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Engineering prokaryotic gene circuits
Author(s) -
Michalodimitrakis Konstantinos,
Isalan Mark
Publication year - 2009
Publication title -
fems microbiology reviews
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.91
H-Index - 212
eISSN - 1574-6976
pISSN - 0168-6445
DOI - 10.1111/j.1574-6976.2008.00139.x
Subject(s) - synthetic biology , multicellular organism , biology , computational biology , metabolic engineering , gene regulatory network , systems biology , prokaryote , gene , genome engineering , regulation of gene expression , genome , genetics , gene expression , genome editing
Engineering of synthetic gene circuits is a rapidly growing discipline, currently dominated by prokaryotic transcription networks, which can be easily rearranged or rewired to give different output behaviours. In this review, we examine both a rational and a combinatorial design of such networks and discuss progress on using in vitro evolution techniques to obtain functional systems. Moving beyond pure transcription networks, more and more networks are being implemented at the level of RNA, taking advantage of mechanisms of translational control and aptamer–small molecule complex formation. Unlike gene expression systems, metabolic components are generally not as interconnectable in any combination, and so engineering of metabolic circuits is a particularly challenging field. Nonetheless, metabolic engineering has immense potential to provide useful biosynthesis tools for biotechnology applications. Finally, although prokaryotes are mostly studied as single cell systems, cell–cell communication networks are now being developed that result in spatial pattern formation in multicellular prokaryote colonies. This represents a crossover with multicellular organisms, showing that prokaryotic systems have the potential to tackle questions traditionally associated with developmental biology. Overall, the current advances in synthetic gene synthesis, ultra‐high‐throughput DNA sequencing and computation are synergizing to drive synthetic gene network design at an unprecedented pace.

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