Phenotypic constraints promote latent versatility and carbon efficiency in metabolic networks
Abstract
Systemlevel properties of metabolic networks may be the direct product of natural selection or arise as a byproduct of selection on other properties. Here we study the effect of direct selective pressure for growth or viability in particular environments on two properties of metabolic networks: latent versatility to function in additional environments and carbon usage efficiency. Using a Markov chain Monte Carlo (MCMC) sampling based on flux balance analysis (FBA), we sample from a known biochemical universe random viable metabolic networks that differ in the number of directly constrained environments. We find that the latent versatility of sampled metabolic networks increases with the number of directly constrained environments and with the size of the networks. We then show that the average carbon wastage of sampled metabolic networks across the constrained environments decreases with the number of directly constrained environments and with the size of the networks. Our work expands the growing body of evidence about nonadaptive origins of key functional properties of biological networks.
 Publication:

Physical Review E
 Pub Date:
 July 2015
 DOI:
 10.1103/PhysRevE.92.012809
 arXiv:
 arXiv:1408.4555
 Bibcode:
 2015PhRvE..92a2809B
 Keywords:

 87.18.Vf;
 87.10.Rt;
 Systems biology;
 Monte Carlo simulations;
 Quantitative Biology  Molecular Networks;
 Physics  Biological Physics
 EPrint:
 9 pages, 7 figures