https://github.com/sysbiochalmers/ecfactory

A constraint-based method for prediction of metabolic engineering targets using ecModels of metabolism
https://github.com/sysbiochalmers/ecfactory

cell-factory enzyme-constraints metabolic-models microbes

Last synced: 19 days ago
JSON representation

A constraint-based method for prediction of metabolic engineering targets using ecModels of metabolism

• Host: GitHub
• URL: https://github.com/sysbiochalmers/ecfactory
• Owner: SysBioChalmers
• License: gpl-3.0
• Created: 2022-06-16T12:18:08.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-11-15T07:38:02.000Z (about 1 month ago)
• Last Synced: 2024-11-15T08:28:14.192Z (about 1 month ago)
• Topics: cell-factory, enzyme-constraints, metabolic-models, microbes
• Language: MATLAB
• Homepage:
• Size: 359 KB
• Stars: 8
• Watchers: 1
• Forks: 4
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

Awesome Lists containing this project

README

        
# ecFactory: A multi-step method for prediction of metabolic engineering gene targets

![fig1](https://user-images.githubusercontent.com/26483972/175298382-c3ceb172-bf59-4eb7-85e6-aa0ec60928c9.jpg)

The ecFactory method is a series of sequential steps for identification of metabolic engineering gene targets. These targets show which genes should be subject to overexpression, modulated expression (knock-down) or deletion (knock-out), with the objective of increasing production of a given metabolite. This method was developed by combining the principles of the FSEOF algorithm (flux scanning with enforced objective function) together with the features of GECKO enzyme-constrained metabolic models (ecModels), which incorporate enzymes as part of genome-scale metabolic networks.

## Required Software

* A functional Matlab installation (MATLAB 7.3 or higher). 

* The [RAVEN toolbox for MATLAB](https://github.com/SysBioChalmers/RAVEN).

* [Gurobi Optimizer](http://www.gurobi.com/registration/download-reg) for any simulations.

* [Git](https://git-scm.com/downloads)

## Installation

Clone this repository into an accesible directory in your computer. No further steps are needed.

## Tutorial

A case study for prediction of metabolic engineering targets for increased production of 2-phenylethanol in *S. cerevisiae* cells using [ecYeastGEM](https://github.com/SysBioChalmers/yeast-GEM) and the **ecFactory** method is explained in detail in a MATLAB live script. To run this example, open the [live script](https://github.com/SysBioChalmers/ecFactory-case-studies/blob/main/code/find_gene_targets.mlx) in MATLAB and run it! with this, you will see the outputs of the method scripts in real time. 

* An additional case study for prediction of gene targets for enhanced heme production in *S. cerevisiae* has been added. Validation of a subset of the predicted gene targets can be seen [in this publication](https://doi.org/10.1073/pnas.2108245119).

All the relevant outputs of the method are stored in the `tutorials/results` folder in this repository.

Last update: 2022-09-17

This repository is administered by [Iván Domenzain](https://github.com/IVANDOMENZAIN), Division of Systems and Synthetic Biology, Department of Biology and Biological Engineering, Chalmers University of Technology.