University of Cambridge > > Microsoft Research Computational Science Seminars > Molecular arms race between host and parasite leads to evolution of robustness against gene loss in signaling networks

Molecular arms race between host and parasite leads to evolution of robustness against gene loss in signaling networks

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If you have a question about this talk, please contact Dr Fabien Petitcolas.

Abstract: In several organisms, gene deletion studies suggest a large fraction of genes to be dispensable. While part of this observation stems from genes that are required under environments not assayed in the lab, a still appreciable number of genes can be lost with seemingly no phenotypic effect. Such robustness can result from duplicate genes that maintain a functional overlap despite molecular divergence (redundancy), or from system architecture. The emergence and maintenance of these two mechanisms poses significant challenges. In particular, no explanation currently exists for how evolution can lead to specific network architectures that are robust against deletion of parts. Also, the selective pressure for redundancy is expected to be weak, resulting in its evolution only under specific conditions. In this talk, I will demonstrate that antagonistic host-parasite interactions can lead to the evolution of robustness against gene loss in signaling networks. Using a mathematical model of host networks and simulating their co-evolution with parasites that can interfere with proteins in such networks, I will show how such networks can evolve both redundancy and specific architectures allowing them to maintain their response despite removal of proteins. Contrary to the intuition, increased parasite virulence hampers the ability of the host to evolve robustness by limiting the generation of population level diversity. However, when robustness emerges under high virulence it tends to be stronger and more likely to be mediated through system architecture rather than redundancy. These findings indicate that the arms race between parasites and their hosts is a significant ecological factor shaping biological network properties.

Biography: Orkun S. Soyer graduated from Bogazici University, Istanbul in 2000. He received his PhD from University of Michigan, Ann Arbor for his work on models of protein evolution. During his post – doctoral studies at ETH , Zürich, he developed toy models of biological signaling networks and applied these to the study of pathway evolution and dynamics.

His research is driven by the fact that biology is the result of evolution and focuses to reach an understanding of how evolutionary processes and selective pressures shape the structural and dynamical features of biological systems. This line of research relies heavily on theoretical models that are simplified versions of the reality and that can still capture the essential features and complexity of biological systems. The resulting understanding from such theoretical models is than used to generate testable hypotheses to fuel and direct experimental research.

This talk is part of the Microsoft Research Computational Science Seminars series.

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