Accelerated discovery via a whole-cell model

Details

• Alternative Title:
  Nat Methods
• Personal Author:
  Sanghvi, Jayodita C. ; Regot, Sergi ; Carrasco, Silvia ; Karr, Jonathan R. ; Gutschow, Miriam V. ; Bolival, Benjamin ; Covert, Markus W.
• Description:
  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.
• Subjects:
  Article Bacterial Proteins Catalysis Computational Biology Computer Simulation Gene Expression Profiling Gene Expression Regulation, Bacterial Gene Regulatory Networks Genes, Bacterial Models, Biological Mycoplasma Genitalium Phenotype Regression Analysis Reproducibility Of Results Systems Biology

  More +
• Source:
  Nat Methods. 10(12):1192-1195.
• Pubmed ID:
  24185838
• Pubmed Central ID:
  PMC3856890
• Document Type:
  Journal Article
• Funding:
  5DP1LM01150-05/DP/NCCDPHP CDC HHS/United States ; DP1 LM011510/LM/NLM NIH HHS/United States ; DP1 OD006413/OD/NIH HHS/United States
• Volume:
  10
• Issue:
  12
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:38820c73a7b373110b74b9fa1411a288d5c8868e85cedc9507259d2cbcc7872d
• Download URL:
  https://stacks.cdc.gov/view/cdc/29799/cdc_29799_DS1.pdf
• File Type:
  [PDF - 1014.87 KB ]