Genome-Scale Reconstruction Of Human Metabolism
Tech ID: 19464 / UC Case 2006-294-0
Background
Historically, metabolic networks have been studied in a piecemeal fashion using biochemical, then genomic and proteomic approaches. The abundance and complexity of data dwarfed the ability to understand and use the information in an intelligent and integrated fashion. The development of systems-level, computational approaches have provided new tools for extracting useful information from the morass.Technology Description
Human genomic information (NCI Build 35) and over 50 years of legacy data were manually reconstructed to yield a global human metabolic network, which was mathematically represented as an in silico model. This was used to compute allowable network states under governing chemical and genetic constraints. The product of this endeavor (“Recon 1”) is a comprehensive reconstruction of human metabolism, which was validated by five iterative rounds of reconstruction and simulation of 288 known metabolic functions found in a variety of cell and tissue types.
Furthermore, Recon 1 includes:
- Carefully formulated metabolites and reactions, based on 2,004 proteins, 2,766 metabolites, and 3,311 metabolic and transport reactions.
- Full compartmentalization of metabolites in and their exchange between seven intracellular locations .
- Precise Boolean descriptions of gene-protein relationships (e.g., alternatively spliced variants, protein complexes, and isozymes).
- Confidence scores and literature references based on known biological evidence associated with each gene, protein, and reaction.
Applications
Recon 1 is a mathematically-structured database that enables systematic studies of human metabolism, which:- enables the identification of gaps in our understanding of human metabolism.
- facilitates the computational interrogation of the overall properties of the human metabolic network.
- provides context for analysis of ‘-omics’ data sets.
- may be used as a tool for discovery and for the
analysis and interpretation of high-throughput data.
It is anticipated that these capabilities will likely
be critical in elucidating underlying mechanisms of
disease and identifying treatment strategies by developing
cell-specific, tissue-specific, and context-specific
models and building additional layers of complexity
(such as gene regulation) into the framework.
Related Materials
- Duarte et. al., PNAS, 2007 Feb 6;104(6):1777-82.
- http://gcrg.ucsd.edu/personnel/palsson.htm
- The entire contents of Homo sapiens Recon 1 is available in several formats (searchable database, metabolite and reaction lists, human-specific metabolic maps, stoichiometric matrix, Systems Biology Markup Language) at http://bigg.ucsd.edu.
Intellectual Property Info
U.S. and international patents pending.Patent Status
| Country | Type | Number | Dated | Case |
| United States Of America | Issued Patent | 7,788,041 | 08/31/2010 | 2006-294 |
Other Information
Related cases
2006-294-0
Keywords
metabolic, networks, genomic, proteomic, computational, model, discovery, platform, framework
Contact
University of California, San Diego Technology Transfer Office / invent@ucsd.edu / tel: View Phone Number. Please reference Tech ID #19464.