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Evolutionary design and analysis of ribozyme-based logic gates

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Abstract

A main goal of synthetic biology is the design of logic gates that can reprogram cells to perform various user-defined tasks. One approach is the use of ribozyme-based logic gates (ribogates) consisting of catalytic RNA strands. However, existing ribogate design approaches face limitations in terms of complexity, diversity, ease of use, and reliability. To address these challenges, we introduce a multi-objective evolutionary algorithm called Truth-Seq-Er, which generates diverse and complex ribogate designs while improving user-friendliness and accessibility. Truth-Seq-Er uses a quality diversity approach and a novel technique called viability nullification to design 1, 2, and 3-input integrated ribogates that implement both linearly separable and inseparable functions. By requiring only a target Boolean function as input, the algorithm eliminates the need for domain knowledge and streamlines the design process. The diverse designs generated by Truth-Seq-Er are robust against unexpected requirements and provide a large, unbiased dataset for characterizing candidate ribogates. Moreover, we propose a graph-based model for ribogate operation and analyze the design principles shared by different ribogate families. The results demonstrate the potential of Truth-Seq-Er in advancing ribogate design and contributing to the development of novel synthetic biology and unconventional computing applications. Truth-Seq-Er is available for download at https://github.com/nickkamel/Truth_Seq_Er_CLI.

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Acknowledgements

We would like to thank Joey Paquet for reviewing earlier versions of this manuscript and providing critical feedback.

Funding

This work was supported by the Natural Sciences and Engineering Research Council of Canada Discovery Grant (individual) and CREATE program (SynBioApps), as well as the Canadian Institutes of Health Research project grant (bridge).

Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada

    Nicolas Kamel & Nawwaf Kharma

  2. Institut National de la Recherche Scientifique, Laval, Canada

    Jonathan Perreault

Authors
  1. Nicolas Kamel
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  2. Nawwaf Kharma
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  3. Jonathan Perreault
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Contributions

Kharma and Kamel performed an extensive review on different ways to implement logic gates in biological matter, and identified ribozymes as an appropriate approach. Kamel wrote the manuscript, drew the figures, designed and coded the Truth-Seq-Er evolutionary algorithm, and proposed the additive segment competition model (mechanism graphs). Kharma made substantial contributions to the formulation of the evolutionary algorithm, the presentation and discussion of the results, and the writing and critical review of the manuscript. J.P. provided critical insight into the structure and function of ribozymes, and provided feedback to ensure that the designed ribogates were biologically plausible.

Corresponding author

Correspondence to Nicolas Kamel.

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The authors have no conflicts of interest to declare.

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Area Editor: Ting Hu.

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Kamel, N., Kharma, N. & Perreault, J. Evolutionary design and analysis of ribozyme-based logic gates. Genet Program Evolvable Mach 24, 11 (2023). https://doi.org/10.1007/s10710-023-09459-x

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  • DOI: https://doi.org/10.1007/s10710-023-09459-x

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