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cc-by (c) Güell Riera, Oriol et al., 2014
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/147802

Essential plasticity and redundancy of metabolism unveiled by synthetic lethality analysis

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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.

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GÜELL RIERA, Oriol, SAGUÉS I MESTRE, Francesc and SERRANO MORAL, Ma. Ángeles (María Ángeles). Essential plasticity and redundancy of metabolism unveiled by synthetic lethality analysis. PLoS Computational Biology. 2014. Vol. 10, num. 5, pags. e1003637. ISSN 1553-734X. [consulted: 9 of August of 2026]. Available at: https://hdl.handle.net/2445/147802

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