FDH knockout and TsFDH transformation lead to enhanced growth rate of Escherichia coli

TL;DR

This study demonstrates that knocking out FDH genes and introducing TsFDH enhances E. coli growth by reducing CO2 release and utilizing glycerol more effectively, supported by experimental and RNA-seq data.

Contribution

It introduces a genetic modification strategy that improves E. coli growth and CO2 reduction, providing insights into glycerol metabolism and gene expression.

Findings

Knockout of FDH genes increases growth rate.

TsFDH enhances growth across strains.

Glycerol is confirmed as a preferred carbon source.

Abstract

Increased Atmospheric CO2 to over 400 ppm has prompted global climate irregularities. Reducing the released CO2 from biotechnological processes could remediate these phenomena. In this study, we sought to find a solution to reduce the amount of CO2 in the process of growth and reproduction by preventing the conversion of formic acid into CO2. The (bio)chemical conversion of formic acid to CO2 is a key reaction. Therefore, we compared the growth of BL21, being a subfamily of K12, alongside two strains in which two different genes related to the formate metabolism were deleted, in complex and simple media. Experimental results were entirely consistent with metabolic predictions. Subsequently, the knockout bacteria grew more efficiently than BL21. Interestingly, TsFDH, a formate dehydrogenase with the tendency of converting CO2 to formate, increased the growth of all strains compared with cells without the TsFDH. Most mutants grew in a simple medium containing glycerol, which showed that glycerol is the preferred carbon source compared to glucose for the growth of E. coli. These results explain the reasons for the inconsistency of predictions in previous metabolic models that declared glycerol as a suitable carbon source for the growth of E. coli but failed to achieve it in practice. To conduct a more mechanistic evaluation of our observations, RNA sequencing data analysis was conducted on an E. coli RNA-seq dataset. The gene expression correlation outcome revealed the increased expression levels of several genes related to protein biosynthesis and glycerol degradation as a possible explanation of our observations.