- Brief Model Description
This repository contains the collection of the current genome-scale metabolic models for 24 Penicillium species, which were reconstructed to study their secondary metabolism.
- Abstract:
Modeling of metabolism at the genome scale have proved to be an efficient approach to explain observed phenotypic traits in living organisms. Further, it can be used as a means of predicting the effect of genetic modifications e.g. for generation of microbial cell factories. With the increasing amount of genome sequencing data available, a need exists to accurately and efficiently generate such genome scale metabolic models (GEMs) of non-model organisms, which have limited experimental characterization associated to them. In this study, we present an automatic reconstruction approach applied to 24 Penicillium species, which have potential for production of small molecule pharmaceuticals, so-called secondary metabolites. The models were based on the MetaCyc database and a previously published Penicillium GEM, and gave rise to comprehensive genome scale descriptions of their metabolism. The models proved that while central carbon metabolism is conserved, secondary metabolic pathways represent the main diversity among the species. The automatic reconstruction approach presented in this study can be applied to generate GEMs of other understudied organisms, and the developed GEMs are a useful resource for the study of Penicillium metabolism, for example with the scope of developing novel cell factories.
- Model KeyWords:
GEM Category: Collection; Utilisation: maximising product growth, experimental data reconstruction; Field: metabolic-network reconstruction; Type of Model: reconstruction; Model Source: MetaCyC, iAL1006; Omic Source: Genomics; Taxonomy: Penicillium; Metabolic System: General Metabolism, Secondary metabolism; Condition: Rich Media;
S. Prigent, J.C. Nielsen, J.C. Frisvad, J. Nielsen. Reconstruction of 24 Penicillium genome-scale metabolic models shows diversity based on their secondary metabolism Biotechnology and Bioengineering [https://doi.org/10.1002/bit.26739] (https://doi.org/10.1002/bit.26739)
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Last update: 2023-01-27
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The model:
| Taxonomy | Template Model | Reactions | Metabolites | Genes |
|---|---|---|---|---|
| Penicillium antarcticum | Pantarcticum.xml | 2572 | 3064 | 1755 |
| Penicillium arizonense | Parizonense.xml | 2629 | 3120 | 1954 |
| Penicillium biforme | Pbiforme.xml | 2638 | 3134 | 1878 |
| Penicillium brasilianum | Pbrasilianum.xml | 2658 | 3192 | 1894 |
| Penicillium camemberti | Pcamemberti.xml | 2631 | 3134 | 1859 |
| Penicillium carneum | Pcarneum.xml | 2469 | 2931 | 1611 |
| Penicillium coprophilum | Pcoprophilum.xml | 2443 | 2895 | 1530 |
| Penicillium decumbens | Pdecumbens.xml | 2211 | 2623 | 1256 |
| Penicillium digitatum | Pdigitatum.xml | 2351 | 2829 | 1403 |
| Penicillium expansum | Pexpansum.xml | 2601 | 3085 | 1873 |
| Penicillium flavigenum | Pflavigenum.xml | 2506 | 2973 | 1712 |
| Penicillium freii | Pfreii.xml | 2562 | 3037 | 1766 |
| Penicillium fuscoglaucum | Pfuscoglaucum.xml | 2637 | 3154 | 1886 |
| Penicillium griseofulvum | Pgriseofulvum.xml | 2579 | 3066 | 1700 |
| Penicillium italicum | Pitalicum.xml | 2453 | 2924 | 1536 |
| Penicillium nalgiovense | Pnalgiovense.xml | 2515 | 2967 | 1677 |
| Penicillium oxalicum | Poxalicum.xml | 2458 | 2967 | 1435 |
| Penicillium paneum | Ppaneum.xml | 2468 | 2935 | 1581 |
| Penicillium polonicum | Ppolonicum.xml | 2537 | 3016 | 1727 |
| Penicillium roqueforti | Proqueforti.xml | 2467 | 2935 | 1611 |
| Penicillium rubens | Prubens.xml | 2574 | 3058 | 1771 |
| Penicillium solitum | Psolitum.xml | 2623 | 3134 | 1886 |
| Penicillium steckii | Psteckii.xml | 2555 | 3101 | 1748 |
| Penicillium vulpinum | Pvulpinum.xml | 2501 | 2949 | 1627 |
This repository is administered by Sylvain Prigent @syprigen, Division of Systems and Synthetic Biology, Department of Biology and Biological Engineering, Chalmers University of Technology
You need either:
- A functional COBRApy installation, find it here or
- A functional Matlab installation of Matlab_R_2015_b (MATLAB 7.3 and higher)
- The RAVEN toolbox for MATLAB. An up-to-date version from COBRA GitHub repository is strongly recommended . Add the directory to your Matlab path, instructions here
- libSBML MATLAB API (version 5.13.0 is recommended).
- Clone Penicillium-GEMs branch from SysBioChalmers GitHub
- Add the directory to your Matlab path, instructions here
The snakefile contains a workflow to parse MetaCyc flat files and create files that could be used for Blast or HMMs studies.
- MetaCyc flat files should be put in the "data" folder
- Sylvain Prigent, Chalmers University of Technology, Gothenburg Sweden
- Jens Christian F. Nielsen, Chalmers University of Technology, Gothenburg Sweden
The MIT License (MIT)
Copyright (c) 2017 Systems and Synthetic Biology
Chalmers University of Technology Gothenburg, Sweden
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