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M2R: a Python add-on to cobrapy for modifying human genome-scale metabolic reconstruction using the gut microbiota

Ewelina Weglarz-Tomczak1, Jakub M Tomczak2, Stanley Brul1

  • 1Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, The Netherlands.

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Summary

M2R is a new Python tool that integrates gut microbiota metabolism into human metabolic models. This software aids in analyzing the complex metabolic interactions between gut microbes and human cells.

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Area of Science:

  • Computational Biology
  • Metabolic Modeling
  • Microbiome Research

Background:

  • The human gut microbiota comprises trillions of microorganisms crucial for nutrient processing and impacting host physiology, immunity, and metabolism.
  • Understanding the interplay between gut microbes and human cells is vital for deciphering gastrointestinal health and disease.

Purpose of the Study:

  • To introduce M2R, a novel Python add-on for integrating gut microbiota metabolic models with human genome-scale metabolic models (GEMs).
  • To facilitate the analysis of host-microbe metabolic interactions and their dysregulation.

Main Methods:

  • M2R modifies the lower bounds of exchange reactions in human GEMs (e.g., RECON3D) using aggregated microbial in- and out-fluxes.
  • The software allows users to easily adjust metabolite pools entering and leaving the GEM.

Main Results:

  • M2R enables the incorporation of gut microbiota metabolic information into human GEMs.
  • The tool simplifies the process of analyzing metabolic exchanges between host and microbes.

Conclusions:

  • M2R provides a valuable resource for researchers studying gut microbiota-human cell metabolic interactions.
  • This integration is essential for understanding metabolic dysregulation in the gut.