  Understanding the system level adaptive changes taking place in an organism
in response to variations in the environment is a key issue of contemporary
biology. Current modeling approaches such as the constraint-based flux balance
analyses (FBA) have proved highly successful in analyzing the capabilities of
cellular metabolism, including its capacity to predict deletion phenotypes, the
ability to calculate the relative flux values of metabolic reactions and the
properties of alternate optimal growth states. Here, we use FBA to thoroughly
assess the activity of the Escherichia coli, Helicobacter pylori, and
Saccharomyces cerevisiae metabolism in 30,000 diverse simulated environments.
We identify a set of metabolic reactions forming a connected metabolic core
that carry non-zero fluxes under all growth conditions, and whose flux
variations are highly correlated. Furthermore, we find that the enzymes
catalyzing the core reactions display a considerably higher fraction of
phenotypic essentiality and evolutionary conservation than those catalyzing
non-core reactions. Cellular metabolism is characterized by a large number of
species-specific conditionally-active reactions organized around an
evolutionary conserved always active metabolic core. Finally, we find that most
current antibiotics interfering with the bacterial metabolism target the core
enzymes, indicating that our findings may have important implications for
antimicrobial drug target discovery.
