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Multiple knockout analysis of genetic robustness in the yeast metabolic network

Nature Genetics volume 38, pages 993–998 (2006)Cite this article

Abstract

Genetic robustness characterizes the constancy of the phenotype in face of heritable perturbations. Previous investigations have used comprehensive single and double gene knockouts to study gene essentiality and pairwise gene interactions in the yeast Saccharomyces cerevisiae. Here we conduct an in silico multiple knockout investigation of a flux balance analysis model of the yeast's metabolic network. Cataloging gene sets that provide mutual functional backup, we identify sets of up to eight interacting genes and characterize the 'k robustness' (the depth of backup interactions) of each gene. We find that 74% (360) of the metabolic genes participate in processes that are essential to growth in a standard laboratory environment, compared with only 13% previously found to be essential using single knockouts. The genes' k robustness is shown to be a solid indicator of their biological buffering capacity and is correlated with both the genes' environmental specificity and their evolutionary retention.

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Figure 1: Fraction of essential genes in each k robustness level.
Figure 2: k robustness gene histograms and the distribution of backup mechanisms for contributing genes at different levels of k robustness, on rich (a–d) and minimal media (e–h).
Figure 3: Metabolic network robustness across different functional GO-Slim categories on rich medium, showing for each category the proportions of essential genes (dark), backed up genes (light), and genes not found to contribute in our analysis (white).
Figure 4: Functional backup capacity on rich medium.
Figure 5: Environmental specificity (ES) and propensity for gene loss (PGL) as a function of robustness level.

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Acknowledgements

We thank the Tauber fund for supporting D.D. Discussions with and comments of A. Hirsh, A. Kaufman, O. Meshi, Y. Pilpel, T. Pupko, R. Sharan, T. Shlomi and I. Venger are much appreciated. Figure 4 was drawn using Pajek from http://vlado.fmf.uni-lj.si/pub/networks/pajek/. M.K.'s work was supported by grants from the Israeli Science Foundation (ISF) and the Israeli Ministry of Health. E.R.'s research is supported by the Yishayahu Horowitz Center for Complexity Science, the Israeli Science Foundation (ISF), and the German-Israeli Foundation for scientific research and development (GIF).

Author information

Authors and Affiliations

  1. School of Computer Science, Tel Aviv University, PO Box 39040, Tel Aviv, 69978, Israel

    David Deutscher & Eytan Ruppin

  2. School of Mathematical Sciences, Tel Aviv University, PO Box 39040, Tel Aviv, 69978, Israel

    Isaac Meilijson

  3. Department of Molecular Microbiology and Biotechnology, Tel Aviv University, PO Box 39040, Tel Aviv, 69978, Israel

    Martin Kupiec

  4. School of Medicine, Tel Aviv University, PO Box 39040, Tel Aviv, 69978, Israel

    Eytan Ruppin

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  1. David Deutscher
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  2. Isaac Meilijson
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  4. Eytan Ruppin
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Correspondence to Eytan Ruppin.

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Supplementary information

Supplementary Fig. 1

Proline and arginine metabolism (partial diagram). (PDF 32 kb)

Supplementary Fig. 2

Distribution of the number of essential gene sets per gene. (PDF 9 kb)

Supplementary Fig. 3

Functional distance values of coessential genes. (PDF 15 kb)

Supplementary Fig. 4

Growth rates of tested mutants missing two to four genes. (PDF 22 kb)

Supplementary Table 1

Model genes and the essential sets found. (PDF 60 kb)

Supplementary Table 2

Correlation of k robustness and several biological indicators. (PDF 25 kb)

Supplementary Methods (PDF 45 kb)

Supplementary Note (PDF 75 kb)

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Deutscher, D., Meilijson, I., Kupiec, M. et al. Multiple knockout analysis of genetic robustness in the yeast metabolic network. Nat Genet 38, 993–998 (2006). https://doi.org/10.1038/ng1856

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