| Title |
Proteomics analysis of metabolically engineered yeast cells and medium-chained hydrocarbon biofuel precursors synthesis
|
|---|---|
| Published in |
AMB Express, August 2014
|
| DOI | 10.1186/s13568-014-0061-8 |
| Pubmed ID | |
| Authors |
Xiang Li, Wei Ning Chen |
| Abstract |
Recently, various biofuels have been synthesized through metabolic engineering approaches to meet the exploding energy demands. Hydrocarbon biofuels, energy-equivalent to petroleum-based fuels, are identified as promising replacements for petroleum. Metabolically engineered Saccharomyces cerevisiae capable of synthesize precursors of medium-chained hydrocarbons is proposed in this study. The hydroperoxide pathway introduced in S. cerevisiae consisted of lipoxygenase (LOX) and hydroperoxide lyase (HPL) from almond, which catalyzes linoleic acid to 3(Z)-nonenal, the precursor for medium-chained hydrocarbon biofuels. Proteomics study showed that 31 proteins displayed different expression levels among four functional strains and most of them were related to carbohydrate metabolism and protein synthesis, suggested prospective capabilities of energy generation and exogenous protein synthesis. Biotransformation efficiency studies carried out by GC-FID were in accordance with the expectations. The highest yield of 3(Z)-nonenal was up to 1.21 ± 0.05 mg/L with the carbon recovery of up to 12.4%. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 1 | 5% |
| China | 1 | 5% |
| Unknown | 17 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 26% |
| Researcher | 4 | 21% |
| Professor > Associate Professor | 2 | 11% |
| Student > Master | 2 | 11% |
| Professor | 1 | 5% |
| Other | 3 | 16% |
| Unknown | 2 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 32% |
| Biochemistry, Genetics and Molecular Biology | 3 | 16% |
| Engineering | 3 | 16% |
| Chemistry | 2 | 11% |
| Medicine and Dentistry | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 4 | 21% |
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 10 June 2015.
All research outputs
#18,378,085
of 22,763,032 outputs
Outputs from AMB Express
#796
of 1,231 outputs
Outputs of similar age
#168,224
of 235,902 outputs
Outputs of similar age from AMB Express
#10
of 20 outputs
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