna E

    2002-01-01

    Background The recent completion of the Drosophila melanogaster genomic sequence to high quality and the availability of a greatly expanded set of Drosophila cDNA sequences, aligning to 78% of the predicted euchromatic genes, afforded FlyBase the opportunity to significantly improve genomic annotations. We made the annotation process more rigorous by inspecting each gene visually, utilizing a comprehensive set of curation rules, requiring traceable evidence for each gene model, and comparing each predicted peptide to SWISS-PROT and TrEMBL sequences. Results Although the number of predicted protein-coding genes in Drosophila remains essentially unchanged, the revised annotation significantly improves gene models, resulting in structural changes to 85% of the transcripts and 45% of the predicted proteins. We annotated transposable elements and non-protein-coding RNAs as new features, and extended the annotation of untranslated (UTR) sequences and alternative transcripts to include more than 70% and 20% of genes, respectively. Finally, cDNA sequence provided evidence for dicistronic transcripts, neighboring genes with overlapping UTRs on the same DNA sequence strand, alternatively spliced genes that encode distinct, non-overlapping peptides, and numerous nested genes. Conclusions Identification of so many unusual gene models not only suggests that some mechanisms for gene regulation are more prevalent than previously believed, but also underscores the complex challenges of eukaryotic gene prediction. At present, experimental data and human curation remain essential to generate high-quality genome annotations. PMID:12537572

  12. A semantic analysis of the annotations of the human genome

    PubMed Central

    Khatri, Purvesh; Done, Bogdan; Rao, Archana; Done, Arina

    2008-01-01

    The correct interpretation of any biological experiment depends in an essential way on the accuracy and consistency of the existing annotation databases. Such databases are ubiquitous and used by all life scientists in most experiments. However, it is well known that such databases are incomplete and many annotations may also be incorrect. In this paper we describe a technique that can be used to analyze the semantic content of such annotation databases. Our approach is able to extract implicit semantic relationships between genes and functions. This ability allows us to discover novel functions for known genes. This approach is able to identify missing and inaccurate annotations in existing annotation databases, and thus help improve their accuracy. We used our technique to analyze the current annotations of the human genome. From this body of annotations, we were able to predict 212 additional gene–function assignments. A subsequent literature search found that 138 of these gene–functions assignments are supported by existing peer-reviewed papers. An additional 23 assignments have been confirmed in the meantime by the addition of the respective annotations in later releases of the Gene Ontology database. Overall, the 161 confirmed assignments represent 75.95% of the proposed gene–function assignments. Only one of our predictions (0.4%) was contradicted by the existing literature. We could not find any relevant articles for 50 of our predictions (23.58%). The method is independent of the organism and can be used to analyze and improve the quality of the data of any public or private annotation database. Availability http://vortex.cs.wayne.edu/papers/semantic_analysis_bioinfo.pdf Contact sod@cs.wayne.edu PMID:15955782

  13. PRIMe Update: innovative content for plant metabolomics and integration of gene expression and metabolite accumulation.

    PubMed

    Sakurai, Tetsuya; Yamada, Yutaka; Sawada, Yuji; Matsuda, Fumio; Akiyama, Kenji; Shinozaki, Kazuo; Hirai, Masami Yokota; Saito, Kazuki

    2013-02-01

    PRIMe (http://prime.psc.riken.jp/), the Platform for RIKEN Metabolomics, is a website that was designed and implemented to support research and analyses ranging from metabolomics to transcriptomics. To achieve functional genomics and annotation of unknown metabolites, we established the following PRIMe contents: MS2T, a library comprising >1 million entries of untargeted tandem mass spectrometry (MS/MS) data of plant metabolites; AtMetExpress LC-MS, a database of transcriptomics and metabolomics approaches in Arabidopsis developmental stages (AtMetExpress Development LC-MS) and a data set of the composition of secondary metabolites among 20 Arabidopsis ecotypes (AtMetExpress 20 ecotypes LC-MS); and ReSpect, hybrid reference MS/MS data resources (acquisitions and literature). PRIMeLink is a new web application that allows access to the innovative data resources of PRIMe. The MS2T library was generated from a set of MS/MS spectra acquired using the automatic data acquisition function of mass spectrometry. To increase the understanding of mechanisms driving variations in metabolic profiles among plant tissues, we further provided the AtMetExpress Development LC-MS database in PRIMe, facilitating the investigation of relationships between gene expression and metabolite accumulation. This information platform therefore provides an integrative analysis resource by linking Arabidopsis transcriptome and metabolome data. Moreover, we developed the ReSpect database, a plant-specific MS/MS data resource, which allows users to identify candidate structures from the suite of complex phytochemical structures. Finally, we integrated the three databases into PRIMeLink and established a walk-through link between transcriptome and metabolome information. PRIMeLink offers a bi-directional searchable function, from the gene and the metabolite perspective, to search for targets seamlessly and effectively.

  14. Precautions for harvest, sampling, storage, and transport of crop plant metabolomics samples.

    PubMed

    Biais, Benoît; Bernillon, Stéphane; Deborde, Catherine; Cabasson, Cécile; Rolin, Dominique; Tadmor, Yaakov; Burger, Joseph; Schaffer, Arthur A; Moing, Annick

    2012-01-01

    Plant metabolomics is increasingly a routine option for plant biologists and food scientists. Here, we suggest some precautions for preparation and handling of samples issued from crop plants, in order to ensure sample representativeness and quality before their biochemical analysis. These precautions concern organ harvest either in the greenhouse or in the field, transport to the laboratory, and sampling, as well as sample pooling, storage, and transport to the analytical laboratory. They are in agreement with the recommendations of the "Plant Biology Context" group of the Metabolomics Standards Initiative concerning reporting practices for sample preparation. Some quality checking methods for long-term stability of metabolomics samples are also covered. The corresponding experimental procedures are illustrated using a representative study on melon fruit.

  15. Disease monitoring of hepatocellular carcinoma through metabolomics

    PubMed Central

    Fitian, Asem I; Cabrera, Roniel

    2017-01-01

    We elucidate major pathways of hepatocarcinogenesis and accurate diagnostic metabolomic biomarkers of hepatocellular carcinoma (HCC) identified by contemporary HCC metabolomics studies, and delineate a model HCC metabolomics study design. A literature search was carried out on Pubmed for HCC metabolomics articles published in English. All relevant articles were accessed in full text. Major search terms included “HCC”, “metabolomics”, “metabolomics”, “metabonomic” and “biomarkers”. We extracted clinical and demographic data on all patients and consolidated the lead candidate biomarkers, pathways, and diagnostic performance of metabolomic expression patterns reported by all studies in tables. Where reported, we also extracted and summarized the metabolites and pathways most highly associated with the development of cirrhosis in table format. Pathways of lysophospholipid, sphingolipid, bile acid, amino acid, and reactive oxygen species metabolism were most consistently associated with HCC in the cited works. Several studies also elucidate metabolic alterations strongly associated with cirrhosis, with γ-glutamyl peptides, bile acids, and dicarboxylic acids exhibiting the highest capacity for stratifying cirrhosis patients from appropriately matched controls. Collectively, global metabolomic profiles of the referenced works exhibit a promising diagnostic capacity for HCC at a capacity greater than that of conventional diagnostic biomarker alpha-fetoprotein. Metabolomics is a powerful strategy for identifying global metabolic signatures that exhibit potential to be leveraged toward the screening, diagnosis, and management of HCC. A streamlined study design and patient matching methodology may improve concordance among metabolomic datasets in future works. PMID:28105254

  16. HAMAP in 2015: updates to the protein family classification and annotation system

    PubMed Central

    Pedruzzi, Ivo; Rivoire, Catherine; Auchincloss, Andrea H.; Coudert, Elisabeth; Keller, Guillaume; de Castro, Edouard; Baratin, Delphine; Cuche, Béatrice A.; Bougueleret, Lydie; Poux, Sylvain; Redaschi, Nicole; Xenarios, Ioannis; Bridge, Alan

    2015-01-01

    HAMAP (High-quality Automated and Manual Annotation of Proteins—available at http://hamap.expasy.org/) is a system for the automatic classification and annotation of protein sequences. HAMAP provides annotation of the same quality and detail as UniProtKB/Swiss-Prot, using manually curated profiles for protein sequence family classification and expert curated rules for functional annotation of family members. HAMAP data and tools are made available through our website and as part of the UniRule pipeline of UniProt, providing annotation for millions of unreviewed sequences of UniProtKB/TrEMBL. Here we report on the growth of HAMAP and updates to the HAMAP system since our last report in the NAR Database Issue of 2013. We continue to augment HAMAP with new family profiles and annotation rules as new protein families are characterized and annotated in UniProtKB/Swiss-Prot; the latest version of HAMAP (as of 3 September 2014) contains 1983 family classification profiles and 1998 annotation rules (up from 1780 and 1720). We demonstrate how the complex logic of HAMAP rules allows for precise annotation of individual functional variants within large homologous protein families. We also describe improvements to our web-based tool HAMAP-Scan which simplify the classification and annotation of sequences, and the incorporation of an improved sequence-profile search algorithm. PMID:25348399

  17. Sma3s: a three-step modular annotator for large sequence datasets.

    PubMed

    Muñoz-Mérida, Antonio; Viguera, Enrique; Claros, M Gonzalo; Trelles, Oswaldo; Pérez-Pulido, Antonio J

    2014-08-01

    Automatic sequence annotation is an essential component of modern 'omics' studies, which aim to extract information from large collections of sequence data. Most existing tools use sequence homology to establish evolutionary relationships and assign putative functions to sequences. However, it can be difficult to define a similarity threshold that achieves sufficient coverage without sacrificing annotation quality. Defining the correct configuration is critical and can be challenging for non-specialist users. Thus, the development of robust automatic annotation techniques that generate high-quality annotations without needing expert knowledge would be very valuable for the research community. We present Sma3s, a tool for automatically annotating very large collections of biological sequences from any kind of gene library or genome. Sma3s is composed of three modules that progressively annotate query sequences using either: (i) very similar homologues, (ii) orthologous sequences or (iii) terms enriched in groups of homologous sequences. We trained the system using several random sets of known sequences, demonstrating average sensitivity and specificity values of ~85%. In conclusion, Sma3s is a versatile tool for high-throughput annotation of a wide variety of sequence datasets that outperforms the accuracy of other well-established annotation algorithms, and it can enrich existing database annotations and uncover previously hidden features. Importantly, Sma3s has already been used in the functional annotation of two published transcriptomes.

  18. Sma3s: A Three-Step Modular Annotator for Large Sequence Datasets

    PubMed Central

    Muñoz-Mérida, Antonio; Viguera, Enrique; Claros, M. Gonzalo; Trelles, Oswaldo; Pérez-Pulido, Antonio J.

    2014-01-01

    Automatic sequence annotation is an essential component of modern ‘omics’ studies, which aim to extract information from large collections of sequence data. Most existing tools use sequence homology to establish evolutionary relationships and assign putative functions to sequences. However, it can be difficult to define a similarity threshold that achieves sufficient coverage without sacrificing annotation quality. Defining the correct configuration is critical and can be challenging for non-specialist users. Thus, the development of robust automatic annotation techniques that generate high-quality annotations without needing expert knowledge would be very valuable for the research community. We present Sma3s, a tool for automatically annotating very large collections of biological sequences from any kind of gene library or genome. Sma3s is composed of three modules that progressively annotate query sequences using either: (i) very similar homologues, (ii) orthologous sequences or (iii) terms enriched in groups of homologous sequences. We trained the system using several random sets of known sequences, demonstrating average sensitivity and specificity values of ∼85%. In conclusion, Sma3s is a versatile tool for high-throughput annotation of a wide variety of sequence datasets that outperforms the accuracy of other well-established annotation algorithms, and it can enrich existing database annotations and uncover previously hidden features. Importantly, Sma3s has already been used in the functional annotation of two published transcriptomes. PMID:24501397

  19. Training Nuclei Detection Algorithms with Simple Annotations.

    PubMed

    Kost, Henning; Homeyer, André; Molin, Jesper; Lundström, Claes; Hahn, Horst Karl

    2017-01-01

    Generating good training datasets is essential for machine learning-based nuclei detection methods. However, creating exhaustive nuclei contour annotations, to derive optimal training data from, is often infeasible. We compared different approaches for training nuclei detection methods solely based on nucleus center markers. Such markers contain less accurate information, especially with regard to nuclear boundaries, but can be produced much easier and in greater quantities. The approaches use different automated sample extraction methods to derive image positions and class labels from nucleus center markers. In addition, the approaches use different automated sample selection methods to improve the detection quality of the classification algorithm and reduce the run time of the training process. We evaluated the approaches based on a previously published generic nuclei detection algorithm and a set of Ki-67-stained breast cancer images. A Voronoi tessellation-based sample extraction method produced the best performing training sets. However, subsampling of the extracted training samples was crucial. Even simple class balancing improved the detection quality considerably. The incorporation of active learning led to a further increase in detection quality. With appropriate sample extraction and selection methods, nuclei detection algorithms trained on the basis of simple center marker annotations can produce comparable quality to algorithms trained on conventionally created training sets.

  20. Mixture model normalization for non-targeted gas chromatography/mass spectrometry metabolomics data.

    PubMed

    Reisetter, Anna C; Muehlbauer, Michael J; Bain, James R; Nodzenski, Michael; Stevens, Robert D; Ilkayeva, Olga; Metzger, Boyd E; Newgard, Christopher B; Lowe, William L; Scholtens, Denise M

    2017-02-02

    Metabolomics offers a unique integrative perspective for health research, reflecting genetic and environmental contributions to disease-related phenotypes. Identifying robust associations in population-based or large-scale clinical studies demands large numbers of subjects and therefore sample batching for gas-chromatography/mass spectrometry (GC/MS) non-targeted assays. When run over weeks or months, technical noise due to batch and run-order threatens data interpretability. Application of existing normalization methods to metabolomics is challenged by unsatisfied modeling assumptions and, notably, failure to address batch-specific truncation of low abundance compounds. To curtail technical noise and make GC/MS metabolomics data amenable to analyses describing biologically relevant variability, we propose mixture model normalization (mixnorm) that accommodates truncated data and estimates per-metabolite batch and run-order effects using quality control samples. Mixnorm outperforms other approaches across many metrics, including improved correlation of non-targeted and targeted measurements and superior performance when metabolite detectability varies according to batch. For some metrics, particularly when truncation is less frequent for a metabolite, mean centering and median scaling demonstrate comparable performance to mixnorm. When quality control samples are systematically included in batches, mixnorm is uniquely suited to normalizing non-targeted GC/MS metabolomics data due to explicit accommodation of batch effects, run order and varying thresholds of detectability. Especially in large-scale studies, normalization is crucial for drawing accurate conclusions from non-targeted GC/MS metabolomics data.

  1. A Metabolomic Perspective on Coeliac Disease

    PubMed Central

    Calabrò, Antonio

    2014-01-01

    Metabolomics is an “omic” science that is now emerging with the purpose of elaborating a comprehensive analysis of the metabolome, which is the complete set of metabolites (i.e., small molecules intermediates) in an organism, tissue, cell, or biofluid. In the past decade, metabolomics has already proved to be useful for the characterization of several pathological conditions and offers promises as a clinical tool. A metabolomics investigation of coeliac disease (CD) revealed that a metabolic fingerprint for CD can be defined, which accounts for three different but complementary components: malabsorption, energy metabolism, and alterations in gut microflora and/or intestinal permeability. In this review, we will discuss the major advancements in metabolomics of CD, in particular with respect to the role of gut microbiome and energy metabolism. PMID:24665364

  2. NMR Metabolomics Analysis of Parkinson's Disease

    PubMed Central

    Lei, Shulei; Powers, Robert

    2015-01-01

    Parkinson's disease (PD) is a neurodegenerative disease, which is characterized by progressive death of dopaminergic neurons in the substantia nigra pars compacta. Although mitochondrial dysfunction and oxidative stress are linked to PD pathogenesis, its etiology and pathology remain to be elucidated. Metabolomics investigates metabolite changes in biofluids, cell lysates, tissues and tumors in order to correlate these metabolomic changes to a disease state. Thus, the application of metabolomics to investigate PD provides a systematic approach to understand the pathology of PD, to identify disease biomarkers, and to complement genomics, transcriptomics and proteomics studies. This review will examine current research into PD mechanisms with a focus on mitochondrial dysfunction and oxidative stress. Neurotoxin-based PD animal models and the rationale for metabolomics studies in PD will also be discussed. The review will also explore the potential of NMR metabolomics to address important issues related to PD treatment and diagnosis. PMID:26078917

  3. Getting the right answers: understanding metabolomics challenges.

    PubMed

    Beisken, Stephan; Eiden, Michael; Salek, Reza M

    2015-01-01

    Small molecules within biological systems provide powerful insights into the biological roles, processes and states of organisms. Metabolomics is the study of the concentrations, structures and interactions of these thousands of small molecules, collectively known as the metabolome. Metabolomics is at the interface between chemistry, biology, statistics and computer science, requiring multidisciplinary skillsets. This presents unique challenges for researchers to fully utilize the information produced and to capture its potential diagnostic power. A good understanding of study design, sample preparation, analysis methods and data analysis is essential to get the right answers for the right questions. We outline the current state of the art, benefits and challenges of metabolomics to create an understanding of metabolomics studies from the experimental design to data analysis.

  4. Development of a universal metabolome-standard method for long-term LC-MS metabolome profiling and its application for bladder cancer urine-metabolite-biomarker discovery.

    PubMed

    Peng, Jun; Chen, Yi-Ting; Chen, Chien-Lun; Li, Liang

    2014-07-01

    Large-scale metabolomics study requires a quantitative method to generate metabolome data over an extended period with high technical reproducibility. We report a universal metabolome-standard (UMS) method, in conjunction with chemical isotope labeling liquid chromatography-mass spectrometry (LC-MS), to provide long-term analytical reproducibility and facilitate metabolome comparison among different data sets. In this method, UMS of a specific type of sample labeled by an isotope reagent is prepared a priori. The UMS is spiked into any individual samples labeled by another form of the isotope reagent in a metabolomics study. The resultant mixture is analyzed by LC-MS to provide relative quantification of the individual sample metabolome to UMS. UMS is independent of a study undertaking as well as the time of analysis and useful for profiling the same type of samples in multiple studies. In this work, the UMS method was developed and applied for a urine metabolomics study of bladder cancer. UMS of human urine was prepared by (13)C2-dansyl labeling of a pooled sample from 20 healthy individuals. This method was first used to profile the discovery samples to generate a list of putative biomarkers potentially useful for bladder cancer detection and then used to analyze the verification samples about one year later. Within the discovery sample set, three-month technical reproducibility was examined using a quality control sample and found a mean CV of 13.9% and median CV of 9.4% for all the quantified metabolites. Statistical analysis of the urine metabolome data showed a clear separation between the bladder cancer group and the control group from the discovery samples, which was confirmed by the verification samples. Receiver operating characteristic (ROC) test showed that the area under the curve (AUC) was 0.956 in the discovery data set and 0.935 in the verification data set. These results demonstrated the utility of the UMS method for long-term metabolomics and

  5. Video data annotation, archiving, and access

    NASA Astrophysics Data System (ADS)

    Wilkin, D.; Connor, J.; Stout, N. J.; Walz, K.; Schlining, K.; Graybeal, J.

    2002-12-01

    Scientifically useful, high-quality video data can be challenging to integrate with other data, and to analyze and archive for use in ocean science. The Monterey Bay Aquarium Research Institute (MBARI) uses high-resolution video equipment to record over 300 remotely operated vehicle dives per year. Over the past 14 years, 13,000 videotapes have been archived and maintained as a centralized institutional resource. MBARI has developed a set of software applications to annotate and access video data. Users can identify the location of video sequences using a data query component; complex queries can be made by constraining temporal, spatial, or physical parameters (e.g., season, location, or depth). The applications reference a knowledge base of over 3,000 biological, geological and technical terms, providing consistent hierarchical information about objects and associated descriptions for annotating video at sea or on shore. The annotation, knowledge base, and query components together provide a comprehensive video archive software system that can be applied to a variety of scientific disciplines. Also in development, using the XML data format, is an interactive reference interface to explore MBARI's deep-sea knowledge base. When complete, the full software system will be disseminated to the research community via the web or CD, to help meet the challenges inherent in archiving video data.

  6. Automated eukaryotic gene structure annotation using EVidenceModeler and the Program to Assemble Spliced Alignments.

    PubMed

    Haas, Brian J; Salzberg, Steven L; Zhu, Wei; Pertea, Mihaela; Allen, Jonathan E; Orvis, Joshua; White, Owen; Buell, C Robin; Wortman, Jennifer R

    2008-01-11

    EVidenceModeler (EVM) is presented as an automated eukaryotic gene structure annotation tool that reports eukaryotic gene structures as a weighted consensus of all available evidence. EVM, when combined with the Program to Assemble Spliced Alignments (PASA), yields a comprehensive, configurable annotation system that predicts protein-coding genes and alternatively spliced isoforms. Our experiments on both rice and human genome sequences demonstrate that EVM produces automated gene structure annotation approaching the quality of manual curation.

  7. Automated Eukaryotic Gene Structure Annotation Using EVidenceModeler and the Program to Assemble Spliced Alignments

    SciTech Connect

    Haas, B J; Salzberg, S L; Zhu, W; Pertea, M; Allen, J E; Orvis, J; White, O; Buell, C R; Wortman, J R

    2007-12-10

    EVidenceModeler (EVM) is presented as an automated eukaryotic gene structure annotation tool that reports eukaryotic gene structures as a weighted consensus of all available evidence. EVM, when combined with the Program to Assemble Spliced Alignments (PASA), yields a comprehensive, configurable annotation system that predicts protein-coding genes and alternatively spliced isoforms. Our experiments on both rice and human genome sequences demonstrate that EVM produces automated gene structure annotation approaching the quality of manual curation.

  8. Current Advances in the Metabolomics Study on Lotus Seeds

    PubMed Central

    Zhu, Mingzhi; Liu, Ting; Guo, Mingquan

    2016-01-01

    Lotus (Nelumbo nucifera), which is distributed widely throughout Asia, Australia and North America, is an aquatic perennial that has been cultivated for over 2,000 years. It is very stimulating that almost all parts of lotus have been consumed as vegetable as well as food, especially the seeds. Except for the nutritive values of lotus, there has been increasing interest in its potential as functional food due to its rich secondary metabolites, such as flavonoids and alkaloids. Not only have these metabolites greatly contributed to the biological process of lotus seeds, but also have been reported to possess multiple health-promoting effects, including antioxidant, anti-amnesic, anti-inflammatory, and anti-tumor activities. Thus, comprehensive metabolomic profiling of these metabolites is of key importance to help understand their biological activities, and other chemical biology features. In this context, this review will provide an update on the current technological platforms, and workflow associated with metabolomic studies on lotus seeds, as well as insights into the application of metabolomics for the improvement of food safety and quality, assisting breeding, and promotion of the study of metabolism and pharmacokinetics of lotus seeds; meanwhile it will also help explore new perspectives and outline future challenges in this fast-growing research subject. PMID:27379154

  9. Behavioral metabolomics analysis identifies novel neurochemical signatures in methamphetamine sensitization

    PubMed Central

    Adkins, Daniel E.; McClay, Joseph L.; Vunck, Sarah A.; Batman, Angela M.; Vann, Robert E.; Clark, Shaunna L.; Souza, Renan P.; Crowley, James J.; Sullivan, Patrick F.; van den Oord, Edwin J.C.G.; Beardsley, Patrick M.

    2014-01-01

    Behavioral sensitization has been widely studied in animal models and is theorized to reflect neural modifications associated with human psychostimulant addiction. While the mesolimbic dopaminergic pathway is known to play a role, the neurochemical mechanisms underlying behavioral sensitization remain incompletely understood. In the present study, we conducted the first metabolomics analysis to globally characterize neurochemical differences associated with behavioral sensitization. Methamphetamine-induced sensitization measures were generated by statistically modeling longitudinal activity data for eight inbred strains of mice. Subsequent to behavioral testing, nontargeted liquid and gas chromatography-mass spectrometry profiling was performed on 48 brain samples, yielding 301 metabolite levels per sample after quality control. Association testing between metabolite levels and three primary dimensions of behavioral sensitization (total distance, stereotypy and margin time) showed four robust, significant associations at a stringent metabolome-wide significance threshold (false discovery rate < 0.05). Results implicated homocarnosine, a dipeptide of GABA and histidine, in total distance sensitization, GABA metabolite 4-guanidinobutanoate and pantothenate in stereotypy sensitization, and myo-inositol in margin time sensitization. Secondary analyses indicated that these associations were independent of concurrent methamphetamine levels and, with the exception of the myo-inositol association, suggest a mechanism whereby strain-based genetic variation produces specific baseline neurochemical differences that substantially influence the magnitude of MA-induced sensitization. These findings demonstrate the utility of mouse metabolomics for identifying novel biomarkers, and developing more comprehensive neurochemical models, of psychostimulant sensitization. PMID:24034544

  10. Behavioral metabolomics analysis identifies novel neurochemical signatures in methamphetamine sensitization.

    PubMed

    Adkins, D E; McClay, J L; Vunck, S A; Batman, A M; Vann, R E; Clark, S L; Souza, R P; Crowley, J J; Sullivan, P F; van den Oord, E J C G; Beardsley, P M

    2013-11-01

    Behavioral sensitization has been widely studied in animal models and is theorized to reflect neural modifications associated with human psychostimulant addiction. While the mesolimbic dopaminergic pathway is known to play a role, the neurochemical mechanisms underlying behavioral sensitization remain incompletely understood. In this study, we conducted the first metabolomics analysis to globally characterize neurochemical differences associated with behavioral sensitization. Methamphetamine (MA)-induced sensitization measures were generated by statistically modeling longitudinal activity data for eight inbred strains of mice. Subsequent to behavioral testing, nontargeted liquid and gas chromatography-mass spectrometry profiling was performed on 48 brain samples, yielding 301 metabolite levels per sample after quality control. Association testing between metabolite levels and three primary dimensions of behavioral sensitization (total distance, stereotypy and margin time) showed four robust, significant associations at a stringent metabolome-wide significance threshold (false discovery rate, FDR <0.05). Results implicated homocarnosine, a dipeptide of GABA and histidine, in total distance sensitization, GABA metabolite 4-guanidinobutanoate and pantothenate in stereotypy sensitization, and myo-inositol in margin time sensitization. Secondary analyses indicated that these associations were independent of concurrent MA levels and, with the exception of the myo-inositol association, suggest a mechanism whereby strain-based genetic variation produces specific baseline neurochemical differences that substantially influence the magnitude of MA-induced sensitization. These findings demonstrate the utility of mouse metabolomics for identifying novel biomarkers, and developing more comprehensive neurochemical models, of psychostimulant sensitization. © 2013 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

  11. Establishment of Protocols for Global Metabolomics by LC-MS for Biomarker Discovery

    PubMed Central

    Okamura, Yasunobu; Motoike, Ikuko N.; Katoh, Yasutake; Kurosawa, Yasuhiro; Saijyo, Reina; Koshiba, Seizo; Yasuda, Jun; Motohashi, Hozumi; Sugawara, Junichi; Tanabe, Osamu; Kinoshita, Kengo; Yamamoto, Masayuki

    2016-01-01

    Metabolomics is a promising avenue for biomarker discovery. Although the quality of metabolomic analyses, especially global metabolomics (G-Met) using mass spectrometry (MS), largely depends on the instrumentation, potential bottlenecks still exist at several basic levels in the metabolomics workflow. Therefore, we established a precise protocol initially for the G-Met analyses of human blood plasma to overcome some these difficulties. In our protocol, samples are deproteinized in a 96-well plate using an automated liquid-handling system, and conducted either using a UHPLC-QTOF/MS system equipped with a reverse phase column or a LC-FTMS system equipped with a normal phase column. A normalization protocol of G-Met data was also developed to compensate for intra- and inter-batch differences, and the variations were significantly reduced along with our normalization, especially for the UHPLC-QTOF/MS data with a C18 reverse-phase column for positive ions. Secondly, we examined the changes in metabolomic profiles caused by the storage of EDTA-blood specimens to identify quality markers for the evaluation of the specimens’ pre-analytical conditions. Forty quality markers, including lysophospholipids, dipeptides, fatty acids, succinic acid, amino acids, glucose, and uric acid were identified by G-Met for the evaluation of plasma sample quality and established the equation of calculating the quality score. We applied our quality markers to a small-scale study to evaluate the quality of clinical samples. The G-Met protocols and quality markers established here should prove useful for the discovery and development of biomarkers for a wider range of diseases. PMID:27579980

  12. Annotated Bibliography on Religious Development.

    ERIC Educational Resources Information Center

    Bucher, Anton A.; Reich, K. Helmut

    1991-01-01

    Presents an annotated bibliography on religious development that covers the areas of psychology and religion, measurement of religiousness, religious development during the life cycle, religious experiences, conversion, religion and morality, and images of God. (Author/BB)

  13. Patient Education: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Simmons, Jeannette

    Topics included in this annotated bibliography on patient education are (1) background on development of patient education programs, (2) patient education interventions, (3) references for health professionals, and (4) research and evaluation in patient education. (TA)

  14. Hopi Linguistics: An Annotated Bibliography

    ERIC Educational Resources Information Center

    Seaman, P. David

    1977-01-01

    This is a preliminary research-oriented bibliography on the Hopi language. All known items, through mid-1976, are included, with an annotation for each item sketching its nature and/or possible value. (Author/RM)

  15. Butternut (Juglans cinerea) annotated bibliography.

    Treesearch

    M.E. Ostry; M.J. Moore; S.A.N. Worrall

    2003-01-01

    An annotated bibliography of the major literature related to butternut (Juglans cinerea) from 1890 to 2002. Includes 230 citations and a topical index. Topics include diseases, conservation, genetics, insect pests, silvics, nut production, propagation, silviculture, and utilization.

