MitoMAMMAL: a genome scale model of mammalian mitochondria predicts cardiac and BAT metabolism.

Abstract

Motivation: Mitochondria are essential for cellular metabolism and are inherently flexible to allow correct function in a wide range of tissues. Consequently, dysregulated mitochondrial metabolism affects different tissues in different ways leading to challenges in understanding the pathology of mitochondrial diseases. System-level metabolic modelling is useful in studying tissue-specific mitochondrial metabolism, yet despite the mouse being a common model organism in research, no mouse specific mitochondrial metabolic model is currently available.

Results: Building upon the similarity between human and mouse mitochondrial metabolism, we present mitoMammal, a genome-scale metabolic model that contains human and mouse specific gene-product reaction rules. MitoMammal is able to model mouse and human mitochondrial metabolism. To demonstrate this, using an adapted E-Flux algorithm, we integrated proteomic data from mitochondria of isolated mouse cardiomyocytes and mouse brown adipocyte tissue, as well as transcriptomic data from in vitro differentiated human brown adipocytes and modelled the context specific metabolism using flux balance analysis. In all three simulations, mitoMammal made mostly accurate, and some novel predictions relating to energy metabolism in the context of cardiomyocytes and brown adipocytes. This demonstrates its usefulness in research in cardiac disease and diabetes in both mouse and human contexts.

Availability and implementation: The MitoMammal Jupyter Notebook is available at: https://gitlab.com/habermann_lab/mitomammal.