  System-level properties of metabolic networks may be the direct product of
natural selection or arise as a by-product 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.
