| Title |
An enhanced genome-scale metabolic reconstruction of Streptomyces clavuligerus identifies novel strain improvement strategies
|
|---|---|
| Published in |
Bioprocess and Biosystems Engineering, February 2018
|
| DOI | 10.1007/s00449-018-1900-9 |
| Pubmed ID | |
| Authors |
León Toro, Laura Pinilla, Claudio Avignone-Rossa, Rigoberto Ríos-Estepa |
| Abstract |
In this work, we expanded and updated a genome-scale metabolic model of Streptomyces clavuligerus. The model includes 1021 genes and 1494 biochemical reactions; genome-reaction information was curated and new features related to clavam metabolism and to the biomass synthesis equation were incorporated. The model was validated using experimental data from the literature and simulations were performed to predict cellular growth and clavulanic acid biosynthesis. Flux balance analysis (FBA) showed that limiting concentrations of phosphate and an excess of ammonia accumulation are unfavorable for growth and clavulanic acid biosynthesis. The evaluation of different objective functions for FBA showed that maximization of ATP yields the best predictions for cellular behavior in continuous cultures, while the maximization of growth rate provides better predictions for batch cultures. Through gene essentiality analysis, 130 essential genes were found using a limited in silico media, while 100 essential genes were identified in amino acid-supplemented media. Finally, a strain design was carried out to identify candidate genes to be overexpressed or knocked out so as to maximize antibiotic biosynthesis. Interestingly, potential metabolic engineering targets, identified in this study, have not been tested experimentally. |
X Demographics
The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 5 | 56% |
| Colombia | 1 | 11% |
| Mexico | 1 | 11% |
| Unknown | 2 | 22% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 89% |
| Scientists | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 64 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 16% |
| Researcher | 7 | 11% |
| Professor | 6 | 9% |
| Other | 6 | 9% |
| Student > Master | 6 | 9% |
| Other | 12 | 19% |
| Unknown | 17 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 17 | 27% |
| Chemical Engineering | 8 | 13% |
| Engineering | 8 | 13% |
| Agricultural and Biological Sciences | 6 | 9% |
| Environmental Science | 2 | 3% |
| Other | 7 | 11% |
| Unknown | 16 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 08 February 2018.
All research outputs
#6,326,496
of 25,461,852 outputs
Outputs from Bioprocess and Biosystems Engineering
#120
of 604 outputs
Outputs of similar age
#116,930
of 446,463 outputs
Outputs of similar age from Bioprocess and Biosystems Engineering
#1
of 1 outputs
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So far Altmetric has tracked 604 research outputs from this source. They receive a mean Attention Score of 3.1. This one has done well, scoring higher than 87% of its peers.
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