13C metabolic flux analysis (MFA) provides a rigorous approach to quantify host metabolic phenotypes by applying isotope tracers to map the flow of carbon through intracellular biochemical pathways. In particular, dynamic measurements of isotope incorporation following a step change from unlabeled to labeled CO2 can be used to assess carbon fluxes in photosynthetic hosts by applying isotopically nonstationary MFA (INST-MFA). We have previously developed a publicly available software tool called INCA that automates the computational workflow of INST-MFA. INCA was applied to model the photoautotrophic metabolism of an isobutyraldehyde (IBA)-producing strain of Synechococcus 7942 (denoted SA590) originally developed by Atsumi et al. Flux analysis identified a potential bottleneck at the pyruvate kinase (PK) reaction and indicated significant flux through an alternative three-step route from PEP to pyruvate. Based on these results, we overexpressed PK in SA590 and achieved &gt;50% improvement in IBA production without inhibiting growth. 13C flux analysis of the resulting SA590-PK strain identified further targets for debottlenecking IBA production. Two separate metabolic engineering strategies were developed that provided substantial further increases in aldehyde productivity of ~50% relative to SA590-PK: (i) downregulation of pyruvate dehydrogenase (PDH) expression (through antisense RNA expression) or (ii) heterologous expression of E. coli PEP carboxykinase (PCK). While knockdown of PDH did not negatively impact growth of SA590-PK, PCK expression dramatically reduced growth rate and altered the intracellular levels of several amino acids. These results illustrate the potential of 13C INST-MFA to enable a systematic approach for iterative identification and removal of pathway bottlenecks in cyanobacteria and other non-model autotrophic host cells.

Systematic identification and elimination of flux bottlenecks in aldehyde-producing strains of Synechococcus elongatus PCC 7942

ACS Spring 2022

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