MeltDB: a software platform for the analysis and integration of metabolomics experiment data

Neuweger H, Albaum S, Dondrup M, Persicke M, Watt T, Niehaus K, Stoye J, Goesmann A (2008)
Bioinformatics 24(23): 2726-2732.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
Download
Es wurden keine Dateien hochgeladen. Nur Publikationsnachweis!
Abstract / Bemerkung
Motivation: The recent advances in metabolomics have created the potential to measure the levels of hundreds of metabolites which are the end products of cellular regulatory processes. The automation of the sample acquisition and subsequent analysis in high-throughput instruments that are capable of measuring metabolites is posing a challenge on the necessary systematic storage and computational processing of the experimental datasets. Whereas a multitude of specialized software systems for individual instruments and preprocessing methods exists, there is clearly a need for a free and platform-independent system that allows the standardized and integrated storage and analysis of data obtained from metabolomics experiments. Currently there exists no such system that on the one hand supports preprocessing of raw datasets but also allows to visualize and integrate the results of higher level statistical analyses within a functional genomics context. Results: To facilitate the systematic storage, analysis and integration of metabolomics experiments, we have implemented MeltDB, a web-based software platform for the analysis and annotation of datasets from metabolomics experiments. MeltDB supports open file formats (netCDF, mzXML, mzDATA) and facilitates the integration and evaluation of existing preprocessing methods. The system provides researchers with means to consistently describe and store their experimental datasets. Comprehensive analysis and visualization features of metabolomics datasets are offered to the community through a web-based user interface. The system covers the process from raw data to the visualization of results in a knowledge-based background and is integrated into the context of existing software platforms of genomics and transcriptomics at Bielefeld University. We demonstrate the potential of MeltDB by means of a sample experiment where we dissect the influence of three different carbon sources on the gram-negative bacterium Xanthomonas campestris pv. campestris on the level of measured metabolites. Experimental data are stored, analyzed and annotated within MeltDB and accessible via the public MeltDB web server. Availability: The system is publicly available at http://meltdb.cebitec.uni-bielefeld.de.
Stichworte
Bacterial; Database Management Systems; Genome; Metabolomics; Software; Proteomics
Erscheinungsjahr
2008
Zeitschriftentitel
Bioinformatics
Band
24
Ausgabe
23
Seite(n)
2726-2732
ISSN
1367-4803
eISSN
1460-2059
Page URI
https://pub.uni-bielefeld.de/record/1636699

Zitieren

Neuweger H, Albaum S, Dondrup M, et al. MeltDB: a software platform for the analysis and integration of metabolomics experiment data. Bioinformatics. 2008;24(23):2726-2732.
Neuweger, H., Albaum, S., Dondrup, M., Persicke, M., Watt, T., Niehaus, K., Stoye, J., et al. (2008). MeltDB: a software platform for the analysis and integration of metabolomics experiment data. Bioinformatics, 24(23), 2726-2732. https://doi.org/10.1093/bioinformatics/btn452
Neuweger, Heiko, Albaum, Stefan, Dondrup, Michael, Persicke, Marcus, Watt, Tony, Niehaus, Karsten, Stoye, Jens, and Goesmann, Alexander. 2008. “MeltDB: a software platform for the analysis and integration of metabolomics experiment data”. Bioinformatics 24 (23): 2726-2732.
Neuweger, H., Albaum, S., Dondrup, M., Persicke, M., Watt, T., Niehaus, K., Stoye, J., and Goesmann, A. (2008). MeltDB: a software platform for the analysis and integration of metabolomics experiment data. Bioinformatics 24, 2726-2732.
Neuweger, H., et al., 2008. MeltDB: a software platform for the analysis and integration of metabolomics experiment data. Bioinformatics, 24(23), p 2726-2732.
H. Neuweger, et al., “MeltDB: a software platform for the analysis and integration of metabolomics experiment data”, Bioinformatics, vol. 24, 2008, pp. 2726-2732.
Neuweger, H., Albaum, S., Dondrup, M., Persicke, M., Watt, T., Niehaus, K., Stoye, J., Goesmann, A.: MeltDB: a software platform for the analysis and integration of metabolomics experiment data. Bioinformatics. 24, 2726-2732 (2008).
Neuweger, Heiko, Albaum, Stefan, Dondrup, Michael, Persicke, Marcus, Watt, Tony, Niehaus, Karsten, Stoye, Jens, and Goesmann, Alexander. “MeltDB: a software platform for the analysis and integration of metabolomics experiment data”. Bioinformatics 24.23 (2008): 2726-2732.

