In Silico Evolution of Multi-scale Microbial Systems in the Presence of Mobile Genetic Elements and Horizontal Gene Transfer

  • Vadim Mozhayskiy
  • Ilias Tagkopoulos
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6674)

Abstract

Recent phylogenetic studies reveal that Horizontal Gene Transfer (HGT) events are likely ubiquitous in the Tree of Life. However, our knowledge of HGT’s role in evolution and biological organization is very limited, mainly due to the difficulty tracing HGT events experimentally, and lack of computational models that can capture its dynamics. Here, we present a novel, multi-scale model of microbial populations with the capacity to study the effect of HGT on complex traits and regulatory network evolution. We describe a parallel load-balancing framework, which was developed to overcome the innate challenges of simulating evolving populations of such magnitude and complexity. Supercomputer simulations of in silico cells that mutate, compete, and evolve, show that HGT can significantly accelerate, but also disrupt, the emergence of advantageous traits in microbial populations. We show that HGT leaves a lasting imprint to gene regulatory networks when it comes to their size and sparsity. In any given experiment, we observed phenotypic variability that can be explained by individual gain and loss of function during evolution. Analysis of the fossil mutational and HGT event record, both for evolved and non-evolved populations, reveals that the distribution of fitness effect for HGT has different characteristics in terms of symmetry, shape and bias from its mutational counterpart. Interestingly, we observed that evolution can be accelerated when populations are exposed in correlated environments of increased complexity, especially in the presence of HGT.

Keywords

Horizontal Gene Transfer Microbial Evolution Biological Networks Simulation Multi-scale Modeling High Performance Computing 

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References

  1. 1.
    Ragan, M.A., Beiko, R.G.: Lateral genetic transfer: open issues. Philosophical Transactions of the Royal Society B-Biological Sciences 364, 2241–2251 (2009)CrossRefGoogle Scholar
  2. 2.
    Boto, L.: Horizontal gene transfer in evolution: facts and challenges. Proc. Biol. Sci. 277, 819–827 (2010)CrossRefGoogle Scholar
  3. 3.
    Koonin, E.V., Makarova, K.S., Aravind, L.: Horizontal gene transfer in prokaryotes: Quantification and classification. Annual Review of Microbiology 55, 709–742 (2001)CrossRefGoogle Scholar
  4. 4.
    Gogarten, J.P., Doolittle, W.F., Lawrence, J.G.: Prokaryotic evolution in light of gene transfer. Molecular Biology and Evolution 19, 2226–2238 (2002)CrossRefGoogle Scholar
  5. 5.
    Koslowski, T., Zehender, F.: Towards a quantitative understanding of horizontal gene transfer: A kinetic model. Journal of Theoretical Biology 237, 23–29 (2005)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Nielsen, K.M., Townsend, J.P.: Monitoring and modeling horizontal gene transfer. Nature Biotechnology 22, 1110–1114 (2004)CrossRefGoogle Scholar
  7. 7.
    Novozhilov, A.S., Karev, G.P., Koonin, E.V.: Mathematical modeling of evolution of horizontally transferred genes. Molecular Biology and Evolution 22, 1721–1732 (2005)CrossRefGoogle Scholar
  8. 8.
    Levin, B.R., Cornejo, O.E.: The Population and Evolutionary Dynamics of Homologous Gene Recombination in Bacteria. PLoS Genetics 5, Article No.: e1000601 (2009)Google Scholar
  9. 9.
    Philipsen, K.R., Christiansen, L.E., Hasman, H., Madsen, H.: Modelling conjugation with stochastic differential equations. Journal of Theoretical Biology 263, 134–142 (2010)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Tagkopoulos, I., Liu, Y.C., Tavazoie, S.: Predictive behavior within microbial genetic networks. Science 320, 1313–1317 (2008)CrossRefGoogle Scholar
  11. 11.
    Duda, R.O., Hart, P.E.: Pattern classification and scene analysis. Wiley-Interscience, Hoboken (1973)MATHGoogle Scholar
  12. 12.
    Ando, T., Itakura, S., Uchii, K., Sobue, R., Maeda, S.: Horizontal transfer of non-conjugative plasmid in colony biofilm of Escherichia coli on food-based media. World Journal of Microbiology & Biotechnology 25, 1865–1869 (2009)CrossRefGoogle Scholar
  13. 13.
    Baur, B., Hanselmann, K., Schlimme, W., Jenni, B.: Genetic transformation in freshwater: Escherichia coli is able to develop natural competence. Appl. Environ. Microbiol. 62, 3673–3678 (1996)Google Scholar
  14. 14.
    Jiang, S.C., Paul, J.H.: Gene transfer by transduction in the marine environment. Applied and Environmental Microbiology 64, 2780–2787 (1998)Google Scholar
  15. 15.
    McDaniel, L., Young, E., Delaney, J., Ruhnau, F., Ritchie, K., Paul, J.: High Frequency of Horizontal Gene Transfer in the Oceans. Nature 330, 1 (2010)Google Scholar
  16. 16.
    Park, S.C., Simon, D., Krug, J.: The Speed of Evolution in Large Asexual Populations. Journal of Statistical Physics 138, 381–410 (2010)MathSciNetCrossRefMATHGoogle Scholar
  17. 17.
    Gerrish, P.J., Lenski, R.E.: The fate of competing beneficial mutations in an asexual population. Genetica 102-103, 127–144 (1998)CrossRefGoogle Scholar
  18. 18.
    Kashtan, N., Noor, E., Alon, U.: Varying environments can speed up evolution. Proceedings of the National Academy of Sciences of the United States of America 104, 13711–13716 (2007)CrossRefGoogle Scholar
  19. 19.
    Parter, M., Kashtan, N., Alon, U.: Facilitated Variation: How Evolution Learns from Past Environments To Generalize to New Environments. Plos Computational Biology 4 (2008)Google Scholar
  20. 20.
    Elena, S.F., Ekunwe, L., Hajela, N., Oden, S.A., Lenski, R.E.: Distribution of fitness effects caused by random insertion mutations in Escherichia coli. Genetica 102-103, 349–358 (1998)CrossRefGoogle Scholar
  21. 21.
    Peris, J.B., Davis, P., Cuevas, J.M., Nebot, M.R., Sanjuan, R.: Distribution of Fitness Effects Caused by Single-Nucleotide Substitutions in Bacteriophage f1. Genetics 185, U308–U603 (2010)CrossRefGoogle Scholar
  22. 22.
    Kibota, T.T., Lynch, M.: Estimate of the genomic mutation rate deleterious to overall fitness in E-coli. Nature 381, 694–696 (1996)CrossRefGoogle Scholar
  23. 23.
    Eyre-Walker, A., Keightley, P.D.: The distribution of fitness effects of new mutations. Nature Reviews Genetics 8, 610–618 (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Vadim Mozhayskiy
    • 1
  • Ilias Tagkopoulos
    • 1
  1. 1.Department of Computer Science and Genome CenterUniversity of California DavisDavisUSA

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