Skip to main content
SpringerLink
Log in

Reply to "Challenges in modeling the human gut microbiome"

  • Correspondence
  • Published:

From Nature Biotechnology

View current issue Submit your manuscript

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1: Growth rates of models under conditions constrained with the Western diet (minimum 0.0046 h−1, maximum 3.10 h−1, median 0.35 h−1), of generic reconstructions (minimum 11.4 h−1, maximum 255 h−1, median 76.9 h−1), and of the default downloaded collection (January 2017), which included a mix of condition-specific models and generic reconstructions (minimum 0.0045 h−1, maximum 255 h−1, median 59.7 h−1).
Figure 2: Blocked reactions and reactions involved in stoichiometrically balanced cycles (SBCs) in BiGG and AGORA reconstruction.
Figure 3: Histogram showing the Jaccard similarities between every pair of the 773 AGORA reconstructions, and of the 74 BiGG reconstructions.

References

  1. Babaei et al. Nat. Biotechnol. 36, 682–686 (2018).

    Article  CAS  Google Scholar 

  2. Magnúsdóttir, S. et al. Nat. Biotechnol. 35, 81–89 (2017).

    Article  Google Scholar 

  3. Oberhardt, M.A., Palsson, B.O. & Papin, J.A. Mol. Syst. Biol. 5, 320 (2009).

    Article  Google Scholar 

  4. King, Z.A. et al. Nucleic Acids Res. 44 D1, D515–D522 (2016).

    Article  Google Scholar 

  5. Chesbro, W., Evans, T. & Eifert, R. J. Bacteriol. 139, 625–638 (1979).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Gudmundsson, S. & Thiele, I. BMC Bioinformatics 11, 489 (2010).

    Article  Google Scholar 

  7. Satish Kumar, V., Dasika, M.S. & Maranas, C.D. BMC Bioinformatics 8, 212 (2007).

    Article  Google Scholar 

  8. Reed, J.L. et al. Proc. Natl. Acad. Sci. USA 103, 17480–17484 (2006).

    Article  CAS  Google Scholar 

  9. Thiele, I., Vlassis, N. & Fleming, R.M. Bioinformatics 30, 2529–2531 (2014).

    Article  CAS  Google Scholar 

  10. Monk, J., Nogales, J. & Palsson, B.O. Nat. Biotechnol. 32, 447–452 (2014).

    Article  CAS  Google Scholar 

  11. Ravikrishnan, A. & Raman, K. Brief. Bioinform. 16, 1057–1068 (2015).

    Article  CAS  Google Scholar 

  12. Fleming, R.M.T., Vlassis, N., Thiele, I. & Saunders, M.A. J. Theor. Biol. 409, 1–10 (2016).

    Article  CAS  Google Scholar 

  13. Fleming, R.M., Maes, C.M., Saunders, M.A., Ye, Y. & Palsson, B.O. J. Theor. Biol. 292, 71–77 (2012).

    Article  CAS  Google Scholar 

  14. Papin, J.A. et al. Trends Biotechnol. 22, 400–405 (2004).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  16. Beard, D.A., Liang, S.D. & Qian, H. Biophys. J. 83, 79–86 (2002).

    Article  CAS  Google Scholar 

  17. Schellenberger, J., Lewis, N.E. & Palsson, B.Ø. Biophys. J. 100, 544–553 (2011).

    Article  CAS  Google Scholar 

  18. Desouki, A.A., Jarre, F., Gelius-Dietrich, G. & Lercher, M.J. Bioinformatics 31, 2159–2165 (2015).

    Article  CAS  Google Scholar 

  19. Noor, E., Haraldsdóttir, H.S., Milo, R. & Fleming, R.M.T. PLoS Comput. Biol. 9, e1003098 (2013).

    Article  CAS  Google Scholar 

  20. Thiele, I. & Palsson, B.O. Nat. Protoc. 5, 93–121 (2010).

    Article  CAS  Google Scholar 

  21. Wolfe, A.J. Microbiol. Mol. Biol. Rev. 69, 12–50 (2005).

    Article  CAS  Google Scholar 

  22. Zhu, L.W. et al. Sci. Rep. 5, 17321 (2015).

    Article  CAS  Google Scholar 

  23. Fleming, R.M. & Thiele, I. Bioinformatics 27, 142–143 (2011).

    Article  CAS  Google Scholar 

  24. Lewis, N.E. et al. Mol. Syst. Biol. 6, 390 (2010).

    Article  Google Scholar 

  25. Schuster, S., Fell, D.A. & Dandekar, T. Nat. Biotechnol. 18, 326–332 (2000).

    Article  CAS  Google Scholar 

  26. Blazier, A.S. & Papin, J.A. Front. Physiol. 3, 299 (2012).

    Article  Google Scholar 

  27. Heirendt, L. et al. Preprint at https://arxiv.org/abs/1710.04038 (2017).

Download references

Author information

Authors and Affiliations

  1. Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg

    Stefanía Magnúsdóttir, Almut Heinken & Ines Thiele

  2. Division of Analytical Biosciences, Leiden Academic Centre for Drug Research, Faculty of Science, University of Leiden, Leiden, The Netherlands

    Ronan M T Fleming

Authors
  1. Stefanía Magnúsdóttir
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Almut Heinken
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ronan M T Fleming
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ines Thiele
    View author publications

    You can also search for this author in PubMed Google Scholar

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Notes 1–3 and Supplementary Figures 1–4 (PDF 1029 kb)

Supplementary Table 1

The 74 BiGG reconstructions that were used in the analysis. (XLSX 33 kb)

Supplementary Table 2

Exchange reactions set when applying the Western diet and the lower bound constraints set to each reaction. (XLSX 12 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Magnúsdóttir, S., Heinken, A., Fleming, R. et al. Reply to "Challenges in modeling the human gut microbiome". Nat Biotechnol 36, 686–691 (2018). https://doi.org/10.1038/nbt.4212

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nbt.4212

  • Springer Nature America, Inc.

This article is cited by

Search

Navigation