Robust design of microbial strains

Jole Costanza, Giovanni Carapezza, Claudio Angione, Pietro Lió, Giuseppe Nicosia

    Research output: Contribution to journalArticlepeer-review

    34 Citations (Scopus)

    Abstract

    Motivation: Metabolic engineering algorithms provide means to optimize a biological process leading to the improvement of a biotechnological interesting molecule. Therefore, it is important to understand how to act in a metabolic pathway in order to have the best results in terms of productions. In this work, we present a computational framework that searches for optimal and robust microbial strains that are able to produce target molecules. Our framework performs three tasks: it evaluates the parameter sensitivity of the microbial model searches for the optimal genetic or fluxes design and finally calculates the robustness of the microbial strains.We are capable to combine the exploration of species, reactions, pathways and knockout parameter spaces with the Pareto-optimality principle. Results: Our framework provides also theoretical and practical guidelines for design automation. The statistical cross comparison of our new optimization procedures, performed with respect to currently widely used algorithms for bacteria (e.g. Escherichia coli) over different multiple functions, reveals good performances over a variety of biotechnological products.

    Original languageEnglish
    Pages (from-to)3097-3104
    Number of pages8
    JournalBioinformatics
    Volume28
    Issue number23
    DOIs
    Publication statusPublished - 1 Dec 2012

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