This repository provides Supplementary files regarding 13C-metabolic flux analysis (13C-MFA) that are part of the manuscripts:
Mitochondrial ATP generation is more proteome efficient than glycolysis
Yihui Shen, Hoang V. Dinh, Edward R. Cruz, Zihong Chen, Caroline R. Bartman, Tianxia Xiao, Catherine M. Call, Rolf-Peter Ryseck, Jimmy Pratas, Daniel Weilandt, Heide Baron, Arjuna Subramanian, Zia Fatma, Zong-Yen Wu, Sudharsan Dwaraknath, John I. Hendry, Vinh G. Tran, Lifeng Yang, Yasuo Yoshikuni, Huimin Zhao, Costas D. Maranas, Martin Wühr & Joshua D. Rabinowitz
Nature Chemical Biology. 2024. doi: https://doi.org/10.1101/2022.08.10.503479
Comparative study of two Saccharomyces cerevisiae strains with kinetic model at genome-scale
Mengqi Hu, Hoang V. Dinh, Yihui Shen, Patrick F. Suthers, Charles Foster, Catherine M. Call, Xuanjia Ye, Zia Fatma, Huimin Zhao, Joshua D. Rabinowitz, and Costas D. Maranas
Metabolic Engineering. 76:1-17. 2023. https://doi.org/10.1016/j.ymben.2023.01.001
References notice: Please cite the paper corresponding to the dataset that you use. The details are provided in the README.md file within the sub-directories. If you use the common resources and scripts, please cite Shen et al., 2022.
1) mfa_scripts
Source MATLAB scripts to run 13C-MFA. Available at https://github.com/maranasgroup/SteadyState-MFA.
2) run_scripts
Scripts that combine and arrange source MATLAB 13C-MFA scripts.
3) resources
Collected resources regarding carbon mappings and other setups to run 13C-MFA scripts
4) mfa
13C-MFA run files and results, arranged by directory for each organism.
- ./mfa/<dataset>/metabolic_rxns_mappings: Metabolic network and carbon mappings of metabolic reactions only. The input files are generated from this metabolic_rxns_mappings and ./resources/dilutions_network_modules.xlsx
- ./mfa/<dataset>/run_files: list of input files for 13C-MFA software run
- ./mfa/<dataset>/result_files: processed output files containing simulated 13C-labeling patterns and best-fit metabolic fluxes
There are the following <dataset> in this repository:
- S_cerevisiae: 14 datasets on S. cerevisiae (Shen et al., 2022)
- I_orientalis: 16 datasets on I. orientalis (Shen et al., 2022)
- Hu2022_KFIT_SC: 9 datasets on S. cerevisiae (Hu et al., 2023)