531 research outputs found
Essential plasticity and redundancy of metabolism unveiled by synthetic lethality analysis
We unravel how functional plasticity and redundancy are essential mechanisms
underlying the ability to survive of metabolic networks. We perform an
exhaustive computational screening of synthetic lethal reaction pairs in
Escherichia coli in a minimal medium and we find that synthetic lethal pairs
divide in two different groups depending on whether the synthetic lethal
interaction works as a backup or as a parallel use mechanism, the first
corresponding to essential plasticity and the second to essential redundancy.
In E. coli, the analysis of pathways entanglement through essential redundancy
supports the view that synthetic lethality affects preferentially a single
function or pathway. In contrast, essential plasticity, the dominant class,
tends to be inter-pathway but strongly localized and unveils Cell Envelope
Biosynthesis as an essential backup for Membrane Lipid Metabolism. When
comparing E. coli and Mycoplasma pneumoniae, we find that the metabolic
networks of the two organisms exhibit a large difference in the relative
importance of plasticity and redundancy which is consistent with the conjecture
that plasticity is a sophisticated mechanism that requires a complex
organization. Finally, coessential reaction pairs are explored in different
environmental conditions to uncover the interplay between the two mechanisms.
We find that synthetic lethal interactions and their classification in
plasticity and redundancy are basically insensitive to medium composition, and
are highly conserved even when the environment is enriched with nonessential
compounds or overconstrained to decrease maximum biomass formation.Comment: 22 pages, 4 figure
Assessing the significance of knockout cascades in metabolic networks
Complex networks have been shown to be robust against random structural
perturbations, but vulnerable against targeted attacks. Robustness analysis
usually simulates the removal of individual or sets of nodes, followed by the
assessment of the inflicted damage. For complex metabolic networks, it has been
suggested that evolutionary pressure may favor robustness against reaction
removal. However, the removal of a reaction and its impact on the network may
as well be interpreted as selective regulation of pathway activities,
suggesting a tradeoff between the efficiency of regulation and vulnerability.
Here, we employ a cascading failure algorithm to simulate the removal of single
and pairs of reactions from the metabolic networks of two organisms, and
estimate the significance of the results using two different null models:
degree preserving and mass-balanced randomization. Our analysis suggests that
evolutionary pressure promotes larger cascades of non-viable reactions, and
thus favors the ability of efficient metabolic regulation at the expense of
robustness
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