Materials and installation#

Software#

This protocol runs in MATLAB (R2013b or later; no extra MathWorks toolboxes required), complemented with software for reconstructing and analysing GEMs. Most of it is open source or available under an academic license.

Software

Dependency

Source

MATLAB

License

https://mathworks.com/products/matlab.html

RAVEN

libSBML, solver

CompMetEng/RAVEN

COBRA

MATLAB

opencobra/cobratoolbox

Gurobi

License

https://www.gurobi.com/products/gurobi-optimizer/

libSBML

MATLAB

http://sbml.org/Software/libSBML

  • RAVEN is the toolbox that drives the reconstruction.

  • libSBML enables import/export of the community-standard SBML (.xml) format.

  • A linear-programming solver is needed for simulation. This protocol uses Gurobi (free academic license); RAVEN can alternatively use the open-source GLPK solver bundled with COBRA.

See Installation for the full setup.

Files#

Homology-based reconstruction requires files for both the target organism and the template organisms.

File type

Usage

Organism

Source

GEM (SBML)

Template network

S. cerevisiae

yeast-GEM v8.3.0

GEM (SBML)

Template network

R. toruloides

rhto-GEM v1.1.2

Protein FASTA

BLAST

S. cerevisiae

hanpo-GEM data/genomes/sce.faa

Protein FASTA

BLAST

R. toruloides

hanpo-GEM data/genomes/rhto.faa

Protein FASTA

BLAST

H. polymorpha

JGI Hanpo2

DNA FASTA

Biomass curation

H. polymorpha

NCBI GCF_001664045.1_Hanpo2

GenBank

Biomass curation

H. polymorpha

NCBI GCF_001664045.1_Hanpo2

For the target organism you need (1) a protein FASTA of all proteins in its genome, (2) a DNA FASTA for nucleotide ratios, and (3) a GenBank file for ribonucleotide ratios. For each template you need a protein FASTA and a model file in SBML format.

Important

Matching identifiers For automatic gene matching, the protein FASTA and the model file of each template must use the same gene identifiers.

All required files for H. polymorpha are provided in the hanpo-GEM repository; clone it to get a local copy.

Literature data#

Model quality improves by leveraging any known metabolic behaviour of the target organism: macromolecule fractions of biomass, essential/non-essential genes, usable nutrient sources, and growth rate. A short literature search yields total protein, lipid and carbohydrate content for H. polymorpha, used to set the biomass stoichiometric coefficients (Biomass composition). Where organism-specific data is missing, values from related organisms can be used.

Install RAVEN#

After obtaining the software and files, install RAVEN (see Installing RAVEN). Use pathtool to add the RAVEN, libSBML and Gurobi subfolders to the MATLAB path, then verify with:

checkRaven

See Installing RAVEN for what a successful run looks like.

Warning

If checkRaven reports that importing SBML format failed, uninstall MATLAB's Text Analytics Toolbox, which conflicts with RAVEN's Excel parser. For support, see the RAVEN issues page.