Control theory meets synthetic biology.

J R Soc Interface

Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

Published: July 2016

AI Article Synopsis

  • The review discusses the integration of control theory in synthetic biology, focusing on how these concepts help solve challenges in designing synthetic biomolecular circuits.
  • It highlights successful examples of control design methods that enhance the reliability and predictability of genetic circuits within individual cells and across populations.
  • The paper aims to guide synthetic biologists in applying feedback control principles while also informing control theorists about the emerging field of synthetic biology.

Article Abstract

The past several years have witnessed an increased presence of control theoretic concepts in synthetic biology. This review presents an organized summary of how these control design concepts have been applied to tackle a variety of problems faced when building synthetic biomolecular circuits in living cells. In particular, we describe success stories that demonstrate how simple or more elaborate control design methods can be used to make the behaviour of synthetic genetic circuits within a single cell or across a cell population more reliable, predictable and robust to perturbations. The description especially highlights technical challenges that uniquely arise from the need to implement control designs within a new hardware setting, along with implemented or proposed solutions. Some engineering solutions employing complex feedback control schemes are also described, which, however, still require a deeper theoretical analysis of stability, performance and robustness properties. Overall, this paper should help synthetic biologists become familiar with feedback control concepts as they can be used in their application area. At the same time, it should provide some domain knowledge to control theorists who wish to enter the rising and exciting field of synthetic biology.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4971224PMC
http://dx.doi.org/10.1098/rsif.2016.0380DOI Listing

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