  16. Publication Production: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Firman, Anthony H.

    1994-01-01

    Offers brief annotations of 52 articles and papers on document production (from the Society for Technical Communication's journal and proceedings) on 9 topics: information processing, document design, using color, typography, tables, illustrations, photography, printing and binding, and production management. (SR)

  17. Publication Production: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Firman, Anthony H.

    1994-01-01

    Offers brief annotations of 52 articles and papers on document production (from the Society for Technical Communication's journal and proceedings) on 9 topics: information processing, document design, using color, typography, tables, illustrations, photography, printing and binding, and production management. (SR)

  18. Metagenomic gene annotation by a homology-independent approach

    SciTech Connect

    Froula, Jeff; Zhang, Tao; Salmeen, Annette; Hess, Matthias; Kerfeld, Cheryl A.; Wang, Zhong; Du, Changbin

    2011-06-02

    Fully understanding the genetic potential of a microbial community requires functional annotation of all the genes it encodes. The recently developed deep metagenome sequencing approach has enabled rapid identification of millions of genes from a complex microbial community without cultivation. Current homology-based gene annotation fails to detect distantly-related or structural homologs. Furthermore, homology searches with millions of genes are very computational intensive. To overcome these limitations, we developed rhModeller, a homology-independent software pipeline to efficiently annotate genes from metagenomic sequencing projects. Using cellulases and carbonic anhydrases as two independent test cases, we demonstrated that rhModeller is much faster than HMMER but with comparable accuracy, at 94.5percent and 99.9percent accuracy, respectively. More importantly, rhModeller has the ability to detect novel proteins that do not share significant homology to any known protein families. As {approx}50percent of the 2 million genes derived from the cow rumen metagenome failed to be annotated based on sequence homology, we tested whether rhModeller could be used to annotate these genes. Preliminary results suggest that rhModeller is robust in the presence of missense and frameshift mutations, two common errors in metagenomic genes. Applying the pipeline to the cow rumen genes identified 4,990 novel cellulases candidates and 8,196 novel carbonic anhydrase candidates.In summary, we expect rhModeller to dramatically increase the speed and quality of metagnomic gene annotation.

  19. MITOS: improved de novo metazoan mitochondrial genome annotation.

    PubMed

    Bernt, Matthias; Donath, Alexander; Jühling, Frank; Externbrink, Fabian; Florentz, Catherine; Fritzsch, Guido; Pütz, Joern; Middendorf, Martin; Stadler, Peter F

    2013-11-01

    About 2000 completely sequenced mitochondrial genomes are available from the NCBI RefSeq data base together with manually curated annotations of their protein-coding genes, rRNAs, and tRNAs. This annotation information, which has accumulated over two decades, has been obtained with a diverse set of computational tools and annotation strategies. Despite all efforts of manual curation it is still plagued by misassignments of reading directions, erroneous gene names, and missing as well as false positive annotations in particular for the RNA genes. Taken together, this causes substantial problems for fully automatic pipelines that aim to use these data comprehensively for studies of animal phylogenetics and the molecular evolution of mitogenomes. The MITOS pipeline is designed to compute a consistent de novo annotation of the mitogenomic sequences. We show that the results of MITOS match RefSeq and MitoZoa in terms of annotation coverage and quality. At the same time we avoid biases, inconsistencies of nomenclature, and typos originating from manual curation strategies. The MITOS pipeline is accessible online at http://mitos.bioinf.uni-leipzig.de. Copyright © 2012 Elsevier Inc. All rights reserved.

  20. NCBI prokaryotic genome annotation pipeline.

    PubMed

    Tatusova, Tatiana; DiCuccio, Michael; Badretdin, Azat; Chetvernin, Vyacheslav; Nawrocki, Eric P; Zaslavsky, Leonid; Lomsadze, Alexandre; Pruitt, Kim D; Borodovsky, Mark; Ostell, James

    2016-08-19

    Recent technological advances have opened unprecedented opportunities for large-scale sequencing and analysis of populations of pathogenic species in disease outbreaks, as well as for large-scale diversity studies aimed at expanding our knowledge across the whole domain of prokaryotes. To meet the challenge of timely interpretation of structure, function and meaning of this vast genetic information, a comprehensive approach to automatic genome annotation is critically needed. In collaboration with Georgia Tech, NCBI has developed a new approach to genome annotation that combines alignment based methods with methods of predicting protein-coding and RNA genes and other functional elements directly from sequence. A new gene finding tool, GeneMarkS+, uses the combined evidence of protein and RNA placement by homology as an initial map of annotation to generate and modify ab initio gene predictions across the whole genome. Thus, the new NCBI's Prokaryotic Genome Annotation Pipeline (PGAP) relies more on sequence similarity when confident comparative data are available, while it relies more on statistical predictions in the absence of external evidence. The pipeline provides a framework for generation and analysis of annotation on the full breadth of prokaryotic taxonomy. For additional information on PGAP see https://www.ncbi.nlm.nih.gov/genome/annotation_prok/ and the NCBI Handbook, https://www.ncbi.nlm.nih.gov/books/NBK174280/. Published by Oxford University Press on behalf of Nucleic Acids Research 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

  1. Global LC/MS Metabolomics Profiling of Calcium Stressed and Immunosuppressant Drug Treated Saccharomyces cerevisiae.

    PubMed

    Jenkins, Stefan; Fischer, Steven M; Chen, Lily; Sana, Theodore R

    2013-12-06

    Previous studies have shown that calcium stressed Saccharomyces cerevisiae, challenged with immunosuppressant drugs FK506 and Cyclosporin A, responds with comprehensive gene expression changes and attenuation of the generalized calcium stress response. Here, we describe a global metabolomics workflow for investigating the utility of tracking corresponding phenotypic changes. This was achieved by efficiently analyzing relative abundance differences between intracellular metabolite pools from wild-type and calcium stressed cultures, with and without prior immunosuppressant drugs exposure. We used pathway database content from WikiPathways and YeastCyc to facilitate the projection of our metabolomics profiling results onto biological pathways. A key challenge was to increase the coverage of the detected metabolites. This was achieved by applying both reverse phase (RP) and aqueous normal phase (ANP) chromatographic separations, as well as electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) sources for detection in both ion polarities. Unsupervised principle component analysis (PCA) and ANOVA results revealed differentiation between wild-type controls, calcium stressed and immunosuppressant/calcium challenged cells. Untargeted data mining resulted in 247 differentially expressed, annotated metabolites, across at least one pair of conditions. A separate, targeted data mining strategy identified 187 differential, annotated metabolites. All annotated metabolites were subsequently mapped onto curated pathways from YeastCyc and WikiPathways for interactive pathway analysis and visualization. Dozens of pathways showed differential responses to stress conditions based on one or more matches to the list of annotated metabolites or to metabolites that had been identified further by MS/MS. The purine salvage, pantothenate and sulfur amino acid pathways were flagged as being enriched, which is consistent with previously published literature for

  2. Evolution of metabolomics profile of crab paste during fermentation.

    PubMed

    Chen, Daian; Ye, Yangfang; Chen, Juanjuan; Yan, Xiaojun

    2016-02-01

    Crab paste is regularly consumed by people in the coastal area of China. The fermentation time plays a key role on the quality of crab paste. Here, we investigated the dynamic evolution of metabolite profile of crab paste during fermentation by combined use of NMR spectroscopy and multivariate data analysis. Our results showed that crab paste quality was significantly affected by fermentation. The quality change was manifested in the decline of lactate, betaine, taurine, trimethylamine-N-oxide, trigonelline, inosine, adenosine diphosphate, and 2-pyridinemethanol, and in the fluctuation of a range of amino acids as well as in the accumulation of glutamate, sucrose, formate, acetate, trimethylamine, and hypoxanthine. Trimethylamine production and its increased level with fermentation could be considered as a freshness index of crab paste. These results contribute to quality assessment of crab paste and confirm the metabolomics technique as a useful tool to provide important information on the crab paste quality. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Plant tissue extraction for metabolomics.

    PubMed

    Roessner, Ute; Dias, Daniel Anthony

    2013-01-01

    Plants are not only important producers of foods and energy storages (e.g., sugars, carbohydrates, proteins, and fats) in the form of grains, fruits, and vegetables, they also provide many valuable products to human existence including wood, fibers, oils, resins, pigments, antioxidants, and sources of medicine. Most importantly in light of this book, plants have been a source of therapeutic and health promoting compounds throughout history. This chapter describes several essential considerations for the extraction process when aiming to study plant metabolism or to characterize the chemical composition of plant originated samples using metabolomics technologies.

  4. MAKER2: an annotation pipeline and genome-database management tool for second-generation genome projects.

    PubMed

    Holt, Carson; Yandell, Mark

    2011-12-22

    Second-generation sequencing technologies are precipitating major shifts with regards to what kinds of genomes are being sequenced and how they are annotated. While the first generation of genome projects focused on well-studied model organisms, many of today's projects involve exotic organisms whose genomes are largely terra incognita. This complicates their annotation, because unlike first-generation projects, there are no pre-existing 'gold-standard' gene-models with which to train gene-finders. Improvements in genome assembly and the wide availability of mRNA-seq data are also creating opportunities to update and re-annotate previously published genome annotations. Today's genome projects are thus in need of new genome annotation tools that can meet the challenges and opportunities presented by second-generation sequencing technologies. We present MAKER2, a genome annotation and data management tool designed for second-generation genome projects. MAKER2 is a multi-threaded, parallelized application that can process second-generation datasets of virtually any size. We show that MAKER2 can produce accurate annotations for novel genomes where training-data are limited, of low quality or even non-existent. MAKER2 also provides an easy means to use mRNA-seq data to improve annotation quality; and it can use these data to update legacy annotations, significantly improving their quality. We also show that MAKER2 can evaluate the quality of genome annotations, and identify and prioritize problematic annotations for manual review. MAKER2 is the first annotation engine specifically designed for second-generation genome projects. MAKER2 scales to datasets of any size, requires little in the way of training data, and can use mRNA-seq data to improve annotation quality. It can also update and manage legacy genome annotation datasets.

  5. MAKER2: an annotation pipeline and genome-database management tool for second-generation genome projects

    PubMed Central

    2011-01-01

    Background Second-generation sequencing technologies are precipitating major shifts with regards to what kinds of genomes are being sequenced and how they are annotated. While the first generation of genome projects focused on well-studied model organisms, many of today's projects involve exotic organisms whose genomes are largely terra incognita. This complicates their annotation, because unlike first-generation projects, there are no pre-existing 'gold-standard' gene-models with which to train gene-finders. Improvements in genome assembly and the wide availability of mRNA-seq data are also creating opportunities to update and re-annotate previously published genome annotations. Today's genome projects are thus in need of new genome annotation tools that can meet the challenges and opportunities presented by second-generation sequencing technologies. Results We present MAKER2, a genome annotation and data management tool designed for second-generation genome projects. MAKER2 is a multi-threaded, parallelized application that can process second-generation datasets of virtually any size. We show that MAKER2 can produce accurate annotations for novel genomes where training-data are limited, of low quality or even non-existent. MAKER2 also provides an easy means to use mRNA-seq data to improve annotation quality; and it can use these data to update legacy annotations, significantly improving their quality. We also show that MAKER2 can evaluate the quality of genome annotations, and identify and prioritize problematic annotations for manual review. Conclusions MAKER2 is the first annotation engine specifically designed for second-generation genome projects. MAKER2 scales to datasets of any size, requires little in the way of training data, and can use mRNA-seq data to improve annotation quality. It can also update and manage legacy genome annotation datasets. PMID:22192575

  6. Environmental metabolomics: Biological markers for metal toxicity.

    PubMed

    García-Sevillano, Miguel Ángel; García-Barrera, Tamara; Gómez-Ariza, José Luis

    2015-07-14

    Environmental metabolomics is an emerging field referred to the application of metabolomics to characterize the interactions of living organisms with their environment. In this sense, the importance of monitoring the effects of toxic metals on living organisms has increased as a consequence of natural changes and anthropogenic activities that have led to an increase of toxic metals levels in terrestrial and aquatic ecosystems. For this purpose, the use of metabolomics based on mass spectrometry to study metal toxicity is gaining importance in recent years. Environmental metabolomics can be used to: discover the mode of action (MOA) of toxic metals through controlled laboratory experiments; evaluate toxicity (biological adverse response to a substance), that may be useful in risk assessment; and develop new biomarkers (based in metabolome shifts discovered through controlled laboratory experiments) that may be applied in environmental biomonitoring (environmental realistic scenario). In this review, it is discussed how metabolomics based on mass spectrometry can be applied to study metal toxicity, considering the most important hallmarks related to metabolomic experiments. This article is protected by copyright. All rights reserved.

  7. Metabolomics in neonatology: fact or fiction?

    PubMed

    Fanos, V; Van den Anker, J; Noto, A; Mussap, M; Atzori, L

    2013-02-01

    The newest 'omics' science is metabolomics, the latest offspring of genomics, considered the most innovative of the 'omics' sciences. Metabolomics, also called the 'new clinical biochemistry', is an approach based on the systematic study of the complete set of metabolites in a biological sample. The metabolome is considered the most predictive phenotype and is capable of considering epigenetic differences. It is so close to the phenotype that it can be considered the phenotype itself. In the last three years about 5000 papers have been listed in PubMed on this topic, but few data are available in the newborn. The aim of this review, after a description of background and technical procedures, is to analyse the clinical applications of metabolomics in neonatology, covering the following points: gestational age, postnatal age, type of delivery, zygosity, perinatal asphyxia, intrauterine growth restriction, prenatal inflammation and brain injury, respiratory, cardiovascular renal, metabolic diseases; sepsis, necrotizing enterocolitis and antibiotic treatment; nutritional studies on maternal milk and formula, pharma-metabolomics, long-term diseases. Pros and cons of metabolomics are also discussed. All this comes about with the non-invasive collection of a few drops of urine (exceptionally important for the neonate, especially those of low birth weight). Only time and large-scale studies to validate initial results will place metabolomics within neonatology. In any case, it is important for perinatologists to learn and understand this new technology to offer their patients the utmost in diagnostic and therapeutic opportunities.

  8. Metabolomics for Biomarker Discovery in Gastroenterological Cancer

    PubMed Central

    Nishiumi, Shin; Suzuki, Makoto; Kobayashi, Takashi; Matsubara, Atsuki; Azuma, Takeshi; Yoshida, Masaru

    2014-01-01

    The study of the omics cascade, which involves comprehensive investigations based on genomics, transcriptomics, proteomics, metabolomics, etc., has developed rapidly and now plays an important role in life science research. Among such analyses, metabolome analysis, in which the concentrations of low molecular weight metabolites are comprehensively analyzed, has rapidly developed along with improvements in analytical technology, and hence, has been applied to a variety of research fields including the clinical, cell biology, and plant/food science fields. The metabolome represents the endpoint of the omics cascade and is also the closest point in the cascade to the phenotype. Moreover, it is affected by variations in not only the expression but also the enzymatic activity of several proteins. Therefore, metabolome analysis can be a useful approach for finding effective diagnostic markers and examining unknown pathological conditions. The number of studies involving metabolome analysis has recently been increasing year-on-year. Here, we describe the findings of studies that used metabolome analysis to attempt to discover biomarker candidates for gastroenterological cancer and discuss metabolome analysis-based disease diagnosis. PMID:25003943

  9. Metabolomics-assisted biotechnological interventions for developing plant-based functional foods and nutraceuticals.

    PubMed

    Kumar, Arun; Mosa, Kareem A; Ji, Liyao; Kage, Udaykumar; Dhokane, Dhananjay; Karre, Shailesh; Madalageri, Deepa; Pathania, Neemisha

    2017-03-08

    Today, the dramatic changes in types of food consumed have led to an increased burden of chronic diseases. Therefore, the emphasis of food research is not only to ensure quality food that can supply adequate nutrients to prevent nutrition related diseases, but also to ensure overall physical and mental-health. This has led to the concept of functional foods and nutraceuticals (FFNs), which can be ideally produced and delivered through plants. Metabolomics can help in getting the most relevant functional information, and thus has been considered the greatest -OMICS technology to date. However, metabolomics has not been exploited to the best potential in plant sciences. The technology can be leveraged to identify the health promoting compounds and metabolites that can be used for the development of FFNs. This article reviews (i) plant-based FFNs-related metabolites and their health benefits; (ii) use of different analytic platforms for targeted and non-targeted metabolite profiling along with experimental considerations; (iii) exploitation of metabolomics to develop FFNs in plants using various biotechnological tools; and (iv) potential use of metabolomics in plant breeding. We have also provided some insights into integration of metabolomics with latest genome editing tools for metabolic pathway regulation in plants.

  10. Service Quality Management Systems: An Annotated Bibliography

    DTIC Science & Technology

    1992-05-01

    procedures or guidelines to use for implementing a useful service management program. The ful- crum of the authors’ program rests upon their Service...people who can act upon it. Case studies of our high-growth companies are presented: The Goodyear Tire & Rubber Company, Proctor & Gamble, Benet

  11. Metabolomics applied to the pancreatic islet

    PubMed Central

    Gooding, Jessica R.; Jensen, Mette V.; Newgard, Christopher B.

    2016-01-01

    Metabolomics, the characterization of the set of small molecules in a biological system, is advancing research in multiple areas of islet biology. Measuring a breadth of metabolites simultaneously provides a broad perspective on metabolic changes as the islets respond dynamically to metabolic fuels, hormones, or environmental stressors. As a result, metabolomics has the potential to provide new mechanistic insights into islet physiology and pathophysiology. Here we summarize advances in our understanding of islet physiology and the etiologies of type-1 and type-2 diabetes gained from metabolomics studies. PMID:26116790

  12. Mouse genome annotation by the RefSeq project.

    PubMed

    McGarvey, Kelly M; Goldfarb, Tamara; Cox, Eric; Farrell, Catherine M; Gupta, Tripti; Joardar, Vinita S; Kodali, Vamsi K; Murphy, Michael R; O'Leary, Nuala A; Pujar, Shashikant; Rajput, Bhanu; Rangwala, Sanjida H; Riddick, Lillian D; Webb, David; Wright, Mathew W; Murphy, Terence D; Pruitt, Kim D

    2015-10-01

    Complete and accurate annotation of the mouse genome is critical to the advancement of research conducted on this important model organism. The National Center for Biotechnology Information (NCBI) develops and maintains many useful resources to assist the mouse research community. In particular, the reference sequence (RefSeq) database provides high-quality annotation of multiple mouse genome assemblies using a combinatorial approach that leverages computation, manual curation, and collaboration. Implementation of this conservative and rigorous approach, which focuses on representation of only full-length and non-redundant data, produces high-quality annotation products. RefSeq records explicitly link sequences to current knowledge in a timely manner, updating public records regularly and rapidly in response to nomenclature updates, addition of new relevant publications, collaborator discussion, and user feedback. Whole genome re-annotation is also conducted at least every 12-18 months, and often more frequently in response to assembly updates or availability of informative data. This article highlights key features and advantages of RefSeq genome annotation products and presents an overview of NCBI processes to generate these data. Further discussion of NCBI's resources highlights useful features and the best methods for accessing our data.

  13. The guard cell metabolome: functions in stomatal movement and global food security.

    PubMed

    Misra, Biswapriya B; Acharya, Biswa R; Granot, David; Assmann, Sarah M; Chen, Sixue

    2015-01-01

    Guard cells represent a unique single cell-type system for the study of cellular responses to abiotic and biotic perturbations that affect stomatal movement. Decades of effort through both classical physiological and functional genomics approaches have generated an enormous amount of information on the roles of individual metabolites in stomatal guard cell function and physiology. Recent application of metabolomics methods has produced a substantial amount of new information on metabolome control of stomatal movement. In conjunction with other "omics" approaches, the knowledge-base is growing to reach a systems-level description of this single cell-type. Here we summarize current knowledge of the guard cell metabolome and highlight critical metabolites that bear significant impact on future engineering and breeding efforts to generate plants/crops that are resistant to environmental challenges and produce high yield and quality products for food and energy security.

  14. The guard cell metabolome: functions in stomatal movement and global food security

    PubMed Central

    Misra, Biswapriya B.; Acharya, Biswa R.; Granot, David; Assmann, Sarah M.; Chen, Sixue

    2015-01-01

    Guard cells represent a unique single cell-type system for the study of cellular responses to abiotic and biotic perturbations that affect stomatal movement. Decades of effort through both classical physiological and functional genomics approaches have generated an enormous amount of information on the roles of individual metabolites in stomatal guard cell function and physiology. Recent application of metabolomics methods has produced a substantial amount of new information on metabolome control of stomatal movement. In conjunction with other “omics” approaches, the knowledge-base is growing to reach a systems-level description of this single cell-type. Here we summarize current knowledge of the guard cell metabolome and highlight critical metabolites that bear significant impact on future engineering and breeding efforts to generate plants/crops that are resistant to environmental challenges and produce high yield and quality products for food and energy security. PMID:26042131

  15. Evaluation of hydrophilic interaction chromatography versus reversed-phase chromatography in a plant metabolomics perspective.

    PubMed

    T'kindt, Ruben; Storme, Michael; Deforce, Dieter; Van Bocxlaer, Jan

    2008-05-01

    The metabolomics goal, the unbiased relative quantification of all metabolites in a biological system, still lacks a universal analytical approach. In the LC-MS line of approach, one of the major problems encountered is the polar nature of a large group of (plant) metabolites. Here, we investigate the potential of hydrophilic interaction chromatography (HILIC) and compare its qualities with extended polarity RP chromatography. Two opposite LC phase compositions (Atlantis dC18 vs. TSKgel Amide-80) are compared in a plant metabolomics setting. Both performed equally well with regard to retentive capacities, but variation in peak area was about 5% higher for the HILIC approach. Focussing on matrix effects (ME) on the other hand, it was observed that this well-known problem in RP LC-MS metabolomics was not reduced on using hydrophilic interaction chromatography.

  16. Proteomics and metabolomics of Arabidopsis responses to perturbation of glucosinolate biosynthesis.

    PubMed

    Chen, Ya-zhou; Pang, Qiu-Ying; He, Yan; Zhu, Ning; Branstrom, Isabel; Yan, Xiu-Feng; Chen, Sixue

    2012-09-01

    To understand plant molecular networks of glucosinolate metabolism, perturbation of aliphatic glucosinolate biosynthesis was established using inducible RNA interference (RNAi) in Arabidopsis. Two RNAi lines were chosen for examining global protein and metabolite changes using complementary proteomics and metabolomics approaches. Proteins involved in metabolism including photosynthesis and hormone metabolism, protein binding, energy, stress, and defense showed marked responses to glucosinolate perturbation. In parallel, metabolomics revealed major changes in the levels of amino acids, carbohydrates, peptides, and hormones. The metabolomics data were correlated with the proteomics results and revealed intimate molecular connections between cellular pathways/processes and glucosinolate metabolism. This study has provided an unprecedented view of the molecular networks of glucosinolate metabolism and laid a foundation towards rationale glucosinolate engineering for enhanced defense and quality.

  17. Metabolomics: building on a century of biochemistry to guide human health

    PubMed Central

    German, J. Bruce; Hammock, Bruce D.; Watkins, Steven M.