51 Zitationen in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

Micro-organisms growing on rapeseed during storage affect the profile of volatile compounds of virgin rapeseed oil.
Wagner C, Bonte A, Brühl L, Niehaus K, Bednarz H, Matthäus B., J Sci Food Agric 98(6), 2018
PMID: 28960362
Linking root exudates to functional plant traits.
Herz K, Dietz S, Gorzolka K, Haider S, Jandt U, Scheel D, Bruelheide H., PLoS One 13(10), 2018
PMID: 30281675
Systems and synthetic biology perspective of the versatile plant-pathogenic and polysaccharide-producing bacterium Xanthomonas campestris.
Schatschneider S, Schneider J, Blom J, Létisse F, Niehaus K, Goesmann A, Vorhölter FJ., Microbiology 163(8), 2017
PMID: 28795660
Genetic regulation and manipulation for natural product discovery.
Chen J, Wu Q, Hawas UW, Wang H., Appl Microbiol Biotechnol 100(7), 2016
PMID: 26860941
The Metabolic Signature of Biomass Formation in Barley.
Ghaffari MR, Shahinnia F, Usadel B, Junker B, Schreiber F, Sreenivasulu N, Hajirezaei MR., Plant Cell Physiol 57(9), 2016
PMID: 27388338
Bioinformatics: the next frontier of metabolomics.
Johnson CH, Ivanisevic J, Benton HP, Siuzdak G., Anal Chem 87(1), 2015
PMID: 25389922
Workflow4Metabolomics: a collaborative research infrastructure for computational metabolomics.
Giacomoni F, Le Corguillé G, Monsoor M, Landi M, Pericard P, Pétéra M, Duperier C, Tremblay-Franco M, Martin JF, Jacob D, Goulitquer S, Thévenot EA, Caron C., Bioinformatics 31(9), 2015
PMID: 25527831
Learning to Classify Organic and Conventional Wheat - A Machine Learning Driven Approach Using the MeltDB 2.0 Metabolomics Analysis Platform.
Kessler N, Bonte A, Albaum SP, Mäder P, Messmer M, Goesmann A, Niehaus K, Langenkämper G, Nattkemper TW., Front Bioeng Biotechnol 3(), 2015
PMID: 25853128
Metabolite profiling of somatic embryos of Cyclamen persicum in comparison to zygotic embryos, endosperm, and testa.
Winkelmann T, Ratjens S, Bartsch M, Rode C, Niehaus K, Bednarz H., Front Plant Sci 6(), 2015
PMID: 26300898
Missing value imputation strategies for metabolomics data.
Armitage EG, Godzien J, Alonso-Herranz V, López-Gonzálvez Á, Barbas C., Electrophoresis 36(24), 2015
PMID: 26376450
Metabolic Adaptations of White Lupin Roots and Shoots under Phosphorus Deficiency.
Müller J, Gödde V, Niehaus K, Zörb C., Front Plant Sci 6(), 2015
PMID: 26635840
Metabolite profiling on wheat grain to enable a distinction of samples from organic and conventional farming systems.
Bonte A, Neuweger H, Goesmann A, Thonar C, Mäder P, Langenkämper G, Niehaus K., J Sci Food Agric 94(13), 2014
PMID: 24425170
Extraction for metabolomics: access to the metabolome.
Mushtaq MY, Choi YH, Verpoorte R, Wilson EG., Phytochem Anal 25(4), 2014
PMID: 24523261
Metabolic flux pattern of glucose utilization by Xanthomonas campestris pv. campestris: prevalent role of the Entner-Doudoroff pathway and minor fluxes through the pentose phosphate pathway and glycolysis.
Schatschneider S, Huber C, Neuweger H, Watt TF, Pühler A, Eisenreich W, Wittmann C, Niehaus K, Vorhölter FJ., Mol Biosyst 10(10), 2014
PMID: 25072918
Metabolite profiling on wheat grain to enable a distinction of samples from organic and conventional farming systems
Bonte A, Neuweger H, Goesmann A, Thonar C, Mäder P, Langenkämper G, Niehaus K., J Sci Food Agric 94(13), 2014
PMID: IND600814173
Metabolomic study of Chilean biomining bacteria Acidithiobacillus ferrooxidans strain Wenelen and Acidithiobacillus thiooxidans strain Licanantay.
Martínez P, Gálvez S, Ohtsuka N, Budinich M, Cortés MP, Serpell C, Nakahigashi K, Hirayama A, Tomita M, Soga T, Martínez S, Maass A, Parada P., Metabolomics 9(1), 2013
PMID: 23335869
Tools for the functional interpretation of metabolomic experiments.
Chagoyen M, Pazos F., Brief Bioinform 14(6), 2013
PMID: 23063930
Metabolomic fingerprinting: challenges and opportunities.
Kosmides AK, Kamisoglu K, Calvano SE, Corbett SA, Androulakis IP., Crit Rev Biomed Eng 41(3), 2013
PMID: 24579644
Computational tools for the secondary analysis of metabolomics experiments.
