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RBS and Promoter Strengths Determine the Cell-Growth-Dependent Protein Mass Fractions and Their Optimal Synthesis

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Summary

This study introduces a simple model for bacterial gene expression, revealing how limited cellular resources affect protein production. The model explains gene expression strategies and aids in designing synthetic biological systems.

Keywords:
RBS strengthburdengene expressiongrowth ratepromoter strengthprotein synthesis mass fractionsresources allocation

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Area of Science:

  • Systems Biology
  • Molecular Biology
  • Synthetic Biology

Background:

  • Understanding gene expression in bacteria is crucial for both evolutionary insights and synthetic biology applications.
  • Host-circuit interactions, driven by limited cellular resources, significantly influence gene expression dynamics.
  • Existing models often simplify or overlook the interplay between host resource allocation and heterologous gene expression.

Purpose of the Study:

  • To develop a simplified model of bacterial gene expression that incorporates host-circuit interactions and limited cellular resources.
  • To define and analyze a key coefficient, 'cellular resources recruitment strength,' governing resource distribution.
  • To provide a framework for understanding endogenous gene strategies and designing synthetic gene expression systems.

Main Methods:

  • Developed a small-size mathematical model for gene expression dynamics in bacterial cells.
  • Incorporated host-circuit interactions by accounting for limited cellular resources.
  • Defined 'cellular resources recruitment strength' as a functional coefficient.
  • Validated the model against experimental data for *Escherichia coli* growth rates and protein expression levels.

Main Results:

  • The model accurately captures the differential impact of promoter and ribosome binding site (RBS) strengths on protein mass fractions across varying growth rates.
  • It successfully predicts the optimal protein synthesis rate, aligning with experimental observations.
  • The 'cellular resources recruitment strength' effectively explains resource distribution and its link to cell growth.

Conclusions:

  • The model provides a parsimonious yet powerful explanation for the diverse strategies evolved by endogenous genes in expression.
  • It offers insights into the trade-offs associated with resource allocation in gene expression.
  • The model is suitable for the rational design of synthetic gene expression systems with predictable characteristics.