    2006-01-01

    Medical diagnosis and treatment efficacy will improve significantly when a more personalized system for health assessment is implemented. This system will require diagnostics that provide sufficiently detailed information about the metabolic status of individuals such that assay results will be able to guide food, drug and lifestyle choices to maintain or improve distinct aspects of health without compromising others. Achieving this goal will use the new science of metabolomics – comprehensive metabolic profiling of individuals linked to the biological understanding of human integrative metabolism. Candidate technologies to accomplish this goal are largely available, yet they have not been brought into practice for this purpose. Metabolomic technologies must be sufficiently rapid, accurate and affordable to be routinely accessible to both healthy and acutely ill individuals. The use of metabolomic data to predict the health trajectories of individuals will require bioinformatic tools and quantitative reference databases. These databases containing metabolite profiles from the population must be built, stored and indexed according to metabolic and health status. Building and annotating these databases with the knowledge to predict how a specific metabolic pattern from an individual can be adjusted with diet, drugs and lifestyle to improve health represents a logical application of the biochemistry knowledge that the life sciences have produced over the past 100 years. PMID:16680201

  18. HAMAP in 2013, new developments in the protein family classification and annotation system

    PubMed Central

    Pedruzzi, Ivo; Rivoire, Catherine; Auchincloss, Andrea H.; Coudert, Elisabeth; Keller, Guillaume; de Castro, Edouard; Baratin, Delphine; Cuche, Béatrice A.; Bougueleret, Lydie; Poux, Sylvain; Redaschi, Nicole; Xenarios, Ioannis; Bridge, Alan

    2013-01-01

    HAMAP (High-quality Automated and Manual Annotation of Proteins—available at http://hamap.expasy.org/) is a system for the classification and annotation of protein sequences. It consists of a collection of manually curated family profiles for protein classification, and associated annotation rules that specify annotations that apply to family members. HAMAP was originally developed to support the manual curation of UniProtKB/Swiss-Prot records describing microbial proteins. Here we describe new developments in HAMAP, including the extension of HAMAP to eukaryotic proteins, the use of HAMAP in the automated annotation of UniProtKB/TrEMBL, providing high-quality annotation for millions of protein sequences, and the future integration of HAMAP into a unified system for UniProtKB annotation, UniRule. HAMAP is continuously updated by expert curators with new family profiles and annotation rules as new protein families are characterized. The collection of HAMAP family classification profiles and annotation rules can be browsed and viewed on the HAMAP website, which also provides an interface to scan user sequences against HAMAP profiles. PMID:23193261

  19. Annotating WordNet

    DTIC Science & Technology

    2004-01-01

    interrupted by one or more intervening words , for example ‘His performance blew the competition out of the water ’, where “blow out of the water ” is a WordNet...clarity.princeton.edu Abstract High-quality lexical resources are needed to both train and evaluate Word Sense Disam- biguation (WSD) systems. The problem of am...create a more in- tegrated lexical resource. 1 Introduction High-quality lexical resources are needed to both train and evaluate Word Sense Disambiguation

  20. How Large Is the Metabolome? A Critical Analysis of Data Exchange Practices in Chemistry

    PubMed Central

    Kind, Tobias; Scholz, Martin; Fiehn, Oliver

    2009-01-01

    Background Calculating the metabolome size of species by genome-guided reconstruction of metabolic pathways misses all products from orphan genes and from enzymes lacking annotated genes. Hence, metabolomes need to be determined experimentally. Annotations by mass spectrometry would greatly benefit if peer-reviewed public databases could be queried to compile target lists of structures that already have been reported for a given species. We detail current obstacles to compile such a knowledge base of metabolites. Results As an example, results are presented for rice. Two rice (oryza sativa) subspecies have been fully sequenced, oryza japonica and oryza indica. Several major small molecule databases were compared for listing known rice metabolites comprising PubChem, Chemical Abstracts, Beilstein, Patent databases, Dictionary of Natural Products, SetupX/BinBase, KNApSAcK DB, and finally those databases which were obtained by computational approaches, i.e. RiceCyc, KEGG, and Reactome. More than 5,000 small molecules were retrieved when searching these databases. Unfortunately, most often, genuine rice metabolites were retrieved together with non-metabolite database entries such as pesticides. Overlaps from database compound lists were very difficult to compare because structures were either not encoded in machine-readable format or because compound identifiers were not cross-referenced between databases. Conclusions We conclude that present databases are not capable of comprehensively retrieving all known metabolites. Metabolome lists are yet mostly restricted to genome-reconstructed pathways. We suggest that providers of (bio)chemical databases enrich their database identifiers to PubChem IDs and InChIKeys to enable cross-database queries. In addition, peer-reviewed journal repositories need to mandate submission of structures and spectra in machine readable format to allow automated semantic annotation of articles containing chemical structures. Such changes in

  1. PhenoMeter: A Metabolome Database Search Tool Using Statistical Similarity Matching of Metabolic Phenotypes for High-Confidence Detection of Functional Links.

    PubMed

    Carroll, Adam J; Zhang, Peng; Whitehead, Lynne; Kaines, Sarah; Tcherkez, Guillaume; Badger, Murray R

    2015-01-01

    This article describes PhenoMeter (PM), a new type of metabolomics database search that accepts metabolite response patterns as queries and searches the MetaPhen database of reference patterns for responses that are statistically significantly similar or inverse for the purposes of detecting functional links. To identify a similarity measure that would detect functional links as reliably as possible, we compared the performance of four statistics in correctly top-matching metabolic phenotypes of Arabidopsis thaliana metabolism mutants affected in different steps of the photorespiration metabolic pathway to reference phenotypes of mutants affected in the same enzymes by independent mutations. The best performing statistic, the PM score, was a function of both Pearson correlation and Fisher's Exact Test of directional overlap. This statistic outperformed Pearson correlation, biweight midcorrelation and Fisher's Exact Test used alone. To demonstrate general applicability, we show that the PM reliably retrieved the most closely functionally linked response in the database when queried with responses to a wide variety of environmental and genetic perturbations. Attempts to match metabolic phenotypes between independent studies were met with varying success and possible reasons for this are discussed. Overall, our results suggest that integration of pattern-based search tools into metabolomics databases will aid functional annotation of newly recorded metabolic phenotypes analogously to the way sequence similarity search algorithms have aided the functional annotation of genes and proteins. PM is freely available at MetabolomeExpress (https://www.metabolome-express.org/phenometer.php).

  2. Experiential Learning: An Annotated Literature Guide. CAEL Project Report.

    ERIC Educational Resources Information Center

    Stutz, Jane Porter, Ed.; Knapp, Joan, Ed.

    This guide is organized into three parts. Parts A and B contain bibliographic citations and brief annotations; Part C is an alphabetical listing of all references. Topics included in Part A are: the rationale and history of experiential learning, types of programs, program planning and implementation, program evaluation and quality assurance,…

  3. Chicano Perspectives in Literature--A Critical and Annotated Bibliography.

    ERIC Educational Resources Information Center

    Lomeli, Francisco A.; Urioste, Donaldo W.

    As an effort to define and explore the horizons of Chicano literature, this annotated and critical bibliography provides bibliographical data and critical evaluations and judgments regarding the quality, importance, and impact of 131 literary works by Chicanos. The commentaries are intended to be taken as opinions with the objective for promoting…

  4. An Annotated Bibliography of Selected Research on Collaborative Writing.

    ERIC Educational Resources Information Center

    Wynn, Evelyn Shepherd

    This annotated bibliography is intended to help teachers of composition improve writing quality of entering college students. The main body of the report is preceded by a brief summary of sources for faculty interested in examining the causes attributed to the decline in college students' writing skills, including: "National Assessment and the…

  5. Metabolomics in Population-Based Research

    Cancer.gov

    Metabolomics is the study of small molecules of both endogenous and exogenous origin, such as metabolic substrates and their products, lipids, small peptides, vitamins and other protein cofactors generated by metabolism, which are downstream from genes.

  6. De novo assembly and functional annotation of Myrciaria dubia fruit transcriptome reveals multiple metabolic pathways for L-ascorbic acid biosynthesis.

    PubMed

    Castro, Juan C; Maddox, J Dylan; Cobos, Marianela; Requena, David; Zimic, Mirko; Bombarely, Aureliano; Imán, Sixto A; Cerdeira, Luis A; Medina, Andersson E

    2015-11-24

    Myrciaria dubia is an Amazonian fruit shrub that produces numerous bioactive phytochemicals, but is best known by its high L-ascorbic acid (AsA) content in fruits. Pronounced variation in AsA content has been observed both within and among individuals, but the genetic factors responsible for this variation are largely unknown. The goals of this research, therefore, were to assemble, characterize, and annotate the fruit transcriptome of M. dubia in order to reconstruct metabolic pathways and determine if multiple pathways contribute to AsA biosynthesis. In total 24,551,882 high-quality sequence reads were de novo assembled into 70,048 unigenes (mean length = 1150 bp, N50 = 1775 bp). Assembled sequences were annotated using BLASTX against public databases such as TAIR, GR-protein, FB, MGI, RGD, ZFIN, SGN, WB, TIGR_CMR, and JCVI-CMR with 75.2 % of unigenes having annotations. Of the three core GO annotation categories, biological processes comprised 53.6 % of the total assigned annotations, whereas cellular components and molecular functions comprised 23.3 and 23.1 %, respectively. Based on the KEGG pathway assignment of the functionally annotated transcripts, five metabolic pathways for AsA biosynthesis were identified: animal-like pathway, myo-inositol pathway, L-gulose pathway, D-mannose/L-galactose pathway, and uronic acid pathway. All transcripts coding enzymes involved in the ascorbate-glutathione cycle were also identified. Finally, we used the assembly to identified 6314 genic microsatellites and 23,481 high quality SNPs. This study describes the first next-generation sequencing effort and transcriptome annotation of a non-model Amazonian plant that is relevant for AsA production and other bioactive phytochemicals. Genes encoding key enzymes were successfully identified and metabolic pathways involved in biosynthesis of AsA, anthocyanins, and other metabolic pathways have been reconstructed. The identification of these genes and pathways is in agreement with

  7. Mass-based metabolomic analysis of soybean sprouts during germination.

    PubMed

    Gu, Eun-Ji; Kim, Dong Wook; Jang, Gwang-Ju; Song, Seong Hwa; Lee, Jae-In; Lee, Sang Bong; Kim, Bo-Min; Cho, Yeongrae; Lee, Hyeon-Jeong; Kim, Hyun-Jin

    2017-02-15

    We investigated the metabolite profile of soybean sprouts at 0, 1, 2, 3, and 4days after germination using gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-MS (LC-MS) to understand the relationship between germination and nutritional quality. Data were analyzed by partial least squares-discriminant analysis (PLS-DA), and sprout samples were separated successfully using their PLS-DA scores. Fifty-eight metabolites, including macromolecular derivatives related to energy production, amino acids, myo-inositol metabolites, phytosterols, antioxidants, isoflavones, and soyasaponins, contributed to the separation. Amino acids, myo-inositol metabolites, isoflavone aglycones, B soyasaponins, antioxidants, and phytosterols, associated with health benefits and/or taste quality, increased with germination time while isoflavone glycosides and DDMP soyasaponins decreased. Based on these metabolites, the metabolomic pathway associated with energy production in soybean sprouts is suggested. Our data suggest that sprouting is a useful processing step to improve soybean nutritional quality, and metabolomic analysis is useful in understanding nutritional change during sprouting. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. Updating annotations with the distributed annotation system and the automated sequence annotation pipeline

    PubMed Central

    Speier, William; Ochs, Michael F.

    2012-01-01

    Summary: The integration between BioDAS ProServer and Automated Sequence Annotation Pipeline (ASAP) provides an interface for querying diverse annotation sources, chaining and linking results, and standardizing the output using the Distributed Annotation System (DAS) protocol. This interface allows pipeline plans in ASAP to be integrated into any system using HTTP and also allows the information returned by ASAP to be included in the DAS registry for use in any DAS-aware system. Three example implementations have been developed: the first accesses TRANSFAC information to automatically create gene sets for the Coordinated Gene Activity in Pattern Sets (CoGAPS) algorithm; the second integrates annotations from multiple array platforms and provides unified annotations in an R environment; and the third wraps the UniProt database for integration with the SPICE DAS client. Availability: Source code for ASAP 2.7 and the DAS 1.6 interface is available under the GNU public license. Proserver 2.20 is free software available from SourceForge. Scripts for installation and configuration on Linux are provided at our website: http://www.rits.onc.jhmi.edu/dbb/custom/A6/ Contact: Speier@mii.ucla.edu or mfo@jhu.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22945787

  9. Characterization of differences between blood sample matrices in untargeted metabolomics.

    PubMed

    Denery, Judith R; Nunes, Ashlee A K; Dickerson, Tobin J

    2011-02-01

    Large-scale proteomic and metabolomic technologies are increasingly gaining attention for their use in the diagnosis of human disease. In order to ensure the statistical power of relevant markers, such analyses must incorporate a large number of representative samples. While in a best-case scenario these samples are collected through a study design that is specifically tailored for the desired analysis, often studies must rely upon the analysis of large numbers of previously banked samples that may or may not have complete and accurate documentation of their associated collection and storage methods. In this study, several human blood matrices were analyzed and compared for the quality of metabolomic output. The sample types that were tested include plasma prepared with a variety of anticoagulants and serum collected by venipuncture and capillary blood collection protocols. Analysis with liquid chromatography-mass spectrometry (LC-MS) revealed only subtle differences between the various plasma preparation methods. Differences between the serum and plasma samples appear to be largely peptide/protein-based and are consistent with the biological distinction of the two matrices. Interestingly, the small molecule lysophosphatidylinositol was found to be in higher abundance in plasma, as a possible consequence of the effect of the intrinsic clotting cascade on adjacent metabolic pathways. Comparison of the small-molecule profiles of the capillary- and venipuncture-collected samples revealed 23 statistically significant compound differences between these sample types. Most of these features can be attributed to surfactants and detergents used to pretreat the skin in order to maintain the sterility of sample collection. However, several have identical mass and molecular formulas as endogenous human metabolites and could be erroneously attributed to actual metabolic perturbations. Understanding the extent of these matrix effects is important for control of systematic bias

  10. Automatic annotation of outdoor photographs

    NASA Astrophysics Data System (ADS)

    Cusano, Claudio; Schettini, Raimondo

    2011-01-01

    We propose here a strategy for the automatic annotation of outdoor photographs. Images are segmented in homogeneous regions which may be then assigned to seven different classes: sky, vegetation, snow, water, ground, street, and sand. These categories allows for content-aware image processing strategies. Our annotation strategy uses a normalized cut segmentation to identify the regions to be classified by a multi-class Support Vector Machine. The strategy has been evaluated on a set of images taken from the LabelMe dataset.

  11. Alignment-Annotator web server: rendering and annotating sequence alignments.

    PubMed

    Gille, Christoph; Fähling, Michael; Weyand, Birgit; Wieland, Thomas; Gille, Andreas

    2014-07-01

    Alignment-Annotator is a novel web service designed to generate interactive views of annotated nucleotide and amino acid sequence alignments (i) de novo and (ii) embedded in other software. All computations are performed at server side. Interactivity is implemented in HTML5, a language native to web browsers. The alignment is initially displayed using default settings and can be modified with the graphical user interfaces. For example, individual sequences can be reordered or deleted using drag and drop, amino acid color code schemes can be applied and annotations can be added. Annotations can be made manually or imported (BioDAS servers, the UniProt, the Catalytic Site Atlas and the PDB). Some edits take immediate effect while others require server interaction and may take a few seconds to execute. The final alignment document can be downloaded as a zip-archive containing the HTML files. Because of the use of HTML the resulting interactive alignment can be viewed on any platform including Windows, Mac OS X, Linux, Android and iOS in any standard web browser. Importantly, no plugins nor Java are required and therefore Alignment-Anotator represents the first interactive browser-based alignment visualization. http://www.bioinformatics.org/strap/aa/ and http://strap.charite.de/aa/. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  12. Alignment-Annotator web server: rendering and annotating sequence alignments

    PubMed Central

    Gille, Christoph; Fähling, Michael; Weyand, Birgit; Wieland, Thomas; Gille, Andreas

    2014-01-01

    Alignment-Annotator is a novel web service designed to generate interactive views of annotated nucleotide and amino acid sequence alignments (i) de novo and (ii) embedded in other software. All computations are performed at server side. Interactivity is implemented in HTML5, a language native to web browsers. The alignment is initially displayed using default settings and can be modified with the graphical user interfaces. For example, individual sequences can be reordered or deleted using drag and drop, amino acid color code schemes can be applied and annotations can be added. Annotations can be made manually or imported (BioDAS servers, the UniProt, the Catalytic Site Atlas and the PDB). Some edits take immediate effect while others require server interaction and may take a few seconds to execute. The final alignment document can be downloaded as a zip-archive containing the HTML files. Because of the use of HTML the resulting interactive alignment can be viewed on any platform including Windows, Mac OS X, Linux, Android and iOS in any standard web browser. Importantly, no plugins nor Java are required and therefore Alignment-Anotator represents the first interactive browser-based alignment visualization. Availability: http://www.bioinformatics.org/strap/aa/ and http://strap.charite.de/aa/. PMID:24813445

  13. Chemical annotation of small and peptide-like molecules at the Protein Data Bank.

    PubMed

    Young, Jasmine Y; Feng, Zukang; Dimitropoulos, Dimitris; Sala, Raul; Westbrook, John; Zhuravleva, Marina; Shao, Chenghua; Quesada, Martha; Peisach, Ezra; Berman, Helen M

    2013-01-01

    Over the past decade, the number of polymers and their complexes with small molecules in the Protein Data Bank archive (PDB) has continued to increase significantly. To support scientific advancements and ensure the best quality and completeness of the data files over the next 10 years and beyond, the Worldwide PDB partnership that manages the PDB archive is developing a new deposition and annotation system. This system focuses on efficient data capture across all supported experimental methods. The new deposition and annotation system is composed of four major modules that together support all of the processing requirements for a PDB entry. In this article, we describe one such module called the Chemical Component Annotation Tool. This tool uses information from both the Chemical Component Dictionary and Biologically Interesting molecule Reference Dictionary to aid in annotation. Benchmark studies have shown that the Chemical Component Annotation Tool provides significant improvements in processing efficiency and data quality. Database URL: http://wwpdb.org.

  14. Chemical annotation of small and peptide-like molecules at the Protein Data Bank

    PubMed Central

    Young, Jasmine Y.; Feng, Zukang; Dimitropoulos, Dimitris; Sala, Raul; Westbrook, John; Zhuravleva, Marina; Shao, Chenghua; Quesada, Martha; Peisach, Ezra; Berman, Helen M.

    2013-01-01

    Over the past decade, the number of polymers and their complexes with small molecules in the Protein Data Bank archive (PDB) has continued to increase significantly. To support scientific advancements and ensure the best quality and completeness of the data files over the next 10 years and beyond, the Worldwide PDB partnership that manages the PDB archive is developing a new deposition and annotation system. This system focuses on efficient data capture across all supported experimental methods. The new deposition and annotation system is composed of four major modules that together support all of the processing requirements for a PDB entry. In this article, we describe one such module called the Chemical Component Annotation Tool. This tool uses information from both the Chemical Component Dictionary and Biologically Interesting molecule Reference Dictionary to aid in annotation. Benchmark studies have shown that the Chemical Component Annotation Tool provides significant improvements in processing efficiency and data quality. Database URL: http://wwpdb.org PMID:24291661

  15. High Metabolomic Microdiversity within Co-Occurring Isolates of the Extremely Halophilic Bacterium Salinibacter ruber

    PubMed Central

    Antón, Josefa; Lucio, Marianna; Peña, Arantxa; Cifuentes, Ana; Brito-Echeverría, Jocelyn; Moritz, Franco; Tziotis, Dimitrios; López, Cristina; Urdiain, Mercedes; Schmitt-Kopplin, Philippe; Rosselló-Móra, Ramon

    2013-01-01

    Salinibacter ruber is an extremely halophilic member of the Bacteroidetes that thrives in crystallizer ponds worldwide. Here, we have analyzed two sets of 22 and 35 co-occurring S. ruber strains, newly isolated respectively, from 100 microliters water samples from crystalizer ponds in Santa Pola and Mallorca, located in coastal and inland Mediterranean Spain and 350 km apart from each other. A set of old strains isolated from the same setting were included in the analysis. Genomic and taxonomy relatedness of the strains were analyzed by means of PFGE and MALDI-TOF, respectively, while their metabolomic potential was explored with high resolution ion cyclotron resonance Fourier transform mass spectrometry (ICR-FT/MS). Overall our results show a phylogenetically very homogeneous species expressing a very diverse metabolomic pool. The combination of MALDI-TOF and PFGE provides, for the newly isolated strains, the same scenario presented by the previous studies of intra-specific diversity of S. ruber using a more restricted number of strains: the species seems to be very homogeneous at the ribosomal level while the genomic diversity encountered was rather high since no identical genome patterns could be retrieved from each of the samples. The high analytical mass resolution of ICR-FT/MS enabled the description of thousands of putative metabolites from which to date only few can be annotated in databases. Some metabolomic differences, mainly related to lipid metabolism and antibiotic-related compounds, provided enough specificity to delineate different clusters within the co-occurring strains. In addition, metabolomic differences were found between old and new strains isolated from the same ponds that could be related to extended exposure to laboratory conditions. PMID:23741374

  16. Metabolomics Analysis of Metabolic Effects of Nicotinamide Phosphoribosyltransferase (NAMPT) Inhibition on Human Cancer Cells

    PubMed Central

    Tolstikov, Vladimir; Nikolayev, Alexander; Dong, Sucai; Zhao, Genshi; Kuo, Ming-Shang

    2014-01-01

    Nicotinamide phosphoribosyltransferase (NAMPT) plays an important role in cellular bioenergetics. It is responsible for converting nicotinamide to nicotinamide adenine dinucleotide, an essential molecule in cellular metabolism. NAMPT has been extensively studied over the past decade due to its role as a key regulator of nicotinamide adenine dinucleotide–consuming enzymes. NAMPT is also known as a potential target for therapeutic intervention due to its involvement in disease. In the current study, we used a global mass spectrometry–based metabolomic approach to investigate the effects of FK866, a small molecule inhibitor of NAMPT currently in clinical trials, on metabolic perturbations in human cancer cells. We treated A2780 (ovarian cancer) and HCT-116 (colorectal cancer) cell lines with FK866 in the presence and absence of nicotinic acid. Significant changes were observed in the amino acids metabolism and the purine and pyrimidine metabolism. We also observed metabolic alterations in glycolysis, the citric acid cycle (TCA), and the pentose phosphate pathway. To expand the range of the detected polar metabolites and improve data confidence, we applied a global metabolomics profiling platform by using both non-targeted and targeted hydrophilic (HILIC)-LC-MS and GC-MS analysis. We used Ingenuity Knowledge Base to facilitate the projection of metabolomics data onto metabolic pathways. Several metabolic pathways showed differential responses to FK866 based on several matches to the list of annotated metabolites. This study suggests that global metabolomics can be a useful tool in pharmacological studies of the mechanism of action of drugs at a cellular level. PMID:25486521

  17. Metabolomics analysis of metabolic effects of nicotinamide phosphoribosyltransferase (NAMPT) inhibition on human cancer cells.

    PubMed

    Tolstikov, Vladimir; Nikolayev, Alexander; Dong, Sucai; Zhao, Genshi; Kuo, Ming-Shang

    2014-01-01

    Nicotinamide phosphoribosyltransferase (NAMPT) plays an important role in cellular bioenergetics. It is responsible for converting nicotinamide to nicotinamide adenine dinucleotide, an essential molecule in cellular metabolism. NAMPT has been extensively studied over the past decade due to its role as a key regulator of nicotinamide adenine dinucleotide-consuming enzymes. NAMPT is also known as a potential target for therapeutic intervention due to its involvement in disease. In the current study, we used a global mass spectrometry-based metabolomic approach to investigate the effects of FK866, a small molecule inhibitor of NAMPT currently in clinical trials, on metabolic perturbations in human cancer cells. We treated A2780 (ovarian cancer) and HCT-116 (colorectal cancer) cell lines with FK866 in the presence and absence of nicotinic acid. Significant changes were observed in the amino acids metabolism and the purine and pyrimidine metabolism. We also observed metabolic alterations in glycolysis, the citric acid cycle (TCA), and the pentose phosphate pathway. To expand the range of the detected polar metabolites and improve data confidence, we applied a global metabolomics profiling platform by using both non-targeted and targeted hydrophilic (HILIC)-LC-MS and GC-MS analysis. We used Ingenuity Knowledge Base to facilitate the projection of metabolomics data onto metabolic pathways. Several metabolic pathways showed differential responses to FK866 based on several matches to the list of annotated metabolites. This study suggests that global metabolomics can be a useful tool in pharmacological studies of the mechanism of action of drugs at a cellular level.

  18. Preserving sequence annotations across reference sequences.

    PubMed

    Tatum, Zuotian; Roos, Marco; Gibson, Andrew P; Taschner, Peter Em; Thompson, Mark; Schultes, Erik A; Laros, Jeroen Fj

    2014-01-01

    Matching and comparing sequence annotations of different reference sequences is vital to genomics research, yet many annotation formats do not specify the reference sequence types or versions used. This makes the integration of annotations from different sources difficult and error prone. As part of our effort to create linked data for interoperable sequence annotations, we present an RDF data model for sequence annotation using the ontological framework established by the OBO Foundry ontologies and the Basic Formal Ontology (BFO). We defined reference sequences as the common domain of integration for sequence annotations, and identified three semantic relationships between sequence annotations. In doing so, we created the Reference Sequence Annotation to compensate for gaps in the SO and in its mapping to BFO, particularly for annotations that refer to versions of consensus reference sequences. Moreover, we present three integration models for sequence annotations using different reference assemblies. We demonstrated a working example of a sequence annotation instance, and how this instance can be linked to other annotations on different reference sequences. Sequence annotations in this format are semantically rich and can be integrated easily with different assemblies. We also identify other challenges of modeling reference sequences with the BFO.

  19. Preserving sequence annotations across reference sequences

    PubMed Central

    2014-01-01

    Background Matching and comparing sequence annotations of different reference sequences is vital to genomics research, yet many annotation formats do not specify the reference sequence types or versions used. This makes the integration of annotations from different sources difficult and error prone. Results As part of our effort to create linked data for interoperable sequence annotations, we present an RDF data model for sequence annotation using the ontological framework established by the OBO Foundry ontologies and the Basic Formal Ontology (BFO). We defined reference sequences as the common domain of integration for sequence annotations, and identified three semantic relationships between sequence annotations. In doing so, we created the Reference Sequence Annotation to compensate for gaps in the SO and in its mapping to BFO, particularly for annotations that refer to versions of consensus reference sequences. Moreover, we present three integration models for sequence annotations using different reference assemblies. Conclusions We demonstrated a working example of a sequence annotation instance, and how this instance can be linked to other annotations on different reference sequences. Sequence annotations in this format are semantically rich and can be integrated easily with different assemblies. We also identify other challenges of modeling reference sequences with the BFO. PMID:25093075

  20. The application of metabolomics for herbal medicine pharmacovigilance: a case study on ginseng.

    PubMed

    Crighton, Elly; Mullaney, Ian; Trengove, Robert; Bunce, Michael; Maker, Garth

    2016-12-15

    Herbal medicines are growing in popularity, use and commercial value; however, there remain problems with the quality and consequently safety of these products. Adulterated, contaminated and fraudulent products are often found on the market, a risk compounded by the fact that these products are available to consumers with little or no medical advice. Current regulations and quality control methods are lacking in their ability to combat these serious problems. Metabolomics is a biochemical profiling tool that may help address these issues if applied to quality control of both raw ingredients and final products. Using the example of the popular herbal medicine, ginseng, this essay offers an overview of the potential use of metabolomics for quality control in herbal medicines and also highlights where more research is needed. © 2016 The Author(s). published by Portland Press Limited on behalf of the Biochemical Society.

