title: Accelerated discovery via a whole-cell model.
abstract: To test the promise of whole-cell modeling to facilitate scientific inquiry, we compared growth rates simulated in a whole-cell model with experimental measurements for all viable single-gene disruption Mycoplasma genitalium strains. Discrepancies between simulations and experiments led to predictions about kinetic parameters of specific enzymes that we subsequently validated. These findings represent, to our knowledge, the first application of whole-cell modeling to accelerate biological discovery.
authors.affiliation: 1] Department of Bioengineering, Stanford University, Stanford, California, USA. [2].
authors.forename: Jayodita C
authors.initials: JC
authors.lastname: Sanghvi
authors.forename: Sergi
authors.initials: S
authors.lastname: Regot
authors.forename: Silvia
authors.initials: S
authors.lastname: Carrasco
authors.forename: Jonathan R
authors.initials: JR
authors.lastname: Karr
authors.forename: Miriam V
authors.initials: MV
authors.lastname: Gutschow
authors.forename: Benjamin
authors.initials: B
authors.lastname: Bolival
authors.forename: Markus W
authors.initials: MW
authors.lastname: Covert
mesh_terms: D001426:Bacterial Proteins / Q000378:metabolism; D002384:Catalysis; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D020869:Gene Expression Profiling; D015964:Gene Expression Regulation, Bacterial; D053263:Gene Regulatory Networks; D005798:Genes, Bacterial / Q000235:genetics; D008954:Models, Biological; D045704:Mycoplasma genitalium / Q000235:genetics* / Q000378:metabolism*; D010641:Phenotype; D012044:Regression Analysis; D015203:Reproducibility of Results; D049490:Systems Biology
chemical_list: D001426:Bacterial Proteins