Automatic design of synthetic gene circuits through mixed integer non-linear programming

Linh Huynh, John D Kececioglu, Matthias Köppe, Ilias Tagkopoulos

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

Automatic design of synthetic gene circuits poses a significant challenge to synthetic biology, primarily due to the complexity of biological systems, and the lack of rigorous optimization methods that can cope with the combinatorial explosion as the number of biological parts increases. Current optimization methods for synthetic gene design rely on heuristic algorithms that are usually not deterministic, deliver sub-optimal solutions, and provide no guaranties on convergence or error bounds. Here, we introduce an optimization framework for the problem of part selection in synthetic gene circuits that is based on mixed integer non-linear programming (MINLP), which is a deterministic method that finds the globally optimal solution and guarantees convergence in finite time. Given a synthetic gene circuit, a library of characterized parts, and user-defined constraints, our method can find the optimal selection of parts that satisfy the constraints and best approximates the objective function given by the user. We evaluated the proposed method in the design of three synthetic circuits (a toggle switch, a transcriptional cascade, and a band detector), with both experimentally constructed and synthetic promoter libraries. Scalability and robustness analysis shows that the proposed framework scales well with the library size and the solution space. The work described here is a step towards a unifying, realistic framework for the automated design of biological circuits.

Original languageEnglish (US)
Article numbere35529
JournalPLoS One
Volume7
Issue number4
DOIs
StatePublished - Apr 20 2012

Fingerprint

Synthetic Genes
synthetic genes
Gene Regulatory Networks
Nonlinear programming
Genes
Networks (circuits)
system optimization
Libraries
synthetic biology
Synthetic Biology
explosions
Explosions
detectors
Biological systems
Heuristic algorithms
methodology
promoter regions
Scalability
Switches
gene regulatory networks

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Automatic design of synthetic gene circuits through mixed integer non-linear programming. / Huynh, Linh; Kececioglu, John D; Köppe, Matthias; Tagkopoulos, Ilias.

In: PLoS One, Vol. 7, No. 4, e35529, 20.04.2012.

Research output: Contribution to journalArticle

Huynh, Linh ; Kececioglu, John D ; Köppe, Matthias ; Tagkopoulos, Ilias. / Automatic design of synthetic gene circuits through mixed integer non-linear programming. In: PLoS One. 2012 ; Vol. 7, No. 4.
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