Chapter title |
Regulatory Tools for Controlling Gene Expression in Cyanobacteria
|
---|---|
Chapter number | 12 |
Book title |
Synthetic Biology of Cyanobacteria
|
Published in |
Advances in experimental medicine and biology, January 2018
|
DOI | 10.1007/978-981-13-0854-3_12 |
Pubmed ID | |
Book ISBNs |
978-9-81-130853-6, 978-9-81-130854-3
|
Authors |
Gina C. Gordon, Brian F. Pfleger, Gordon, Gina C., Pfleger, Brian F., Gina Gordon, Brian Pfleger |
Abstract |
Cyanobacteria are attractive hosts for converting carbon dioxide and sunlight into desirable chemical products. To engineer these organisms and manipulate their metabolic pathways, the biotechnology community has developed genetic tools to control gene expression. Many native cyanobacterial promoters and related sequence elements have been used to regulate genes of interest, and heterologous tools that use non-native small molecules to induce gene expression have been demonstrated. Overall, IPTG-based induction systems seem to be leaky and initially demonstrate small dynamic ranges in cyanobacteria. Consequently, a variety of other induction systems have been optimized to enable tighter control of gene expression. Tools require significant optimization because they function quite differently in cyanobacteria when compared to analogous use in model heterotrophs. We hypothesize that these differences are due to fundamental differences in physiology between organisms. This review is not intended to summarize all known products made in cyanobacteria nor the performance (titer, rate, yield) of individual strains, but instead will focus on the genetic tools and the inherent aspects of cellular physiology that influence gene expression in cyanobacteria. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 92 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 15 | 16% |
Student > Bachelor | 11 | 12% |
Researcher | 10 | 11% |
Student > Doctoral Student | 7 | 8% |
Student > Master | 5 | 5% |
Other | 10 | 11% |
Unknown | 34 | 37% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 33 | 36% |
Agricultural and Biological Sciences | 8 | 9% |
Chemical Engineering | 4 | 4% |
Engineering | 3 | 3% |
Chemistry | 2 | 2% |
Other | 5 | 5% |
Unknown | 37 | 40% |