Parasites lead to evolution of robustness against gene loss in host signaling networks

Marcel Salathé^1,a & Orkun S Soyer²

^aPresent address: Department of Biological Sciences, Stanford University, Stanford, CA 94305, USA

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Synopsis

The shift in the focus of molecular biology research from studying single entities to systems brings with itself interesting findings. One such finding is the robustness of biological systems against removal of their parts (Alonso et al, 2003; Wilson et al, 2005). More specifically, many protein networks involved in diverse functions such as signaling, metabolism or transcription regulation are all shown to possess the ability to maintain proper function despite removal of individual proteins (Hoffmann, 1991; Goldstein, 1993; Cadigan et al, 1994; Emmerling et al, 2002). Where does this ability come from? Is it an inherent feature of these complex networks, or is robustness a property selected for during evolution?

There is another recent, seemingly unrelated, finding coming from molecular biology: the ability of parasites to interfere with the protein networks of their host. Antagonistic host–parasite interactions result in the host trying to clear the parasite while the parasite tries to escape such defence. There is now ample evidence showing that such an arms race between host and parasite has led to parasite interference with host networks (Sacks and Sher, 2002; Bhavsar et al, 2007; Marques and Carthew, 2007). Such interference involves many different strategies, including inhibiting host proteins from folding, expressing proteins (e.g. kinases) with targets inside the host cell and inhibiting the activity (or translocation) of specific host proteins. Ultimately, all these interference strategies disturb the dynamics and the function of the host networks, thereby reducing the fitness of the host and benefiting that of the parasite. Although it is clear to see why parasites would evolve such mechanisms, it is not clear what the consequences would be on the host networks.

In this paper, we study the evolution of host signaling networks under parasite interference. Using an abstract model that captures network dynamics and parasite interference with it, we simulate coevolution of the host with its parasite. In these simulations, we assume that host networks are under selection to maintain a specific signal–response dynamics (i.e. stabilizing selection) and that parasites are under selection for maximum disturbance of that dynamics. As shown in Figure 5, we find that the resulting antagonistic fitness interaction quickly leads to highly fit parasites (see inset, red curve) that can interfere with a specific protein in the host network. However, later on, highly fit host networks evolve (see inset, black curve) that can maintain response dynamics despite parasite interference. As we model parasite interference as complete inhibition of the targeted host protein activity, these evolved networks are robust against single gene deletion (see Figure 2). We find that such robustness results from either functionally redundant proteins or specific network architectures. Although these network architectures also involve redundancy to some extent, we find their robustness to be more stable compared with that based only on functional redundancy. Subsequent evolution without any parasites (but still under stabilizing selection) leads to loss of redundant proteins and robustness, whereas robustness tends to be maintained in networks with specific architectures (see Figure 2).

Figure 5

Diversity in host and parasite population shown as the number of networks in the host population that utilizes a given protein (top) and the number of parasites interfering with a given protein in the host network (bottom). Each colored line represents a protein identity with the color coding in two panels being the same; black, red, blue, yellow, green, cyan, violet and gray represent proteins 2, 3, 4, 5, 6, 7, 8 and 9. Note that receptor and effector in the host network are excluded from this plot, as they are not involved in parasite targeting (see Supplementary information). The inset shows the mean fitness for host (black) and parasite (red) population. Data are from a sample simulation with virulence equal to 1.

Full figure and legend (237K)Figures & Tables index

Figure 2

Left: The average fitness effect of single gene deletion on the networks of the population. Straight lines show the data for the population at the end of evolution with parasites (generation 2000 on the right panel). Dashed lines show the data for the population at the end of subsequent evolution without parasites (generation 4000 on the right panel). Orange and black indicate simulations starting from the same founder but with virulence values 0.1, and 1.0, respectively. The straight black line corresponds to the simulation shown in Figure 1. Data are shown as empirical cumulative distributions; each vertical line represents the fraction of networks in the population for which average fitness effect of a gene deletion is below, or equal to, the value shown on the x-axis. Right: Network size (i.e. number of proteins in the network) averaged over the host population during the course of evolution with (first 2000 generations) and without (last 2000 generations) parasites.

Figure 1

Host and parasite fitness (black and red lines, respectively) for a sample simulation with virulence equal to 1. For robustness of networks from the final host population resulting from this simulation, see Figure 2. For the dynamics of the most frequent network in the final population, see Supplementary Figure 1.

Full figure and legend (56K)Figures & Tables index

Full figure and legend (96K)Figures & Tables index

Taken together, these findings show that parasite interference with network dynamics can lead to evolution of robustness against gene loss in host networks and that such robustness might be maintained even after removal of interference. Does this mean that parasites are required for the evolution of robustness? Could there be other evolutionary conditions that would explain the observed robustness of networks? To explore these questions, we analyzed other evolutionary scenarios. We find that stabilizing selection by itself is not enough for robustness against gene loss to evolve, even under high mutation rates. This is in contrast to robustness against variations in kinetic rates, which is shown to evolve under stabilizing selection only (Wagner, 1996; Siegal and Bergman, 2002). Another possible evolutionary factor that could play a role in the evolution of robustness is environmental fluctuations (Harrison et al, 2007). Assuming that the environment contains a toxin or drug that specifically interferes with a given protein in the network, and modeling environmental fluctuations as changes in the identity of the target protein, we find that such fluctuations can result in the evolution of robustness against gene deletion. However, in a more biologically plausible model, where environmental fluctuations correspond to changes in the stabilizing selection forced on the network, we do not find any significant robustness evolving. Finally, we confirm previous findings that extreme rates of developmental errors can lead to the evolution of robustness against gene deletion (Nowak et al, 1997).

Although host–parasite interactions are ubiquitous in biology, this does not mean that any network under parasite interference would evolve robustness. We find that parasite-imposed fitness reduction (i.e. virulence) is a key parameter controlling the evolution of robustness. In particular, we find that virulence impairs population level diversity in terms of network structures, and thereby reduces the chance of emergence of robust networks. Conversely, if hosts can generate diversity and break parasite effects early on, higher virulence leads to stronger robustness (see Figure 5).

In conclusion, the key prediction of this study is that signaling networks (and other biological systems) operating under parasite interference would show increased redundancy or specific architectures that can tolerate removal of parts. Conversely, the presence of such properties in a network could be taken as a sign of current or past parasite interference. Furthermore, this work highlights the importance of evolutionary considerations, in particular ecological factors during evolution, in achieving a complete understanding of system level properties in molecular biology.

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