4.7 Article

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

Journal

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fbioe.2020.00942

Keywords

whole-cell models; synthetic biology; systems biology; multiscale models; bioengineering; biodesign

Funding

  1. Engineering and Physical Sciences Research Council (EPSRC) [EP/R041695/1, EP/S01876X/1]
  2. Horizon 2020 (CosyBio) [766840]
  3. Systems Biology Grant of the University of Surrey
  4. National Institutes of Health [R35GM119771]
  5. EPSRC [EP/R020957/1]
  6. Biotechnology and Biological Sciences Research Council (BBSRC) [BB/T001968/1]
  7. BrisSynBio, a BBSRC/EPSRC Synthetic Biology Research Centre [BB/L01386X/]
  8. EPSRC Future Opportunity Ph.D. scholarships
  9. INCT BioSyn (National Institute of Science and Technology in Synthetic Biology), Brazil
  10. CNPq (National Council for Scientific and Technological Development), Brazil
  11. CAPES (Coordination for the Improvement of Higher Education Personnel), Brazil
  12. Brazilian Ministry of Health, Brazil
  13. FAPDF (Research Support Foundation of the Federal District), Brazil
  14. BBSRC [BB/T001968/1, BB/L01386X/1] Funding Source: UKRI
  15. EPSRC [EP/S01876X/1, 1793989, EP/R041695/1, EP/N018591/1] Funding Source: UKRI

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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-cellsin silicooffers an opportunity to develop increasingly automatized, precise and accessible CAD tools and strategies.

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