Abstract
Cellular functions are based on the complex interplay of proteins, therefore the structure and dynamics of these protein-protein interaction (PPI) networks are the key to the functional understanding of cells. In the last years, large-scale PPI networks of several model organisms were investigated. A number of theoretical models have been developed to explain both the network formation and the current structure. Favored are models based on duplication and divergence of genes, as they most closely represent the biological foundation of network evolution. However, studies are often based on simulated instead of empirical data or they cover only single organisms. Methodological improvements now allow the analysis of PPI networks of multiple organisms simultaneously as well as the direct modeling of ancestral networks. This provides the opportunity to challenge existing assumptions on network evolution. We utilized present-day PPI networks from integrated datasets of seven model organisms and developed a theoretical and bioinformatic framework for studying the evolutionary dynamics of PPI networks. A novel filtering approach using percolation analysis was developed to remove low confidence interactions based on topological constraints. We then reconstructed the ancient PPI networks of different ancestors, for which the ancestral proteomes, as well as the ancestral interactions, were inferred. Ancestral proteins were reconstructed using orthologous groups on different evolutionary levels. A stochastic approach, using the duplication-divergence model, was developed for estimating the probabilities of ancient interactions from today's PPI networks. The growth rates for nodes, edges, sizes and modularities of the networks indicate multiplicative growth and are consistent with the results from independent static analysis. Our results support the duplication-divergence model of evolution and indicate fractality and multiplicative growth as general properties of the PPI network structure and dynamics.
Highlights
A living cell relies on a wide network of protein-protein interactions (PPIs) of structural and functional relevance, the understanding of cell function is intrinsically tied to the understanding of this network
Besides functional interactions, which are not considered in this study, STRING provides physical PPIs for many species
It is known that PPI networks are invariant or selfsimilar under a length-scale transformation [28]
Summary
A living cell relies on a wide network of protein-protein interactions (PPIs) of structural and functional relevance, the understanding of cell function is intrinsically tied to the understanding of this network. Technical advances in molecular and cellular biology and bioinformatics enabled extensive studies on protein-protein interaction networks (PIN) during the last decade. While a significant amount of data was collected during this time, theoretical analyses were focused on PINs from very few model organisms. General theoretical models explaining the formation, function and emerging properties of biological networks often lack the connection to empirical data, making it difficult to validate the models [3]. We improve network theory for studying the evolutionary dynamics of PIN in multiple organisms
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