Abstract
Despite the importance of intracellular signaling networks, there is currently no consensus regarding the fundamental nature of the protein complexes such networks employ. One prominent view involves stable signaling machines with well-defined quaternary structures. The combinatorial complexity of signaling networks has led to an opposing perspective, namely that signaling proceeds via heterogeneous pleiomorphic ensembles of transient complexes. Since many hypotheses regarding network function rely on how we conceptualize signaling complexes, resolving this issue is a central problem in systems biology. Unfortunately, direct experimental characterization of these complexes has proven technologically difficult, while combinatorial complexity has prevented traditional modeling methods from approaching this question. Here we employ rule-based modeling, a technique that overcomes these limitations, to construct a model of the yeast pheromone signaling network. We found that this model exhibits significant ensemble character while generating reliable responses that match experimental observations. To contrast the ensemble behavior, we constructed a model that employs hierarchical assembly pathways to produce scaffold-based signaling machines. We found that this machine model could not replicate the experimentally observed combinatorial inhibition that arises when the scaffold is overexpressed. This finding provides evidence against the hierarchical assembly of machines in the pheromone signaling network and suggests that machines and ensembles may serve distinct purposes in vivo. In some cases, e.g. core enzymatic activities like protein synthesis and degradation, machines assembled via hierarchical energy landscapes may provide functional stability for the cell. In other cases, such as signaling, ensembles may represent a form of weak linkage, facilitating variation and plasticity in network evolution. The capacity of ensembles to signal effectively will ultimately shape how we conceptualize the function, evolution and engineering of signaling networks.
Highlights
Much of our reasoning about the function of biological systems relies on the formation of multi-subunit protein complexes [1]
We focused on the pheromone response network (Fig. 1A), one of multiple mitogenactivated protein kinase (MAPK) cascades in Saccharomyces cerevisiae
The signaling cascade is initiated by the interaction between extracellular pheromone molecules and a G-protein coupled receptor (GPCR), which induces dissociation between the a subunit (Gpa1) and bc subunits of the G-protein [37]
Summary
Much of our reasoning about the function of biological systems relies on the formation of multi-subunit protein complexes [1]. Most of the complexes formed during signal transmission and processing have not had their global three-dimensional structures experimentally determined, and as such we currently do not know the extent to which signaling occurs via machines [7]. Despite this uncertainty, the machine-like perspective on signaling complexes is pervasive in the literature, if often implicit; for instance, one commonly represents signaling networks graphically by drawing large complexes in which all of the relevant proteins interact simultaneously [8,9,10,11,12,13,14] (Fig. 1A). Such diagrams are often presented as compact summaries of a set of interactions, they are certainly evocative of a machine-like structure, and lead naturally to analogies between signaling complexes and highly ordered objects such as circuit boards [7,9]
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