Translational control of Ybx1 expression regulates cardiac function in response to pressure overload in vivo.

RNA-protein interactions are central to cardiac function, but how activity of individual RNA-binding protein is regulated through signaling cascades in cardiomyocytes during heart failure development is largely unknown. The mechanistic target of rapamycin kinase is a central signaling hub that controls mRNA translation in cardiomyocytes; however, a direct link between mTOR signaling and RNA-binding proteins in the heart has not been established. Integrative transcriptome and translatome analysis revealed mTOR dependent translational upregulation of the RNA binding protein Ybx1 during early pathological remodeling independent of mRNA levels.

Muscle-specific Cand2 is translationally upregulated by mTORC1 and promotes adverse cardiac remodeling.

The mechanistic target of rapamycin (mTOR) promotes pathological remodeling in the heart by activating ribosomal biogenesis and mRNA translation. Inhibition of mTOR in cardiomyocytes is protective; however, a detailed role of mTOR in translational regulation of specific mRNA networks in the diseased heart is unknown. We performed cardiomyocyte genome-wide sequencing to define mTOR-dependent gene expression control at the level of mRNA translation.

Saraf-dependent activation of mTORC1 regulates cardiac growth.

Pathological cardiac hypertrophy is an independent risk for heart failure (HF) and sudden death. Deciphering signaling pathways regulating intracellular Ca homeostasis that control adaptive and pathological cardiac growth may enable identification of novel therapeutic targets. The objective of the present study is to determine the role of the store-operated calcium entry-associated regulatory factor (Saraf), encoded by the Tmem66 gene, on cardiac growth control in vitro and in vivo.

Monitoring Cell-Type-Specific Gene Expression Using Ribosome Profiling In Vivo During Cardiac Hemodynamic Stress.

Rationale: Gene expression profiles have been mainly determined by analysis of transcript abundance. However, these analyses cannot capture posttranscriptional gene expression control at the level of translation, which is a key step in the regulation of gene expression, as evidenced by the fact that transcript levels often poorly correlate with protein levels. Furthermore, genome-wide transcript profiling of distinct cell types is challenging due to the fact that lysates from tissues always represent a mixture of cells.