(188av) Combining Metabolic Flux Analysis and Proteomics to Decipher Regulation of Carbon Fixation in Cyanobacteria | AIChE

(188av) Combining Metabolic Flux Analysis and Proteomics to Decipher Regulation of Carbon Fixation in Cyanobacteria

Authors 

Yu King Hing, N. - Presenter, Purdue University
Morgan, J., Purdue University
Liang, F., Uppsala University
Lindblad, P., Uppsala University
Photosynthetic organisms are increasingly being investigated as a sustainable alternative to existing bio-industrial processes, converting CO2 into desirable end products without the use of carbohydrate feedstock. The Calvin-Benson-Bassham (CBB) cycle describes carbon fixation metabolism in photosynthetic organisms and therefore plays an integral role in photosynthetic metabolism. In this study, we overexpressed fructose-1,6-bisphosphatase and transketolase, two potential carbon flux control enzymes in the CBB cycle, in the model cyanobacterium Synechocystis sp. PCC 6803. The growth rates of Synechocystis sp. PCC 6803 were measured under atmospheric and high (3% v/v) CO2 conditions at 80 µmol m-2 s-1. Surprisingly, the cells overexpressing transketolase (tktA) demonstrated no significant increase in growth rates when CO2 was increased, suggesting a growth-disrupted carbon flux distribution and a potential metabolic bottleneck. In contrast, the fructose-1,6-bisphosphatase (70glpX) and wild-type cells demonstrated slight increases in growth rates as expected.

To investigate the disparate phenotypical responses of these different Synechocystis strains, isotopically non-stationary metabolic flux analysis (INST-MFA) will be used to estimate the carbon flux distribution of tktA, 70glpX and WT cells under both atmospheric and high CO2 conditions. In addition, untargeted label-free proteomics, which can detect changes in relative enzymatic abundance, was employed to study possible cascading effects on the proteome caused by overexpressing each enzyme. These results are an example of the integration of multiple omic-level experimental techniques and can be used to guide future metabolic engineering efforts.