Increased mTOR Signaling and Impaired Autophagic Flux Are Hallmarks of SARS-CoV-2 Infection.
Erika Pereira ZambaldeThomaz Luscher DiasGrazielle Celeste MakturaMariene Ribeiro AmorimBianca BrenhaLuana Nunes SantosLucas BuscarattiJoão Gabriel de Angeli ElstonMariana Camargo Silva ManciniIsadora Carolina Betim PavanDaniel Augusto de Toledo-TeixeiraKarina Bispo-Dos-SantosPierina Lorencini PariseAna Paula MorelliLuiz Guilherme Salvino da SilvaÍcaro Maia Santos de CastroTatiana D SacconMarcelo A MoriFabiana GranjaHelder I NakayaJosé Luis Proença ModenaHenrique Marques-SouzaFernando Moreira SimabucoPublished in: Current issues in molecular biology (2022)
The COVID-19 (Coronavirus Disease 2019), caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), severely affects mainly individuals with pre-existing comorbidities. Here our aim was to correlate the mTOR (mammalian/mechanistic Target of Rapamycin) and autophagy pathways with the disease severity. Through western blotting and RNA analysis, we found increased mTOR signaling and suppression of genes related to autophagy, lysosome, and vesicle fusion in Vero E6 cells infected with SARS-CoV-2 as well as in transcriptomic data mining of bronchoalveolar epithelial cells from severe COVID-19 patients. Immunofluorescence co-localization assays also indicated that SARS-CoV-2 colocalizes within autophagosomes but not with a lysosomal marker. Our findings indicate that SARS-CoV-2 can benefit from compromised autophagic flux and inhibited exocytosis in individuals with chronic hyperactivation of mTOR signaling.
Keyphrases
- sars cov
- respiratory syndrome coronavirus
- cell death
- coronavirus disease
- cell proliferation
- cell cycle arrest
- endoplasmic reticulum stress
- induced apoptosis
- signaling pathway
- oxidative stress
- south africa
- early onset
- high throughput
- single cell
- machine learning
- electronic health record
- rna seq
- deep learning
- drug induced
- data analysis
- big data
- pi k akt