Booth SC, Weljie AM, Turner RJ., Comput Struct Biotechnol J 4(), 2013
PMID: 24688685
Computational mass spectrometry for small molecules.
Scheubert K, Hufsky F, Böcker S., J Cheminform 5(1), 2013
PMID: 23453222
MeltDB 2.0-advances of the metabolomics software system.
Kessler N, Neuweger H, Bonte A, Langenkämper G, Niehaus K, Nattkemper TW, Goesmann A., Bioinformatics 29(19), 2013
PMID: 23918246
Metabolite profiling of wheat flag leaf and grains during grain filling phase as affected by sulfur fertilisation
Zörb C, Steinfurth D, Gödde V, Niehaus K, Mühling KH., Funct Plant Biol 39(2), 2012
PMID: IND44676479
Computational tools for metabolic engineering.
Copeland WB, Bartley BA, Chandran D, Galdzicki M, Kim KH, Sleight SC, Maranas CD, Sauro HM., Metab Eng 14(3), 2012
PMID: 22629572
MetaboAnalyst 2.0--a comprehensive server for metabolomic data analysis.
Xia J, Mandal R, Sinelnikov IV, Broadhurst D, Wishart DS., Nucleic Acids Res 40(web server issue), 2012
PMID: 22553367
EasyLCMS: an asynchronous web application for the automated quantification of LC-MS data.
Fructuoso S, Sevilla A, Bernal C, Lozano AB, Iborra JL, Cánovas M., BMC Res Notes 5(), 2012
PMID: 22884039
Combining peak- and chromatogram-based retention time alignment algorithms for multiple chromatography-mass spectrometry datasets.
Hoffmann N, Keck M, Neuweger H, Wilhelm M, Högy P, Niehaus K, Stoye J., BMC Bioinformatics 13(), 2012
PMID: 22920415
metaP-server: a web-based metabolomics data analysis tool.
Kastenmüller G, Römisch-Margl W, Wägele B, Altmaier E, Suhre K., J Biomed Biotechnol 2011(), 2011
PMID: 20936179
Pathogenomics of Xanthomonas: understanding bacterium-plant interactions.
Ryan RP, Vorhölter FJ, Potnis N, Jones JB, Van Sluys MA, Bogdanove AJ, Dow JM., Nat Rev Microbiol 9(5), 2011
PMID: 21478901
Metabolomic data processing, analysis, and interpretation using MetaboAnalyst.
Xia J, Wishart DS., Curr Protoc Bioinformatics Chapter 14(), 2011
PMID: 21633943
MeRy-B: a web knowledgebase for the storage, visualization, analysis and annotation of plant NMR metabolomic profiles.
Ferry-Dumazet H, Gil L, Deborde C, Moing A, Bernillon S, Rolin D, Nikolski M, de Daruvar A, Jacob D., BMC Plant Biol 11(), 2011
PMID: 21668943
Knowledge discovery in metabolomics: an overview of MS data handling.
Boccard J, Veuthey JL, Rudaz S., J Sep Sci 33(3), 2010
PMID: 20087872
Practical metabolomics in drug discovery.
Wilcoxen KM, Uehara T, Myint KT, Sato Y, Oda Y., Expert Opin Drug Discov 5(3), 2010
PMID: 22823021
MSEA: a web-based tool to identify biologically meaningful patterns in quantitative metabolomic data.
Xia J, Wishart DS., Nucleic Acids Res 38(web server issue), 2010
PMID: 20457745
Enhancement of plant metabolite fingerprinting by machine learning.
Scott IM, Vermeer CP, Liakata M, Corol DI, Ward JL, Lin W, Johnson HE, Whitehead L, Kular B, Baker JM, Walsh S, Dave A, Larson TR, Graham IA, Wang TL, King RD, Draper J, Beale MH., Plant Physiol 153(4), 2010
PMID: 20566707
EMMA 2--a MAGE-compliant system for the collaborative analysis and integration of microarray data.
Dondrup M, Albaum SP, Griebel T, Henckel K, Jünemann S, Kahlke T, Kleindt CK, Küster H, Linke B, Mertens D, Mittard-Runte V, Neuweger H, Runte KJ, Tauch A, Tille F, Pühler A, Goesmann A., BMC Bioinformatics 10(), 2009
PMID: 19200358
MetaboAnalyst: a web server for metabolomic data analysis and interpretation.
Xia J, Psychogios N, Young N, Wishart DS., Nucleic Acids Res 37(web server issue), 2009
PMID: 19429898
Visualizing post genomics data-sets on customized pathway maps by ProMeTra-aeration-dependent gene expression and metabolism of Corynebacterium glutamicum as an example.
Neuweger H, Persicke M, Albaum SP, Bekel T, Dondrup M, Hüser AT, Winnebald J, Schneider J, Kalinowski J, Goesmann A., BMC Syst Biol 3(), 2009
PMID: 19698148
Qupe--a Rich Internet Application to take a step forward in the analysis of mass spectrometry-based quantitative proteomics experiments.
Albaum SP, Neuweger H, Fränzel B, Lange S, Mertens D, Trötschel C, Wolters D, Kalinowski J, Nattkemper TW, Goesmann A., Bioinformatics 25(23), 2009
PMID: 19808875