  1. Metabolomics Standards Workshop and the development of international standards for reporting metabolomics experimental results.

    PubMed

    Castle, Arthur L; Fiehn, Oliver; Kaddurah-Daouk, Rima; Lindon, John C

    2006-06-01

    Informatics standards and controlled vocabularies are essential for allowing information technology to help exchange, manage, interpret and compare large data collections. In a rapidly evolving field, the challenge is to work out how best to describe, but not prescribe, the use of these technologies and methods. A Metabolomics Standards Workshop was held by the US National Institutes of Health (NIH) to bring together multiple ongoing standards efforts in metabolomics with the NIH research community. The goals were to discuss metabolomics workflows (methods, technologies and data treatments) and the needs, challenges and potential approaches to developing a Metabolomics Standards Initiative that will help facilitate this rapidly growing field which has been a focus of the NIH roadmap effort. This report highlights specific aspects of what was presented and discussed at the 1st and 2nd August 2005 Metabolomics Standards Workshop.

  2. Statistical algorithms for ontology-based annotation of scientific literature

    PubMed Central

    2014-01-01

    Background Ontologies encode relationships within a domain in robust data structures that can be used to annotate data objects, including scientific papers, in ways that ease tasks such as search and meta-analysis. However, the annotation process requires significant time and effort when performed by humans. Text mining algorithms can facilitate this process, but they render an analysis mainly based upon keyword, synonym and semantic matching. They do not leverage information embedded in an ontology's structure. Methods We present a probabilistic framework that facilitates the automatic annotation of literature by indirectly modeling the restrictions among the different classes in the ontology. Our research focuses on annotating human functional neuroimaging literature within the Cognitive Paradigm Ontology (CogPO). We use an approach that combines the stochastic simplicity of naïve Bayes with the formal transparency of decision trees. Our data structure is easily modifiable to reflect changing domain knowledge. Results We compare our results across naïve Bayes, Bayesian Decision Trees, and Constrained Decision Tree classifiers that keep a human expert in the loop, in terms of the quality measure of the F1-mirco score. Conclusions Unlike traditional text mining algorithms, our framework can model the knowledge encoded by the dependencies in an ontology, albeit indirectly. We successfully exploit the fact that CogPO has explicitly stated restrictions, and implicit dependencies in the form of patterns in the expert curated annotations. PMID:25093071

  3. Metabolomics and dereplication strategies in natural products.

    PubMed

    Tawfike, Ahmed Fares; Viegelmann, Christina; Edrada-Ebel, Ruangelie

    2013-01-01

    Metabolomic methods can be utilized to screen diverse biological sources of potentially novel and sustainable sources of antibiotics and pharmacologically-active drugs. Dereplication studies by high resolution Fourier transform mass spectrometry coupled to liquid chromatography (LC-HRFTMS) and nuclear magnetic resonance (NMR) spectroscopy can establish the chemical profile of endophytic and/or endozoic microbial extracts and their plant or animal sources. Identifying the compounds of interest at an early stage will aid in the isolation of the bioactive components. Therefore metabolite profiling is important for functional genomics and in the search for new pharmacologically active compounds. Using the tools of metabolomics through the employment of LC-HRFTMS as well as high resolution NMR will be a very efficient approach. Metabolomic profiling has found its application in screening extracts of macroorganisms as well as in the isolation and cultivation of suspected microbial producers of bioactive natural products.Metabolomics is being applied to identify and biotechnologically optimize the production of pharmacologically active secondary metabolites. The links between metabolome evolution during optimization and processing factors can be identified through metabolomics. Information obtained from a metabolomics dataset can efficiently establish cultivation and production processes at a small scale which will be finally scaled up to a fermenter system, while maintaining or enhancing synthesis of the desired compounds. MZmine (BMC Bioinformatics 11:395-399, 2010; http://mzmine.sourceforge.net/download.shtml ) and SIEVE ( http://www.vastscientific.com/resources/index.html ; Rapid Commun Mass Spectrom 22:1912-1918, 2008) softwares are utilized to perform differential analysis of sample populations to find significant expressed features of complex biomarkers between parameter variables. Metabolomes are identified with the aid of existing high resolution MS and NMR

  4. A manual curation strategy to improve genome annotation: application to a set of haloarchael genomes.

    PubMed

    Pfeiffer, Friedhelm; Oesterhelt, Dieter

    2015-06-02

    Genome annotation errors are a persistent problem that impede research in the biosciences. A manual curation effort is described that attempts to produce high-quality genome annotations for a set of haloarchaeal genomes (Halobacterium salinarum and Hbt. hubeiense, Haloferax volcanii and Hfx. mediterranei, Natronomonas pharaonis and Nmn. moolapensis, Haloquadratum walsbyi strains HBSQ001 and C23, Natrialba magadii, Haloarcula marismortui and Har. hispanica, and Halohasta litchfieldiae). Genomes are checked for missing genes, start codon misassignments, and disrupted genes. Assignments of a specific function are preferably based on experimentally characterized homologs (Gold Standard Proteins). To avoid overannotation, which is a major source of database errors, we restrict annotation to only general function assignments when support for a specific substrate assignment is insufficient. This strategy results in annotations that are resistant to the plethora of errors that compromise public databases. Annotation consistency is rigorously validated for ortholog pairs from the genomes surveyed. The annotation is regularly crosschecked against the UniProt database to further improve annotations and increase the level of standardization. Enhanced genome annotations are submitted to public databases (EMBL/GenBank, UniProt), to the benefit of the scientific community. The enhanced annotations are also publically available via HaloLex.

  5. IMG ER: A System for Microbial Genome Annotation Expert Review and Curation

    SciTech Connect

    Markowitz, Victor M.; Mavromatis, Konstantinos; Ivanova, Natalia N.; Chen, I-Min A.; Chu, Ken; Kyrpides, Nikos C.

    2009-05-25

    A rapidly increasing number of microbial genomes are sequenced by organizations worldwide and are eventually included into various public genome data resources. The quality of the annotations depends largely on the original dataset providers, with erroneous or incomplete annotations often carried over into the public resources and difficult to correct. We have developed an Expert Review (ER) version of the Integrated Microbial Genomes (IMG) system, with the goal of supporting systematic and efficient revision of microbial genome annotations. IMG ER provides tools for the review and curation of annotations of both new and publicly available microbial genomes within IMG's rich integrated genome framework. New genome datasets are included into IMG ER prior to their public release either with their native annotations or with annotations generated by IMG ER's annotation pipeline. IMG ER tools allow addressing annotation problems detected with IMG's comparative analysis tools, such as genes missed by gene prediction pipelines or genes without an associated function. Over the past year, IMG ER was used for improving the annotations of about 150 microbial genomes.

  6. Annotated Bibliography of Professional Socialization.

    ERIC Educational Resources Information Center

    Rogers, John M.

    This bibliography contains annotations of 49 articles on the topic of professional socialization. The articles were identified using the Educational Resources Information Center (ERIC), Sociological Abstracts, Medline, and Cumulative Index of Nursing and Allied Health Literature data bases. A bias exists in the selection process towards items…

  7. MSDAC Resource Library Annotated Bibliography.

    ERIC Educational Resources Information Center

    Schlee, Phillip F., Comp.; And Others

    The Midwest Sex Discrimination Assistance Center presents an annotated bibliography of 56 monographs and 11 other media materials relating to women and sex discrimination for use in public schools. Media materials include slides, films, filmstrips, audio recordings, and posters. The bibliography is organized by subject and each annotation…

  8. Workforce Reductions. An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Hickok, Thomas A.; Hickok, Thomas A.

    This report, which is based on a review of practitioner-oriented sources and scholarly journals, uses a three-part framework to organize annotated bibliographies that, together, list a total of 104 sources that provide the following three perspectives on work force reduction issues: organizational, organizational-individual relationship, and…

  9. Meaningful Assessment: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Thrond, Mary A.

    The annotated bibliography contains citations of nine references on alternative student assessment methods in second language programs, particularly at the secondary school level. The references include a critique of conventional reading comprehension assessment, a discussion of performance assessment, a proposal for a multi-trait, multi-method…

  10. Annotated Videography. Part 3. [Revised].

    ERIC Educational Resources Information Center

    United States Holocaust Memorial Museum, Washington, DC.

    This annotated videography has been designed to identify videotapes addressing Holocaust history that have been used effectively in classrooms and are available readily to most communities. The guide is divided into 15 topical categories, including: life before the Holocaust; perpetrators; propaganda; racism; antisemitism; mosaic of victims;…

  11. Hispanic Heritage. An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Denver Univ., CO. School of Education.

    This annotated bibliography of a wide range of materials for the social studies teacher is concerned with the Hispano heritage. The sections are introduced by a brief description. The sections are: 1) general materials, 2) the land and the people, 3) the European background, 4) Spain's colonial system, 5) the Spanish borderlands, 6) the Anglo…

  12. Annotated Bibliography on Humanistic Education

    ERIC Educational Resources Information Center

    Ganung, Cynthia

    1975-01-01

    Part I of this annotated bibliography deals with books and articles on such topics as achievement motivation, process education, transactional analysis, discipline without punishment, role-playing, interpersonal skills, self-acceptance, moral education, self-awareness, values clarification, and non-verbal communication. Part II focuses on…

  13. English Language Learners: Annotated Bibliography

    ERIC Educational Resources Information Center

    Hector-Mason, Anestine; Bardack, Sarah

    2010-01-01

    This annotated bibliography represents a first step toward compiling a comprehensive overview of current research on issues related to English language learners (ELLs). It is intended to be a resource for researchers, policymakers, administrators, and educators who are engaged in efforts to bridge the divide between research, policy, and practice…

  14. Migrant Education: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Palmer, Barbara C., Comp.

    Materials selected for inclusion in the annotated bibliography of 139 publications from 1970 to 1980 give a general understanding of the lives of migrant children, their educational needs and problems, and various attempts made to meet those needs. The bibliography, a valuable tool for researchers and teachers in migrant education, includes books,…

  15. Nikos Kazantzakis: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Qiu, Kui

    This research paper consists of an annotated bibliography about Nikos Kazantzakis, one of the major modern Greek writers and author of "The Last Temptation of Christ,""Zorba the Greek," and many other works. Because of Kazantzakis' position in world literature there are many critical works about him; however, bibliographical…

  16. Radiocarbon Dating: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Fortine, Suellen

    This selective annotated bibliography covers various sources of information on the radiocarbon dating method, including journal articles, conference proceedings, and reports, reflecting the most important and useful sources of the last 25 years. The bibliography is divided into five parts--general background on radiocarbon, radiocarbon dating,…

  17. MSDAC Resource Library Annotated Bibliography.

    ERIC Educational Resources Information Center

    Watson, Cristel; And Others

    This annotated bibliography lists books, films, filmstrips, recordings, and booklets on sex equity. Entries are arranged according to the following topics: career resources, curriculum resources, management, sex equity, sex roles, women's studies, student activities, and sex-fair fiction. Included in each entry are name of author, editor or…

  18. Radiocarbon Dating: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Fortine, Suellen

    This selective annotated bibliography covers various sources of information on the radiocarbon dating method, including journal articles, conference proceedings, and reports, reflecting the most important and useful sources of the last 25 years. The bibliography is divided into five parts--general background on radiocarbon, radiocarbon dating,…

  19. Peaceful Peoples: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Bonta, Bruce D.

    This annotated bibliography includes 438 selected references to books, journal articles, essays within edited volumes, and dissertations that provide significant information about peaceful societies. Peaceful societies are groups that have developed harmonious social structures that allow them to get along with each other, and with outsiders,…

  20. Oral History: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Friedman, Paul G.

    Defining oral history as a method of inquiry by which the memories of individuals are elicited, preserved in interview transcripts or on tape recordings, and then used to enrich understanding of individuals' lives and the events in which they participated, this annotated bibliography provides a broad overview and a sampling of the resources…

  1. Music Analysis: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Fink, Michael

    One hundred and forty citations comprise this annotated bibliography of books, articles, and selected dissertations that encompass trends in music theory and k-16 music education since the late 19th century. Special emphasis is upon writings since the 1950's. During earlier development, music analysts concentrated upon the elements of music (i.e.,…

  2. Teacher Aides; An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Marin County Public Schools, Corte Madera, CA.

    This annotated bibliography lists 40 items, published between 1966 and 1971, that have to do with teacher aides. The listing is arranged alphabetically by author. In addition to the abstract and standard bibliographic information, addresses where the material can be purchased are often included. The items cited include handbooks, research studies,…

  3. Staff Differentiation. An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Marin County Superintendent of Schools, Corte Madera, CA.

    This annotated bibliography reviews selected literature focusing on the concept of staff differentiation. Included are 62 items (dated 1966-1970), along with a list of mailing addresses where copies of individual items can be obtained. Also a list of 31 staff differentiation projects receiving financial assistance from the U.S. Office of Education…

  4. Rural Education: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Massey, Sara

    The 120-item annotated bibliography was compiled to facilitate the development of a recently approved course entitled "Topics in Rural Education" at the University of Maine at Machias. Although the dates range from 1964 to 1982, most of the materials were prepared in the 1970s and 1980s. The interrelatedness of the issues makes categorization…

  5. Annotated Selected Puerto Rican Bibliography.

    ERIC Educational Resources Information Center

    Bravo, Enrique R., Comp.

    This work represents an effort on the part of The Urban Center to come one step closer to the realization of its goal to further the growth of ethnic studies. After extensive consultation with educationists from within and without the Puerto Rican community, it was decided that an annotated bilingual bibliography should be published to assist and…

  6. Vietnamese Amerasians: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Johnson, Mark C.; And Others

    This annotated bibliography on Vietnamese Amerasians includes primary and secondary sources as well as reviews of three documentary films. Sources were selected in order to provide an overview of the historical and political context of Amerasian resettlement and a review of the scant available research on coping and adaptation with this…

  7. Vietnamese Amerasians: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Johnson, Mark C.; And Others

    This annotated bibliography on Vietnamese Amerasians includes primary and secondary sources as well as reviews of three documentary films. Sources were selected in order to provide an overview of the historical and political context of Amerasian resettlement and a review of the scant available research on coping and adaptation with this…

  8. Workforce Reductions. An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Hickok, Thomas A.; Hickok, Thomas A.

    This report, which is based on a review of practitioner-oriented sources and scholarly journals, uses a three-part framework to organize annotated bibliographies that, together, list a total of 104 sources that provide the following three perspectives on work force reduction issues: organizational, organizational-individual relationship, and…

  9. Aging Awareness: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Grant, Rugh; And Others

    This annotated bibliography cites books and articles on aging. The bibliography was compiled by a resource team who are helping teachers and elderly volunteers create classroom environments in which the strengths and uniqueness of these volunteers are recognized. The books in the first section "Aging in Society" describe the problems, aspirations,…

  10. Annotated Selected Puerto Rican Bibliography.

    ERIC Educational Resources Information Center

    Bravo, Enrique R., Comp.

    This work represents an effort on the part of The Urban Center to come one step closer to the realization of its goal to further the growth of ethnic studies. After extensive consultation with educationists from within and without the Puerto Rican community, it was decided that an annotated bilingual bibliography should be published to assist and…

  11. Infant Feeding: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Crowhurst, Christine Marie, Comp.; Kumer, Bonnie Lee, Comp.

    Intended for parents, health professionals and allied health workers, and others involved in caring for infants and young children, this annotated bibliography brings together in one selective listing a review of over 700 current publications related to infant feeding. Reflecting current knowledge in infant feeding, the bibliography has as its…

  12. Appalachian Women. An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Hamm, Mary Margo

    This bibliography compiles annotations of 178 books, journal articles, ERIC documents, and dissertations on Appalachian women and their social, cultural, and economic environment. Entries were published 1966-93 and are listed in the following categories: (1) authors and literary criticism; (2) bibliographies and resource guides; (3) economics,…

  13. Teacher Evaluation: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    McKenna, Bernard H.; And Others

    In his introduction to the 86-item annotated bibliography by Mueller and Poliakoff, McKenna discusses his views on teacher evaluation and his impressions of the documents cited. He observes, in part, that the current concern is with the process of evaluation and that most researchers continue to believe that student achievement is the most…

  14. Annotated Bibliography, Grades K-6.

    ERIC Educational Resources Information Center

    Massachusetts Dept. of Education, Boston. Bureau of Nutrition Education and School Food Services.

    This annotated bibliography on nutrition is for the use of teachers at the elementary grade level. It contains a list of books suitable for reading about nutrition and foods for pupils from kindergarten through the sixth grade. Films and audiovisual presentations for classroom use are also listed. The names and addresses from which these materials…

  15. ANNOTATED BIBLIOGRAPHY OF GEOLOGICAL EDUCATION.

    ERIC Educational Resources Information Center

    BERG, J. ROBERT; AND OTHERS

    ARTICLES ABOUT GEOLOGICAL EDUCATION WRITTEN DURING THE PERIOD 1919-62 ARE INCLUDED IN THIS ANNOTATED BIBLIOGRAPHY. RECOMMENDATIONS OF INDIVIDUAL EDUCATORS AND PROFESSIONAL GROUPS FOR THE UNDERGRADUATE AND GRADUATE PREPARATION OF GEOLOGISTS ARE CONTAINED IN MOST OF THE ITEMS. THE ARTICLES WERE ORIGINALLY PUBLISHED IN PROFESSIONAL JOURNALS OR…

  16. Statistical methods for handling unwanted variation in metabolomics data.

    PubMed

    De Livera, Alysha M; Sysi-Aho, Marko; Jacob, Laurent; Gagnon-Bartsch, Johann A; Castillo, Sandra; Simpson, Julie A; Speed, Terence P

    2015-04-07

    Metabolomics experiments are inevitably subject to a component of unwanted variation, due to factors such as batch effects, long runs of samples, and confounding biological variation. Although the removal of this unwanted variation is a vital step in the analysis of metabolomics data, it is considered a gray area in which there is a recognized need to develop a better understanding of the procedures and statistical methods required to achieve statistically relevant optimal biological outcomes. In this paper, we discuss the causes of unwanted variation in metabolomics experiments, review commonly used metabolomics approaches for handling this unwanted variation, and present a statistical approach for the removal of unwanted variation to obtain normalized metabolomics data. The advantages and performance of the approach relative to several widely used metabolomics normalization approaches are illustrated through two metabolomics studies, and recommendations are provided for choosing and assessing the most suitable normalization method for a given metabolomics experiment. Software for the approach is made freely available.

  17. METABOLOMICS IN SMALL FISH TOXICOLOGY AND OTHER ENVIRONMENTAL APPLICATIONS

    EPA Science Inventory

    Although lagging behind applications targeted to human endpoints, metabolomics offers great potential in environmental applications, including ecotoxicology. Indeed, the advantages of metabolomics (relative to other 'omic techniques) may be more tangible in ecotoxicology because...

  18. NMR-based Metabolomics Applications in Biological and Environmental Science

    EPA Science Inventory

    As a complimentary tool to other omics platforms, metabolomics is increasingly being used bybiologists to study the dynamic response of biological systems (cells, tissues, or wholeorganisms) under diverse physiological or pathological conditions. Metabolomics deals with the quali...

  19. NMR-based Metabolomics Applications in Biological and Environmental Science

    EPA Science Inventory

    As a complimentary tool to other omics platforms, metabolomics is increasingly being used bybiologists to study the dynamic response of biological systems (cells, tissues, or wholeorganisms) under diverse physiological or pathological conditions. Metabolomics deals with the quali...

  20. METABOLOMICS IN SMALL FISH TOXICOLOGY AND OTHER ENVIRONMENTAL APPLICATIONS

    EPA Science Inventory

    Although lagging behind applications targeted to human endpoints, metabolomics offers great potential in environmental applications, including ecotoxicology. Indeed, the advantages of metabolomics (relative to other 'omic techniques) may be more tangible in ecotoxicology because...

  1. Systems Theory and Communication. Annotated Bibliography.

    ERIC Educational Resources Information Center

    Covington, William G., Jr.

    This annotated bibliography presents annotations of 31 books and journal articles dealing with systems theory and its relation to organizational communication, marketing, information theory, and cybernetics. Materials were published between 1963 and 1992 and are listed alphabetically by author. (RS)

  2. Next Generation Models for Storage and Representation of Microbial Biological Annotation

    SciTech Connect

    Quest, Daniel J; Land, Miriam L; Brettin, Thomas S; Cottingham, Robert W

    2010-01-01

    Background Traditional genome annotation systems were developed in a very different computing era, one where the World Wide Web was just emerging. Consequently, these systems are built as centralized black boxes focused on generating high quality annotation submissions to GenBank/EMBL supported by expert manual curation. The exponential growth of sequence data drives a growing need for increasingly higher quality and automatically generated annotation. Typical annotation pipelines utilize traditional database technologies, clustered computing resources, Perl, C, and UNIX file systems to process raw sequence data, identify genes, and predict and categorize gene function. These technologies tightly couple the annotation software system to hardware and third party software (e.g. relational database systems and schemas). This makes annotation systems hard to reproduce, inflexible to modification over time, difficult to assess, difficult to partition across multiple geographic sites, and difficult to understand for those who are not domain experts. These systems are not readily open to scrutiny and therefore not scientifically tractable. The advent of Semantic Web standards such as Resource Description Framework (RDF) and OWL Web Ontology Language (OWL) enables us to construct systems that address these challenges in a new comprehensive way. Results Here, we develop a framework for linking traditional data to OWL-based ontologies in genome annotation. We show how data standards can decouple hardware and third party software tools from annotation pipelines, thereby making annotation pipelines easier to reproduce and assess. An illustrative example shows how TURTLE (Terse RDF Triple Language) can be used as a human readable, but also semantically-aware, equivalent to GenBank/EMBL files. Conclusions The power of this approach lies in its ability to assemble annotation data from multiple databases across multiple locations into a representation that is understandable to

  3. Dynamic metabolome profiling reveals significant metabolic changes during grain development of bread wheat (Triticum aestivum L.).

    PubMed

    Zhen, Shoumin; Dong, Kun; Deng, Xiong; Zhou, Jiaxing; Xu, Xuexin; Han, Caixia; Zhang, Wenying; Xu, Yanhao; Wang, Zhimin; Yan, Yueming

    2016-08-01

    Metabolites in wheat grains greatly influence nutritional values. Wheat provides proteins, minerals, B-group vitamins and dietary fiber to humans. These metabolites are important to human health. However, the metabolome of the grain during the development of bread wheat has not been studied so far. In this work the first dynamic metabolome of the developing grain of the elite Chinese bread wheat cultivar Zhongmai 175 was analyzed, using non-targeted gas chromatography/mass spectrometry (GC/MS) for metabolite profiling. In total, 74 metabolites were identified over the grain developmental stages. Metabolite-metabolite correlation analysis revealed that the metabolism of amino acids, carbohydrates, organic acids, amines and lipids was interrelated. An integrated metabolic map revealed a distinct regulatory profile. The results provide information that can be used by metabolic engineers and molecular breeders to improve wheat grain quality. The present metabolome approach identified dynamic changes in metabolite levels, and correlations among such levels, in developing seeds. The comprehensive metabolic map may be useful when breeding programs seek to improve grain quality. The work highlights the utility of GC/MS-based metabolomics, in conjunction with univariate and multivariate data analysis, when it is sought to understand metabolic changes in developing seeds. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

  4. Metabolomic unveiling of a diverse range of green tea (Camellia sinensis) metabolites dependent on geography.

    PubMed

    Lee, Jang-Eun; Lee, Bum-Jin; Chung, Jin-Oh; Kim, Hak-Nam; Kim, Eun-Hee; Jung, Sungheuk; Lee, Hyosang; Lee, Sang-Jun; Hong, Young-Shick

    2015-05-01

    Numerous factors such as geographical origin, cultivar, climate, cultural practices, and manufacturing processes influence the chemical compositions of tea, in the same way as growing conditions and grape variety affect wine quality. However, the relationships between these factors and tea chemical compositions are not well understood. In this study, a new approach for non-targeted or global analysis, i.e., metabolomics, which is highly reproducible and statistically effective in analysing a diverse range of compounds, was used to better understand the metabolome of Camellia sinensis and determine the influence of environmental factors, including geography, climate, and cultural practices, on tea-making. We found a strong correlation between environmental factors and the metabolome of green, white, and oolong teas from China, Japan, and South Korea. In particular, multivariate statistical analysis revealed strong inter-country and inter-city relationships in the levels of theanine and catechin derivatives found in green and white teas. This information might be useful for assessing tea quality or producing distinct tea products across different locations, and highlights simultaneous identification of diverse tea metabolites through an NMR-based metabolomics approach.

  5. Metabolomics data normalization with EigenMS.

    PubMed

    Karpievitch, Yuliya V; Nikolic, Sonja B; Wilson, Richard; Sharman, James E; Edwards, Lindsay M

    2014-01-01

    Liquid chromatography mass spectrometry has become one of the analytical platforms of choice for metabolomics studies. However, LC-MS metabolomics data can suffer from the effects of various systematic biases. These include batch effects, day-to-day variations in instrument performance, signal intensity loss due to time-dependent effects of the LC column performance, accumulation of contaminants in the MS ion source and MS sensitivity among others. In this study we aimed to test a singular value decomposition-based method, called EigenMS, for normalization of metabolomics data. We analyzed a clinical human dataset where LC-MS serum metabolomics data and physiological measurements were collected from thirty nine healthy subjects and forty with type 2 diabetes and applied EigenMS to detect and correct for any systematic bias. EigenMS works in several stages. First, EigenMS preserves the treatment group differences in the metabolomics data by estimating treatment effects with an ANOVA model (multiple fixed effects can be estimated). Singular value decomposition of the residuals matrix is then used to determine bias trends in the data. The number of bias trends is then estimated via a permutation test and the effects of the bias trends are eliminated. EigenMS removed bias of unknown complexity from the LC-MS metabolomics data, allowing for increased sensitivity in differential analysis. Moreover, normalized samples better correlated with both other normalized samples and corresponding physiological data, such as blood glucose level, glycated haemoglobin, exercise central augmentation pressure normalized to heart rate of 75, and total cholesterol. We were able to report 2578 discriminatory metabolite peaks in the normalized data (p<0.05) as compared to only 1840 metabolite signals in the raw data. Our results support the use of singular value decomposition-based normalization for metabolomics data.

