ArticlePLoS computational biology2009
Genome-scale reconstruction of Escherichia coli's transcriptional and translational machinery: a knowledge base, its mathematical formulation, and its functional characterization.
Article in PLoS computational biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 94 papers.
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Who cites it
94 citing papers in PubMed, 189 citations in OpenAlex.
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- How reliable are Chinese hamster ovary (CHO) cell genome-scale metabolic models?Biotechnology and bioengineering · 2023Article
- Genome-scale models as a vehicle for knowledge transfer from microbial to mammalian cell systems.Computational and structural biotechnology journal · 2023Review
- Construction of Multiscale Genome-Scale Metabolic Models: Frameworks and Challenges.Biomolecules · 2022Review
- Genome-Scale Reconstruction of Microbial Dynamic Phenotype: Successes and Challenges.Microorganisms · 2021Review
- Expression Dysregulation as a Mediator of Fitness Costs in Antibiotic Resistance.Antimicrobial agents and chemotherapy · 2021Article
- BiPSim: a flexible and generic stochastic simulator for polymerization processes.Scientific reports · 2021Article
- Datanator: an integrated database of molecular data for quantitatively modeling cellular behavior.Nucleic acids research · 2021Article
- Reconstructing organisms in silico: genome-scale models and their emerging applications.Nature reviews. Microbiology · 2020Review
- Transforming the study of organisms: Phenomic data models and knowledge bases.PLoS computational biology · 2020Review
- The Bitome: digitized genomic features reveal fundamental genome organization.Nucleic acids research · 2020Article
- VFFVA: dynamic load balancing enables large-scale flux variability analysis.BMC bioinformatics · 2020Article
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34 more citing papers are in PubMed but not listed here.
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Metabolic network reconstructions represent valuable scaffolds for '-omics' data integration and are used to computationally interrogate network properties. However, they do not explicitly account for the synthesis of macromolecules (i.e., proteins and RNA). Here, we present the first genome-scale, fine-grained reconstruction of Escherichia coli's transcriptional and translational machinery, which produces 423 functional gene products in a sequence-specific manner and accounts for all necessary chemical transformations. Legacy data from over 500 publications and three databases were reviewed, and many pathways were considered, including stable RNA maturation and modification, protein complex formation, and iron-sulfur cluster biogenesis. This reconstruction represents the most comprehensive knowledge base for these important cellular functions in E. coli and is unique in its scope. Furthermore, it was converted into a mathematical model and used to: (1) quantitatively integrate gene expression data as reaction constraints and (2) compute functional network states, which were compared to reported experimental data. For example, the model predicted accurately the ribosome production, without any parameterization. Also, in silico rRNA operon deletion suggested that a high RNA polymerase density on the remaining rRNA operons is needed to reproduce the reported experimental ribosome numbers. Moreover, functional protein modules were determined, and many were found to contain gene products from multiple subsystems, highlighting the functional interaction of these proteins. This genome-scale reconstruction of E. coli's transcriptional and translational machinery presents a milestone in systems biology because it will enable quantitative integration of '-omics' datasets and thus the study of the mechanistic principles underlying the genotype-phenotype relationship.
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