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Penicillium-GEMs

  • 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;

Citation

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)

  • Last update: 2023-01-27

  • 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

Installation

Required Software:

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

Dependencies - Recommended Software:

  • libSBML MATLAB API (version 5.13.0 is recommended).

Installation Instructions

Complementary Scripts

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

Contributors

License

The MIT License (MIT)

Copyright (c) 2017 Systems and Synthetic Biology

Chalmers University of Technology Gothenburg, Sweden

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.