The completion of the genome sequence for an organism such as a disease-causing bacterium marks the start of a phase of accelerated research that can now lead to the production of a quantitative metabolic flux model for the organism. Such metabolic flux models have diverse applications. They enable basic scientific understanding of biochemical pathways. They allow computational predictions of which genes and reactions within the metabolic network are essential, thus facilitating the design of drugs against disease-causing bacteria. They support the engineering of new metabolic pathways, such as for bioenergy research. The huge quantity of data and knowledge defined by the genome sequence, and by the large number of past and future experimental findings for the organism, requires using a database as a central repository for information about the genome, the biochemical network, and the regulatory processes of that organism. The Pathway Tools software is a robust and comprehensive system for constructing organism-specific databases, and for pathway analysis of genomes. Pathway Tools enables communities of scientists to create, query, visualize, analyze MODs, and to publish the MODs on the web. Pathway Tools supports construction of MODs that combine a large number of bioinformatics datatypes, including genome maps, genes, operons, RNAs, proteins, chemical compounds, biochemical reactions, metabolic pathways, and regulatory interactions. Pathway Tools is a mature and production grade software environment that has been used by 264 groups outside SRI (see Appendix) to analyze 1,969 genomes. We propose major improvements to the new Pathway Tools module for producing metabolic flux models for individual organisms and for microbial communities. This tool allows much faster creation of these complex models than does comparable tools. We propose to perform a major redesign of the Pathway Tools web interfaces. We propose to enhance the Pathway Tools web metabolic network diagram and regulatory network diagram, which provide interactive, web-based cellular network maps. We propose to create a change-reporting system for notifying scientists of updates to Pathway Tools databases. We propose to create a tool for inferring multimeric protein complexes in sequenced genomes, and to extend Pathway Tools with several sequence-related operations. We propose to provide support services for the large and growing user community for Pathway Tools, to maintain quality documentation for the software, and to create two thoroughly tested releases of the software per year.

Public Health Relevance

The proposed project will generate software tools that increase the ability of scientists to use genome sequence data to advance human health. This software enables creating central database repositories and websites con- training genome data and data on cellular networks for disease-causing bacteria, and for experimental model organisms such as the laboratory mouse. The software allows researchers to access the most up-to-date information about those organisms using intuitive querying tools, and provides scientific visualization capabilities that aid scientists in more quickly understanding large, complex collections of data, and applying that data to advance health.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
2R01GM075742-09A1
Application #
8290089
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Sledjeski, Darren D
Project Start
2005-04-01
Project End
2016-05-31
Budget Start
2012-07-01
Budget End
2013-05-31
Support Year
9
Fiscal Year
2012
Total Cost
$1,057,181
Indirect Cost
$483,853
Name
Sri International
Department
Type
DUNS #
009232752
City
Menlo Park
State
CA
Country
United States
Zip Code
94025
Karp, Peter D; Latendresse, Mario; Paley, Suzanne M et al. (2016) Pathway Tools version 19.0 update: software for pathway/genome informatics and systems biology. Brief Bioinform 17:877-90
Paley, Suzanne; O'Maille, Paul E; Weaver, Daniel et al. (2016) Pathway collages: personalized multi-pathway diagrams. BMC Bioinformatics 17:529
Caspi, Ron; Billington, Richard; Ferrer, Luciana et al. (2016) The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Res 44:D471-80
Paley, Suzanne; Krummenacker, Markus; Karp, Peter D (2016) Representation and inference of cellular architecture for metabolic reconstruction and modeling. Bioinformatics 32:1074-9
Karp, Peter D; Billington, Richard; Holland, Timothy A et al. (2015) Computational Metabolomics Operations at BioCyc.org. Metabolites 5:291-310
Dingerdissen, Hayley; Weaver, Daniel S; Karp, Peter D et al. (2014) A framework for application of metabolic modeling in yeast to predict the effects of nsSNV in human orthologs. Biol Direct 9:9
Latendresse, Mario (2014) Efficiently gap-filling reaction networks. BMC Bioinformatics 15:225
Hanson, Niels W; Konwar, Kishori M; Hawley, Alyse K et al. (2014) Metabolic pathways for the whole community. BMC Genomics 15:619
Caspi, Ron; Altman, Tomer; Billington, Richard et al. (2014) The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases. Nucleic Acids Res 42:D459-71
Caspi, Ron; Dreher, Kate; Karp, Peter D (2013) The challenge of constructing, classifying, and representing metabolic pathways. FEMS Microbiol Lett 345:85-93

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