  6. THE METABOLOMIC WINDOW INTO HEPATOBILIARY DISEASE

    PubMed Central

    Beyoğlu, Diren; Idle, Jeffrey R.

    2014-01-01

    Summary The emergent discipline of metabolomics has attracted considerable research effort in hepatology. Here we review the metabolomic data for nonalcoholic fatty liver disease (NAFLD), nonalcoholic steatohepatitis (NASH), cirrhosis, hepatocellular carcinoma (HCC), cholangiocarcinoma (CCA), alcoholic liver disease (ALD), hepatitis B and C, cholecystitis, cholestasis, liver transplantation and acute hepatotoxicity in animal models. A metabolomic window has permitted a view into the changing biochemistry occurring in the transitional phases between a healthy liver and hepatocellular carcinoma or cholangiocarcinoma. Whether provoked by obesity and diabetes, alcohol use or oncogenic viruses, the liver develops a core metabolomic phenotype (CMP) that involves dysregulation of bile acid and phospholipid homeostasis. The CMP commences at the transition between the healthy liver (Phase 0) and NAFLD/NASH, ALD or viral hepatitis (Phase 1). This CMP is maintained in the presence or absence of cirrhosis (Phase 2) and whether or not either HCC or CCA (Phase 3) develop. Inflammatory signalling in the liver triggers the appearance of the CMP. Many other metabolomic markers distinguish between Phases 0, 1, 2 and 3. A metabolic remodelling in HCC has been described but metabolomic data from all four Phases demonstrate that the Warburg shift from mitochondrial respiration to cytosolic glycolysis foreshadows HCC and may occur as early as Phase 1. The metabolic remodelling also involves an upregulation of fatty acid β-oxidation, also beginning in Phase 1. The storage of triglycerides in fatty liver provides high energy-yielding substrates for Phases 2 and 3 of liver pathology. The metabolomic window into hepatobiliary disease sheds new light on the systems pathology of the liver. PMID:23714158

  7. Annotation and Classification of Argumentative Writing Revisions

    ERIC Educational Resources Information Center

    Zhang, Fan; Litman, Diane

    2015-01-01

    This paper explores the annotation and classification of students' revision behaviors in argumentative writing. A sentence-level revision schema is proposed to capture why and how students make revisions. Based on the proposed schema, a small corpus of student essays and revisions was annotated. Studies show that manual annotation is reliable with…

  8. Annotation and Classification of Argumentative Writing Revisions

    ERIC Educational Resources Information Center

    Zhang, Fan; Litman, Diane

    2015-01-01

    This paper explores the annotation and classification of students' revision behaviors in argumentative writing. A sentence-level revision schema is proposed to capture why and how students make revisions. Based on the proposed schema, a small corpus of student essays and revisions was annotated. Studies show that manual annotation is reliable with…

  9. Genome re-annotation: a wiki solution?

    PubMed Central

    Salzberg, Steven L

    2007-01-01

    The annotation of most genomes becomes outdated over time, owing in part to our ever-improving knowledge of genomes and in part to improvements in bioinformatics software. Unfortunately, annotation is rarely if ever updated and resources to support routine reannotation are scarce. Wiki software, which would allow many scientists to edit each genome's annotation, offers one possible solution. PMID:17274839

  10. Loss-of-function variants influence the human serum metabolome

    PubMed Central

    Yu, Bing; Li, Alexander H.; Metcalf, Ginger A.; Muzny, Donna M.; Morrison, Alanna C.; White, Simon; Mosley, Thomas H.; Gibbs, Richard A.; Boerwinkle, Eric

    2016-01-01

    The metabolome is a collection of small molecules resulting from multiple cellular and biological processes that can act as biomarkers of disease, and African-Americans exhibit high levels of genetic diversity. Exome sequencing of a sample of deeply phenotyped African-Americans allowed us to analyze the effects of annotated loss-of-function (LoF) mutations on 308 serum metabolites measured by untargeted liquid and gas chromatography coupled with mass spectrometry. In an independent sample, we identified and replicated four genes harboring six LoF mutations that significantly affected five metabolites. These sites were related to a 19 to 45% difference in geometric mean metabolite levels, with an average effect size of 25%. We show that some of the affected metabolites are risk predictors or diagnostic biomarkers of disease and, using the principle of Mendelian randomization, are in the causal pathway of disease. For example, LoF mutations in SLCO1B1 elevate the levels of hexadecanedioate, a fatty acid significantly associated with increased blood pressure levels and risk of incident heart failure in both African-Americans and an independent sample of European-Americans. We show that SLCO1B1 LoF mutations significantly increase the risk of incident heart failure, thus implicating the metabolite in the causal pathway of disease. These results reveal new avenues into gene function and the understanding of disease etiology by integrating -omic technologies into a deeply phenotyped population study. PMID:27602404

  11. Psychosocial Stress and Ovarian Cancer Risk: Metabolomics and Perceived Stress

    DTIC Science & Technology

    2014-10-01

    AWARD NUMBER: W81XWH-13-1-0493 TITLE: Psychosocial Stress and Ovarian Cancer Risk: Metabolomics and...SUBTITLE Psychosocial Stress and Ovarian Cancer Risk: Metabolomics and Perceived Stress 5a. CONTRACT NUMBER Perceived Stress...SUBJECT TERMS ovarian cancer, psychosocial stress, depression, anxiety, social support, metabolomics 16. SECURITY CLASSIFICATION OF: 17. LIMITATION

  12. Plant metabolomics: from holistic data to relevant biomarkers.

    PubMed

    Wolfender, Jean-Luc; Rudaz, Serge; Choi, Young Hae; Kim, Hye Kyong

    2013-01-01

    Metabolomics is playing an increasingly important role in plant science. It aims at the comprehensive analysis of the plant metabolome which consists both of primary and secondary metabolites. The goal of metabolomics is ultimately to identify and quantify this wide array of small molecules in biological samples. This new science is included in several systems biology approaches and is based primarily on the unbiased acquisition of mass spectrometric (MS) or nuclear magnetic resonance (NMR) data from carefully selected samples. This approach provides the most ''functional'' information of the 'omics' technologies of a given organism since metabolites are the end products of the cellular regulatory processes. The application of state-of-the-art data mining, that includes various untargeted and targeted multivariate data analysis methods, to the vast amount of data generated by this data-driven approach leads to sample classification and the identification of relevant biomarkers. The biological areas that have been successfully studied by this holistic approach include global metabolite composition assessment, mutant and phenotype characterisation, taxonomy, developmental processes, stress response, interaction with the environment, quality control assessment, lead finding and mode of action of botanicals. This review summarises the main MS- and NMR-based approaches that are used to perform these studies and discusses the potential and current limitations of the various methods. The intent is not to provide an exhaustive overview of the field, which has grown considerably over the past decade, but to summarise the main strategies that are used and to discuss the potential and limitations of the different approaches as well as future trends.

  13. Smoke Engulfs Singapore [annotated

    NASA Image and Video Library

    2017-09-28

    On June 19, 2013, NASA’s Aqua satellite captured a striking image of smoke billowing from illegal wildfires on the Indonesian island of Sumatra. The smoke blew east toward southern Malaysia and Singapore, and news media reported that thick clouds of haze had descended on Singapore, pushing pollution levels to record levels. Singapore’s primary measure of pollution, the Pollutant Standards Index (PSI)—a uniform measure of key pollutants similar to the Air Quality Index (AQI) used by the U.S. Environmental Protection Agency—spiked to 371 on the afternoon of June 20, 2013, the highest level ever recorded. The previous record occurred in 1997, when the index hit 226. Health experts consider any level above 300 to be “hazardous” to human health. Levels above 200 are considered “very unhealthy.” The image above was captured by the Moderate Resolution Imaging Spectroradiometer (MODIS), an instrument that observes the entire surface of Earth’s every 1 to 2 days. The image was captured during the afternoon at 6:30 UTC (2:30 p.m. local time). Though local laws prohibit it, farmers in Sumatra often burn forests during the dry season to prepare soil for new crops. The BBC reported that Singapore’s Prime Minister Lee Hsien Loong warned that the haze could “easily last for several weeks and quite possibly longer until the dry season ends in Sumatra.” NASA image by Jeff Schmaltz, LANCE/EOSDIS Rapid Response. Caption by Adam Voiland. Credit: NASA Earth Observatory Instrument: Aqua - MODIS NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

  14. Dictionary-driven protein annotation

    PubMed Central

    Rigoutsos, Isidore; Huynh, Tien; Floratos, Aris; Parida, Laxmi; Platt, Daniel

    2002-01-01

    Computational methods seeking to automatically determine the properties (functional, structural, physicochemical, etc.) of a protein directly from the sequence have long been the focus of numerous research groups. With the advent of advanced sequencing methods and systems, the number of amino acid sequences that are being deposited in the public databases has been increasing steadily. This has in turn generated a renewed demand for automated approaches that can annotate individual sequences and complete genomes quickly, exhaustively and objectively. In this paper, we present one such approach that is centered around and exploits the Bio-Dictionary, a collection of amino acid patterns that completely covers the natural sequence space and can capture functional and structural signals that have been reused during evolution, within and across protein families. Our annotation approach also makes use of a weighted, position-specific scoring scheme that is unaffected by the over-representation of well-conserved proteins and protein fragments in the databases used. For a given query sequence, the method permits one to determine, in a single pass, the following: local and global similarities between the query and any protein already present in a public database; the likeness of the query to all available archaeal/bacterial/eukaryotic/viral sequences in the database as a function of amino acid position within the query; the character of secondary structure of the query as a function of amino acid position within the query; the cytoplasmic, transmembrane or extracellular behavior of the query; the nature and position of binding domains, active sites, post-translationally modified sites, signal peptides, etc. In terms of performance, the proposed method is exhaustive, objective and allows for the rapid annotation of individual sequences and full genomes. Annotation examples are presented and discussed in Results, including individual queries and complete genomes that were

  15. Dictionary-driven protein annotation.

    PubMed

    Rigoutsos, Isidore; Huynh, Tien; Floratos, Aris; Parida, Laxmi; Platt, Daniel

    2002-09-01

    Computational methods seeking to automatically determine the properties (functional, structural, physicochemical, etc.) of a protein directly from the sequence have long been the focus of numerous research groups. With the advent of advanced sequencing methods and systems, the number of amino acid sequences that are being deposited in the public databases has been increasing steadily. This has in turn generated a renewed demand for automated approaches that can annotate individual sequences and complete genomes quickly, exhaustively and objectively. In this paper, we present one such approach that is centered around and exploits the Bio-Dictionary, a collection of amino acid patterns that completely covers the natural sequence space and can capture functional and structural signals that have been reused during evolution, within and across protein families. Our annotation approach also makes use of a weighted, position-specific scoring scheme that is unaffected by the over-representation of well-conserved proteins and protein fragments in the databases used. For a given query sequence, the method permits one to determine, in a single pass, the following: local and global similarities between the query and any protein already present in a public database; the likeness of the query to all available archaeal/ bacterial/eukaryotic/viral sequences in the database as a function of amino acid position within the query; the character of secondary structure of the query as a function of amino acid position within the query; the cytoplasmic, transmembrane or extracellular behavior of the query; the nature and position of binding domains, active sites, post-translationally modified sites, signal peptides, etc. In terms of performance, the proposed method is exhaustive, objective and allows for the rapid annotation of individual sequences and full genomes. Annotation examples are presented and discussed in Results, including individual queries and complete genomes that were

  16. Fatty acid and metabolomic profiling approaches differentiate heterotrophic and mixotrophic culture conditions in a microalgal food supplement 'Euglena'.

    PubMed

    Zeng, Min; Hao, Wenlong; Zou, Yongdong; Shi, Mengliang; Jiang, Yongguang; Xiao, Peng; Lei, Anping; Hu, Zhangli; Zhang, Weiwen; Zhao, Liqing; Wang, Jiangxin

    2016-06-02

    Microalgae have been recognized as a good food source of natural biologically active ingredients. Among them, the green microalga Euglena is a very promising food and nutritional supplements, providing high value-added poly-unsaturated fatty acids, paramylon and proteins. Different culture conditions could affect the chemical composition and food quality of microalgal cells. However, little information is available for distinguishing the different cellular changes especially the active ingredients including poly-saturated fatty acids and other metabolites under different culture conditions, such as light and dark. In this study, together with fatty acid profiling, we applied a gas chromatography-mass spectrometry (GC-MS)-based metabolomics to differentiate hetrotrophic and mixotrophic culture conditions. This study suggests metabolomics can shed light on understanding metabolomic changes under different culture conditions and provides a theoretical basis for industrial applications of microalgae, as food with better high-quality active ingredients.

  17. Metabolomics: a new era in cardiology?

    PubMed

    Mercuro, Giuseppe; Bassareo, Pier P; Deidda, Martino; Cadeddu, Christian; Barberini, Luigi; Atzori, Luigi

    2011-11-01

    The metabolome represents the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end-products of cellular processes. Metabolomics is the systematic study of small-molecule metabolite profiles that specific cellular processes leave behind. RNA messenger gene expression data and proteomic analyses do not tell the whole story of what might be happening in a cell. Metabolic profiling, in turn, amplifies changes both in the proteome and the genome, and represents a more accurate approximation to the phenotype of an organism in health and disease. In this article, we have provided a description of metabolomics, in the presence of other, more familiar 'omics' disciplines, such as genomics and proteomics. In addition, we have reviewed the current rationale for metabolomics in cardiology, its basic methodology and the data actually available in human studies in this discipline. The discussed topics highlight the importance of being able to use the metabolomics information in order to understand disease mechanisms from a systems biology perspective as a noninvasive approach to diagnose, grade and treat cardiovascular diseases.

  18. Systematic Applications of Metabolomics in Metabolic Engineering

    PubMed Central

    Dromms, Robert A.; Styczynski, Mark P.

    2012-01-01

    The goals of metabolic engineering are well-served by the biological information provided by metabolomics: information on how the cell is currently using its biochemical resources is perhaps one of the best ways to inform strategies to engineer a cell to produce a target compound. Using the analysis of extracellular or intracellular levels of the target compound (or a few closely related molecules) to drive metabolic engineering is quite common. However, there is surprisingly little systematic use of metabolomics datasets, which simultaneously measure hundreds of metabolites rather than just a few, for that same purpose. Here, we review the most common systematic approaches to integrating metabolite data with metabolic engineering, with emphasis on existing efforts to use whole-metabolome datasets. We then review some of the most common approaches for computational modeling of cell-wide metabolism, including constraint-based models, and discuss current computational approaches that explicitly use metabolomics data. We conclude with discussion of the broader potential of computational approaches that systematically use metabolomics data to drive metabolic engineering. PMID:24957776

  19. Metabolomics: Applications and Promise in Mycobacterial Disease

    PubMed Central

    Banoei, Mohammad Mehdi; Winston, Brent W.; Schraufnagel, Dean E.

    2015-01-01

    Until recently, the study of mycobacterial diseases was trapped in culture-based technology that is more than a century old. The use of nucleic acid amplification is changing this, and powerful new technologies are on the horizon. Metabolomics, which is the study of sets of metabolites of both the bacteria and host, is being used to clarify mechanisms of disease, and can identify changes leading to better diagnosis, treatment, and prognostication of mycobacterial diseases. Metabolomic profiles are arrays of biochemical products of genes in their environment. These complex patterns are biomarkers that can allow a more complete understanding of cell function, dysfunction, and perturbation than genomics or proteomics. Metabolomics could herald sweeping advances in personalized medicine and clinical trial design, but the challenges in metabolomics are also great. Measured metabolite concentrations vary with the timing within a condition, the intrinsic biology, the instruments, and the sample preparation. Metabolism profoundly changes with age, sex, variations in gut microbial flora, and lifestyle. Validation of biomarkers is complicated by measurement accuracy, selectivity, linearity, reproducibility, robustness, and limits of detection. The statistical challenges include analysis, interpretation, and description of the vast amount of data generated. Despite these drawbacks, metabolomics provides great opportunity and the potential to understand and manage mycobacterial diseases. PMID:26196272

  20. Applying Metabolomics to differentiate amphibian responses ...

    EPA Pesticide Factsheets

    Introduction/Objectives/Methods One of the biggest challenges in ecological risk assessment is determining the impact of multiple stressors on individual organisms and populations in ‘real world’ scenarios. Emerging ‘omic technologies, notably, metabolomics, provides an opportunity to address the uncertainties surrounding ecological risk assessment of multiple stressors. The objective of this study was to use a metabolomics biomarker approach to investigate the effect of multiple stressors on amphibian metamorphs. To this end, metamorphs of Rana pipiens (northern leopard frogs) were exposed to the insecticide Carbaryl (0.32 μg/L), a conspecific predator alarm call (Lithobates catesbeianus), Carbaryl and the predator alarm call, and a control with no stressor. In addition to metabolomic fingerprinting, we measured corticosterone levels in each treatment to assess general stress response. We analyzed relative abundances of endogenous metabolites collected in liver tissue with gas chromatography coupled with mass spectrometry. Support vector machine (SVM) methods with recursive feature elimination (RFE) were applied to rank the metabolomic profiles produced. Results/Conclusions SVM-RFE of the acquired metabolomic spectra demonstrated 85-96% classification accuracy among control and all treatment groups when using the top 75 ranked retention time bins. Biochemical fluxes observed in the groups exposed to carbaryl, predation threat, and the combined treatmen

  1. Metabolomics: Developing a chemical specific fingerprint

    USGS Publications Warehouse

    Putnam, Joel G.

    2016-01-01

    We combine cell assays and metabolomics to create a powerful tool, which emerges to elevate the identification of new control chemicals. We combined the use of bigheaded carp fry cell line with metabolite profiling to describe the dose response to thiram. Thiram is a registered pesticide commonly used as a fungicide in the field or as a seed protectant and is known to be toxic to fish. Seven concentrations of thiram were used to dose bighead carp fry cells and silver carp fry cells. We identified 700 metabolomic markers and 41 of those markers exhibited a dose response to thiram in the bighead carp fry cells. We identified 1590 metabolomic markers with 205 of those markers exhibited a dose response to thiram in the silver carp fry cells. When the metabolites of both cell lines are compared using volcano plots, 16 metabolomic markers were identified as significant. A smaller subset of metabolites indicate that a thiram specific metabolomic fingerprint exists that is not species specific, but instead toxin specific. Application of toxin fingerprints (toxin specific but species independent metabolites) can be used to address the cause of ecological significant events, such as mass fish kills.

  2. Clinical application of metabolomics in neonatology.

    PubMed

    Fanos, Vassilios; Antonucci, Roberto; Barberini, Luigi; Noto, Antonio; Atzori, Luigi

    2012-04-01

    The youngest and more rapidly increasing "omic" discipline, called metabolomics, is the process of describing the phenotype of a cell, tissue or organism through the full complement of metabolites present. Metabolomics measure global sets of low molecular weight metabolites (including amino acids, organic acids, sugars, fatty acids, lipids, steroids, small peptides, vitamins, etc.), thus providing a "snapshot" of the metabolic status of a cell, tissue or organism in relation to genetic variations or external stimuli. The use of metabolomics appears to be a promising tool in neonatology. The management of sick newborns might improve if more information on perinatal/neonatal maturational processes and their metabolic background were available. Urine ("a window on the organism") is a biofluid particularly suitable for metabolomic analysis in neonatology because it may be collected by using simple, noninvasive techniques and because it may provide valuable diagnostic information. In this review, the authors report the few literature data on neonatal metabolomics, including their personal experience, in the following fields: intrauterine growth restriction, perinatal transition, asphyxia, brain injury and hypothermia, maternal milk evaluation, postnatal maturation, bronchiolitis, sepsis, patent ductus arteriosus, respiratory distress syndrome, nephrouropathies, metabolic diseases, antibiotic treatment, perinatal programming and long-term outcome in extremely low birth-weight infants.

  3. Metabolomics: towards understanding traditional Chinese medicine.

    PubMed

    Zhang, Aihua; Sun, Hui; Wang, Zhigang; Sun, Wenjun; Wang, Ping; Wang, Xijun

    2010-12-01

    Metabolomics represent a global understanding of metabolite complement of integrated living systems and dynamic responses to the changes of both endogenous and exogenous factors and has many potential applications and advantages for the research of complex systems. As a systemic approach, metabolomics adopts a "top-down" strategy to reflect the function of organisms from the end products of the metabolic network and to understand metabolic changes of a complete system caused by interventions in a holistic context. This property agrees with the holistic thinking of Traditional Chinese Medicine (TCM), a complex medical science, suggesting that metabolomics has the potential to impact our understanding of the theory behind the evidence-based Chinese medicine. Consequently, the development of robust metabolomic platforms will greatly facilitate, for example, the understanding of the action mechanisms of TCM formulae and the analysis of Chinese herbal (CHM) and mineral medicine, acupuncture, and Chinese medicine syndromes. This review summarizes some of the applications of metabolomics in special TCM issues with an emphasis on metabolic biomarker discovery.

  4. Basics of mass spectrometry based metabolomics.

    PubMed

    Courant, Frédérique; Antignac, Jean-Philippe; Dervilly-Pinel, Gaud; Le Bizec, Bruno

    2014-11-01

    The emerging field of metabolomics, aiming to characterize small molecule metabolites present in biological systems, promises immense potential for different areas such as medicine, environmental sciences, agronomy, etc. The purpose of this article is to guide the reader through the history of the field, then through the main steps of the metabolomics workflow, from study design to structure elucidation, and help the reader to understand the key phases of a metabolomics investigation and the rationale underlying the protocols and techniques used. This article is not intended to give standard operating procedures as several papers related to this topic were already provided, but is designed as a tutorial aiming to help beginners understand the concept and challenges of MS-based metabolomics. A real case example is taken from the literature to illustrate the application of the metabolomics approach in the field of doping analysis. Challenges and limitations of the approach are then discussed along with future directions in research to cope with these limitations. This tutorial is part of the International Proteomics Tutorial Programme (IPTP18).

  5. RysannMD: A biomedical semantic annotator balancing speed and accuracy.

    PubMed

    Cuzzola, John; Jovanović, Jelena; Bagheri, Ebrahim

    2017-07-01

    Recently, both researchers and practitioners have explored the possibility of semantically annotating large and continuously evolving collections of biomedical texts such as research papers, medical reports, and physician notes in order to enable their efficient and effective management and use in clinical practice or research laboratories. Such annotations can be automatically generated by biomedical semantic annotators - tools that are specifically designed for detecting and disambiguating biomedical concepts mentioned in text. The biomedical community has already presented several solid automated semantic annotators. However, the existing tools are either strong in their disambiguation capacity, i.e., the ability to identify the correct biomedical concept for a given piece of text among several candidate concepts, or they excel in their processing time, i.e., work very efficiently, but none of the semantic annotation tools reported in the literature has both of these qualities. In this paper, we present RysannMD (Ryerson Semantic Annotator for Medical Domain), a biomedical semantic annotation tool that strikes a balance between processing time and performance while disambiguating biomedical terms. In other words, RysannMD provides reasonable disambiguation performance when choosing the right sense for a biomedical term in a given context, and does that in a reasonable time. To examine how RysannMD stands with respect to the state of the art biomedical semantic annotators, we have conducted a series of experiments using standard benchmarking corpora, including both gold and silver standards, and four modern biomedical semantic annotators, namely cTAKES, MetaMap, NOBLE Coder, and Neji. The annotators were compared with respect to the quality of the produced annotations measured against gold and silver standards using precision, recall, and F1 measure and speed, i.e., processing time. In the experiments, RysannMD achieved the best median F1 measure across the

  6. Use of Annotations for Component and Framework Interoperability

    NASA Astrophysics Data System (ADS)

    David, O.; Lloyd, W.; Carlson, J.; Leavesley, G. H.; Geter, F.

    2009-12-01

    The popular programming languages Java and C# provide annotations, a form of meta-data construct. Software frameworks for web integration, web services, database access, and unit testing now take advantage of annotations to reduce the complexity of APIs and the quantity of integration code between the application and framework infrastructure. Adopting annotation features in frameworks has been observed to lead to cleaner and leaner application code. The USDA Object Modeling System (OMS) version 3.0 fully embraces the annotation approach and additionally defines a meta-data standard for components and models. In version 3.0 framework/model integration previously accomplished using API calls is now achieved using descriptive annotations. This enables the framework to provide additional functionality non-invasively such as implicit multithreading, and auto-documenting capabilities while achieving a significant reduction in the size of the model source code. Using a non-invasive methodology leads to models and modeling components with only minimal dependencies on the modeling framework. Since models and modeling components are not directly bound to framework by the use of specific APIs and/or data types they can more easily be reused both within the framework as well as outside of it. To study the effectiveness of an annotation based framework approach with other modeling frameworks, a framework-invasiveness study was conducted to evaluate the effects of framework design on model code quality. A monthly water balance model was implemented across several modeling frameworks and several software metrics were collected. The metrics selected were measures of non-invasive design methods for modeling frameworks from a software engineering perspective. It appears that the use of annotations positively impacts several software quality measures. In a next step, the PRMS model was implemented in OMS 3.0 and is currently being implemented for water supply forecasting in the

  7. The automatic annotation of bacterial genomes

    PubMed Central

    Richardson, Emily J.

    2013-01-01

    With the development of ultra-high-throughput technologies, the cost of sequencing bacterial genomes has been vastly reduced. As more genomes are sequenced, less time can be spent manually annotating those genomes, resulting in an increased reliance on automatic annotation pipelines. However, automatic pipelines can produce inaccurate genome annotation and their results often require manual curation. Here, we discuss the automatic and manual annotation of bacterial genomes, identify common problems introduced by the current genome annotation process and suggests potential solutions. PMID:22408191

  8. Automatic annotation of organellar genomes with DOGMA

    SciTech Connect

    Wyman, Stacia; Jansen, Robert K.; Boore, Jeffrey L.

    2004-06-01

    Dual Organellar GenoMe Annotator (DOGMA) automates the annotation of extra-nuclear organellar (chloroplast and animal mitochondrial) genomes. It is a web-based package that allows the use of comparative BLAST searches to identify and annotate genes in a genome. DOGMA presents a list of putative genes to the user in a graphical format for viewing and editing. Annotations are stored on our password-protected server. Complete annotations can be extracted for direct submission to GenBank. Furthermore, intergenic regions of specified length can be extracted, as well the nucleotide sequences and amino acid sequences of the genes.