35 References

Daten bereitgestellt von Europe PubMed Central.

Comprehensive metabolite profiling of Sinorhizobium meliloti using gas chromatography-mass spectrometry.
Barsch A, Patschkowski T, Niehaus K., Funct. Integr. Genomics 4(4), 2004
PMID: 15372312
Potential of metabolomics as a functional genomics tool.
Bino RJ, Hall RD, Fiehn O, Kopka J, Saito K, Draper J, Nikolau BJ, Mendes P, Roessner-Tunali U, Beale MH, Trethewey RN, Lange BM, Wurtele ES, Sumner LW., Trends Plant Sci. 9(9), 2004
PMID: 15337491
MET-IDEA: data extraction tool for mass spectrometry-based metabolomics.
Broeckling CD, Reddy IR, Duran AL, Zhao X, Sumner LW., Anal. Chem. 78(13), 2006
PMID: 16808440
EMMA: a platform for consistent storage and efficient analysis of microarray data.
Dondrup M, Goesmann A, Bartels D, Kalinowski J, Krause L, Linke B, Rupp O, Sczyrba A, Puhler A, Meyer F., J. Biotechnol. 106(2-3), 2003
PMID: 14651856
Metabolomics: Current analytical platforms and methodologies
Dunn, Trends Anal. Chem. 4(), 2005
Nomenclature for Chromatography (IUPAC Recommendations 1993)
Ettre, Pure Appl. Chem. 65(), 1993
Metabolomics--the link between genotypes and phenotypes.
Fiehn O., Plant Mol. Biol. 48(1-2), 2002
PMID: 11860207
Quality control for plant metabolomics: reporting MSI-compliant studies.
Fiehn O, Wohlgemuth G, Scholz M, Kind T, Lee DY, Lu Y, Moon S, Nikolau B., Plant J. 53(4), 2008
PMID: 18269577

