Autophagy is a highly conserved self-digestion process, which is essential for maintaining homeostasis and viability in response to nutrient starvation. Although the components of autophagy in the cytoplasm have been well studied, the molecular basis for the transcriptional and epigenetic regulation of autophagy is poorly understood. Here we identify co-activator-associated arginine methyltransferase 1 (CARM1) as a crucial component of autophagy in mammals. Notably, CARM1 stability is regulated by the SKP2-containing SCF (SKP1-cullin1-F-box protein) E3 ubiquitin ligase in the nucleus, but not in the cytoplasm, under nutrient-rich conditions. Furthermore, we show that nutrient starvation results in AMP-activated protein kinase (AMPK)-dependent phosphorylation of FOXO3a in the nucleus, which in turn transcriptionally represses SKP2. This repression leads to increased levels of CARM1 protein and subsequent increases in histone H3 Arg17 dimethylation. Genome-wide analyses reveal that CARM1 exerts transcriptional co-activator function on autophagy-related and lysosomal genes through transcription factor EB (TFEB). Our findings demonstrate that CARM1-dependent histone arginine methylation is a crucial nuclear event in autophagy, and identify a new signalling axis of AMPK-SKP2-CARM1 in the regulation of autophagy induction after nutrient starvation.
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http://dx.doi.org/10.1038/nature18014 | DOI Listing |
J Biochem Mol Toxicol
January 2025
Zoology and Entomology Department, Faculty of Science, Helwan University, Helwan, Egypt.
Mycobacterium tuberculosis (Mtb) complex, responsible for tuberculosis (TB) infection, continues to be a predominant global cause of mortality due to intricate host-pathogen interactions that affect disease progression. MicroRNAs (miRNAs), essential posttranscriptional regulators, have become pivotal modulators of these relationships. Recent findings indicate that miRNAs actively regulate immunological responses to Mtb complex by modulating autophagy, apoptosis, and immune cell activities.
View Article and Find Full Text PDFXi Bao Yu Fen Zi Mian Yi Xue Za Zhi
January 2025
Department of Pathogen Biology and Immunology, Kunming Medical University, Kunming 650500, China. *Corresponding authors, E-mail:
The innate immune response is the first line of defense for the host against viral infections. Targeted degradation of pathogenic microorganisms through autophagy, in conjunction with pattern recognition receptors synergistically inducing the production of interferon (IFN), constitutes an important pathway for the body to resist viral infections. Rubicon, a Run domain Beclin 1-interacting and cysteine-rich domain protein, has an inhibitory effect on autophagy and IFN production.
View Article and Find Full Text PDFXi Bao Yu Fen Zi Mian Yi Xue Za Zhi
January 2025
Department of Neurosurgery, Wuhan NO.1 Hospital, Wuhan 432000, China. *Corresponding author, E-mail:
Objective To investigate the effects and molecular mechanism of Homer protein homolog 1a (Homer 1a) overexpression on nerve injury in mice with traumatic brain injury (TBI). Methods Sixty male C57BL/6 mice were randomly divided into five groups: sham group, TBI group, empty lentivirus (Lv-NC) group, Homer 1a overexpression lentivirus (Lv-Homer 1a) group and Lv-Homer 1a + 740 Y-P group, with 12 mice in each group. The lentivirus was orthotopic injected into the cerebral cortex of mice 5 d before modeling, while 740 Y-P was injected intraperitoneally 1 d before modeling.
View Article and Find Full Text PDFXi Bao Yu Fen Zi Mian Yi Xue Za Zhi
January 2025
National Key Laboratory of Bioreactors, School of Biological Engineering, East China University of Science and Technology, Shanghai 200237, China. *Corresponding author, E-mail:
Immunol Res
January 2025
Department of Dermatology, Shaanxi Provincial People's Hospital, Xi'an, 710068, China.
Mitophagy, the selective degradation of mitochondria by autophagy, plays a crucial role in cancer progression and therapy response. This study aims to elucidate the role of mitophagy-related genes (MRGs) in cutaneous melanoma (CM) through single-cell RNA sequencing (scRNA-seq) and machine learning approaches, ultimately developing a predictive model for patient prognosis. The scRNA-seq data, bulk transcriptomic data, and clinical data of CM were obtained from publicly available databases.
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