Abstract
Methylglyoxal is a highly toxic metabolite that can be produced in all living organisms. Methylglyoxal was artificially elevated by removal of the tpiA gene from a growth optimized Escherichia coli strain. The initial response to elevated methylglyoxal and its toxicity was characterized, and detoxification mechanisms were studied using adaptive laboratory evolution. We found that: 1) Multi-omics analysis revealed biological consequences of methylglyoxal toxicity, which included attack on macromolecules including DNA and RNA and perturbation of nucleotide levels; 2) Counter-intuitive cross-talk between carbon starvation and inorganic phosphate signalling was revealed in the tpiA deletion strain that required mutations in inorganic phosphate signalling mechanisms to alleviate; and 3) The split flux through lower glycolysis depleted glycolytic intermediates requiring a host of synchronized and coordinated mutations in non-intuitive network locations in order to re-adjust the metabolic flux map to achieve optimal growth. Such mutations included a systematic inactivation of the Phosphotransferase System (PTS) and alterations in cell wall biosynthesis enzyme activity. This study demonstrated that deletion of major metabolic genes followed by ALE was a productive approach to gain novel insight into the systems biology underlying optimal phenotypic states.
| Original language | English |
|---|---|
| Pages (from-to) | 82-93 |
| Number of pages | 12 |
| Journal | Metabolic Engineering |
| Volume | 48 |
| DOIs | |
| Publication status | Published - Jul 2018 |
Bibliographical note
Funding Information: We thank José Utrilla for helpful discussion and guidance when implementing the knockouts in the pre-evolved strain. We thank Jamey Young for helpful discussions throughout the MFA analysis. We thank Laurence Yang for helpful discussions regarding optimization and statistical analysis. This work was funded by the Novo Nordisk Foundation Grant Number NNF10CC1016517 . Publisher Copyright: © 2018Other keywords
- Adaptive laboratory evolution
- E. coli
- Multi-omics data integration
- Mutation analysis
- Systems biology
- tpiA gene knockout
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