Bioinformatics Approaches to Integrate Metabolomics and Other Systems Biology Data

In this chapter we have addressed some of the bioinformatic issues related to metabolomics and its integration within the systems biology framework. We believe that metabolite, transcript, and protein analyses are much more powerful combined than individually. In order to extract maximal benefit from such combined studies, specific bioinformatics support is necessary in the form of databases, visualization, and data analysis. Ultimately, a full understanding of the underlying phenomena will require an additional layer of computational and theoretical tools, supporting the formulation and evaluation of dynamic models that attempt to represent the biological system. Such models will need to be predictive, but we believe that, much more than that, they need to be explanatory. Within our laboratory we are pursuing several projects in this direction and have a strong interest in combining that approach with the data and informatics systems described here, as have others. This will be a topic of much discussion in the near future and we await it with excitement.

[1]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[2]  I. Wilson,et al.  Physiological variation in metabolic phenotyping and functional genomic studies: use of orthogonal signal correction and PLS‐DA , 2002, FEBS letters.

[3]  Rolf Apweiler,et al.  Common interchange standards for proteomics data: Public availability of tools and schema. Report on the Proteomic Standards Initiative Workshop, 2nd Annual HUPO Congress, Montreal, Canada, 8–11th October 2003 , 2004, Proteomics.

[4]  P. Mendes,et al.  Chapter One Bioinformatics and computational biology for plant functional genomics , 2002 .

[5]  D. Kell.  Metabolomics and systems biology: making sense of the soup. , 2004, Current opinion in microbiology.

[6]  R. Goodacre,et al.  Metabolic Profiling: Its Role in Biomarker Discovery and Gene Function Analysis , 2003, Springer US.

[7]  D. Kell,et al.  High-throughput classification of yeast mutants for functional genomics using metabolic footprinting , 2003, Nature Biotechnology.

[8]  W. Weckwerth.  Metabolomics in systems biology. , 2003, Annual review of plant biology.

[9]  D. Kell,et al.  Metabolomics by numbers: acquiring and understanding global metabolite data. , 2004, Trends in biotechnology.

[10]  D B Kell,et al.  Detection of the dipicolinic acid biomarker in Bacillus spores using Curie-point pyrolysis mass spectrometry and Fourier transform infrared spectroscopy. , 2000, Analytical chemistry.

[11]  Peter D. Karp,et al.  MetaCyc: a multiorganism database of metabolic pathways and enzymes. , 2004, Nucleic acids research.

[12]  Hiroaki Kitano,et al.  Foundations of systems biology , 2001 .

[13]  S. Rhee,et al.  MAPMAN: a user-driven tool to display genomics data sets onto diagrams of metabolic pathways and other biological processes. , 2004, The Plant journal : for cell and molecular biology.

[14]  Kara Dolinski,et al.  Saccharomyces genome database: Underlying principles and organisation , 2004, Briefings Bioinform..

[15]  P. Mendes,et al.  The origin of correlations in metabolomics data , 2005, Metabolomics.

[16]  J. Kopka,et al.  Construction and application of a mass spectral and retention time index database generated from plant GC/EI-TOF-MS metabolite profiles. , 2003, Phytochemistry.

[17]  David M. Rocke,et al.  Discrimination models using variance-stabilizing transformation of metabolomic NMR data. , 2004, Omics : a journal of integrative biology.

[18]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[19]  H. Kitano.  Systems Biology: A Brief Overview , 2002, Science.

[20]  A. Fernie,et al.  Metabolite profiling: from diagnostics to systems biology , 2004, Nature Reviews Molecular Cell Biology.

[21]  R. Goodacre,et al.  Metabolic fingerprinting of salt-stressed tomatoes. , 2003, Phytochemistry.

[22]  Mariusz Kowalczyk,et al.  A strategy for identifying differences in large series of metabolomic samples analyzed by GC/MS. , 2004, Analytical chemistry.

[23]  Chris F. Taylor,et al.  A systematic approach to modeling, capturing, and disseminating proteomics experimental data , 2003, Nature Biotechnology.

[24]  Antoine H. C. van Kampen,et al.  Visualizing metabolic activity on a genome-wide scale , 2002, Bioinform..

[25]  Eve Syrkin Wurtele,et al.  Functional genomics: high-throughput mRNA, protein, and metabolite analyses. , 2002, Metabolic engineering.

[26]  Nigel W. Hardy,et al.  A proposed framework for the description of plant metabolomics experiments and their results , 2004, Nature Biotechnology.

[27]  John Quackenbush,et al.  Computational genetics: Computational analysis of microarray data , 2001, Nature Reviews Genetics.

[28]  Jason E. Stewart,et al.  Minimum information about a microarray experiment (MIAME)—toward standards for microarray data , 2001, Nature Genetics.

[29]  Kazuki Saito,et al.  Potential of metabolomics as a functional genomics tool. , 2004, Trends in plant science.

[30]  Hiroaki Kitano,et al.  The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models , 2003, Bioinform..

[31]  Peter Buneman,et al.  Challenges in Integrating Biological Data Sources , 1995, J. Comput. Biol..

[32]  Pedro Mendes,et al.  Emerging bioinformatics for the metabolome , 2002, Briefings Bioinform..

[33]  John Quackenbush,et al.  The TIGR Gene Indices: clustering and assembling EST and known genes and integration with eukaryotic genomes , 2004, Nucleic Acids Res..

[34]  Ulrike Wittig,et al.  Analysis and Comparison of Metabolic Pathway Databases , 2001, Briefings Bioinform..

[35]  D. Kell,et al.  A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations , 2001, Nature Biotechnology.

[36]  Antony N. Davies.  The new Automated Mass Spectrometry Deconvolution and Identification System (AMDIS) , 1998 .

[37]  K. Brindle,et al.  Discrimination of pathogenic clinical isolates and laboratory strains of Bacillus cereus by NMR-based metabolomic profiling. , 2005, FEMS microbiology letters.

[38]  B. M. Lange,et al.  Comprehensive post-genomic data analysis approaches integrating biochemical pathway maps. , 2005, Phytochemistry.

[39]  R. Goodacre.  Making sense of the metabolome using evolutionary computation: seeing the wood with the trees. , 2004, Journal of experimental botany.

[40]  Honglian Shi,et al.  Development of biomarkers based on diet-dependent metabolic serotypes: practical issues in development of expert system-based classification models in metabolomic studies. , 2004, Omics : a journal of integrative biology.

[41]  Jürgen Kurths,et al.  Observing and Interpreting Correlations in Metabolic Networks , 2003, Bioinform..

[42]  R. Dixon,et al.  Plant metabolomics: large-scale phytochemistry in the functional genomics era. , 2003, Phytochemistry.

[43]  Jan van der Greef,et al.  Characterization of anti-inflammatory compounds using transcriptomics, proteomics, and metabolomics in combination with multivariate data analysis. , 2004, International immunopharmacology.

[44]  S. Rhee,et al.  AraCyc: A Biochemical Pathway Database for Arabidopsis1 , 2003, Plant Physiology.

[45]  R. Dixon,et al.  Metabolic profiling of Medicago truncatula cell cultures reveals the effects of biotic and abiotic elicitors on metabolism. , 2005, Journal of experimental botany.

[46]  Susumu Goto,et al.  The KEGG resource for deciphering the genome , 2004, Nucleic Acids Res..

[47]  Dianjing Guo,et al.  Databases and Visualization for Metabolomics , 2003 .