hanpo-GEM: A genome-scale metabolic model of Hansenula polymorpha & accompanying reconstruction protocol

Abstract

Genome-scale metabolic models (GEMs) provide a useful framework for modeling the metabolism of microorganisms. While the applications of GEMs are wide and far reaching, the reconstruction and continuous curation of such models can be perceived as a tedious and time-consuming task. Using RAVEN, a MATLAB-based toolbox designed to facilitate the reconstruction analysis of metabolic networks, this protocol practically demonstrates how researchers can create their own GEMs using a homology-based approach. To provide a complete example, a draft GEM for the industrially relevant yeast Hansenula polymorpha is reconstructed.

Description

This repository contains the current genome-scale metabolic model of Hansenula polymorpha, synonymously known as Ogataea polymorpha/Pichia angusta, as well as the protocol used for its reconstruction. Hansenula polymorpha is a filamentous yeast from the family Saccharomycetaceae, and is an industrially relevant methylotrophic species.

Clone this repo to download the model, code, and associated data:

$ git clone https://github.com/SysBioChalmers/hanpo-GEM.git

What are genome-scale metabolic models?

Figure 1: Conceptual representation of the information stored in a genome-scale metabolic model. A GEM is fundamentally based on the S-matrix, which is an elegant summary of the stoichiometry of an organism’s specific biochemical pathways and metabolic capabilities. This matrix is sparse and of dimensions M by N, where M represents the number of metabolites and N the number of reactions present in the metabolism of a given organism. Each reaction in this matrix is constrained by some lower bound (LB) and upper bound (UB), which reflects the biological constraints of each reaction (e.g., thermodynamics, reversibility). Additionally, genetic information about each enzyme-catalyzed reaction is stored in the grRules structure

Reconstruction protocol

Figure 2: Flow diagram representation of this protocol. Note that each box corresponds to a subsection in the Methods section.

Figure 3: Visual summary of files used for model reconstruction. Various key RAVEN functions are shown in Courier New font. Arrows show which files are used by the different functions and tasks. Each dot in the flow diagram represents an intermediate version of the target GEM.

Citation

If you use hanpo-GEM, or the reconstruction protocol used for its generation, please cite the following textbook chapter:

Zorrilla, F., Kerkhoven, E.J. (2022). Reconstruction of Genome-Scale Metabolic Model for Hansenula polymorpha Using RAVEN. In: Mapelli, V., Bettiga, M. (eds) Yeast Metabolic Engineering. Methods in Molecular Biology, vol 2513. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2399-2_16

Keywords

Utilisation: predictive simulation\ Field: metabolic-network reconstruction\ Type of Model: homology-based reconstruction\ Model Source: hanpo-GEM\ Omic Source: genome;protein\ Taxonomy: Hansenula polymorpha/Ogataea polymorpha/Pichia angusta\ Metabolic System: General Metabolism\ Strain: NCYC 495 leu1.1\ Condition: Complex medium

Model overview

|Taxonomy | Template Model | Reactions | Metabolites| Genes | | ------------- |:-------------:|:-------------:|:-------------:|-----:| |Hansenula polymorpha| yeast-GEM & rhto-GEM | 2370 | 2118 | 984 |

Dependencies

If you want to use the model for your own model simulations, you can use any software that accepts SBML L3V1 FBCv3 formatted model files. This includes any of the following: * MATLAB-based * RAVEN Toolbox version 2.8.3 or later (recommended)
* COBRA Toolbox

• Python-based
  • cobrapy
    

Please see the installation instructions for each software package.

Contributing

Contributions are always welcome! Please read the contributions guideline to get started.

Contributors

• Eduard J. Kerkhoven (@edkerk), Chalmers University of Technology, Göteborg, Sweden
• Francisco Zorrilla (@franciscozorrilla), MRC Toxicology Unit, University of Cambridge, UK