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PMID: 16729053 Published · ppublish English Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Refactoring bacteriophage T7.

Molecular systems biology ·Vol. 1 ·2005-00-00 ·Pages 2005.0018

Chan LY, Kosuri S, Endy D

Abstract

Natural biological systems are selected by evolution to continue to exist and evolve. Evolution likely gives rise to complicated systems that are difficult to understand and manipulate. Here, we redesign the genome of a natural biological system, bacteriophage T7, in order to specify an engineered surrogate that, if viable, would be easier to study and extend. Our initial design goals were to physically separate and enable unique manipulation of primary genetic elements. Implicit in our design are the hypotheses that overlapping genetic elements are, in aggregate, nonessential for T7 viability and that our models for the functions encoded by elements are sufficient. To test our initial design, we replaced the left 11,515 base pairs (bp) of the 39,937 bp wild-type genome with 12,179 bp of engineered DNA. The resulting chimeric genome encodes a viable bacteriophage that appears to maintain key features of the original while being simpler to model and easier to manipulate. The viability of our initial design suggests that the genomes encoding natural biological systems can be systematically redesigned and built anew in service of scientific understanding or human intention.

MeSH Terms
Algorithms Bacteriophage T7/genetics,growth & development,physiology Base Pairing DNA, Recombinant/chemical synthesis,genetics DNA, Viral/genetics Escherichia coli/virology Genes, Overlapping Genes, Viral Genetic Engineering Genome, Viral Models, Biological Models, Genetic Molecular Sequence Data Organisms, Genetically Modified/genetics,growth & development,physiology Sequence Deletion Systems Biology/methods Transfection Viral Proteins/genetics,physiology Virus Replication
Chemicals
DNA, Recombinant DNA, Viral Viral Proteins
Authors & Affiliations
3 authors, click to expand affiliations / ORCID
Chan Leon Y
Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Kosuri Sriram
Endy Drew
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Article Info
Journal
Molecular systems biology
Abbr.
Mol Syst Biol
ISSN
1744-4292
DOI
10.1038/msb4100025
Published
2005-00-00
Epub
2005-00-13
Pages
2005.0018
Language
English
Region
England
NLM ID
101235389
PMCID
PMC1681472
Subset
IM
Databases
GENBANK
DQ100054, DQ100055
Corrections
CommentIn
PMID: 16729055
External Links
PubMed source DOI: 10.1038/msb4100025 PMC Full Text View journal details
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