Multiple Optimal Phenotypes Overcome Redox and Glycolytic Intermediate Metabolite Imbalances in Escherichia coli pgi Knockout Evolutions

Abstract

A mechanistic understanding of how new phenotypes develop to overcome the loss of a gene product provides valuable insight on both the metabolic and regulatory functions of the lost gene. The gene, whose product catalyzes the second step in glycolysis, was deleted in a growth-optimized K-12 MG1655 strain. The initial knockout (KO) strain exhibited an 80% drop in growth rate that was largely recovered in eight replicate, but phenotypically distinct, cultures after undergoing adaptive laboratory evolution (ALE). Multi-omic data sets showed that the loss of substantially shifted pathway usage, leading to a redox and sugar phosphate stress response. These stress responses were overcome by unique combinations of innovative mutations selected for by ALE. Thus, the coordinated mechanisms from genome to metabolome that lead to multiple optimal phenotypes after the loss of a major gene product were revealed. A mechanistic understanding of how microbes are able to overcome the loss of a gene through regulatory and metabolic changes is not well understood. Eight independent adaptive laboratory evolution (ALE) experiments with knockout strains resulted in eight phenotypically distinct endpoints that were able to overcome the gene loss. Utilizing multi-omics analysis, the coordinated mechanisms from genome to metabolome that lead to multiple optimal phenotypes after the loss of a major gene product were revealed.

Kinetic profiling of metabolic specialists demonstrates stability and consistency of in vivo enzyme turnover numbers

“…To obtain strains with high growth rates for which kapp approaches kapp,max, adaptive laboratory evolution 5 was used on the metabolic knockout strains. We profiled 21 strains, representing metabolic specialists with diverse flux profiles that are able to obtain high growth rates [6][7][8][9] . With this data-driven approach, we show that in vivo kcats are stable and robust to genetic perturbations, and that they can be used in genome-scale models to obtain a high predictive performance for unseen protein abundance data.…”

“…With this data-driven approach, we show that in vivo kcats are stable and robust to genetic perturbations, and that they can be used in genome-scale models to obtain a high predictive performance for unseen protein abundance data. Figure 1: Approach for obtaining kcat in vivo from metabolic specialists: Knock out of enzymes in central metabolism was followed by adaptive laboratory evolution (ALE) to obtain 21 strains that had diverse flux profiles, while achieving high growth rates [6][7][8][9] . Fluxomics and proteomics data was then integrated for the evolved strains to obtain the maximum kapp across the 21 strains (kapp,max) for each enzyme that could be mapped uniquely.…”

Evolutionary engineering of Corynebacterium glutamicum

“…Combining evolutionary engineering with rationally engineered system perturbations is a promising approach for the identification of metabolic traits that can be beneficial for target molecule production . Gene knockouts are frequently used to not only investigate the metabolic and regulatory function of gene products, but also for predefining the cell's metabolic network with regard to precursor supply for biotechnological applications (Figure ) . Growth defects that result from system perturbations by introduction of gene knockouts provide a guided selection pressure toward fitness recovery.…”

“…Growth defects that result from system perturbations by introduction of gene knockouts provide a guided selection pressure toward fitness recovery. This can lead to alternative reoptimized metabolic states, for example by harnessing the underground metabolism by building on promiscuous enzyme activity of the particular species …”

“…McCloskey and colleagues intensively studied growth recovery of different E. coli knockout strains during ALE at the systems level. The combination of ALE and multiomics technologies provided deep insights into the versatile pathways allowing rebalancing of the metabolite and redox state . Furthermore, growth coupling approaches with E. coli used the strong evolutionary driving force towards redox homeostasis for increasing fermentative production of lactic acid, 1‐butanol, and linear higher alcohols by inactivating competing NADH oxidizing enzymes.…”