| Title |
Kinetic modeling of rhamnolipid production by Pseudomonas aeruginosa PAO1 including cell density-dependent regulation
|
|---|---|
| Published in |
Applied Microbiology and Biotechnology, April 2014
|
| DOI | 10.1007/s00253-014-5750-3 |
| Pubmed ID | |
| Authors |
Marius Henkel, Anke Schmidberger, Markus Vogelbacher, Christian Kühnert, Janina Beuker, Thomas Bernard, Thomas Schwartz, Christoph Syldatk, Rudolf Hausmann |
| Abstract |
The production of rhamnolipid biosurfactants by Pseudomonas aeruginosa is under complex control of a quorum sensing-dependent regulatory network. Due to a lack of understanding of the kinetics applicable to the process and relevant interrelations of variables, current processes for rhamnolipid production are based on heuristic approaches. To systematically establish a knowledge-based process for rhamnolipid production, a deeper understanding of the time-course and coupling of process variables is required. By combining reaction kinetics, stoichiometry, and experimental data, a process model for rhamnolipid production with P. aeruginosa PAO1 on sunflower oil was developed as a system of coupled ordinary differential equations (ODEs). In addition, cell density-based quorum sensing dynamics were included in the model. The model comprises a total of 36 parameters, 14 of which are yield coefficients and 7 of which are substrate affinity and inhibition constants. Of all 36 parameters, 30 were derived from dedicated experimental results, literature, and databases and 6 of them were used as fitting parameters. The model is able to describe data on biomass growth, substrates, and products obtained from a reference batch process and other validation scenarios. The model presented describes the time-course and interrelation of biomass, relevant substrates, and products on a process level while including a kinetic representation of cell density-dependent regulatory mechanisms. |
Mendeley readers
The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Malaysia | 1 | 2% |
| Poland | 1 | 2% |
| Germany | 1 | 2% |
| Unknown | 60 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 11 | 17% |
| Student > Master | 10 | 16% |
| Researcher | 10 | 16% |
| Student > Ph. D. Student | 9 | 14% |
| Student > Doctoral Student | 4 | 6% |
| Other | 7 | 11% |
| Unknown | 12 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 18 | 29% |
| Engineering | 8 | 13% |
| Biochemistry, Genetics and Molecular Biology | 8 | 13% |
| Chemical Engineering | 5 | 8% |
| Chemistry | 3 | 5% |
| Other | 6 | 10% |
| Unknown | 15 | 24% |
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 07 December 2014.
All research outputs
#21,608,038
of 24,119,703 outputs
Outputs from Applied Microbiology and Biotechnology
#6,994
of 8,034 outputs
Outputs of similar age
#200,469
of 231,621 outputs
Outputs of similar age from Applied Microbiology and Biotechnology
#71
of 96 outputs
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