On this page

Research on metabolic regulation and optimal design of novel biofuels

By: Xiqi Yang 1
1Faculty of Maths & Physical Sciences, University College London, London, United Kingdom

Abstract

Biofuels, as a renewable energy source, are gradually replacing traditional fossil fuels. However, the current yield and conversion efficiency of biofuels still need to be improved. Through metabolic regulation and optimal design, microbial cell factories can be modified to enhance the expression of key enzymes, optimize the supply of precursors, and improve the fermentation conditions, thus significantly increasing the production efficiency of biofuels. In this study, we explored an effective strategy to enhance biofuel production through metabolic regulation and optimal design. Saccharomyces cerevisiae (S. cerevisiae) was used as the host cell, and the biofuel production engineering strain was constructed by LiAc transformation method, and systematic research was carried out to optimize the expression of key enzymes of the synthetic pathway, the supply of precursor substances and the fermentation conditions. The study showed that the best growth state of Saccharomyces cerevisiae was achieved at a glucose concentration of 30 g/L, with an OD600 of up to 2.897, a biofuel yield of 2366.52 mg/L, and a lipid content of more than 55%. The precursor addition experiment showed that the addition of phosphoenolpyruvic acid (PEP) increased the biofuel yield to 202.545 mg/L, which was about 3.3-fold higher compared with that of the no precursor addition group. The results of simultaneous saccharification co-fermentation (SSCF) showed that the recombinant strain optimized for metabolic regulation had a high biofuel yield of 86.91% when using rice straw as feedstock, which was 18.07% higher than that of the original strain. The experimental results confirmed that metabolic regulation and optimal design are effective ways to improve biofuel yield, which provides a scientific basis for the development of an efficient biofuel production process.