Advances and challenges in programming pattern formation using living cells

Jia Lu; Emrah Şimşek; Anita Silver; Lingchong You

doi:10.1016/j.cbpa.2022.102147

Advances and challenges in programming pattern formation using living cells

Curr Opin Chem Biol. 2022 Jun:68:102147. doi: 10.1016/j.cbpa.2022.102147. Epub 2022 Apr 23.

Authors

Jia Lu¹, Emrah Şimşek¹, Anita Silver¹, Lingchong You²

Affiliations

¹ Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA.
² Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA; Center for Genomic and Computational Biology, Duke University, Durham, NC, 27708, USA; Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC, 27708, USA. Electronic address: you@duke.edu.

Abstract

Spatial patterning of cell populations is a ubiquitous phenomenon in nature. Patterns occur at various length and time scales and exhibit immense diversity. In addition to offering a deeper understanding of the emergence of patterns in nature, the ability to program synthetic patterns using living cells has the potential for broad applications. To date, however, progress in engineering pattern formation has been hampered by technical challenges. In this Review, we discuss recent advances in programming pattern formation in terms of biological insights, experimental and computational tool development, and potential applications.

Keywords: Machine learning; Pattern formation; Reaction-diffusion models; Synthetic biology; Turing patterns.

Publication types

Review
Research Support, U.S. Gov't, Non-P.H.S.
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Diffusion
Models, Biological*

Grants and funding

T32 GM008555/GM/NIGMS NIH HHS/United States