A coarse-grained bacterial cell model for resource-aware analysis and design of synthetic gene circuits.

Kirill Sechkar, Harrison Steel, Giansimone Perrino, Guy-Bart Stan
Author Information
  1. Kirill Sechkar: Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK. ORCID
  2. Harrison Steel: Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK. ORCID
  3. Giansimone Perrino: Department of Bioengineering, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK. g.perrino@imperial.ac.uk. ORCID
  4. Guy-Bart Stan: Department of Bioengineering, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK. g.stan@imperial.ac.uk. ORCID

Abstract

Within a cell, synthetic and native genes compete for expression machinery, influencing cellular process dynamics through resource couplings. Models that simplify competitive resource binding kinetics can guide the design of strategies for countering these couplings. However, in bacteria resource availability and cell growth rate are interlinked, which complicates resource-aware biocircuit design. Capturing this interdependence requires coarse-grained bacterial cell models that balance accurate representation of metabolic regulation against simplicity and interpretability. We propose a coarse-grained E. coli cell model that combines the ease of simplified resource coupling analysis with appreciation of bacterial growth regulation mechanisms and the processes relevant for biocircuit design. Reliably capturing known growth phenomena, it provides a unifying explanation to disparate empirical relations between growth and synthetic gene expression. Considering a biomolecular controller that makes cell-wide ribosome availability robust to perturbations, we showcase our model's usefulness in numerically prototyping biocircuits and deriving analytical relations for design guidance.

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Grants

  1. RAEng CiET 1819\5/Royal Academy of Engineering

MeSH Term

Escherichia coli
Genes, Synthetic
Awareness
Binding, Competitive
Cell Cycle

Word Cloud

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