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Connecting lysosomes and mitochondria – a novel role for lipid metabolism in cancer cell death
(2019)
Background
The understanding of lysosomes has been expanded in recent research way beyond their view as cellular trash can. Lysosomes are pivotal in regulating metabolism, endocytosis and autophagy and are implicated in cancer. Recently it was discovered that the lysosomal V-ATPase, which is known to induce apoptosis, interferes with lipid metabolism in cancer, yet the interplay between these organelles is poorly understood.
Methods
LC-MS/MS analysis was performed to investigate lipid distribution in cells. Cell survival and signaling pathways were analyzed by means of cell biological methods (qPCR, Western Blot, flow cytometry, CellTiter-Blue). Mitochondrial structure was analyzed by confocal imaging and electron microscopy, their function was determined by flow cytometry and seahorse measurements.
Results
Our data reveal that interfering with lysosomal function changes composition and subcellular localization of triacylglycerids accompanied by an upregulation of PGC1α and PPARα expression, master regulators of energy and lipid metabolism. Furthermore, cardiolipin content is reduced driving mitochondria into fission, accompanied by a loss of membrane potential and reduction in oxidative capacity, which leads to a deregulation in cellular ROS and induction of mitochondria-driven apoptosis. Additionally, cells undergo a metabolic shift to glutamine dependency, correlated with the fission phenotype and sensitivity to lysosomal inhibition, most prominent in Ras mutated cells.
Conclusion
This study sheds mechanistic light on a largely uninvestigated triangle between lysosomes, lipid metabolism and mitochondrial function. Insight into this organelle crosstalk increases our understanding of mitochondria-driven cell death. Our findings furthermore provide a first hint on a connection of Ras pathway mutations and sensitivity towards lysosomal inhibitors.
Coordinated regulation of the lysosomal and autophagic systems ensures basal catabolism and normal cell physiology, and failure of either system causes disease. Here we describe an epigenetic rheostat orchestrated by c-MYC and histone deacetylases that inhibits lysosomal and autophagic biogenesis by concomitantly repressing the expression of the transcription factors MiT/TFE and FOXH1, and that of lysosomal and autophagy genes. Inhibition of histone deacetylases abates c-MYC binding to the promoters of lysosomal and autophagy genes, granting promoter occupancy to the MiT/TFE members, TFEB and TFE3, and/or the autophagy regulator FOXH1. In pluripotent stem cells and cancer, suppression of lysosomal and autophagic function is directly downstream of c-MYC overexpression and may represent a hallmark of malignant transformation. We propose that, by determining the fate of these catabolic systems, this hierarchical switch regulates the adaptive response of cells to pathological and physiological cues that could be exploited therapeutically.
Protein-protein interaction (PPI) studies are gaining momentum these days due to the plethora of various high-throughput experimental methods available for detecting PPIs. Proteins create complexes and networks by functioning in harmony with other proteins and here in silico network biology hold the promise to reveal new functionality of genes as it is very difficult and laborious to carry out experimental high-throughput genetic screens in living organisms. We demonstrate this approach by computationally screening C. elegans conserved homologs of already reported human tumor suppressor and aging associated genes. We select by this nhr-6, vab-3 and gst-23 as predicted longevity genes for RNAi screen. The RNAi results demonstrated the pro-longevity effect of these genes. Nuclear hormone receptor nhr-6 RNAi inhibition resulted in a C. elegans phenotype of 23.46% lifespan reduction. Moreover, we show that nhr-6 regulates oxidative stress resistance in worms and does not affect the feeding behavior of worms. These findings imply the potential of nhr-6 as a common therapeutic target for aging and cancer ailments, stressing the power of in silico PPI network analysis coupled with RNAi screens to describe gene function.