Genome-scale models of metabolism and gene expression extend and refine growth phenotype prediction

By Edward J. O'Brien, Joshua A. Lerman, Roger L. Chang, Daniel R. Hyduke, Bernhard O. Palsson. Molecular Systems Biology, 2013

495 citations recorded by the source corpus.

Growth is a fundamental process of life. Growth requirements are well‐characterized experimentally for many microbes; however, we lack a unified model for cellular growth. Such a model must be predictive of events at the molecular scale and capable of explaining the high‐level behavior of the cell as a whole. Here, we construct an ME‐Model for Escherichia coli—a genome‐scale model that seamlessly integrates metabolic and gene product expression pathways. The model computes ∼80% of the functional proteome (by mass), which is used by the cell to support growth under a given condition. Metabolism and gene expression are interdependent processes that affect and constrain each other. We formalize these constraints and apply the principle of growth optimization to enable the accurate prediction of multi‐scale phenotypes, ranging from coarse‐grained (growth rate, nutrient uptake, by‐product secretion) to fine‐grained (metabolic fluxes, gene expression levels). Our results unify many existing principles developed to describe bacterial growth.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/6d1330ba40b8708481fdab8a0408eefac08a62da

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Citations in the corpus

Systematic Evaluation of Methods for Integration of Transcriptomic Data into Constraint-Based Models of Metabolism (2014, background): “These types of data can also be used to parameterize next generation of whole-cell models that explicitly represent proteins and transcripts in addition to metabolic fluxes [58,59] Finally, we would like to acknowledge the authors who published their source code with the respective articles.”
Translation of Genotype to Phenotype by a Hierarchy of Cell Subsystems (2016, methodology): “…modeling (e.g., see Cahan et al., 2014; Carrera et al., 2014; Deutscher et al., 2006; Karr et al., 2012; Lerman et al., 2012; Machado et al., 2011; O’Brien et al., 2013; Orth et al., 2010; Segre` et al., 2005; Szappanos et al., 2011; Szczurek et al., 2009; Takahashi et al., 2003; Tomita et al.,…”
Improving the phenotype predictions of a yeast genome‐scale metabolic model by incorporating enzymatic constraints (2017, methodology): “This approach has been used to confirm a limitation in enzyme capacity at a high specific growth rate in E. coli (O’Brien et al, 2013).”
MEMOTE for standardized genome-scale metabolic model testing (2020, methodology): “, to models of metabolism and expression (ME-models) (OBrien et al. 2013), kinetic (Vasilakou et al.”
Using Genome-Scale Models to Predict Biological Capabilities (2015, unknown): “The expansion in the scope and accuracy of predictions continues today, with models of increased scope (Chang et al., 2013a; O’Brien et al., 2013), discussed in section 6.”