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How to use FBA to find the best pathway for microorganisms to produce industrial chemicals?
In biochemistry, flux balance analysis (FBA) is a mathematical method for simulating the metabolism of cells or single-celled organisms such as Escherichia coli or yeast. Through genome-wide metabolic network reconstruction, FBA can detail all biochemical reactions in an organism and calculate metabolic fluxes under specific conditions. In today's biotechnology community, FBA has become an effective tool for finding microbial production of industrial chemicals and can systematically identify the best pathways for the production of pharmaceutically or industrially important products.
FBA provides a more efficient and streamlined approach for metabolic background modeling because it requires much less input data than traditional methods.
Basic principles of FBA
Flux balance analysis is based on the chemical reactions of a metabolic network and assumes that the system is in a steady state, that is, the rates between production and consumption are balanced and remain constant over time. Under this assumption, the metabolic process can be simplified into a set of linear equations, and the optimal metabolic flux distribution can be obtained through linear programming methods.
Historical Background of FBA
The FBA method can be traced back to the 1980s, when researcher Papoutsakis demonstrated the possibility of using metabolic maps to construct flux balance equations, and Watson further proposed the idea of using linear programming to solve pathway fluxes. Subsequent research further promoted the application of this method in bioengineering.
Application of FBA
FBA has been widely used in bioprocess engineering, such as improving the production of industrial chemicals such as alcohol and sulphuric acid by systematically finding potential modifications in microbial metabolic networks. This method is not only of great significance in increasing production, but also can provide support for the identification of drug targets for cancer and pathogenic microorganisms.
With FBA, we are able to build models to predict microbial growth and product generation in different environments.
Throughput analysis technology
In FBA, reaction deletion and perturbation studies are a common technique to explore the criticality of specific reactions in the entire metabolic network. For example, deletion of single reactions can help determine which reactions are critical for biomass production. Further investigation of dual-reactive deletions could help identify the potential of multi-target drugs.
Optimization of Growth Media
By using phenotypic phase plane analysis (PhPP), FBA can be applied iteratively in models to adjust nutrient uptake constraints, thereby optimizing growth media to enhance microbial growth rate and product secretion to meet industrial needs.
Future Outlook
With the development of science and technology and the improvement of computing power, FBA will play an increasingly important role in microbial metabolic engineering. It is not limited to current applications but has the potential to play a key role in new generations of biotechnology research, especially in the design of new biosynthetic pathways and biotechnological products.
How can FBA predict and optimize the product generation potential of microorganisms in advance and further promote the production and development of industrial chemicals?
