Robustness that is the product of evolution can have very different properties to robustness that is the product of an engineering process. For example, biological robustness is often distributed across the entire network, rather than being a simple consequence of redundant parts. Complex interacting networks can act as evolutionary capacitors by concealing and revealing variation, and in the process can turn “wasteful mess” into a creative force in evolution.
We have constructed a model of ensembles of transcriptional networks, to simulate in silico evolution under mutation and selection. Although simplified, the model is unique in retaining four key features of real networks. First, each transcription factor binding site is either occupied or unoccupied, and binding and unbinding are stochastic processes. This, combined with the low and fluctuating copy number of each mRNA in any given cell, creates significant stochasticity in the system, which we capture explicitly in our model. Second, transcription and translation are not instantaneous processes. Our model includes delays, which can lead to the instability of kinetic systems. Third, our model includes cooperativity in transcription factor binding. Finally, natural selection acts on the outcome of the network as a whole, rather than on its individual components. The model uses parameters taken from real data from Saccharomyces cerevisiae.
We have used the model to study adaptive and non-adaptive hypotheses for the evolution of network motifs such as feed forward loops (FFLs). In the case of the C1-FFL, we were able to reproduce adaptive evolution, but our results emphasized that dynamics are more important than topology. C1-FFLs use an AND-gate to integrate information from slow and fast signalling pathways, in order to filter out short spurious signals. Transcriptional regulation is intrinsically slow, and so this dynamic module is more likely to arise from combining transcriptional with non-transcriptional (e.g. post-translational) regulation.
Publications:
- Xiong K., Lancaster A. K., Siegal M. L., & Masel J. (2019) Feed forward regulation adaptively evolves via dynamics rather than topology when there is intrinsic noise, Nature Communications 10:2418.
- Brettner, L.M., Masel, J. (2012) Protein stickiness, rather than number of functional protein-protein interactions, predicts expression noise and plasticity in yeast, BMC Systems Biology, 6:128
- Masel, J., & Siegal, M. L. (2009). Robustness: mechanisms and consequences. Trends Genet. (PubMed) (doi)
- Masel, J. (2004). Genetic assimilation can occur in the absence of selection for the assimilating phenotype, suggesting a role for the canalization heuristic. J Evol Biol, 17(5), 1106-10. (PubMed) (doi)