Model driven analysis of Cabtree Negative Sacharomyces cerevissiae

This repository contains a collection of scripts and data pertaining to the study:

Model driven analysis of Cabtree Negative Sacharomyces cerevissiae

In this study, the three strains of Saccharomyces cerevisiae, one Crabtree Positive and two Crabtree Negative are analyzed through metabolic modeling and integration of absolute proteomics.

Used software and toolbox

• R v4.2.2
• Rstudio v2023.03.0+386
• Matlab v2022a
• The RAVEN toolbox v2.8.0
• The GECKO toolbox v3.0.2

Instructions

code directory contains the code used.

1. differential_analysis.qmd, an r script (quarto file) to analyze to carried out the differential expression and GO analysis.
2. model_driven_analysis.qmd, an r script (quarto file) to (i) process the data required for proteomics integration using GECKO and (ii) to analyze the results from proteomics integration. For this, there some matlab functions used to reconstruct the Enzyme Constrained Model, Integrate the proteomics, and perform some analysis.
   • Run in the following order:
     • get_ecModels.m to obtain an Enzyme-Constrained Model from a GEM. This script uses getAdaptedModel.m function to adapt the yeast-GEM model with the metabolic modifications carried out in sZJD23 and sZJD28 strains. Additionally, it has been identified that some gne rules in yeast-GEM needs curation based on complex portal information; this is done by getUpdatedmodel.m
     • proteomics_integration.m to integrate absolute proteomics data to an ecModel. Requires of experimental fermentation data and absolute proteomics. These files processed and generated in model_driven_analysis.qmd script.
     • analyze_prot_models.m to analyze the protein models obtained in the previous step. At this point, by-products, and others constraint are removed to compare the predictions with experimental data.
     • enhance_growth.m to determine potential bottlenecks in growth.

data directory contains:

• The fermentation raw data.
• The proteomics raw data.
• The custom folder needed in GECKO3 (data/sceYeastGEM). ecModel obtained from get_ecModel.m is stored models subfolder as well as protein models after proteomics integration.

docs directory contains:

• html report of the analysis done here

results directory contains:

• The results from differential expression analysis (results/DE_analysis).
• The results from model driven analysis.