Abstract
BackgroundThe success of genome-scale models (GEMs) can be attributed to the high-quality, bottom-up reconstructions of metabolic, protein synthesis, and transcriptional regulatory networks on an organism-specific basis. Such reconstructions are biochemically, genetically, and genomically structured knowledge bases that can be converted into a mathematical format to enable a myriad of computational biological studies. In recent years, genome-scale reconstructions have been extended to include protein structural information, which has opened up new vistas in systems biology research and empowered applications in structural systems biology and systems pharmacology.ResultsHere, we present the generation, application, and dissemination of genome-scale models with protein structures (GEM-PRO) for Escherichia coli and Thermotoga maritima. We show the utility of integrating molecular scale analyses with systems biology approaches by discussing several comparative analyses on the temperature dependence of growth, the distribution of protein fold families, substrate specificity, and characteristic features of whole cell proteomes. Finally, to aid in the grand challenge of big data to knowledge, we provide several explicit tutorials of how protein-related information can be linked to genome-scale models in a public GitHub repository (https://github.com/SBRG/GEMPro/tree/master/GEMPro_recon/).ConclusionsTranslating genome-scale, protein-related information to structured data in the format of a GEM provides a direct mapping of gene to gene-product to protein structure to biochemical reaction to network states to phenotypic function. Integration of molecular-level details of individual proteins, such as their physical, chemical, and structural properties, further expands the description of biochemical network-level properties, and can ultimately influence how to model and predict whole cell phenotypes as well as perform comparative systems biology approaches to study differences between organisms. GEM-PRO offers insight into the physical embodiment of an organism’s genotype, and its use in this comparative framework enables exploration of adaptive strategies for these organisms, opening the door to many new lines of research. With these provided tools, tutorials, and background, the reader will be in a position to run GEM-PRO for their own purposes.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-016-0271-6) contains supplementary material, which is available to authorized users.
Highlights
The success of genome-scale models (GEMs) can be attributed to the high-quality, bottom-up reconstructions of metabolic, protein synthesis, and transcriptional regulatory networks on an organism-specific basis
Coverage of protein structures in metabolism We find that the coverage of all experimental (X-ray crystallography and NMR) protein structures (PDB) for genes in T. maritima and E. coli is between 30–45 %, which is 6–10 % higher compared to the original GEMPRO reconstructions (Fig. 2)
We find that the updated genome-scale models with protein structures (GEM-PRO) models make use of over 100 recently deposited experimental structures compared to the previous models
Summary
The success of genome-scale models (GEMs) can be attributed to the high-quality, bottom-up reconstructions of metabolic, protein synthesis, and transcriptional regulatory networks on an organism-specific basis. The success of genome-scale modeling can be attributed to high-quality, bottom-up reconstructions of metabolic, protein synthesis, and transcriptional regulatory networks on an organism-specific basis [1,2,3,4] Such network reconstructions are biochemically, genetically, and genomically (BiGG) structured knowledge bases [5] that can be used for discovery purposes Understanding the structural properties of proteins as well as their respective ligand binding events (e.g., metabolite, drug or oncometabolite) enables the characterization of molecularlevel events that trigger changes in states of an entire network Such a multi-scale approach acts as bridge between systems biology and structural biology, two scientific disciplines that, when combined, become the emerging field of structural systems biology [18,19,20,21,22]. This union has brought about exciting advances, which would have otherwise been out of reach: the evolution of fold families in metabolism [7], identification of causal off target actions of drugs [16], identification of protein-protein interactions [23, 24], and determination of causal mutations for disease susceptibility [24, 25]
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