A quantitative method for proteome reallocation using minimal regulatory interventions

Area of Science:

• Synthetic Biology
• Metabolic Engineering
• Systems Biology

Background:

• Cellular resource allocation is a key challenge in engineering biological systems, as natural resource distribution prioritizes survival over synthetic functions.
• Optimizing resource allocation can enhance the productivity of engineered metabolic pathways and improve overall strain performance.

Purpose of the Study:

• To develop a novel method for engineering resource allocation in Escherichia coli.
• To identify minimal genetic interventions that maximize the release of cellular resources for synthetic biology applications.

Main Methods:

• Developed the ReProMin (Resource البروتomics Minimization) method to rationally modify the transcriptional regulatory network.
• Categorized transcription factors based on target essentiality and ranked them using proteomic data.
• Designed combinatorial removal of transcription factors to maximize resource release.

Main Results:

• Engineered an Escherichia coli strain with three mutations, theoretically releasing 0.5% of its proteome.
• The modified strain exhibited a higher proteome budget and increased production of an engineered metabolic pathway.
• Demonstrated high specificity of the regulatory interventions.

Conclusions:

• Combining proteomic and regulatory data enables effective strain optimization using conventional molecular methods.
• The ReProMin approach provides a powerful strategy for enhancing synthetic biology functions by re-engineering cellular resource allocation.