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The evolution of hubs

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Now, research from Thomas Pfeiffer, Orkun Soyer, and Sebastian Bonhoeffer (ETH Zürich, Switzerland) shows that hubs are the natural byproduct of a widely accepted scenario of network evolution.The scenario, originally proposed by Kacser and Beeby, suggests that a few multifunctional enzymes evolved to create a large network of highly specialized enzymes... In the new work, the Swiss group ran computer simulations of this scenario using a small theoretical network initially consisting of 128 metabolites, one metabolite transporter, and seven catalytic enzymes... These constituents evolved via small mutations or duplications that improved projected growth rates... The new simulations suggest, however, that growth rate alone exerts enough selective pressure... Hub frequency varied somewhat from that found in the entire E. coli metabolic network... But if the authors compared their simulations to smaller natural subnetworks, such as glycolysis, then the hub distributions matched closely... Natural hubs are especially important in the transfer of biochemical groups (e.g., phosphate or amino acids) between metabolites... According to the new findings, these group transfer reactions are important for the emergence of hubs... When the simulations were run in their absence—groups were added or taken away, but not transferred—hubs were much less prominent. “Metabolites are hubs because they are key in transfer reactions,” says Pfeiffer. “One metabolite evolves such that it's the best donor for a particular group... The rest of the network benefits by maintaining that donor at a high concentration... And all reactions that require that specific group should specialize to rely on this donor, because it's the best donor around. ” Reference:

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Highly connected hubs are common in a simulated network (top), as in natural networks (middle), but rare if group transfer reactions are excluded (bottom).PFEIFFER
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uro1: Highly connected hubs are common in a simulated network (top), as in natural networks (middle), but rare if group transfer reactions are excluded (bottom).PFEIFFER


The evolution of hubs
Highly connected hubs are common in a simulated network (top), as in natural networks (middle), but rare if group transfer reactions are excluded (bottom).PFEIFFER
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2254866&req=5

uro1: Highly connected hubs are common in a simulated network (top), as in natural networks (middle), but rare if group transfer reactions are excluded (bottom).PFEIFFER

View Article: PubMed Central

AUTOMATICALLY GENERATED EXCERPT
Please rate it.

Now, research from Thomas Pfeiffer, Orkun Soyer, and Sebastian Bonhoeffer (ETH Zürich, Switzerland) shows that hubs are the natural byproduct of a widely accepted scenario of network evolution.The scenario, originally proposed by Kacser and Beeby, suggests that a few multifunctional enzymes evolved to create a large network of highly specialized enzymes... In the new work, the Swiss group ran computer simulations of this scenario using a small theoretical network initially consisting of 128 metabolites, one metabolite transporter, and seven catalytic enzymes... These constituents evolved via small mutations or duplications that improved projected growth rates... The new simulations suggest, however, that growth rate alone exerts enough selective pressure... Hub frequency varied somewhat from that found in the entire E. coli metabolic network... But if the authors compared their simulations to smaller natural subnetworks, such as glycolysis, then the hub distributions matched closely... Natural hubs are especially important in the transfer of biochemical groups (e.g., phosphate or amino acids) between metabolites... According to the new findings, these group transfer reactions are important for the emergence of hubs... When the simulations were run in their absence—groups were added or taken away, but not transferred—hubs were much less prominent. “Metabolites are hubs because they are key in transfer reactions,” says Pfeiffer. “One metabolite evolves such that it's the best donor for a particular group... The rest of the network benefits by maintaining that donor at a high concentration... And all reactions that require that specific group should specialize to rely on this donor, because it's the best donor around. ” Reference:

No MeSH data available.