  9. FunctionAnnotator, a versatile and efficient web tool for non-model organism annotation.

    PubMed

    Chen, Ting-Wen; Gan, Ruei-Chi; Fang, Yi-Kai; Chien, Kun-Yi; Liao, Wei-Chao; Chen, Chia-Chun; Wu, Timothy H; Chang, Ian Yi-Feng; Yang, Chi; Huang, Po-Jung; Yeh, Yuan-Ming; Chiu, Cheng-Hsun; Huang, Tzu-Wen; Tang, Petrus

    2017-09-05

    Along with the constant improvement in high-throughput sequencing technology, an increasing number of transcriptome sequencing projects are carried out in organisms without decoded genome information and even on environmental biological samples. To study the biological functions of novel transcripts, the very first task is to identify their potential functions. We present a web-based annotation tool, FunctionAnnotator, which offers comprehensive annotations, including GO term assignment, enzyme annotation, domain/motif identification and predictions for subcellular localization. To accelerate the annotation process, we have optimized the computation processes and used parallel computing for all annotation steps. Moreover, FunctionAnnotator is designed to be versatile, and it generates a variety of useful outputs for facilitating other analyses. Here, we demonstrate how FunctionAnnotator can be helpful in annotating non-model organisms. We further illustrate that FunctionAnnotator can estimate the taxonomic composition of environmental samples and assist in the identification of novel proteins by combining RNA-Seq data with proteomics technology. In summary, FunctionAnnotator can efficiently annotate transcriptomes and greatly benefits studies focusing on non-model organisms or metatranscriptomes. FunctionAnnotator, a comprehensive annotation web-service tool, is freely available online at: http://fa.cgu.edu.tw/ . This new web-based annotator will shed light on field studies involving organisms without a reference genome.

  10. Oncotator: cancer variant annotation tool.

    PubMed

    Ramos, Alex H; Lichtenstein, Lee; Gupta, Manaswi; Lawrence, Michael S; Pugh, Trevor J; Saksena, Gordon; Meyerson, Matthew; Getz, Gad

    2015-04-01

    Oncotator is a tool for annotating genomic point mutations and short nucleotide insertions/deletions (indels) with variant- and gene-centric information relevant to cancer researchers. This information is drawn from 14 different publicly available resources that have been pooled and indexed, and we provide an extensible framework to add additional data sources. Annotations linked to variants range from basic information, such as gene names and functional classification (e.g. missense), to cancer-specific data from resources such as the Catalogue of Somatic Mutations in Cancer (COSMIC), the Cancer Gene Census, and The Cancer Genome Atlas (TCGA). For local use, Oncotator is freely available as a python module hosted on Github (https://github.com/broadinstitute/oncotator). Furthermore, Oncotator is also available as a web service and web application at http://www.broadinstitute.org/oncotator/.

  11. iMet: A Network-Based Computational Tool To Assist in the Annotation of Metabolites from Tandem Mass Spectra.

    PubMed

    Aguilar-Mogas, Antoni; Sales-Pardo, Marta; Navarro, Miriam; Guimerà, Roger; Yanes, Oscar

    2017-03-21

    Structural annotation of metabolites relies mainly on tandem mass spectrometry (MS/MS) analysis. However, approximately 90% of the known metabolites reported in metabolomic databases do not have annotated spectral data from standards. This situation has fostered the development of computational tools that predict fragmentation patterns in silico and compare these to experimental MS/MS spectra. However, because such methods require the molecular structure of the detected compound to be available for the algorithm, the identification of novel metabolites in organisms relevant for biotechnological and medical applications remains a challenge. Here, we present iMet, a computational tool that facilitates structural annotation of metabolites not described in databases. iMet uses MS/MS spectra and the exact mass of an unknown metabolite to identify metabolites in a reference database that are structurally similar to the unknown metabolite. The algorithm also suggests the chemical transformation that converts the known metabolites into the unknown one. As a proxy for the structural annotation of novel metabolites, we tested 148 metabolites following a leave-one-out cross-validation procedure or by using MS/MS spectra experimentally obtained in our laboratory. We show that for 89% of the 148 metabolites at least one of the top four matches identified by iMet enables the proper annotation of the unknown metabolites. To further validate iMet, we tested 31 metabolites proposed in the 2012-16 CASMI challenges. iMet is freely available at http://imet.seeslab.net .

  12. Evaluating Hierarchical Structure in Music Annotations

    PubMed Central

    McFee, Brian; Nieto, Oriol; Farbood, Morwaread M.; Bello, Juan Pablo

    2017-01-01

    Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR), it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for “flat” descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement. PMID:28824514

  13. Evaluating Hierarchical Structure in Music Annotations.

    PubMed

    McFee, Brian; Nieto, Oriol; Farbood, Morwaread M; Bello, Juan Pablo

    2017-01-01

    Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR), it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for "flat" descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement.

  14. Sulfites and the wine metabolome.

    PubMed

    Roullier-Gall, Chloé; Hemmler, Daniel; Gonsior, Michael; Li, Yan; Nikolantonaki, Maria; Aron, Alissa; Coelho, Christian; Gougeon, Régis D; Schmitt-Kopplin, Philippe

    2017-12-15

    In a context of societal concern about food preservation, the reduction of sulfite input plays a major role in the wine industry. To improve the understanding of the chemistry involved in the SO2 protection, a series of bottle aged Chardonnay wines made from the same must, but with different concentrations of SO2 added at pressing were analyzed by ultrahigh resolution mass spectrometry (FT-ICR-MS) and excitation emission matrix fluorescence (EEMF). Metabolic fingerprints from FT-ICR-MS data could discriminate wines according to the added concentration to the must but they also revealed chemistry-related differences according to the type of stopper, providing a wine metabolomics picture of the impact of distinct stopping strategies. Spearman rank correlation was applied to link the statistically modeled EEMF components (parallel factor analysis (PARAFAC)) and the exact mass information from FT-ICR-MS, and thus revealing the extent of sulfur-containing compounds which could show some correlation with fluorescence fingerprints. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Metabolomic profiling of plant tissues.

    PubMed

    Rambla, José L; López-Gresa, M P; Bellés, J M; Granell, Antonio

    2015-01-01

    Metabolomics is a powerful discipline aimed at a comprehensive and global analysis of the metabolites present in a cell, tissue, or organism, and to which increasing attention has been paid in the last few years. Given the high diversity in physical and chemical properties of plant metabolites, not a single method is able to analyze them all.Here we describe two techniques for the profiling of two quite different groups of metabolites: polar and semi-polar secondary metabolites, including many of those involved in plant response to biotic and abiotic stress, and volatile compounds, which include those responsible of most of our perception of food flavor. According to these techniques, polar and semi-polar metabolites are extracted in methanol, separated by liquid chromatography (UPLC), and detected by a UV-VIS detector (PDA) and a time-of-flight (ToF) mass spectrometer. Volatile compounds, on the other hand, are extracted by headspace solid phase microextraction (HS-SPME), and separated and detected by gas chromatography coupled to mass spectrometry (GC-MS).

  16. The metabolomics of oxidative stress.

    PubMed

    Noctor, Graham; Lelarge-Trouverie, Caroline; Mhamdi, Amna

    2015-04-01

    Oxidative stress resulting from increased availability of reactive oxygen species (ROS) is a key component of many responses of plants to challenging environmental conditions. The consequences for plant metabolism are complex and manifold. We review data on small compounds involved in oxidative stress, including ROS themselves and antioxidants and redox buffers in the membrane and soluble phases, and we discuss the wider consequences for plant primary and secondary metabolism. While metabolomics has been exploited in many studies on stress, there have been relatively few non-targeted studies focused on how metabolite signatures respond specifically to oxidative stress. As part of the discussion, we present results and reanalyze published datasets on metabolite profiles in catalase-deficient plants, which can be considered to be model oxidative stress systems. We emphasize the roles of ROS-triggered changes in metabolites as potential oxidative signals, and discuss responses that might be useful as markers for oxidative stress. Particular attention is paid to lipid-derived compounds, the status of antioxidants and antioxidant breakdown products, altered metabolism of amino acids, and the roles of phytohormone pathways.

  17. New and vintage solutions to enhance the plasma metabolome coverage by LC-ESI-MS untargeted metabolomics: the not-so-simple process of method performance evaluation.

    PubMed

    Tulipani, Sara; Mora-Cubillos, Ximena; Jáuregui, Olga; Llorach, Rafael; García-Fuentes, Eduardo; Tinahones, Francisco J; Andres-Lacueva, Cristina

    2015-03-03

    Although LC-MS untargeted metabolomics continues to expand into exiting research domains, methodological issues have not been solved yet by the definition of unbiased, standardized and globally accepted analytical protocols. In the present study, the response of the plasma metabolome coverage to specific methodological choices of the sample preparation (two SPE technologies, three sample-to-solvent dilution ratios) and the LC-ESI-MS data acquisition steps of the metabolomics workflow (four RP columns, four elution solvent combinations, two solvent quality grades, postcolumn modification of the mobile phase) was investigated in a pragmatic and decision tree-like performance evaluation strategy. Quality control samples, reference plasma and human plasma from a real nutrimetabolomic study were used for intermethod comparisons. Uni- and multivariate data analysis approaches were independently applied. The highest method performance was obtained by combining the plasma hybrid extraction with the highest solvent proportion during sample preparation, the use of a RP column compatible with 100% aqueous polar phase (Atlantis T3), and the ESI enhancement by using UHPLC-MS purity grade methanol as both organic phase and postcolumn modifier. Results led to the following considerations: submit plasma samples to hybrid extraction for removal of interfering components to minimize the major sample-dependent matrix effects; avoid solvent evaporation following sample extraction if loss in detection and peak shape distortion of early eluting metabolites are not noticed; opt for a RP column for superior retention of highly polar species when analysis fractionation is not feasible; use ultrahigh quality grade solvents and "vintage" analytical tricks such as postcolumn organic enrichment of the mobile phase to enhance ESI efficiency. The final proposed protocol offers an example of how novel and old-fashioned analytical solutions may fruitfully cohabit in untargeted metabolomics

  18. Metabolomics in pediatric nephrology: Emerging concepts

    PubMed Central

    Hanna, Mina H; Brophy, Patrick D

    2014-01-01

    Metabolomics, the latest of the “omics” sciences, refers to the systematic study of metabolites and their changes in biological samples due to physiological stimuli and/or genetic modification. Because metabolites represent the downstream expression of genome, transcriptome and proteome, they can closely reflect the phenotype of an organism at a specific time. As an emerging field in analytical biochemistry; metabolomics has the potential to play a major role for monitoring real-time kidney function and detecting adverse renal events. Additionally, small molecule metabolites can provide mechanistic insights for novel biomarkers of kidney diseases, given the limitations of the current traditional markers. The clinical utility of metabolomics in the field of pediatric nephrology includes biomarker discovery, defining as yet unrecognized biologic therapeutic targets, linking of metabolites to relevant standard indices and clinical outcomes, and providing a window of opportunity to investigate the intricacies of environment/genetic interplay in specific disease states. PMID:25027575

  19. Metabolomics in pediatric nephrology: emerging concepts.

    PubMed

    Hanna, Mina H; Brophy, Patrick D

    2015-06-01

    Metabolomics, the latest of the "omics" sciences, refers to the systematic study of metabolites and their changes in biological samples due to physiological stimuli and/or genetic modification. Because metabolites represent the downstream expression of genome, transcriptome, and proteome, they can closely reflect the phenotype of an organism at a specific time. As an emerging field in analytical biochemistry, metabolomics has the potential to play a major role in monitoring real-time kidney function and detecting adverse renal events. Additionally, small molecule metabolites can provide mechanistic insights into novel biomarkers of kidney diseases, given the limitations of the current traditional markers. The clinical utility of metabolomics in the field of pediatric nephrology includes biomarker discovery, defining as yet unrecognized biological therapeutic targets, linking of metabolites to relevant standard indices and clinical outcomes, and providing a window of opportunity to investigate the intricacies of environment/genetic interplay in specific disease states.

  20. Metabolomics in rheumatic diseases: desperately seeking biomarkers.

    PubMed

    Guma, Monica; Tiziani, Stefano; Firestein, Gary S

    2016-05-01

    Metabolomics enables the profiling of large numbers of small molecules in cells, tissues and biological fluids. These molecules, which include amino acids, carbohydrates, lipids, nucleotides and their metabolites, can be detected quantitatively. Metabolomic methods, often focused on the information-rich analytical techniques of NMR spectroscopy and mass spectrometry, have potential for early diagnosis, monitoring therapy and defining disease pathogenesis in many therapeutic areas, including rheumatic diseases. By performing global metabolite profiling, also known as untargeted metabolomics, new discoveries linking cellular pathways to biological mechanisms are being revealed and are shaping our understanding of cell biology, physiology and medicine. These pathways can potentially be targeted to diagnose and treat patients with immune-mediated diseases.

  1. Metabolomics: Definitions and Significance in Systems Biology.

    PubMed

    Klassen, Aline; Faccio, Andréa Tedesco; Canuto, Gisele André Baptista; da Cruz, Pedro Luis Rocha; Ribeiro, Henrique Caracho; Tavares, Marina Franco Maggi; Sussulini, Alessandra

    2017-01-01

    Nowadays, there is a growing interest in deeply understanding biological mechanisms not only at the molecular level (biological components) but also the effects of an ongoing biological process in the organism as a whole (biological functionality), as established by the concept of systems biology. Within this context, metabolomics is one of the most powerful bioanalytical strategies that allow obtaining a picture of the metabolites of an organism in the course of a biological process, being considered as a phenotyping tool. Briefly, metabolomics approach consists in identifying and determining the set of metabolites (or specific metabolites) in biological samples (tissues, cells, fluids, or organisms) under normal conditions in comparison with altered states promoted by disease, drug treatment, dietary intervention, or environmental modulation. The aim of this chapter is to review the fundamentals and definitions used in the metabolomics field, as well as to emphasize its importance in systems biology and clinical studies.

  2. Metabolomics to Explore Impact of Dairy Intake.

    PubMed

    Zheng, Hong; Clausen, Morten R; Dalsgaard, Trine K; Bertram, Hanne C

    2015-06-17

    Dairy products are an important component in the Western diet and represent a valuable source of nutrients for humans. However, a reliable dairy intake assessment in nutrition research is crucial to correctly elucidate the link between dairy intake and human health. Metabolomics is considered a potential tool for assessment of dietary intake instead of traditional methods, such as food frequency questionnaires, food records, and 24-h recalls. Metabolomics has been successfully applied to discriminate between consumption of different dairy products under different experimental conditions. Moreover, potential metabolites related to dairy intake were identified, although these metabolites need to be further validated in other intervention studies before they can be used as valid biomarkers of dairy consumption. Therefore, this review provides an overview of metabolomics for assessment of dairy intake in order to better clarify the role of dairy products in human nutrition and health.

  3. Metabolomics, a Powerful Tool for Agricultural Research.

    PubMed

    Tian, He; Lam, Sin Man; Shui, Guanghou

    2016-11-17

    Metabolomics, which is based mainly on nuclear magnetic resonance (NMR), gas-chromatography (GC) or liquid-chromatography (LC) coupled to mass spectrometry (MS) analytical technologies to systematically acquire the qualitative and quantitative information of low-molecular-mass endogenous metabolites, provides a direct snapshot of the physiological condition in biological samples. As complements to transcriptomics and proteomics, it has played pivotal roles in agricultural and food science research. In this review, we discuss the capacities of NMR, GC/LC-MS in the acquisition of plant metabolome, and address the potential promise and diverse applications of metabolomics, particularly lipidomics, to investigate the responses of Arabidopsis thaliana, a primary plant model for agricultural research, to environmental stressors including heat, freezing, drought, and salinity.

  4. Metabolomics, a Powerful Tool for Agricultural Research

    PubMed Central

    Tian, He; Lam, Sin Man; Shui, Guanghou

    2016-01-01

    Metabolomics, which is based mainly on nuclear magnetic resonance (NMR), gas-chromatography (GC) or liquid-chromatography (LC) coupled to mass spectrometry (MS) analytical technologies to systematically acquire the qualitative and quantitative information of low-molecular-mass endogenous metabolites, provides a direct snapshot of the physiological condition in biological samples. As complements to transcriptomics and proteomics, it has played pivotal roles in agricultural and food science research. In this review, we discuss the capacities of NMR, GC/LC-MS in the acquisition of plant metabolome, and address the potential promise and diverse applications of metabolomics, particularly lipidomics, to investigate the responses of Arabidopsis thaliana, a primary plant model for agricultural research, to environmental stressors including heat, freezing, drought, and salinity. PMID:27869667

  5. Microbiome, Metabolome and Inflammatory Bowel Disease

    PubMed Central

    Ahmed, Ishfaq; Roy, Badal C.; Khan, Salman A.; Septer, Seth; Umar, Shahid

    2016-01-01

    Inflammatory Bowel Disease (IBD) is a multifactorial disorder that conceptually occurs as a result of altered immune responses to commensal and/or pathogenic gut microbes in individuals most susceptible to the disease. During Crohn’s Disease (CD) or Ulcerative Colitis (UC), two components of the human IBD, distinct stages define the disease onset, severity, progression and remission. Epigenetic, environmental (microbiome, metabolome) and nutritional factors are important in IBD pathogenesis. While the dysbiotic microbiota has been proposed to play a role in disease pathogenesis, the data on IBD and diet are still less convincing. Nonetheless, studies are ongoing to examine the effect of pre/probiotics and/or FODMAP reduced diets on both the gut microbiome and its metabolome in an effort to define the healthy diet in patients with IBD. Knowledge of a unique metabolomic fingerprint in IBD could be useful for diagnosis, treatment and detection of disease pathogenesis. PMID:27681914

  6. Metabolomic change precedes apple superficial scald symptoms.

    PubMed

    Rudell, David R; Mattheis, James P; Hertog, Maarten L A T M

    2009-09-23

    Untargeted metabolic profiling was employed to characterize metabolomic changes associated with 'Granny Smith' apple superficial scald development following 1-MCP or DPA treatment. Partial least-squares discriminant analyses were used to link metabolites with scald, postharvest treatments, and storage duration. Models revealed metabolomic differentiation between untreated controls and fruit treated with DPA or 1-MCP within 1 week following storage initiation. Metabolic divergence between controls and DPA-treated fruit after 4 weeks of storage preceded scald symptom development by 2 months. alpha-Farnesene oxidation products with known associations to scald, including conjugated trienols, 6-methyl-5-hepten-2-one, and 6-methyl-5-hepten-2-ol, were associated with presymptomatic as well as scalded control fruit. Likewise, a large group of putative triterpenoids with mass spectral features similar to those of ursolic acid and beta-sitosterol were associated with control fruit and scald. Results demonstrate that extensive metabolomic changes associated with scald precede actual symptom development.

  7. [Metabolomics analysis of taxadiene producing yeasts].

    PubMed

    Yan, Huifang; Ding, Mingzhu; Yuan, Yingjin

    2014-02-01

    In order to study the inherent difference among terpenes producing yeasts from the point of metabolomics, we selected taxadiene producing yeasts as the model system. The changes of cellular metabolites during fermentation log phase of artificial functional yeasts were determined using metabolomics methods. The results represented that compared to W303-1A as a blank control, the metabolites in glycolysis, tricarboxylic acid cycle (TCA) cycle and several amino acids were influenced. And due to the changes of metabolites, the growth of cells was inhibited to a certain extent. Among the metabolites identified, citric acid content in taxadiene producing yeasts changed the most, the decreasing amplitude reached 90% or more. Therefore, citric acid can be a marker metabolite for the future study of artificial functional yeasts. The metabolomics analysis of taxadiene producing yeasts can provide more information in further studies on optimization of terpenes production in heterologous chassis.

  8. Proteomics and metabolomics in inflammatory bowel disease.

    PubMed

    Yau, Yunki; Leong, Rupert W; Zeng, Ming; Wasinger, Valerie C

    2013-07-01

    Genome-wide studies in inflammatory bowel disease (IBD) have allowed us to understand Crohn's disease and ulcerative colitis as forms of related autoinflammatory disorders that arise from a multitude of pathogenic origins. Proteomics and metabolomics are the offspring of genomics that possess unprecedented possibilities to characterize unknown pathogenic pathways. It has been about a decade since proteomics was first applied to IBD, and 5 years for metabolomics. These techniques have yielded novel and potentially important findings, but turning these results into beneficial patient outcomes remains challenging. This review recounts the history and context of clinical IBD developments before and after proteomics and metabolomics IBD in this field, discusses the challenges in consolidating high complexity data with physiological understanding, and provides an outlook on the emerging principles that will help interface the bioanalytical laboratory with IBD prognosis.

  9. Metabolomics to Explore Impact of Dairy Intake

    PubMed Central

    Zheng, Hong; Clausen, Morten R.; Dalsgaard, Trine K.; Bertram, Hanne C.

    2015-01-01

    Dairy products are an important component in the Western diet and represent a valuable source of nutrients for humans. However, a reliable dairy intake assessment in nutrition research is crucial to correctly elucidate the link between dairy intake and human health. Metabolomics is considered a potential tool for assessment of dietary intake instead of traditional methods, such as food frequency questionnaires, food records, and 24-h recalls. Metabolomics has been successfully applied to discriminate between consumption of different dairy products under different experimental conditions. Moreover, potential metabolites related to dairy intake were identified, although these metabolites need to be further validated in other intervention studies before they can be used as valid biomarkers of dairy consumption. Therefore, this review provides an overview of metabolomics for assessment of dairy intake in order to better clarify the role of dairy products in human nutrition and health. PMID:26091233

  10. Metabolomics in rheumatic diseases: desperately seeking biomarkers

    PubMed Central

    Guma, Monica; Tiziani, Stefano; Firestein, Gary S.

    2016-01-01

    Metabolomics enables the profiling of large numbers of small molecules in cells, tissues and biological fluids. These molecules, which include amino acids, carbohydrates, lipids, nucleotides and their metabolites, can be detected quantitatively. Metabolomic methods, often focused on the information-rich analytical techniques of NMR spectroscopy and mass spectrometry, have potential for early diagnosis, monitoring therapy and defining disease pathogenesis in many therapeutic areas, including rheumatic diseases. By performing global metabolite profiling, also known as untargeted metabolomics, new discoveries linking cellular pathways to biological mechanisms are being revealed and are shaping our understanding of cell biology, physiology and medicine. These pathways can potentially be targeted to diagnose and treat patients with immune-mediated diseases. PMID:26935283

  11. Using computational predictions to improve literature-based Gene Ontology annotations: a feasibility study.

    PubMed

    Costanzo, Maria C; Park, Julie; Balakrishnan, Rama; Cherry, J Michael; Hong, Eurie L

    2011-01-01

    Annotation using Gene Ontology (GO) terms is one of the most important ways in which biological information about specific gene products can be expressed in a searchable, computable form that may be compared across genomes and organisms. Because literature-based GO annotations are often used to propagate functional predictions between related proteins, their accuracy is critically important. We present a strategy that employs a comparison of literature-based annotations with computational predictions to identify and prioritize genes whose annotations need review. Using this method, we show that comparison of manually assigned 'unknown' annotations in the Saccharomyces Genome Database (SGD) with InterPro-based predictions can identify annotations that need to be updated. A survey of literature-based annotations and computational predictions made by the Gene Ontology Annotation (GOA) project at the European Bioinformatics Institute (EBI) across several other databases shows that this comparison strategy could be used to maintain and improve the quality of GO annotations for other organisms besides yeast. The survey also shows that although GOA-assigned predictions are the most comprehensive source of functional information for many genomes, a large proportion of genes in a variety of different organisms entirely lack these predictions but do have manual annotations. This underscores the critical need for manually performed, literature-based curation to provide functional information about genes that are outside the scope of widely used computational methods. Thus, the combination of manual and computational methods is essential to provide the most accurate and complete functional annotation of a genome. Database URL: http://www.yeastgenome.org.

  12. Genomic and Metabolomic Profile Associated to Microalbuminuria

    PubMed Central

    Marrachelli, Vannina G.; Monleon, Daniel; Rentero, Pilar; Mansego, María L.; Morales, Jose Manuel; Galan, Inma; Segura, Remedios; Martinez, Fernando; Martin-Escudero, Juan Carlos; Briongos, Laisa; Marin, Pablo; Lliso, Gloria; Chaves, Felipe Javier; Redon, Josep

    2014-01-01

    To identify factors related with the risk to develop microalbuminuria using combined genomic and metabolomic values from a general population study. One thousand five hundred and two subjects, Caucasian, more than 18 years, representative of the general population, were included. Blood pressure measurement and albumin/creatinine ratio were measured in a urine sample. Using SNPlex, 1251 SNPs potentially associated to urinary albumin excretion (UAE) were analyzed. Serum metabolomic profile was assessed by 1H NMR spectra using a Brucker Advance DRX 600 spectrometer. From the total population, 1217 (mean age 54±19, 50.6% men, ACR>30 mg/g in 81 subjects) with high genotyping call rate were analysed. A characteristic metabolomic profile, which included products from mitochondrial and extra mitochondrial metabolism as well as branched amino acids and their derivative signals, were observed in microalbuminuric as compare to normoalbuminuric subjects. The comparison of the metabolomic profile between subjects with different UAE status for each of the genotypes associated to microalbuminuria revealed two SNPs, the rs10492025_TT of RPH3A gene and the rs4359_CC of ACE gene, with minimal or no statistically significant differences. Subjects with and without microalbuminuria, who shared the same genotype and metabolomic profile, differed in age. Microalbuminurics with the CC genotype of the rs4359 polymorphism and with the TT genotype of the rs10492025 polymorphism were seven years older and seventeen years younger, respectively as compared to the whole microalbuminuric subjects. With the same metabolomic environment, characteristic of subjects with microalbuminuria, the TT genotype of the rs10492025 polymorphism seems to increase and the CC genotype of the rs4359 polymorphism seems to reduce risk to develop microalbuminuria. PMID:24918908

  13. Linking metabolomics data to underlying metabolic regulation

    PubMed Central

    Nägele, Thomas

    2014-01-01

    The comprehensive experimental analysis of a metabolic constitution plays a central role in approaches of organismal systems biology. Quantifying the impact of a changing environment on the homeostasis of cellular metabolism has been the focus of numerous studies applying various metabolomics techniques. It has been proven that approaches which integrate different analytical techniques, e.g., LC-MS, GC-MS, CE-MS and H-NMR, can provide a comprehensive picture of a certain metabolic homeostasis. Identification of metabolic compounds and quantification of metabolite levels represent the groundwork for the analysis of regulatory strategies in cellular metabolism. This significantly promotes our current understanding of the molecular organization and regulation of cells, tissues and whole organisms. Nevertheless, it is demanding to elicit the pertinent information which is contained in metabolomics data sets. Based on the central dogma of molecular biology, metabolite levels and their fluctuations are the result of a directed flux of information from gene activation over transcription to translation and posttranslational modification. Hence, metabolomics data represent the summed output of a metabolic system comprising various levels of molecular organization. As a consequence, the inverse assignment of metabolomics data to underlying regulatory processes should yield information which—if deciphered correctly—provides comprehensive insight into a metabolic system. Yet, the deduction of regulatory principles is complex not only due to the high number of metabolic compounds, but also because of a high level of cellular compartmentalization and differentiation. Motivated by the question how metabolomics approaches can provide a representative view on regulatory biochemical processes, this article intends to present and discuss current metabolomics applications, strategies of data analysis and their limitations with respect to the interpretability in context of

  14. Toward Supportive Data Collection Tools for Plant Metabolomics[w

    PubMed Central

    Jenkins, Helen; Johnson, Helen; Kular, Baldeep; Wang, Trevor; Hardy, Nigel

    2005-01-01

    Over recent years, a number of initiatives have proposed standard reporting guidelines for functional genomics experiments. Associated with these are data models that may be used as the basis of the design of software tools that store and transmit experiment data in standard formats. Central to the success of such data handling tools is their usability. Successful data handling tools are expected to yield benefits in time saving and in quality assurance. Here, we describe the collection of datasets that conform to the recently proposed data model for plant metabolomics known as ArMet (architecture for metabolomics) and illustrate a number of approaches to robust data collection that have been developed in collaboration between software engineers and biologists. These examples also serve to validate ArMet from the data collection perspective by demonstrating that a range of software tools, supporting data recording and data upload to central databases, can be built using the data model as the basis of their design. PMID:15888680

  15. MetaboAnalyst 3.0--making metabolomics more meaningful.

    PubMed

    Xia, Jianguo; Sinelnikov, Igor V; Han, Beomsoo; Wishart, David S

    2015-07-01

    MetaboAnalyst (www.metaboanalyst.ca) is a web server designed to permit comprehensive metabolomic data analysis, visualization and interpretation. It supports a wide range of complex statistical calculations and high quality graphical rendering functions that require significant computational resources. First introduced in 2009, MetaboAnalyst has experienced more than a 50X growth in user traffic (>50 000 jobs processed each month). In order to keep up with the rapidly increasing computational demands and a growing number of requests to support translational and systems biology applications, we performed a substantial rewrite and major feature upgrade of the server. The result is MetaboAnalyst 3.0. By completely re-implementing the MetaboAnalyst suite using the latest web framework technologies, we have been able substantially improve its performance, capacity and user interactivity. Three new modules have also been added including: (i) a module for biomarker analysis based on the calculation of receiver operating characteristic curves; (ii) a module for sample size estimation and power analysis for improved planning of metabolomics studies and (iii) a module to support integrative pathway analysis for both genes and metabolites. In addition, popular features found in existing modules have been significantly enhanced by upgrading the graphical output, expanding the compound libraries and by adding support for more diverse organisms.

