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Lee, Sung Kuk
Synthetic Biology & Metabolic Engineering Lab.
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BglBrick vectors and datasheets: A synthetic biology platform for gene expression

Author(s)
Lee, Taek SoonKrupa, Rachel AZhang, FuzhongHajimorad, MeghdadHoltz, William JPrasad, NiluLee, Sung KukKeasling, Jay D
Issued Date
2011-09
DOI
10.1186/1754-1611-5-12
URI
https://scholarworks.unist.ac.kr/handle/201301/2573
Fulltext
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=80053175916
Citation
JOURNAL OF BIOLOGICAL ENGINEERING, v.5, no.20, pp.1 - 14
Abstract
Background: As engineered biological systems become more complex, it is increasingly common to express multiple operons from different plasmids and inducible expression systems within a single host cell. Optimizing such systems often requires screening combinations of origins of replication, expression systems, and antibiotic markers. This procedure is hampered by a lack of quantitative data on how these components behave when more than one origin of replication or expression system are used simultaneously. Additionally, this process can be time consuming as it often requires the creation of new vectors or cloning into existing but disparate vectors.Results: Here, we report the development and characterization of a library of expression vectors compatible with the BglBrick standard (BBF RFC 21). We have designed and constructed 96 BglBrick-compatible plasmids with a combination of replication origins, antibiotic resistance genes, and inducible promoters. These plasmids were characterized over a range of inducer concentrations, in the presence of non-cognate inducer molecules, and with several growth media, and their characteristics were documented in a standard format datasheet. A three plasmid system was used to investigate the impact of multiple origins of replication on plasmid copy number.Conclusions: The standardized collection of vectors presented here allows the user to rapidly construct and test the expression of genes with various combinations of promoter strength, inducible expression system, copy number, and antibiotic resistance. The quantitative datasheets created for these vectors will increase the predictability of gene expression, especially when multiple plasmids and inducers are utilized.
Publisher
BIOMED CENTRAL
ISSN
1754-1611

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