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Journal of industrial microbiology & biotechnology
Jul, 2018;45 (7): 599-614.

Bottom-up approaches in synthetic biology and biomaterials for tissue engineering applications.

Mitchell S Weisenberger, Tara L Deans
Author Information
  1. Mitchell S Weisenberger: Department of Bioengineering, University of Utah, Salt Lake City, UT, 84112, USA.
  2. Tara L Deans: Department of Bioengineering, University of Utah, Salt Lake City, UT, 84112, USA. tara.deans@utah.edu. ORCID
PMID: 29552703 DOI: 10.1007/s10295-018-2027-3

Abstract

Synthetic biologists use engineering principles to design and construct genetic circuits for programming cells with novel functions. A bottom-up approach is commonly used to design and construct genetic circuits by piecing together functional modules that are capable of reprogramming cells with novel behavior. While genetic circuits control cell operations through the tight regulation of gene expression, a diverse array of environmental factors within the extracellular space also has a significant impact on cell behavior. This extracellular space offers an addition route for synthetic biologists to apply their engineering principles to program cell-responsive modules within the extracellular space using biomaterials. In this review, we discuss how taking a bottom-up approach to build genetic circuits using DNA modules can be applied to biomaterials for controlling cell behavior from the extracellular milieu. We suggest that, by collectively controlling intrinsic and extrinsic signals in synthetic biology and biomaterials, tissue engineering outcomes can be improved.

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Grants

  1. R21 EB025413/NIBIB NIH HHS
  2. ONR - N00014-16-1-3012/Office of Naval Research
  3. CBET - 1554017/National Science Foundation
  4. 1R21EB025413-01/National Institutes of Health

MeSH Term

Biocompatible Materials
Gene Expression Regulation, Bacterial
Gene Regulatory Networks
Genetic Engineering
Humans
Synthetic Biology
Tissue Engineering
Transcription Factors

Chemicals

Biocompatible Materials
Transcription Factors
Journal Article
Article has an altmetric score of 7

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