Engineering a microbial strain for production sometimes entails metabolic modifications that impair essential physiological processes for growth or production. Restoring these functions may require amending a variety of non-obvious physiological networks, and thus, rational design strategies may not be practical. Here we demonstrate that growth and production may be restored by evolution that repairs impaired metabolic function. Furthermore, we use genomics, metabolomics and proteomics to identify several underlying mutations and metabolic perturbations that allow metabolism to repair. Previously, high titers of butanol production were achieved by Escherichia coli using a growth-coupled, modified Clostridial CoA-dependent pathway after all native fermentative pathways were deleted. However, production was only observed in rich media. Native metabolic function of the host was unable to support growth and production in minimal media. We use directed cell evolution to repair this phenotype and observed improved growth, titers and butanol yields. We found a mutation in pcnB which resulted in decreased plasmid copy numbers and pathway enzymes to balance resource utilization. Increased protein abundance was measured for biosynthetic pathways, glycolytic enzymes have increased activity, and adenosyl energy charge was increased. We also found mutations in the ArcAB two-component system and integration host factor (IHF) that tune redox metabolism to alter byproduct formation. These results demonstrate that directed strain evolution can enable systematic adaptations to repair metabolic function and enhance microbial production. Furthermore, these results demonstrate the versatile repair capabilities of cell metabolism and highlight important aspects of cell physiology that are required for production in minimal media.
Magnetic orientational linear dichroism (MOLD) spectra of magnetic nanoparticles (MNPs) in the UV-Vis wavelength region were found to be useful as a probe to detect changes of the dispersion state due to a restriction of the rotational Brownian motion of MNPs; a change of the medium from liquid to resin and the formation of agglomerates in solution. The magnetic-field dependence of MOLD was analyzed by using the Langevin equation, which gave information about the magnetic moment of MNPs.
Magnetic orientational linear dichroism (MOLD) spectroscopy was found to be useful for detecting the initiation of the agglomeration process of COOH-modified iron-oxide magnetic nanoparticles (MNPs) in water, which was produced by the addition of a small amount of a cationic surfactant or a metal ion. The critical association of MNPs leading to agglomeration was detected from the increase of the maximum MOLD value as well as from the shift of the maximum wavelength of the MOLD spectrum. The magnetic field dependence of MOLD was analyzed by the Langevin equation, and the apparent association numbers of MNPs in the agglomerates were obtained.
Production of 1-butanol from microorganisms has garnered significant interest due to its prospect as a drop-in biofuel and precursor for a variety of commercially relevant chemicals. Previously, high 1-butanol titer has been reported in Escherichia coli strain JCL166, which contains a modified clostridial 1-butanol pathway. Although conventional and metabolomics-based strain improvement strategies of E. coli strain JCL166 have been successful in improving production in rich medium, 1-butanol titer was severely limited in minimal medium. To further improve growth and consequently 1-butanol production in minimal medium, adaptive laboratory evolution (ALE) using mutD5 mutator plasmid was done on JCL166. Comparative metabolomics analysis of JCL166 and BP1 revealed global perturbations in the evolved strain BP1 compared to JCL166 (44 out of 64 metabolites), encompassing major metabolic pathways such as glycolysis, nucleotide biosynthesis, and CoA-related processes. Collectively, these metabolic changes in BP1 result in improved growth and, consequently, 1-butanol production in minimal medium. Furthermore, we found that the mutation in ihfB caused by ALE had a significant effect on the metabolome profile of the evolved strain. This study demonstrates how metabolomics was utilized for characterization of ALE-developed strains to understand the overall effect of mutations acquired through evolution.
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