Synthetic biology--putting engineering into biology

Bioinformatics. 2006 Nov 15;22(22):2790-9. doi: 10.1093/bioinformatics/btl469. Epub 2006 Sep 5.


Synthetic biology is interpreted as the engineering-driven building of increasingly complex biological entities for novel applications. Encouraged by progress in the design of artificial gene networks, de novo DNA synthesis and protein engineering, we review the case for this emerging discipline. Key aspects of an engineering approach are purpose-orientation, deep insight into the underlying scientific principles, a hierarchy of abstraction including suitable interfaces between and within the levels of the hierarchy, standardization and the separation of design and fabrication. Synthetic biology investigates possibilities to implement these requirements into the process of engineering biological systems. This is illustrated on the DNA level by the implementation of engineering-inspired artificial operations such as toggle switching, oscillating or production of spatial patterns. On the protein level, the functionally self-contained domain structure of a number of proteins suggests possibilities for essentially Lego-like recombination which can be exploited for reprogramming DNA binding domain specificities or signaling pathways. Alternatively, computational design emerges to rationally reprogram enzyme function. Finally, the increasing facility of de novo DNA synthesis-synthetic biology's system fabrication process-supplies the possibility to implement novel designs for ever more complex systems. Some of these elements have merged to realize the first tangible synthetic biology applications in the area of manufacturing of pharmaceutical compounds.

Publication types

  • Review

MeSH terms

  • Animals
  • Biotechnology / methods*
  • Computational Biology / methods*
  • DNA / chemistry
  • Engineering
  • Genetic Engineering / methods*
  • Humans
  • Internet
  • Kinetics
  • Models, Biological
  • Protein Engineering / methods*
  • Signal Transduction
  • Software
  • Systems Biology


  • DNA