  16. Metabolomic insight into soy sauce through (1)H NMR spectroscopy.

    PubMed

    Ko, Bong-Kuk; Ahn, Hyuk-Jin; van den Berg, Frans; Lee, Cherl-Ho; Hong, Young-Shick

    2009-08-12

    Soy sauce, a well-known seasoning in Asia and throughout the world, consists of many metabolites that are produced during fermentation or aging and that have various health benefits. However, their comprehensive assessment has been limited due to targeted or instrumentally specific analysis. This paper presents for the first time a metabolic characterization of soy sauce, especially that aged up to 12 years, to obtain a global understanding of the metabolic variations through (1)H NMR spectroscopy coupled with multivariate pattern recognition techniques. Elevated amino acids and organic acids and the consumption of carbohydrate were associated with continuous involvement of microflora in aging for 12 years. In particular, continuous increases in the levels of betaine were found during aging for up to 12 years, demonstrating that microbial- or enzyme-related metabolites were also coupled with osmotolerant or halophilic bacteria present during aging. This work provides global insights into soy sauce through a (1)H NMR-based metabolomic approach that enhances the current understanding of the holistic metabolome and allows assessment of soy sauce quality.

  17. ¹³C NMR metabolomics: applications at natural abundance.

    PubMed

    Clendinen, Chaevien S; Lee-McMullen, Brittany; Williams, Caroline M; Stupp, Gregory S; Vandenborne, Krista; Hahn, Daniel A; Walter, Glenn A; Edison, Arthur S

    2014-09-16

    (13)C NMR has many advantages for a metabolomics study, including a large spectral dispersion, narrow singlets at natural abundance, and a direct measure of the backbone structures of metabolites. However, it has not had widespread use because of its relatively low sensitivity compounded by low natural abundance. Here we demonstrate the utility of high-quality (13)C NMR spectra obtained using a custom (13)C-optimized probe on metabolomic mixtures. A workflow was developed to use statistical correlations between replicate 1D (13)C and (1)H spectra, leading to composite spin systems that can be used to search publicly available databases for compound identification. This was developed using synthetic mixtures and then applied to two biological samples, Drosophila melanogaster extracts and mouse serum. Using the synthetic mixtures we were able to obtain useful (13)C-(13)C statistical correlations from metabolites with as little as 60 nmol of material. The lower limit of (13)C NMR detection under our experimental conditions is approximately 40 nmol, slightly lower than the requirement for statistical analysis. The (13)C and (1)H data together led to 15 matches in the database compared to just 7 using (1)H alone, and the (13)C correlated peak lists had far fewer false positives than the (1)H generated lists. In addition, the (13)C 1D data provided improved metabolite identification and separation of biologically distinct groups using multivariate statistical analysis in the D. melanogaster extracts and mouse serum.

  18. 13C NMR Metabolomics: Applications at Natural Abundance

    PubMed Central

    2015-01-01

    13C NMR has many advantages for a metabolomics study, including a large spectral dispersion, narrow singlets at natural abundance, and a direct measure of the backbone structures of metabolites. However, it has not had widespread use because of its relatively low sensitivity compounded by low natural abundance. Here we demonstrate the utility of high-quality 13C NMR spectra obtained using a custom 13C-optimized probe on metabolomic mixtures. A workflow was developed to use statistical correlations between replicate 1D 13C and 1H spectra, leading to composite spin systems that can be used to search publicly available databases for compound identification. This was developed using synthetic mixtures and then applied to two biological samples, Drosophila melanogaster extracts and mouse serum. Using the synthetic mixtures we were able to obtain useful 13C–13C statistical correlations from metabolites with as little as 60 nmol of material. The lower limit of 13C NMR detection under our experimental conditions is approximately 40 nmol, slightly lower than the requirement for statistical analysis. The 13C and 1H data together led to 15 matches in the database compared to just 7 using 1H alone, and the 13C correlated peak lists had far fewer false positives than the 1H generated lists. In addition, the 13C 1D data provided improved metabolite identification and separation of biologically distinct groups using multivariate statistical analysis in the D. melanogaster extracts and mouse serum. PMID:25140385

  19. Metabolomic applications in radiation biodosimetry: exploring radiation effects through small molecules.

    PubMed

    Pannkuk, Evan L; Fornace, Albert J; Laiakis, Evagelia C

    2017-10-01

    Exposure of the general population to ionizing radiation has increased in the past decades, primarily due to long distance travel and medical procedures. On the other hand, accidental exposures, nuclear accidents, and elevated threats of terrorism with the potential detonation of a radiological dispersal device or improvised nuclear device in a major city, all have led to increased needs for rapid biodosimetry and assessment of exposure to different radiation qualities and scenarios. Metabolomics, the qualitative and quantitative assessment of small molecules in a given biological specimen, has emerged as a promising technology to allow for rapid determination of an individual's exposure level and metabolic phenotype. Advancements in mass spectrometry techniques have led to untargeted (discovery phase, global assessment) and targeted (quantitative phase) methods not only to identify biomarkers of radiation exposure, but also to assess general perturbations of metabolism with potential long-term consequences, such as cancer, cardiovascular, and pulmonary disease. Metabolomics of radiation exposure has provided a highly informative snapshot of metabolic dysregulation. Biomarkers in easily accessible biofluids and biospecimens (urine, blood, saliva, sebum, fecal material) from mouse, rat, and minipig models, to non-human primates and humans have provided the basis for determination of a radiation signature to assess the need for medical intervention. Here we provide a comprehensive description of the current status of radiation metabolomic studies for the purpose of rapid high-throughput radiation biodosimetry in easily accessible biofluids and discuss future directions of radiation metabolomics research.

  20. Two dimensional NMR spectroscopic approaches for exploring plant metabolome: A review

    PubMed Central

    Mahrous, Engy A.; Farag, Mohamed A.

    2014-01-01

    Today, most investigations of the plant metabolome tend to be based on either nuclear magnetic resonance (NMR) spectroscopy or mass spectrometry (MS), with or without hyphenation with chromatography. Although less sensitive than MS, NMR provides a powerful complementary technique for the identification and quantification of metabolites in plant extracts. NMR spectroscopy, well appreciated by phytochemists as a particularly information-rich method, showed recent paradigm shift for the improving of metabolome(s) structural and functional characterization and for advancing the understanding of many biological processes. Furthermore, two dimensional NMR (2D NMR) experiments and the use of chemometric data analysis of NMR spectra have proven highly effective at identifying novel and known metabolites that correlate with changes in genotype or phenotype. In this review, we provide an overview of the development of NMR in the field of metabolomics with special focus on 2D NMR spectroscopic techniques and their applications in phytomedicines quality control analysis and drug discovery from natural sources, raising more attention at its potential to reduce the gap between the pace of natural products research and modern drug discovery demand. PMID:25685540

  1. Metabolomics in bladder cancer: a systematic review

    PubMed Central

    Cheng, Yidong; Yang, Xiao; Deng, Xiaheng; Zhang, Xiaolei; Li, Pengchao; Tao, Jun; Qin, Chao; Wei, Jifu; Lu, Qiang

    2015-01-01

    Bladder cancer (BC) is the most common urological malignancy. Early diagnosis of BC is crucial to improve patient outcomes. Currently, metabolomics is a potential technique that can be used to detect BC. We reviewed current publications and synthesised the findings on BC and metabolomics, i.e. metabolite upregulation and downregulation. Fourteen metabolites (lactic acid, leucine, valine, phenylalanine, glutamate, histidine, aspartic acid, tyrosine, serine, uracil, hypoxanthine, carnitine, pyruvic acid and citric acid) were identified as potential biomarkers for BC. In conclusion, this systematic review presents new opportunities for the diagnosis of BC. PMID:26379905

  2. Metabolomic analysis of sun exposed skin.

    PubMed

    Randhawa, Manpreet; Southall, Michael; Samaras, Samantha Tucker

    2013-08-01

    It is very well known that exposure of skin to sun chronically accelerates the mechanism of aging as well as making it more susceptible toward skin cancer. This aspect of aging has been studied very well through genomics and proteomics tools. In this study we have used a metabolomic approach for the first time to determine the differences in the metabolome from full thickness skin biopsies from sun exposed and sun protected sites. We have primarily investigated the energy metabolism and the oxidative pathway in sun exposed skin. Biochemical pathway analysis revealed that energy metabolism in photoexposed skin is predominantly anaerobic. The study also validated the increased oxidative stress in skin.

  3. Assessment of community-submitted ontology annotations from a novel database-journal partnership

    PubMed Central

    Berardini, Tanya Z.; Li, Donghui; Muller, Robert; Chetty, Raymond; Ploetz, Larry; Singh, Shanker; Wensel, April; Huala, Eva

    2012-01-01

    As the scientific literature grows, leading to an increasing volume of published experimental data, so does the need to access and analyze this data using computational tools. The most commonly used method to convert published experimental data on gene function into controlled vocabulary annotations relies on a professional curator, employed by a model organism database or a more general resource such as UniProt, to read published articles and compose annotation statements based on the articles' contents. A more cost-effective and scalable approach capable of capturing gene function data across the whole range of biological research organisms in computable form is urgently needed. We have analyzed a set of ontology annotations generated through collaborations between the Arabidopsis Information Resource and several plant science journals. Analysis of the submissions entered using the online submission tool shows that most community annotations were well supported and the ontology terms chosen were at an appropriate level of specificity. Of the 503 individual annotations that were submitted, 97% were approved and community submissions captured 72% of all possible annotations. This new method for capturing experimental results in a computable form provides a cost-effective way to greatly increase the available body of annotations without sacrificing annotation quality. Database URL: www.arabidopsis.org PMID:22859749

  4. Using comparative genome analysis to identify problems in annotated microbial genomes.

    PubMed

    Poptsova, Maria S; Gogarten, J Peter

    2010-07-01

    Genome annotation is a tedious task that is mostly done by automated methods; however, the accuracy of these approaches has been questioned since the beginning of the sequencing era. Genome annotation is a multilevel process, and errors can emerge at different stages: during sequencing, as a result of gene-calling procedures, and in the process of assigning gene functions. Missed or wrongly annotated genes differentially impact different types of analyses. Here we discuss and demonstrate how the methods of comparative genome analysis can refine annotations by locating missing orthologues. We also discuss possible reasons for errors and show that the second-generation annotation systems, which combine multiple gene-calling programs with similarity-based methods, perform much better than the first annotation tools. Since old errors may propagate to the newly sequenced genomes, we emphasize that the problem of continuously updating popular public databases is an urgent and unresolved one. Due to the progress in genome-sequencing technologies, automated annotation techniques will remain the main approach in the future. Researchers need to be aware of the existing errors in the annotation of even well-studied genomes, such as Escherichia coli, and consider additional quality control for their results.

  5. Assessment of community-submitted ontology annotations from a novel database-journal partnership.

    PubMed

    Berardini, Tanya Z; Li, Donghui; Muller, Robert; Chetty, Raymond; Ploetz, Larry; Singh, Shanker; Wensel, April; Huala, Eva

    2012-01-01

    As the scientific literature grows, leading to an increasing volume of published experimental data, so does the need to access and analyze this data using computational tools. The most commonly used method to convert published experimental data on gene function into controlled vocabulary annotations relies on a professional curator, employed by a model organism database or a more general resource such as UniProt, to read published articles and compose annotation statements based on the articles' contents. A more cost-effective and scalable approach capable of capturing gene function data across the whole range of biological research organisms in computable form is urgently needed. We have analyzed a set of ontology annotations generated through collaborations between the Arabidopsis Information Resource and several plant science journals. Analysis of the submissions entered using the online submission tool shows that most community annotations were well supported and the ontology terms chosen were at an appropriate level of specificity. Of the 503 individual annotations that were submitted, 97% were approved and community submissions captured 72% of all possible annotations. This new method for capturing experimental results in a computable form provides a cost-effective way to greatly increase the available body of annotations without sacrificing annotation quality. Database URL: www.arabidopsis.org.

  6. An evaluation of GO annotation retrieval for BioCreAtIvE and GOA.

    PubMed

    Camon, Evelyn B; Barrell, Daniel G; Dimmer, Emily C; Lee, Vivian; Magrane, Michele; Maslen, John; Binns, David; Apweiler, Rolf

    2005-01-01

    The Gene Ontology Annotation (GOA) database http://www.ebi.ac.uk/GOA aims to provide high-quality supplementary GO annotation to proteins in the UniProt Knowledgebase. Like many other biological databases, GOA gathers much of its content from the careful manual curation of literature. However, as both the volume of literature and of proteins requiring characterization increases, the manual processing capability can become overloaded. Consequently, semi-automated aids are often employed to expedite the curation process. Traditionally, electronic techniques in GOA depend largely on exploiting the knowledge in existing resources such as InterPro. However, in recent years, text mining has been hailed as a potentially useful tool to aid the curation process. To encourage the development of such tools, the GOA team at EBI agreed to take part in the functional annotation task of the BioCreAtIvE (Critical Assessment of Information Extraction systems in Biology) challenge. BioCreAtIvE task 2 was an experiment to test if automatically derived classification using information retrieval and extraction could assist expert biologists in the annotation of the GO vocabulary to the proteins in the UniProt Knowledgebase. GOA provided the training corpus of over 9000 manual GO annotations extracted from the literature. For the test set, we provided a corpus of 200 new Journal of Biological Chemistry articles used to annotate 286 human proteins with GO terms. A team of experts manually evaluated the results of 9 participating groups, each of which provided highlighted sentences to support their GO and protein annotation predictions. Here, we give a biological perspective on the evaluation, explain how we annotate GO using literature and offer some suggestions to improve the precision of future text-retrieval and extraction techniques. Finally, we provide the results of the first inter-annotator agreement study for manual GO curation, as well as an assessment of our current electronic

  7. OMIGA: Optimized Maker-Based Insect Genome Annotation.

    PubMed

    Liu, Jinding; Xiao, Huamei; Huang, Shuiqing; Li, Fei

    2014-08-01

    Insects are one of the largest classes of animals on Earth and constitute more than half of all living species. The i5k initiative has begun sequencing of more than 5,000 insect genomes, which should greatly help in exploring insect resource and pest control. Insect genome annotation remains challenging because many insects have high levels of heterozygosity. To improve the quality of insect genome annotation, we developed a pipeline, named Optimized Maker-Based Insect Genome Annotation (OMIGA), to predict protein-coding genes from insect genomes. We first mapped RNA-Seq reads to genomic scaffolds to determine transcribed regions using Bowtie, and the putative transcripts were assembled using Cufflink. We then selected highly reliable transcripts with intact coding sequences to train de novo gene prediction software, including Augustus. The re-trained software was used to predict genes from insect genomes. Exonerate was used to refine gene structure and to determine near exact exon/intron boundary in the genome. Finally, we used the software Maker to integrate data from RNA-Seq, de novo gene prediction, and protein alignment to produce an official gene set. The OMIGA pipeline was used to annotate the draft genome of an important insect pest, Chilo suppressalis, yielding 12,548 genes. Different strategies were compared, which demonstrated that OMIGA had the best performance. In summary, we present a comprehensive pipeline for identifying genes in insect genomes that can be widely used to improve the annotation quality in insects. OMIGA is provided at http://ento.njau.edu.cn/omiga.html .

  8. Semantic annotation in biomedicine: the current landscape.

    PubMed

    Jovanović, Jelena; Bagheri, Ebrahim

    2017-09-22

    The abundance and unstructured nature of biomedical texts, be it clinical or research content, impose significant challenges for the effective and efficient use of information and knowledge stored in such texts. Annotation of biomedical documents with machine intelligible semantics facilitates advanced, semantics-based text management, curation, indexing, and search. This paper focuses on annotation of biomedical entity mentions with concepts from relevant biomedical knowledge bases such as UMLS. As a result, the meaning of those mentions is unambiguously and explicitly defined, and thus made readily available for automated processing. This process is widely known as semantic annotation, and the tools that perform it are known as semantic annotators.Over the last dozen years, the biomedical research community has invested significant efforts in the development of biomedical semantic annotation technology. Aiming to establish grounds for further developments in this area, we review a selected set of state of the art biomedical semantic annotators, focusing particularly on general purpose annotators, that is, semantic annotation tools that can be customized to work with texts from any area of biomedicine. We also examine potential directions for further improvements of today's annotators which could make them even more capable of meeting the needs of real-world applications. To motivate and encourage further developments in this area, along the suggested and/or related directions, we review existing and potential practical applications and benefits of semantic annotators.

  9. Computational algorithms to predict Gene Ontology annotations

    PubMed Central

    2015-01-01

    Background Gene function annotations, which are associations between a gene and a term of a controlled vocabulary describing gene functional features, are of paramount importance in modern biology. Datasets of these annotations, such as the ones provided by the Gene Ontology Consortium, are used to design novel biological experiments and interpret their results. Despite their importance, these sources of information have some known issues. They are incomplete, since biological knowledge is far from being definitive and it rapidly evolves, and some erroneous annotations may be present. Since the curation process of novel annotations is a costly procedure, both in economical and time terms, computational tools that can reliably predict likely annotations, and thus quicken the discovery of new gene annotations, are very useful. Methods We used a set of computational algorithms and weighting schemes to infer novel gene annotations from a set of known ones. We used the latent semantic analysis approach, implementing two popular algorithms (Latent Semantic Indexing and Probabilistic Latent Semantic Analysis) and propose a novel method, the Semantic IMproved Latent Semantic Analysis, which adds a clustering step on the set of considered genes. Furthermore, we propose the improvement of these algorithms by weighting the annotations in the input set. Results We tested our methods and their weighted variants on the Gene Ontology annotation sets of three model organism genes (Bos taurus, Danio rerio and Drosophila melanogaster ). The methods showed their ability in predicting novel gene annotations and the weighting procedures demonstrated to lead to a valuable improvement, although the obtained results vary according to the dimension of the input annotation set and the considered algorithm. Conclusions Out of the three considered methods, the Semantic IMproved Latent Semantic Analysis is the one that provides better results. In particular, when coupled with a proper

  10. An annotated bibliography of the effects of logging on fish of the Western United States and Canada.

    Treesearch

    Dave R. Gibbons; Ernest O. Salo

    1973-01-01

    This bibliography is an annotation of the scientific and nonscientific literature published on the effects of logging on fish and aquatic habitat of the Western United States and Canada. It includes 278 annotations and 317 total references. Subject areas include erosion and sedimentation, water quality, related influences upon salmonids, multiple logging effects,...

  11. Qualitative Alterations of Bacterial Metabolome after Exposure to Metal Nanoparticles with Bactericidal Properties: A Comprehensive Workflow Based on (1)H NMR, UHPLC-HRMS, and Metabolic Databases.

    PubMed

    Chatzimitakos, Theodoros G; Stalikas, Constantine D

    2016-09-02

    Metal nanoparticles (NPs) have proven to be more toxic than bulk analogues of the same chemical composition due to their unique physical properties. The NPs, lately, have drawn the attention of researchers because of their antibacterial and biocidal properties. In an effort to shed light on the mechanism through which the bacteria elimination is achieved and the metabolic changes they undergo, an untargeted metabolomic fingerprint study was carried out on Gram-positive (Staphylococcus aureus) and Gram-negative (Escherichia coli) bacteria species. The (1)H NMR spectroscopy, in conjunction with high resolution mass-spectrometry (HRMS) and an unsophisticated data processing workflow were implemented. The combined NMR/HRMS data, supported by an open-access metabolomic database, proved to be efficacious in the process of assigning a putative annotation to a wide range of metabolite signals and is a useful tool to appraise the metabolome alterations, as a consequence of bacterial response to NPs. Interestingly, not all the NPs diminished the intracellular metabolites; bacteria treated with iron NPs produced metabolites not present in the nonexposed bacteria sample, implying the activation of previously inactive metabolic pathways. In contrast, copper and iron-copper NPs reduced the annotated metabolites, alluding to the conclusion that the metabolic pathways (mainly alanine, aspartate, and glutamate metabolism, beta-alanine metabolism, glutathione metabolism, and arginine and proline metabolism) were hindered by the interactions of NPs with the intracellular metabolites.

  12. Multilingual Twitter Sentiment Classification: The Role of Human Annotators

    PubMed Central

    Mozetič, Igor; Grčar, Miha; Smailović, Jasmina

    2016-01-01

    What are the limits of automated Twitter sentiment classification? We analyze a large set of manually labeled tweets in different languages, use them as training data, and construct automated classification models. It turns out that the quality of classification models depends much more on the quality and size of training data than on the type of the model trained. Experimental results indicate that there is no statistically significant difference between the performance of the top classification models. We quantify the quality of training data by applying various annotator agreement measures, and identify the weakest points of different datasets. We show that the model performance approaches the inter-annotator agreement when the size of the training set is sufficiently large. However, it is crucial to regularly monitor the self- and inter-annotator agreements since this improves the training datasets and consequently the model performance. Finally, we show that there is strong evidence that humans perceive the sentiment classes (negative, neutral, and positive) as ordered. PMID:27149621

  13. Metabolomics in the study of kidney diseases.

    PubMed

    Weiss, Robert H; Kim, Kyoungmi

    2011-10-25

    Metabolomics--the nontargeted measurement of all metabolites produced by the body--is beginning to show promise in both biomarker discovery and, in the form of pharmacometabolomics, in aiding the choice of therapy for patients with specific diseases. In its two basic forms (pattern recognition and metabolite identification), this developing field has been used to discover potential biomarkers in several renal diseases, including acute kidney injury (attributable to a variety of causes), autosomal dominant polycystic kidney disease and kidney cancer. NMR and gas chromatography or liquid chromatography, together with mass spectrometry, are generally used to separate and identify metabolites. Many hurdles need to be overcome in this field, such as achieving consistency in collection of biofluid samples, controlling for batch effects during the analysis and applying the most appropriate statistical analysis to extract the maximum amount of biological information from the data obtained. Pathway and network analyses have both been applied to metabolomic analysis, which vastly extends its clinical relevance and effects. In addition, pharmacometabolomics analyses, in which a metabolomic signature can be associated with a given therapeutic effect, are beginning to appear in the literature, which will lead to personalized therapies. Thus, metabolomics holds promise for early diagnosis, increased choice of therapy and the identification of new metabolic pathways that could potentially be targeted in kidney disease.

  14. Cellular Metabolomics for Exposure and Toxicity Assessment

    EPA Science Inventory

    We have developed NMR automation and cell quench methods for cell culture-based metabolomics to study chemical exposure and toxicity. Our flow automation method is robust and free of cross contamination. The direct cell quench method is rapid and effective. Cell culture-based met...

  15. Microbial metabolomics in open microscale platforms

    PubMed Central

    Barkal, Layla J.; Theberge, Ashleigh B.; Guo, Chun-Jun; Spraker, Joe; Rappert, Lucas; Berthier, Jean; Brakke, Kenneth A.; Wang, Clay C. C.; Beebe, David J.; Keller, Nancy P.; Berthier, Erwin

    2016-01-01

    The microbial secondary metabolome encompasses great synthetic diversity, empowering microbes to tune their chemical responses to changing microenvironments. Traditional metabolomics methods are ill-equipped to probe a wide variety of environments or environmental dynamics. Here we introduce a class of microscale culture platforms to analyse chemical diversity of fungal and bacterial secondary metabolomes. By leveraging stable biphasic interfaces to integrate microculture with small molecule isolation via liquid–liquid extraction, we enable metabolomics-scale analysis using mass spectrometry. This platform facilitates exploration of culture microenvironments (including rare media typically inaccessible using established methods), unusual organic solvents for metabolite isolation and microbial mutants. Utilizing Aspergillus, a fungal genus known for its rich secondary metabolism, we characterize the effects of culture geometry and growth matrix on secondary metabolism, highlighting the potential use of microscale systems to unlock unknown or cryptic secondary metabolites for natural products discovery. Finally, we demonstrate the potential for this class of microfluidic systems to study interkingdom communication between fungi and bacteria. PMID:26842393

  16. Lessons learned from metabolomics in cystic fibrosis.

    PubMed

    Muhlebach, Marianne S; Sha, Wei

    2015-12-01

    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.

