Science AdvancesCell BiologyPeer-reviewed journal article
Mitochondrial Calcium Signaling Regulates Branched-Chain Amino Acid Catabolism in Fibrolamellar Carcinoma
Nicole M. Marsh, Melissa J. S. MacEweniD, Jane CheaiD, Heidi L. KenersoniD, Albert A. Kwong, Timothy M. LockeiD, Francisco Javier MirallesiD, Tanmay SapreiD, Natasha Gozali, Madeleine L. HartiD, Theo K. BammleriD, James W. MacDonaldiD, Lucas B. SullivaniD, Gunes Ekin Atilla‐GokcumeniD, Shao‐En OngiD, John D. ScottiD, Raymond S. W. YeungiD, Yasemin SancakiD
Abstract
Metabolic adaptations in response to changes in energy supply and demand are essential for survival. The mitochondrial calcium uniporter plays a key role in coordinating metabolic homeostasis by regulating TCA cycle activation, mitochondrial fatty acid oxidation, and cellular calcium signaling. However, a comprehensive analysis of uniporter-regulated mitochondrial pathways has remained unexplored. Here, we investigate metabolic consequences of uniporter loss- and gain-of-function using uniporter knockout cells and the liver cancer fibrolamellar carcinoma (FLC), which we demonstrate to have elevated mitochondrial calcium levels. Our results reveal that branched-chain amino acid (BCAA) catabolism and the urea cycle are uniporter-regulated metabolic pathways. Reduced uniporter function boosts expression of BCAA catabolism genes, and the urea cycle enzyme ornithine transcarbamylase (OTC). In contrast, high uniporter activity in FLC suppresses their expression. This suppression is mediated by reduced expression of the transcription factor KLF15, a master regulator of liver metabolism. Thus, uniporter responsive calcium signaling plays a central role in FLC-associated metabolic changes, including hyperammonemia. Our study identifies an important role for mitochondrial calcium signaling in metabolic adaptation through transcriptional regulation of metabolism and elucidates its importance for BCAA and ammonia metabolism in FLC.
- organism: human
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: experimental assay
- approach: statistical model
- Citations
- 12
- FWCI
- 2.64
- Field percentile
- top 9%
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