Title |
End-to-end automated microfluidic platform for synthetic biology: from design to functional analysis
|
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Published in |
Journal of Biological Engineering, February 2016
|
DOI | 10.1186/s13036-016-0024-5 |
Pubmed ID | |
Authors |
Gregory Linshiz, Erik Jensen, Nina Stawski, Changhao Bi, Nick Elsbree, Hong Jiao, Jungkyu Kim, Richard Mathies, Jay D. Keasling, Nathan J. Hillson |
Abstract |
Synthetic biology aims to engineer biological systems for desired behaviors. The construction of these systems can be complex, often requiring genetic reprogramming, extensive de novo DNA synthesis, and functional screening. Herein, we present a programmable, multipurpose microfluidic platform and associated software and apply the platform to major steps of the synthetic biology research cycle: design, construction, testing, and analysis. We show the platform's capabilities for multiple automated DNA assembly methods, including a new method for Isothermal Hierarchical DNA Construction, and for Escherichia coli and Saccharomyces cerevisiae transformation. The platform enables the automated control of cellular growth, gene expression induction, and proteogenic and metabolic output analysis. Taken together, we demonstrate the microfluidic platform's potential to provide end-to-end solutions for synthetic biology research, from design to functional analysis. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 9 | 33% |
United Kingdom | 2 | 7% |
Italy | 1 | 4% |
France | 1 | 4% |
Unknown | 14 | 52% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 22 | 81% |
Scientists | 5 | 19% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Belgium | 2 | 1% |
Taiwan | 1 | <1% |
Uruguay | 1 | <1% |
China | 1 | <1% |
United States | 1 | <1% |
Unknown | 174 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 40 | 22% |
Researcher | 38 | 21% |
Student > Master | 23 | 13% |
Student > Bachelor | 18 | 10% |
Other | 14 | 8% |
Other | 23 | 13% |
Unknown | 24 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 55 | 31% |
Agricultural and Biological Sciences | 35 | 19% |
Engineering | 31 | 17% |
Chemical Engineering | 7 | 4% |
Computer Science | 5 | 3% |
Other | 18 | 10% |
Unknown | 29 | 16% |