  17. Apple storage management using postharvest metabolomics

    USDA-ARS?s Scientific Manuscript database

    Using broad metabolic profiling of over 600 metabolites, we have previously demonstrated that diphenylamine treatment, 1-methylcyclopropene treatment, and storage duration all alter the apple peel metabolome during cold storage. Because these changes precede and/or are potentially indicative of pos...

  18. Metabolomics in the fight against malaria

    PubMed Central

    Salinas, Jorge L; Kissinger, Jessica C; Jones, Dean P; Galinski, Mary R

    2014-01-01

    Metabolomics uses high-resolution mass spectrometry to provide a chemical fingerprint of thousands of metabolites present in cells, tissues or body fluids. Such metabolic phenotyping has been successfully used to study various biologic processes and disease states. High-resolution metabolomics can shed new light on the intricacies of host-parasite interactions in each stage of the Plasmodium life cycle and the downstream ramifications on the host’s metabolism, pathogenesis and disease. Such data can become integrated with other large datasets generated using top-down systems biology approaches and be utilised by computational biologists to develop and enhance models of malaria pathogenesis relevant for identifying new drug targets or intervention strategies. Here, we focus on the promise of metabolomics to complement systems biology approaches in the quest for novel interventions in the fight against malaria. We introduce the Malaria Host-Pathogen Interaction Center (MaHPIC), a new systems biology research coalition. A primary goal of the MaHPIC is to generate systems biology datasets relating to human and non-human primate (NHP) malaria parasites and their hosts making these openly available from an online relational database. Metabolomic data from NHP infections and clinical malaria infections from around the world will comprise a unique global resource. PMID:25185001

  19. NMR-based Metabolomics for Cancer Research

    EPA Science Inventory

    Metabolomics is considered as a complementary tool to other omics platforms to provide a snapshot of the cellular biochemistry and physiology taking place at any instant. Metabolmics approaches have been widely used to provide comprehensive and quantitative analyses of the metabo...

  20. Cellular Metabolomics for Exposure and Toxicity Assessment

    EPA Science Inventory

    We have developed NMR automation and cell quench methods for cell culture-based metabolomics to study chemical exposure and toxicity. Our flow automation method is robust and free of cross contamination. The direct cell quench method is rapid and effective. Cell culture-based met...

  1. NMR-based Metabolomics for Cancer Research

    EPA Science Inventory

    Metabolomics is considered as a complementary tool to other omics platforms to provide a snapshot of the cellular biochemistry and physiology taking place at any instant. Metabolmics approaches have been widely used to provide comprehensive and quantitative analyses of the metabo...

  2. Metabolomic profiling of neoplastic lesions in mice.

    PubMed

    Lu, Xiaojie; Ji, Li-Juan; Chen, Jin-Lian

    2014-01-01

    Most cancers develop upon the accumulation of genetic alterations that provoke and sustain the transformed phenotype. Several metabolomic approaches now allow for the global assessment of intermediate metabolites, generating profound insights into the metabolic rewiring associated with malignant transformation. The metabolomic profiling of neoplastic lesions growing in mice, irrespective of their origin, can provide invaluable information on the mechanisms underlying oncogenesis, tumor progression, and response to therapy. Moreover, the metabolomic profiling of tumors growing in mice may result in the identification of novel diagnostic or prognostic biomarkers, which is of great clinical significance. Several methods can be applied to the metabolomic profiling of neoplastic lesions in mice, including mass spectrometry-based techniques (e.g., gas chromatography-, capillary electrophoresis-, or liquid chromatography-coupled mass spectrometry) as well as nuclear magnetic resonance. Here, we compare and discuss the advantages and disadvantages of all these techniques to provide a concise and reliable guide for readers interested in this active area of investigation. © 2014 Elsevier Inc. All rights reserved.

  3. Metabolomic Approaches for Characterizing Aquatic Ecosystems

    EPA Science Inventory

    Metabolomics is becoming a well-established tool for studying how organisms, such as fish, respond to various stressors. For example, the literature is rich with laboratory studies involving analysis of samples from organisms exposed to individual chemical toxicants. These studie...

  4. Metabolomic Approaches for Characterizing Aquatic Ecosystems

    EPA Science Inventory

    Metabolomics is becoming a well-established tool for studying how organisms, such as fish, respond to various stressors. For example, the literature is rich with laboratory studies involving analysis of samples from organisms exposed to individual chemical toxicants. These studie...

  5. Metabolomic Change Precedes Apple Superficial Scald Symptoms

    USDA-ARS?s Scientific Manuscript database

    Metabolic profiling of 621 metabolites was employed to characterize metabolomic changes associated with ‘Granny Smith’ apple superficial scald development following 1-MCP or DPA treatment. Partial least squares-discriminant analyses were used to link metabolites with scald, postharvest treatments, ...

  6. High-resolution mass spectrometry applied to the study of metabolome modifications in various chicken tissues after amoxicillin administration.

    PubMed

    Hermo, M P; Saurina, J; Barbosa, J; Barrón, D

    2014-06-15

    The performance of high resolution accurate mass spectrometry (HRMS) operating in full scan MS mode was investigated for the quantitative determination of amoxicillin (AMX) as well as qualitative analysis of metabolomic profiles in tissues of medicated chickens. The metabolomic approach was exploited to compile analytical information on changes in the metabolome of muscle, kidney and liver from chickens subjected to a pharmacological program with AMX. Data consisting of m/z features taken throughout the entire chromatogram were extracted and filtered to be treated by Principal Component Analysis. As a result, it was found that medicated and non-treated animals were clearly clustered in distinct groups. Besides, the multivariate analysis revealed some relevant mass features contributing to this separation. In this context, recognizing those potential markers of each chicken class was a priority research for both metabolite identification and, obviously, evaluation of food quality and health effects associated to food consumption.

  7. Metabolomic Identification of Subtypes of Nonalcoholic Steatohepatitis.

    PubMed

    Alonso, Cristina; Fernández-Ramos, David; Varela-Rey, Marta; Martínez-Arranz, Ibon; Navasa, Nicolás; Van Liempd, Sebastiaan M; Lavín Trueba, José L; Mayo, Rebeca; Ilisso, Concetta P; de Juan, Virginia G; Iruarrizaga-Lejarreta, Marta; delaCruz-Villar, Laura; Mincholé, Itziar; Robinson, Aaron; Crespo, Javier; Martín-Duce, Antonio; Romero-Gómez, Manuel; Sann, Holger; Platon, Julian; Van Eyk, Jennifer; Aspichueta, Patricia; Noureddin, Mazen; Falcón-Pérez, Juan M; Anguita, Juan; Aransay, Ana M; Martínez-Chantar, María Luz; Lu, Shelly C; Mato, José M

    2017-05-01

    Nonalcoholic fatty liver disease (NAFLD) is a consequence of defects in diverse metabolic pathways that involve hepatic accumulation of triglycerides. Features of these aberrations might determine whether NAFLD progresses to nonalcoholic steatohepatitis (NASH). We investigated whether the diverse defects observed in patients with NAFLD are caused by different NAFLD subtypes with specific serum metabolomic profiles, and whether these can distinguish patients with NASH from patients with simple steatosis. We collected liver and serum from methionine adenosyltransferase 1a knockout (MAT1A-KO) mice, which have chronically low levels of hepatic S-adenosylmethionine (SAMe) and spontaneously develop steatohepatitis, as well as C57Bl/6 mice (controls); the metabolomes of all samples were determined. We also analyzed serum metabolomes of 535 patients with biopsy-proven NAFLD (353 with simple steatosis and 182 with NASH) and compared them with serum metabolomes of mice. MAT1A-KO mice were also given SAMe (30 mg/kg/day for 8 weeks); liver samples were collected and analyzed histologically for steatohepatitis. Livers of MAT1A-KO mice were characterized by high levels of triglycerides, diglycerides, fatty acids, ceramides, and oxidized fatty acids, as well as low levels of SAMe and downstream metabolites. There was a correlation between liver and serum metabolomes. We identified a serum metabolomic signature associated with MAT1A-KO mice that also was present in 49% of the patients; based on this signature, we identified 2 NAFLD subtypes. We identified specific panels of markers that could distinguish patients with NASH from patients with simple steatosis for each subtype of NAFLD. Administration of SAMe reduced features of steatohepatitis in MAT1A-KO mice. In an analysis of serum metabolomes of patients with NAFLD and MAT1A-KO mice with steatohepatitis, we identified 2 major subtypes of NAFLD and markers that differentiate steatosis from NASH in each subtype. These might be

  8. The Lipopolysaccharide-Induced Metabolome Signature in Arabidopsis thaliana Reveals Dynamic Reprogramming of Phytoalexin and Phytoanticipin Pathways

    PubMed Central

    Finnegan, Tarryn; Steenkamp, Paul A.; Piater, Lizelle A.

    2016-01-01

    Lipopolysaccharides (LPSs), as MAMP molecules, trigger the activation of signal transduction pathways involved in defence. Currently, plant metabolomics is providing new dimensions into understanding the intracellular adaptive responses to external stimuli. The effect of LPS on the metabolomes of Arabidopsis thaliana cells and leaf tissue was investigated over a 24 h period. Cellular metabolites and those secreted into the medium were extracted with methanol and liquid chromatography coupled to mass spectrometry was used for quantitative and qualitative analyses. Multivariate statistical data analyses were used to extract interpretable information from the generated multidimensional LC-MS data. The results show that LPS perception triggered differential changes in the metabolomes of cells and leaves, leading to variation in the biosynthesis of specialised secondary metabolites. Time-dependent changes in metabolite profiles were observed and biomarkers associated with the LPS-induced response were tentatively identified. These include the phytohormones salicylic acid and jasmonic acid, and also the associated methyl esters and sugar conjugates. The induced defensive state resulted in increases in indole—and other glucosinolates, indole derivatives, camalexin as well as cinnamic acid derivatives and other phenylpropanoids. These annotated metabolites indicate dynamic reprogramming of metabolic pathways that are functionally related towards creating an enhanced defensive capacity. The results reveal new insights into the mode of action of LPS as an activator of plant innate immunity, broadens knowledge about the defence metabolite pathways involved in Arabidopsis responses to LPS, and identifies specialised metabolites of functional importance that can be employed to enhance immunity against pathogen infection. PMID:27656890

  9. Applying metabolomics to cardiometabolic intervention studies and trials: past experiences and a roadmap for the future.

    PubMed

    Rankin, Naomi J; Preiss, David; Welsh, Paul; Sattar, Naveed

    2016-10-01

    Metabolomics and lipidomics are emerging methods for detailed phenotyping of small molecules in samples. It is hoped that such data will: (i) enhance baseline prediction of patient response to pharmacotherapies (beneficial or adverse); (ii) reveal changes in metabolites shortly after initiation of therapy that may predict patient response, including adverse effects, before routine biomarkers are altered; and( iii) give new insights into mechanisms of drug action, particularly where the results of a trial of a new agent were unexpected, and thus help future drug development. In these ways, metabolomics could enhance research findings from intervention studies. This narrative review provides an overview of metabolomics and lipidomics in early clinical intervention studies for investigation of mechanisms of drug action and prediction of drug response (both desired and undesired). We highlight early examples from drug intervention studies associated with cardiometabolic disease. Despite the strengths of such studies, particularly the use of state-of-the-art technologies and advanced statistical methods, currently published studies in the metabolomics arena are largely underpowered and should be considered as hypothesis-generating. In order for metabolomics to meaningfully improve stratified medicine approaches to patient treatment, there is a need for higher quality studies, with better exploitation of biobanks from randomized clinical trials i.e. with large sample size, adjudicated outcomes, standardized procedures, validation cohorts, comparison witth routine biochemistry and both active and control/placebo arms. On the basis of this review, and based on our research experience using clinically established biomarkers, we propose steps to more speedily advance this area of research towards potential clinical impact.

  10. Bridging the gap between comprehensive extraction protocols in plant metabolomics studies and method validation.

    PubMed

    Bijttebier, Sebastiaan; Van der Auwera, Anastasia; Foubert, Kenn; Voorspoels, Stefan; Pieters, Luc; Apers, Sandra

    2016-09-07

    It is vital to pay much attention to the design of extraction methods developed for plant metabolomics, as any non-extracted or converted metabolites will greatly affect the overall quality of the metabolomics study. Method validation is however often omitted in plant metabolome studies, as the well-established methodologies for classical targeted analyses such as recovery optimization cannot be strictly applied. The aim of the present study is to thoroughly evaluate state-of-the-art comprehensive extraction protocols for plant metabolomics with liquid chromatography-photodiode array-accurate mass mass spectrometry (LC-PDA-amMS) by bridging the gap with method validation. Validation of an extraction protocol in untargeted plant metabolomics should ideally be accomplished by validating the protocol for all possible outcomes, i.e. for all secondary metabolites potentially present in the plant. In an effort to approach this ideal validation scenario, two plant matrices were selected based on their wide versatility of phytochemicals: meadowsweet (Filipendula ulmaria) for its polyphenols content, and spicy paprika powder (from the genus Capsicum) for its apolar phytochemicals content (carotenoids, phytosterols, capsaicinoids). These matrices were extracted with comprehensive extraction protocols adapted from literature and analysed with a generic LC-PDA-amMS characterization platform that was previously validated for broad range phytochemical analysis. The performance of the comprehensive sample preparation protocols was assessed based on extraction efficiency, repeatability and intermediate precision and on ionization suppression/enhancement evaluation. The manuscript elaborates on the finding that none of the extraction methods allowed to exhaustively extract the metabolites. Furthermore, it is shown that depending on the extraction conditions enzymatic degradation mechanisms can occur. Investigation of the fractions obtained with the different extraction methods

  11. Applying metabolomics to cardiometabolic intervention studies and trials: past experiences and a roadmap for the future

    PubMed Central

    Rankin, Naomi J; Preiss, David; Welsh, Paul; Sattar, Naveed

    2016-01-01

    Metabolomics and lipidomics are emerging methods for detailed phenotyping of small molecules in samples. It is hoped that such data will: (i) enhance baseline prediction of patient response to pharmacotherapies (beneficial or adverse); (ii) reveal changes in metabolites shortly after initiation of therapy that may predict patient response, including adverse effects, before routine biomarkers are altered; and( iii) give new insights into mechanisms of drug action, particularly where the results of a trial of a new agent were unexpected, and thus help future drug development. In these ways, metabolomics could enhance research findings from intervention studies. This narrative review provides an overview of metabolomics and lipidomics in early clinical intervention studies for investigation of mechanisms of drug action and prediction of drug response (both desired and undesired). We highlight early examples from drug intervention studies associated with cardiometabolic disease. Despite the strengths of such studies, particularly the use of state-of-the-art technologies and advanced statistical methods, currently published studies in the metabolomics arena are largely underpowered and should be considered as hypothesis-generating. In order for metabolomics to meaningfully improve stratified medicine approaches to patient treatment, there is a need for higher quality studies, with better exploitation of biobanks from randomized clinical trials i.e. with large sample size, adjudicated outcomes, standardized procedures, validation cohorts, comparison witth routine biochemistry and both active and control/placebo arms. On the basis of this review, and based on our research experience using clinically established biomarkers, we propose steps to more speedily advance this area of research towards potential clinical impact. PMID:27789671

  12. Essential Annotation Schema for Ecology (EASE)-A framework supporting the efficient data annotation and faceted navigation in ecology.

    PubMed

    Pfaff, Claas-Thido; Eichenberg, David; Liebergesell, Mario; König-Ries, Birgitta; Wirth, Christian

    2017-01-01

    Ecology has become a data intensive science over the last decades which often relies on the reuse of data in cross-experimental analyses. However, finding data which qualifies for the reuse in a specific context can be challenging. It requires good quality metadata and annotations as well as efficient search strategies. To date, full text search (often on the metadata only) is the most widely used search strategy although it is known to be inaccurate. Faceted navigation is providing a filter mechanism which is based on fine granular metadata, categorizing search objects along numeric and categorical parameters relevant for their discovery. Selecting from these parameters during a full text search creates a system of filters which allows to refine and improve the results towards more relevance. We developed a framework for the efficient annotation and faceted navigation in ecology. It consists of an XML schema for storing the annotation of search objects and is accompanied by a vocabulary focused on ecology to support the annotation process. The framework consolidates ideas which originate from widely accepted metadata standards, textbooks, scientific literature, and vocabularies as well as from expert knowledge contributed by researchers from ecology and adjacent disciplines.

  13. Annotating Socio-Cultural Structures in Text

    DTIC Science & Technology

    2012-10-31

    from the traditional k-Nearest Neighbor (kNN) algorithm. Using experiments on three different multi-label learning problems, i.e. Yeast gene ...annotated NP/ VP Pane: Shows the sentence parsed using the Parts of Speech tagger Document View Pane: Specifies the document (being annotated) in three...used to annotate the document. In the current application we use the Level 1, Level 2 taxonomy. New concepts may be added to or deleted from the

  14. Molecular cartography in acute Chlamydia pneumoniae infections--a non-targeted metabolomics approach.

    PubMed

    Müller, Constanze; Dietz, Inga; Tziotis, Dimitrios; Moritz, Franco; Rupp, Jan; Schmitt-Kopplin, Philippe

    2013-06-01

    Infections with Chlamydia pneumoniae cause several respiratory diseases, such as community-acquired pneumonia, bronchitis or sinusitis. Here, we present an integrated non-targeted metabolomics analysis applying ultra-high-resolution mass spectrometry and ultra-performance liquid chromatography mass spectrometry to determine metabolite alterations in C. pneumoniae-infected HEp-2 cells. Most important permutations are elaborated using uni- and multivariate statistical analysis, logD retention time regression and mass defect-based network analysis. Classes of metabolites showing high variations upon infection are lipids, carbohydrates and amino acids. Moreover, we observed several non-annotated compounds as predominantly abundant after infection, which are promising biomarker candidates for drug-target and diagnostic research.

  15. A Genome-Wide Association Study of the Human Metabolome in a Community-Based Cohort

    PubMed Central

    Rhee, Eugene P.; Ho, Jennifer E.; Chen, Ming-Huei; Shen, Dongxiao; Cheng, Susan; Larson, Martin G.; Ghorbani, Anahita; Shi, Xu; Helenius, Iiro T.; O’Donnell, Christopher J.; Souza, Amanda L.; Deik, Amy; Pierce, Kerry A.; Bullock, Kevin; Walford, Geoffrey A.; Vasan, Ramachandran S.; Florez, Jose C.; Clish, Clary; Yeh, J.-R. Joanna; Wang, Thomas J.; Gerszten, Robert E.

    2014-01-01

    SUMMARY Because metabolites are hypothesized to play key roles as markers and effectors of cardio-metabolic diseases, recent studies have sought to annotate the genetic determinants of circulating metabolite levels. We report a genome-wide association study (GWAS) of 217 plasma metabolites, including >100 not measured in prior GWAS, in 2,076 participants of the Framingham Heart Study. For the majority of analytes, we find that estimated heritability explains >20% of inter-individual variation, and that variation attributable to heritable factors is greater than that attributable to clinical factors. Further, we identify 31 genetic loci associated with plasma metabolites, including 23 that have not previously been reported. Importantly, we include GWAS results for all surveyed metabolites, and demonstrate how this information highlights a role for AGXT2 in cholesterol ester and triacylglycerol metabolism. Thus, our study outlines the relative contributions of inherited and clinical factors on the plasma metabolome and provides a resource for metabolism research. PMID:23823483

  16. Collaborative Design of an Image Annotation Tool for Oceanographic Imaging Systems

    NASA Astrophysics Data System (ADS)

    Futrelle, J.; York, A.

    2012-12-01

    We present a design for a web-based image annotation interface developed to assist in supervised classification of organisms and substrate for habitat assessment from multiple, heterogeneous oceanographic imaging systems. The interface enables human image annotators to count, identify, and measure targets and classify substrate in a variety of kinds of imagery including benthic surveys and imaging flow cytometry. These annotations are then used to build training sets for supervised classification algorithms for purposes of characterizing community structure and habitat assessment. The Ocean Imaging Informatics team at WHOI used the Tetherless World Constellation's collaborative design methodology to develop shared formal information model and system design that applies to a variety of image annotation use cases. Because the information model represents consensus between researchers with differing instrumentation and science needs, it assists with rapid prototyping and establishes a baseline against which existing and forthcoming image annotation tools can be evaluated. A technology review suggested that there are few general-purpose image annotation tools suitable for annotation of high-volume oceanographic imagery. Most tools require too many steps for operations that must be repeated thousands of times, and/or lack critical features such as display of instrument metadata, QA/QC, and management of annotator tasks. While some of these problems are user interface limitations, others suggest that existing tools are missing critically important concepts. For example, QA/QC appears in our information model as an "activity stream" associated with each image annotation, consisting of events indicating review status, specific image quality issues, etc. The model also includes "identification modes" that contextualize annotations according to the annotator's assigned task, assisting both with interpreting annotations and with providing contextual user interface shortcuts

  17. A beginner's guide to eukaryotic genome annotation.

    PubMed

    Yandell, Mark; Ence, Daniel

    2012-04-18

    The falling cost of genome sequencing is having a marked impact on the research community with respect to which genomes are sequenced and how and where they are annotated. Genome annotation projects have generally become small-scale affairs that are often carried out by an individual laboratory. Although annotating a eukaryotic genome assembly is now within the reach of non-experts, it remains a challenging task. Here we provide an overview of the genome annotation process and the available tools and describe some best-practice approaches.

  18. Profiling of Altered Metabolomic States in Nicotiana tabacum Cells Induced by Priming Agents

    PubMed Central

    Mhlongo, Msizi I.; Steenkamp, Paul A.; Piater, Lizelle A.; Madala, Ntakadzeni E.; Dubery, Ian A.

    2016-01-01

    Metabolomics has developed into a valuable tool for advancing our understanding of plant metabolism. Plant innate immune defenses can be activated and enhanced so that, subsequent to being pre-sensitized, plants are able to launch a stronger and faster defense response upon exposure to pathogenic microorganisms, a phenomenon known as priming. Here, three contrasting chemical activators, namely acibenzolar-S-methyl, azelaic acid and riboflavin, were used to induce a primed state in Nicotiana tabacum cells. Identified biomarkers were then compared to responses induced by three phytohormones—abscisic acid, methyljasmonate, and salicylic acid. Altered metabolomes were studied using a metabolite fingerprinting approach based on liquid chromatography and mass spectrometry. Multivariate data models indicated that these inducers cause time-dependent metabolic perturbations in the cultured cells and revealed biomarkers of which the levels are affected by these agents. A total of 34 metabolites were annotated from the mass spectral data and online databases. Venn diagrams were used to identify common biomarkers as well as those unique to a specific agent. Results implicate 20 cinnamic acid derivatives conjugated to (i) quinic acid (chlorogenic acids), (ii) tyramine, (iii) polyamines, or (iv) glucose as discriminatory biomarkers of priming in tobacco cells. Functional roles for most of these metabolites in plant defense responses could thus be proposed. Metabolites induced by the activators belong to the early phenylpropanoid pathway, which indicates that different stimuli can activate similar pathways but with different metabolite fingerprints. Possible linkages to phytohormone-dependent pathways at a metabolomic level were indicated in the case of cells treated with salicylic acid and methyljasmonate. The results contribute to a better understanding of the priming phenomenon and advance our knowledge of cinnamic acid derivatives as versatile defense metabolites. PMID

  19. AICAR stimulation metabolome widely mimics electrical contraction in isolated rat epitrochlearis muscle.

    PubMed

    Miyamoto, Licht; Egawa, Tatsuro; Oshima, Rieko; Kurogi, Eriko; Tomida, Yosuke; Tsuchiya, Koichiro; Hayashi, Tatsuya

    2013-12-15

    Physical exercise has potent therapeutic and preventive effects against metabolic disorders. A number of studies have suggested that 5'-AMP-activated protein kinase (AMPK) plays a pivotal role in regulating carbohydrate and lipid metabolism in contracting skeletal muscles, while several genetically manipulated animal models revealed the significance of AMPK-independent pathways. To elucidate significance of AMPK and AMPK-independent signals in contracting skeletal muscles, we conducted a metabolomic analysis that compared the metabolic effects of 5-aminoimidazole-4-carboxamide-1-β-D-ribonucleoside (AICAR) stimulation with the electrical contraction ex vivo in isolated rat epitrochlearis muscles, in which both α1- and α2-isoforms of AMPK and glucose uptake were equally activated. The metabolomic analysis using capillary electrophoresis time-of-flight mass spectrometry detected 184 peaks and successfully annotated 132 small molecules. AICAR stimulation exhibited high similarity to the electrical contraction in overall metabolites. Principal component analysis (PCA) demonstrated that the major principal component characterized common effects whereas the minor principal component distinguished the difference. PCA and a factor analysis suggested a substantial change in redox status as a result of AMPK activation. We also found a decrease in reduced glutathione levels in both AICAR-stimulated and contracting muscles. The muscle contraction-evoked influences related to the metabolism of amino acids, in particular, aspartate, alanine, or lysine, are supposed to be independent of AMPK activation. Our results substantiate the significance of AMPK activation in contracting skeletal muscles and provide novel evidence that AICAR stimulation closely mimics the metabolomic changes in the contracting skeletal muscles.

  20. Metabolomics as a Potential Chemotaxonomical Tool: Application in the Genus Vernonia Schreb

    PubMed Central

    Martucci, Maria Elvira Poleti; De Vos, Ric C. H.; Carollo, Carlos Alexandre; Gobbo-Neto, Leonardo

    2014-01-01

    The taxonomic classification of the genus Vernonia Schreb is complex and, as yet, unclear. We here report the use of untargeted metabolomics approaches, followed by multivariate analyses methods and a phytochemical characterization of ten Vernonia species. Metabolic fingerprints were obtained by accurate mass measurements and used to determine the phytochemical similarities and differences between species through multivariate analyses approaches. Principal component analysis based on the relative levels of 528 metabolites, indicated that the ten species could be clustered into four groups. Thereby, V. polyanthes was the only species with presence of flavones chrysoeriol-7-O-glycuronyl, acacetin-7-O-glycuronyl and sesquiterpenes lactones piptocarphin A and piptocarphin B, while glaucolide A was detected in both V. brasiliana and V. polyanthes, separating these species from the two other species of the Vernonanthura group. Species from the Lessingianthus group were unique in showing a positive response in the foam test, suggesting the presence of saponins, which could be confirmed by metabolite annotation. V. rufogrisea showed a great variety of sesquiterpene lactones, placing this species into a separate group. Species within the Chrysolaena group were unique in accumulating clovamide. Our results of LC-MS-based profiling combined with multivariate analyses suggest that metabolomics approaches, such as untargeted LC-MS, may be potentially used as a large-scale chemotaxonomical tool, in addition to classical morphological and cytotaxonomical approaches, in order to facilitate taxonomical classifications. PMID:24736747