| Title |
Biosynthesis of di-rhamnolipids and variations of congeners composition in genetically-engineered Escherichia coli
|
|---|---|
| Published in |
Biotechnology Techniques, April 2017
|
| DOI | 10.1007/s10529-017-2333-2 |
| Pubmed ID | |
| Authors |
Jin Du, Aijun Zhang, Jian’an Hao, Jing Wang |
| Abstract |
To engineer Escherichia coli for the heterologous production of di-rhamnolipids, which are important biosurfactants but mainly produced by opportunistic pathogen Pseudomonas aeruginosa. The codon-optimized rhlAB and rhlC genes originating from P. aeruginosa and Burkholderia pseudomallei were combinatorially expressed in E. coli to produce di-rhamnolipids with varied congeners compositions. Genes involved in endogenous upstream pathways (rhamnose and fatty acids synthesis) were co-overexpressed with rhlAB-rhlC, resulting in variations of rhamnolipids production and congeners compositions. Under the shake-flask condition, co-overexpression of rfbD with rhlAB-rhlC increased rhamnolipids production (0.64 ± 0.02 g l(-1)) than that in strain only expressing rhlAB-rhlC (0.446 ± 0.009 g l(-1)), which was mainly composed of di-rhamnolipids congeners Rha-Rha-C10-C10. Biosynthesis of di-rhamnolipids and variations of congeners composition in genetically engineered E. coli strains were achieved via combiniations of mono-/di-rhamnolipids synthesis modules and endogenous upstream modules. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 5% |
| Germany | 1 | 5% |
| Unknown | 19 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 4 | 19% |
| Researcher | 3 | 14% |
| Student > Ph. D. Student | 3 | 14% |
| Student > Doctoral Student | 1 | 5% |
| Other | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 9 | 43% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 24% |
| Agricultural and Biological Sciences | 2 | 10% |
| Environmental Science | 1 | 5% |
| Immunology and Microbiology | 1 | 5% |
| Medicine and Dentistry | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 9 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 April 2017.
All research outputs
#17,289,387
of 25,382,440 outputs
Outputs from Biotechnology Techniques
#2,206
of 2,762 outputs
Outputs of similar age
#206,651
of 323,671 outputs
Outputs of similar age from Biotechnology Techniques
#12
of 25 outputs
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