Gamma, 1995
BRIGEP--the BRIDGE-based genome-transcriptome-proteome browser.
Goesmann A, Linke B, Bartels D, Dondrup M, Krause L, Neuweger H, Oehm S, Paczian T, Wilke A, Meyer F., Nucleic Acids Res. 33(Web Server issue), 2005
PMID: 15980569
Independent component analysis: algorithms and applications.
Hyvarinen A, Oja E., Neural Netw 13(4-5), 2000
PMID: 10946390
Toward supportive data collection tools for plant metabolomics.
Jenkins H, Johnson H, Kular B, Wang T, Hardy N., Plant Physiol. 138(1), 2005
PMID: 15888680
High-throughput data analysis for detecting and identifying differences between samples in GC/MS-based metabolomic analyses.
Jonsson P, Johansson AI, Gullberg J, Trygg J, A J, Grung B, Marklund S, Sjostrom M, Antti H, Moritz T., Anal. Chem. 77(17), 2005
PMID: 16131076
From genomics to chemical genomics: new developments in KEGG.
Kanehisa M, Goto S, Hattori M, Aoki-Kinoshita KF, Itoh M, Kawashima S, Katayama T, Araki M, Hirakawa M., Nucleic Acids Res. 34(Database issue), 2006
PMID: 16381885
MZmine: toolbox for processing and visualization of mass spectrometry based molecular profile data.
Katajamaa M, Miettinen J, Oresic M., Bioinformatics 22(5), 2006
PMID: 16403790
GMD@CSB.DB: the Golm Metabolome Database.
Kopka J, Schauer N, Krueger S, Birkemeyer C, Usadel B, Bergmuller E, Dormann P, Weckwerth W, Gibon Y, Stitt M, Willmitzer L, Fernie AR, Steinhauser D., Bioinformatics 21(8), 2004
PMID: 15613389
Development and validation of a spectral library searching method for peptide identification from MS/MS.
Lam H, Deutsch EW, Eddes JS, Eng JK, King N, Stein SE, Aebersold R., Proteomics 7(5), 2007
PMID: 17295354
GenDB--an open source genome annotation system for prokaryote genomes.
Meyer F, Goesmann A, McHardy AC, Bartels D, Bekel T, Clausen J, Kalinowski J, Linke B, Rupp O, Giegerich R, Puhler A., Nucleic Acids Res. 31(8), 2003
PMID: 12682369
CoryneCenter - an online resource for the integrated analysis of corynebacterial genome and transcriptome data.
Neuweger H, Baumbach J, Albaum S, Bekel T, Dondrup M, Huser AT, Kalinowski J, Oehm S, Puhler A, Rahmann S, Weile J, Goesmann A., BMC Syst Biol 1(), 2007
PMID: 18034885
Five years of progress in the Standardization of Proteomics Data 4th Annual Spring Workshop of the HUPO-Proteomics Standards Initiative April 23-25, 2007 Ecole Nationale Superieure (ENS), Lyon, France.
Orchard S, Montechi-Palazzi L, Deutsch EW, Binz PA, Jones AR, Paton N, Pizarro A, Creasy DM, Wojcik J, Hermjakob H., Proteomics 7(19), 2007
PMID: 17907277
A common open representation of mass spectrometry data and its application to proteomics research.
