ePrints

Computer-Aided Whole-Cell Design: Taking a Holistic Approach by Integrating Synthetic With Systems Biology

Lookup NU author(s): Professor Paul RaceORCiD

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.

Abstract

© Copyright © 2020 Marucci, Barberis, Karr, Ray, Race, de Souza Andrade, Grierson, Hoffmann, Landon, Rech, Rees-Garbutt, Seabrook, Shaw and Woods. Computer-aided design (CAD) for synthetic biology promises to accelerate the rational and robust engineering of biological systems. It requires both detailed and quantitative mathematical and experimental models of the processes to (re)design biology, and software and tools for genetic engineering and DNA assembly. Ultimately, the increased precision in the design phase will have a dramatic impact on the production of designer cells and organisms with bespoke functions and increased modularity. CAD strategies require quantitative models of cells that can capture multiscale processes and link genotypes to phenotypes. Here, we present a perspective on how whole-cell, multiscale models could transform design-build-test-learn cycles in synthetic biology. We show how these models could significantly aid in the design and learn phases while reducing experimental testing by presenting case studies spanning from genome minimization to cell-free systems. We also discuss several challenges for the realization of our vision. The possibility to describe and build whole-cells in silico offers an opportunity to develop increasingly automatized, precise and accessible CAD tools and strategies.

Publication metadata

Author(s): Marucci L, Barberis M, Karr J, Ray O, Race PR, de Souza Andrade M, Grierson C, Hoffmann SA, Landon S, Rech E, Rees-Garbutt J, Seabrook R, Shaw W, Woods C

Publication type: Article

Publication status: Published

Journal: Frontiers in Bioengineering and Biotechnology

Year: 2020

Volume: 8

Online publication date: 07/08/2020

Acceptance date: 21/07/2020

ISSN (electronic): 2296-4185

Publisher: Frontiers Media SA

URL: https://doi.org/10.3389/fbioe.2020.00942

DOI: 10.3389/fbioe.2020.00942

Altmetrics

Share