Mineralocorticoid Receptor and Aldosterone: From Hydro-saline Metabolism to Metabolic Diseases

Armani, Andrea; Caprio, Massimiliano

doi:10.1007/978-3-031-27119-9_14

Cited by 1 publication

(1 citation statement)

References 102 publications

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“…G3PDH then oxidises the imported NADH into NAD+ and releases an electron which reduces CoQ. Both mouse and human BAT express high levels of G3PDH, and knockout of G3PDH in both species are associated with metabolic Type 2 diabetes mellitus and obesity (Armani and Caprio, 2023;Banerjee et al, 2022;Brown et al, 2002). Given this, we believe the prediction of an inactive G3PDH flux in mice associated with proteomic data integration to be a misprediction as the G3PDH protein abundance (ENSMUSG00000026827; 331) was identified in the dataset, and so the upper bound was constrained to a corresponding positive value and the lower bound was constrained to zero.…”

Section: Discussionmentioning

confidence: 99%

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

Chapman,

Brunet,

Mourier

et al. 2024

Preprint

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Mitochondria perform several essential functions in order to maintain cellular homeostasis and mitochondrial metabolism is inherently flexible to allow correct function in a wide range of tissues. Dysregulated mitochondrial metabolism can therefore affect different tissues in different ways which presents experimental challenges in understanding the pathology of mitochondrial diseases. System-level metabolic modelling is therefore useful in gaining in-depth insights into tissue-specific mitochondrial metabolism, yet despite the mouse being a common model organism used in research, there is currently no mouse specific mitochondrial metabolic model available. In this work, building upon the similarity between human and mouse mitochondrial metabolism, we have created mitoMammal, a genome-scale metabolic model that contains human and mouse specific gene-product reaction rules. MitoMammal is therefore able to model mouse and human mitochondrial metabolism. To demonstrate this feature, using an adapted E-Flux2 algorithm, we first integrated proteomic data extracted from mitochondria of isolated mouse cardiomyocytes and mouse brown adipocyte tissue. We then integrated transcriptomic data from in vitro differentiated human brown adipose cells 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 relating to cardiac disease and diabetes in both mouse and human contexts.

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Section: Discussionmentioning

confidence: 99%