This repository contains all source code and raw data to reproduce the figures and computation in the paper An Organism-Level Quantitative Flux Model of Mammalian Energy Metabolism. 🌟

The source code is prefixed with numbers 1 to 12. Run each script sequentially by the prefix. Running each file will generate an associated .RData file, which will be imported in the following script.

The raw data from the metabolic cage-isotope analyzer is in folder data-13CO2. Experimental parameters are in data_13CO2_mouseID_paper.xlsx.

• 1_core_13CO2_import_data.R: imports and clean up all 13CO2 data.
• 2_core_13CO2_bolus_injection.R: analyzes bolus-based 13CO2 data.
• 3_core_13CO2_infusion_physiology_basics.R: analyzes infusion-based 13CO2 data, and integrates all other respirometry data, such as total O2 consumption, CO2 production, RER, energy expenditure, etc.

The serum labeling raw data is in data_serum labeling.xlsm, and the experimental parameters are in data_serum labeling mouse ID.xlsx.

• 4_core_serum_labeling_import data.R: imports and cleanup all 13C-serum labeling data, and performs natural abundance correction. It employs a homemade mini-package vivoFlux (leveraging Xiaoyang's Accucor)

• 5_core_labeling_analysis.R: analyzes serum labeling data, calculate arterial-venous labeling difference, and computes circulatory turnover fluxes.

• 6_core_consumption_flux.R: calculates the consumption (sink) fluxes, including the oxidation and storing fluxes, and the direct fluxes.

• 7_core_production_flux.R: calculates the storage-releasing fluxes, and inter-converting fluxes.

• 8_core_flux extrapolation.R: an integrated analysis, and performs statistical test of metabolic fluxes between phenotypes.

• 9_core_ATP_estimate.R: calculates the ATP wasted by the futile cycles.

• 10_core_draw flux network.R: draws the metabolic flux network for all three phenotypes. The variant 11 maps flux values (significantly different between phenotypes) to color scale; and 12 creates interactive networks.

All scripts have been checked to run smoothly. In case of error:

• Check path of file import
• Check if you have generated the needed .RData file
• Restart R session to clear package conflict
• Check you have the needed package
• Did you change the raw data? This may cause disruption.

Reference of R code for data wrangling and data visualization:

• DataBrewer.co
• R for Data Science (2e)