Models of metabolism are powerful tools to explore the metabolic potential of microorganism. Powerful tools have been created to support Python-based analysis of genome-scale models. These models, however, cannot capture all metabolic phenotypes and the simulation results have high flux variability. Adding protein to each reaction increases the simulation fidelity. The PAModelpy package is designed to integrate protein constraints and protein sectors as described by Alter et al. (2021) to metabolic models. It is the Python implementation of the PAM MATLAB framework to create GECKO like ME models.
The PAModelpy package builds upon the community-wide used COBRApy. We have extended this package with the following features:
- protein-reaction associations
- infrastructure to include isozymes and promiscuous enzymes
- protein sectors
- specialized objects to build protein allocation models
- the possibility to perform a computational efficient sensitivity analysis
PAModelpy is a PiPy package which allows for easy installation with pip:
pip install PAModelpy
Note that the package has been tested with the Gurobi solver.
The documentation including coding examples can be found here.
This repository contains not only the source code, but also examples and scripts which were used in INSERT PUBLICATION HERE.
- Data
- eGFP_expression_Bienick2014: measured growth rate and eGFP expression by Bienick et al. (2014)
- proteinAllocationModel_iML1515_EnzymaticData_py: information about the proteinsectors of the PAM for Escherichia coli (E.coli)
- proteome_data_extract_schmidt2016: quantitative proteomics data from Schmidt et al. (2016) used to parametrize the E.coli core PAM
- Ecoli_phenotypes/Ecoli_phenotypes_py_rev: experimental physiology measurements to validate the model simulations
- Examples: example notebook on how to build, run and validate a PAM using the PAModelpy package
- Figures: scripts used to create Figure 1-3 and supplementary figures
- MATLAB: MATLAB code for doing simulations with the E.coli core PAM and the toy model (validating the sensitivity relationships)
- Models: models used (iML1515 and core ecoli model)
- Results: results of computational performance analysis
- Scripts: scripts used for gathering results
- computational performance analysis:
compare_computational_efficiency_esc.py
andnumeric_error_estimation_schemes_esc.py
- E.coli core PAM creation:
analyze_proteome.ipynb
andcreate_ecolicore_pam_incl_UE.ipynb
- Sensitivity analysis:
toy_ec_pam.py
andEcoli_core_sensitivity_analysis.ipynb
- computational performance analysis:
- src/PAModelpy: source code for PAModelpy package
- EnzymeSectors: The objects which are used to store the data of the different enzyme sectors which are added to the genome-scale model
- PAModel: Proteome Allocation (PA) model class. This class builds on to the
cobra.core.Model
class from the COBRApy toolbox with functions to build enzyme sectors, to add enzyme kinetics parameters and in the future to perform a sensitivity analysis on the enzyme variables. - Enzyme: Different classes which relate enzymes to the model with enzyme constraints and variables.
- CatalyticEvent: A class which serves as an interface between reactions and enzyme. This allows for easy lookup of Protein-Reaction assocations.
- PAMValidator: Functions to validate the model predictions with physiology data and giving a graphical overview. The script uses data for E.coli (found in
./Data/Ecoli_physiology
) by default.
Dependencies for the scripts in this repository, not included in the PAModelpy package:
PAModelpy
plotly
matplotlib
scipy
time
resource
PIL
All dependencies can be installed in one go by downloading this repository and running:
python setup.py install
from the src
directory
The dependencies of the PAModelpy package can be found in src/pyproject.toml
Copyright institute of Applied Microbiology, RWTH Aachen University, Aachen, Germany (2023)
PAModelpy is free of charge open source software, which can be used and modified for your particular purpose under the MIT or Apache 2.0 of the users choice.
Please note that according to these licenses, the software is provided 'as is', WITHOUT WARRANTY OF ANY KIND, without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.