Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Brief Communication
  • Published:

Accelerated discovery via a whole-cell model

Nature Methods volume 10, pages 1192–1195 (2013)Cite this article

Subjects

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.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Model-driven discovery and the quantitative prediction of growth phenotypes.
Figure 2: The whole-cell model quantitatively predicts rate constants of metabolic reactions.
Figure 3: Model-driven discovery.

Similar content being viewed by others

References

  1. Morowitz, H.J. Isr. J. Med. Sci. 20, 750–753 (1984).

    CAS  PubMed  Google Scholar 

  2. Suthers, P.F. et al. PLOS Comput. Biol. 5, e1000285 (2009).

    Article  Google Scholar 

  3. Browning, S.T. & Shuler, M.L. Biotechnol. Bioeng. 76, 187–192 (2001).

    Article  CAS  Google Scholar 

  4. Tomita, M. et al. Bioinformatics 15, 72–84 (1999).

    Article  CAS  Google Scholar 

  5. Karr, J.R. et al. Cell 150, 389–401 (2012).

    Article  CAS  Google Scholar 

  6. Glass, J.I. et al. Proc. Natl. Acad. Sci. USA 103, 425–430 (2006).

    Article  CAS  Google Scholar 

  7. Orth, J.D., Thiele, I. & Palsson, B.O. Nat. Biotechnol. 28, 245–248 (2010).

    Article  CAS  Google Scholar 

  8. Covert, M.W., Knight, E.M., Reed, J.L., Herrgard, M.L. & Palsson, B.O. Nature 429, 92–96 (2004).

    Article  CAS  Google Scholar 

  9. Edwards, J.S. & Palsson, B.O. BMC Bioinformatics 1, 1 (2000).

    Article  CAS  Google Scholar 

  10. Savinell, J.M. & Palsson, B.O. J. Theor. Biol. 155, 215–242 (1992).

    Article  CAS  Google Scholar 

  11. Maier, T. et al. Mol. Syst. Biol. 7, 511 (2011).

    Article  Google Scholar 

  12. Gibson, D.G. et al. Nat. Methods 6, 343–345 (2009).

    Article  CAS  Google Scholar 

  13. Schelling, P., Folkers, G. & Scapozza, L. Anal. Biochem. 295, 82–87 (2001).

    Article  CAS  Google Scholar 

  14. Lester, L.M., Rusch, L.A., Robinson, G.J. & Speckhard, D.C. Biochemistry 37, 5349–5355 (1998).

    Article  CAS  Google Scholar 

  15. Leer, J.C., Hammer-Jespersen, K. & Schwartz, M. Eur. J. Biochem. 75, 217–224 (1977).

    Article  CAS  Google Scholar 

  16. Fong, S.S. & Palsson, B.O. Nat. Genet. 36, 1056–1058 (2004).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We acknowledge support from: an US National Institutes of Health Pioneer Award (5DP1LM01150-05) and an Allen Distinguished Investigator Award to M.W.C.; Siebel Scholars, US National Science Foundation and Stanford University Bio-X Fellowships to J.C.S.; an European Molecular Biology Organization Fellowship (ALTF1371-2011) to S.R.; US National Defense Science and Engineering Graduate Fellowship, US National Science Foundation fellowship, and Stanford Graduate Fellowship to J.R.K.; and Weiland and Rensselaer Engineering Fellowships to M.V.G.

Author information

Author notes

  1. Jayodita C Sanghvi

    Present address: Present address: Institute for Quantitative Biosciences, University of California Berkeley, Berkeley, California, USA.,

Authors and Affiliations

  1. Department of Bioengineering, Stanford University, Stanford, California, USA

    Jayodita C Sanghvi, Sergi Regot, Silvia Carrasco, Miriam V Gutschow, Benjamin Bolival Jr & Markus W Covert

  2. Graduate Program in Biophysics, Stanford University, Stanford, California, USA

    Jonathan R Karr

Authors
  1. Jayodita C Sanghvi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sergi Regot
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Silvia Carrasco
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jonathan R Karr
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Miriam V Gutschow
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Benjamin Bolival Jr
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Markus W Covert
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

J.C.S., J.R.K. and M.W.C. performed the simulations and computational analysis; J.C.S., S.R. and S.C. performed the enzyme expression and kinetic assays; J.C.S., J.R.K., M.V.G. and B.B. performed the growth rate measurements; J.C.S., S.R. and M.W.C. wrote the paper; and M.W.C. supervised the project.

Corresponding author

Correspondence to Markus W Covert.

Ethics declarations

Competing interests

J.C.S., J.R.K. and M.W.C. are listed as inventors on a Patent Cooperation Treaty (PCT) international patent application (PCT/US2013/051167) related to whole-cell modeling.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–5, Supplementary Tables 2 and 3, and Supplementary Results (PDF 1751 kb)

Supplementary Table 1

Details of the chromosome map and growth assay data. Table listing all of the genes in the M. genitalium genome, together with the model/experimental comparison category, as well as the model predicted and experimentally measured (where applicable) growth rates for each disruption strain in the study and wild type. The sample size, standard deviation, t-test, and Wilcoxon test results are also listed. Six of the genes (MG051, MG112, MG271, MG291, MG385 and MG437) were reported as isolated, but unculturable in our growth assay; we considered these genes essential for the purposes of our study. #N/A = not applicable, this was used in cases where the genes were essential and no quantitative growth rate data could be obtained. (XLSX 67 kb)

Source data

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sanghvi, J., Regot, S., Carrasco, S. et al. Accelerated discovery via a whole-cell model. Nat Methods 10, 1192–1195 (2013). https://doi.org/10.1038/nmeth.2724

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nmeth.2724

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing