Bioinformatician Thomas Rattei, University of Vienna, and physicist Hernan Makse, City University New York (CUNY), have reconstructed ancestral protein networks. The results are of high interest not only for evolutionary research but also for the interpretation of genome sequence data. Recently, the researchers published their paper in the renowned journal
The cells of all organisms consist mostly of proteins, which develop various functions through their complex interactions. These functions range from metabolism, maintenance and control of the cellular structure to the exchange of signals with other cells and the environment. Proteins rarely act alone - only their system-wide network makes organisms viable. "The knowledge about function and evolution of these protein networks is currently one of the most fascinating questions in biology and relevant e.g. also to cancer research", explains Thomas Rattei, Head of the Department of Computational Systems Biology at the University Center Althanstrasse.
In pursuit of the blueprint of protein networks
The combination of 20 different building blocks - amino acids - results in an enormous variety of theoretically possible protein variants; many more than the estimated number of stars in the universe. The random formation of an interaction between proteins seems therefore extremely unlikely. Thomas Rattei, Professor of In-Silico Genomics at the University of Vienna, and Hernan Makse, Professor of Physics at the City University New York (CUNY), and their teams investigate how complex and manifold protein networks could still evolve in present-day organisms.
Starting point of the joint research project was a hypothesis emphasising the importance of the duplication of proteins in the course of evolution. If the gene encoding a protein is duplicated in the genome, which often happens in evolution, original and copy will interact with the same partners in the protein network. Once original and copy diverge over time, novel proteins with individual features and own partners in the network will emerge. Interactions in the network would thereby not be newly created but evolve through duplication and divergence from simpler ancestors.