Abstract:
:Cell metabolism is an important platform for sustainable biofuel, chemical and pharmaceutical production but its complexity presents a major challenge for scientists and engineers. Although in silico strains have been designed in the past with predicted performances near the theoretical maximum, real-world performance is often sub-optimal. Here, we simulate how strain performance is impacted when subjected to many randomly varying perturbations, including discrepancies between gene expression and in vivo flux, osmotic stress, and substrate uptake perturbations due to concentration gradients in bioreactors. This computational study asks whether robust performance can be achieved by adopting robustness-enhancing mechanisms from naturally evolved organisms-in particular, redundancy. Our study shows that redundancy, typically perceived as a ubiquitous robustness-enhancing strategy in nature, can either improve or undermine robustness depending on the magnitude of the perturbations. We also show that the optimal number of redundant pathways used can be predicted for a given perturbation size.
journal_name
Metab Engjournal_title
Metabolic engineeringauthors
Yang L,Srinivasan S,Mahadevan R,Cluett WRdoi
10.1016/j.ymben.2014.11.013subject
Has Abstractpub_date
2015-03-01 00:00:00pages
114-122eissn
1096-7176issn
1096-7184pii
S1096-7176(14)00163-3journal_volume
28pub_type
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journal_title:Metabolic engineering
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doi:10.1016/j.ymben.2015.01.002
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journal_title:Metabolic engineering
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