Evolution of bow-tie architectures in biology.

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PLoS computational biology, ISSN: 1553-7358, Vol: 11, Issue: 3, Page: e1004055

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10.1371/journal.pcbi.1004055.g006, 10.1371/journal.pcbi.1004055.g004, 10.1371/journal.pcbi.1004055.g005, 10.1371/journal.pcbi.1004055.g002, 10.1371/journal.pcbi.1004055.g003, 10.1371/journal.pcbi.1004055.g001, 10.1371/journal.pcbi.1004055, 10.1371/journal.pcbi.1004055.t001
4370773, PMC4370773
Tamar Friedlander, Avraham E. Mayo, Tsvi Tlusty, Uri Alon, Andrey Rzhetsky
Public Library of Science (PLoS), Figshare, PUBLIC LIBRARY SCIENCE
Agricultural and Biological Sciences, Mathematics, Environmental Science, Biochemistry, Genetics and Molecular Biology, Neuroscience, Computer Science, Biochemistry, Physical Sciences not elsewhere classified, Genetics, Molecular Biology, Biotechnology, Evolutionary Biology, Biological Sciences not elsewhere classified, Information Systems not elsewhere classified, Developmental Biology, Cancer, Infectious Diseases, output biomass components, rank, bow-tie architectures, 69999 Biological Sciences not elsewhere classified, 29999 Physical Sciences not elsewhere classified, 80699 Information Systems not elsewhere classified
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Bow-tie or hourglass structure is a common architectural feature found in many biological systems. A bow-tie in a multi-layered structure occurs when intermediate layers have much fewer components than the input and output layers. Examples include metabolism where a handful of building blocks mediate between multiple input nutrients and multiple output biomass components, and signaling networks where information from numerous receptor types passes through a small set of signaling pathways to regulate multiple output genes. Little is known, however, about how bow-tie architectures evolve. Here, we address the evolution of bow-tie architectures using simulations of multi-layered systems evolving to fulfill a given input-output goal. We find that bow-ties spontaneously evolve when the information in the evolutionary goal can be compressed. Mathematically speaking, bow-ties evolve when the rank of the input-output matrix describing the evolutionary goal is deficient. The maximal compression possible (the rank of the goal) determines the size of the narrowest part of the network-that is the bow-tie. A further requirement is that a process is active to reduce the number of links in the network, such as product-rule mutations, otherwise a non-bow-tie solution is found in the evolutionary simulations. This offers a mechanism to understand a common architectural principle of biological systems, and a way to quantitate the effective rank of the goals under which they evolved.

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