Pedrioli PG, Eng JK, Hubley R, Vogelzang M, Deutsch EW, Raught B, Pratt B, Nilsson E, Angeletti RH, Apweiler R, Cheung K, Costello CE, Hermjakob H, Huang S, Julian RK, Kapp E, McComb ME, Oliver SG, Omenn G, Paton NW, Simpson R, Smith R, Taylor CF, Zhu W, Aebersold R., Nat. Biotechnol. 22(11), 2004
PMID: 15529173
A dynamic programming approach for the alignment of signal peaks in multiple gas chromatography-mass spectrometry experiments.
Robinson MD, De Souza DP, Keen WW, Saunders EC, McConville MJ, Speed TP, Likic VA., BMC Bioinformatics 8(), 2007
PMID: 17963529
The metabolomics standards initiative.
MSI Board Members, Sansone SA, Fan T, Goodacre R, Griffin JL, Hardy NW, Kaddurah-Daouk R, Kristal BS, Lindon J, Mendes P, Morrison N, Nikolau B, Robertson D, Sumner LW, Taylor C, van der Werf M, van Ommen B, Fiehn O., Nat. Biotechnol. 25(8), 2007
PMID: 17687353
Setupx–a public study design database for metabolomic projects
Scholz, Pac. Symp. Biocomput. 12(), 2007
METLIN: a metabolite mass spectral database.
Smith CA, O'Maille G, Want EJ, Qin C, Trauger SA, Brandon TR, Custodio DE, Abagyan R, Siuzdak G., Ther Drug Monit 27(6), 2005
PMID: 16404815
An integrated method for spectrum extraction and compound identification from gas chromatography/mass spectrometry data
Stein, J. Am. Soc. Mass Spectrom. 10(), 1999
Metabolite profile analysis: from raw data to regression and classification
Steinfath M, Groth D, Lisec J, Selbig J., Physiol Plant 132(2), 2008
PMID: IND43999342
Observing and interpreting correlations in metabolomic networks.
Steuer R, Kurths J, Fiehn O, Weckwerth W., Bioinformatics 19(8), 2003
PMID: 12761066
MAPMAN: a user-driven tool to display genomics data sets onto diagrams of metabolic pathways and other biological processes.
Thimm O, Blasing O, Gibon Y, Nagel A, Meyer S, Kruger P, Selbig J, Muller LA, Rhee SY, Stitt M., Plant J. 37(6), 2004
PMID: 14996223

Unidata, Unidata netcdf. (), 2008
The genome of Xanthomonas campestris pv. campestris B100 and its use for the reconstruction of metabolic pathways involved in xanthan biosynthesis.
Vorholter FJ, Schneiker S, Goesmann A, Krause L, Bekel T, Kaiser O, Linke B, Patschkowski T, Ruckert C, Schmid J, Sidhu VK, Sieber V, Tauch A, Watt SA, Weisshaar B, Becker A, Niehaus K, Puhler A., J. Biotechnol. 134(1-2), 2008
PMID: 18304669
Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry.
De Vos RC, Moco S, Lommen A, Keurentjes JJ, Bino RJ, Hall RD., Nat Protoc 2(4), 2007
PMID: 17446877
Export

Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB

Web of Science

Dieser Datensatz im Web of Science®
Quellen

PMID: 18765459
PubMed | Europe PMC

Suchen in

Google Scholar