A mathematical model of cell-free transcription-translation with plasmid crosstalk

Cell-free expression (CFE) systems are emerging as a powerful tool in synthetic biology, with diverse applications from prototyping genetic circuits to serving as a platform for point-of-care biosensors. When multiple genes need to be expressed in the same CFE reaction, their DNA templates (often added as plasmids) are generally assumed to behave independently of each other, with neither affecting the other's expression. However, recent work in <i>Escherichia coli</i> CFE systems shows that multiple aspects of these templates can lead to antagonistic or synergistic interactions in expression levels of individual genes, a phenomenon referred to as plasmid crosstalk. Plasmid crosstalk can confound efforts for precise engineering of genetic circuits and even give rise to misleading observations about circuit function. Unfortunately, current mathematical and computational models are incapable of reproducing critical aspects of plasmid crosstalk. To address this gap, we created an ordinary differential equation model incorporating mechanisms to account for competition for transcription, translation, and degradation resources, as well as toxic molecule build-up. This model can recapitulate the predominant observed phenomena of plasmid crosstalk. Simulation results and subsequent experimental validation provided insights into the different sources of burden and interactions in CFE systems, including that translation is negatively impacted by macromolecular crowding caused by possibly both transcription and translation. This model thus enables deeper understanding of CFE systems and could serve as a useful tool for future CFE application design.

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Publication Details

Journal
Synthetic Biology
Published
2025-01-01
DOI
https://doi.org/10.1093/synbio/ysaf011
Citations
1
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
0.81

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article

A mathematical model of cell-free transcription-translation with plasmid crosstalk

Alexandra T. Patterson, Mark P. Styczynski, Fernanda Piorino, Yue Han
1 citations
Synthetic Biology
CRISPR and Genetic Engineering
0.81
article

A mathematical model of cell-free transcription-translation with plasmid crosstalk

Alexandra T. Patterson, Mark P. Styczynski, Fernanda Piorino, Yue Han
article en
1 citations

Abstract

Cell-free expression (CFE) systems are emerging as a powerful tool in synthetic biology, with diverse applications from prototyping genetic circuits to serving as a platform for point-of-care biosensors. When multiple genes need to be expressed in the same CFE reaction, their DNA templates (often added as plasmids) are generally assumed to behave independently of each other, with neither affecting the other's expression. However, recent work in <i>Escherichia coli</i> CFE systems shows that multiple aspects of these templates can lead to antagonistic or synergistic interactions in expression levels of individual genes, a phenomenon referred to as plasmid crosstalk. Plasmid crosstalk can confound efforts for precise engineering of genetic circuits and even give rise to misleading observations about circuit function. Unfortunately, current mathematical and computational models are incapable of reproducing critical aspects of plasmid crosstalk. To address this gap, we created an ordinary differential equation model incorporating mechanisms to account for competition for transcription, translation, and degradation resources, as well as toxic molecule build-up. This model can recapitulate the predominant observed phenomena of plasmid crosstalk. Simulation results and subsequent experimental validation provided insights into the different sources of burden and interactions in CFE systems, including that translation is negatively impacted by macromolecular crowding caused by possibly both transcription and translation. This model thus enables deeper understanding of CFE systems and could serve as a useful tool for future CFE application design.

Synthetic BiologyVol. 10(1)
Georgia Institute of Technology (US), National Institute of Standards and Technology (US)
National Science Foundation, Georgia Institute of Technology, National Institutes of Health
Openalex Percentile: Top 27%
CRISPR and Genetic Engineering
0.81
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