SARS-CoV-2 targets mitochondria, exacerbating COVID-19 pneumonia

Danchen Wu1,2, Asish Dasgupta1,2, Jaskaran Singh Hora1

  • 1Department of Medicine, Queen's University, Kingston, Ontario, Canada.

Insights

Coronaviruses damage mitochondria, impacting energy production and cell function, potentially contributing to severe COVID-19 and long COVID. Therapeutic strategies targeting mitochondrial dysfunction show promise in preclinical models.

Area of Science:

  • Cell Biology
  • Virology
  • Pathophysiology

Background:

  • Mitochondrial damage is a common feature across various coronavirus infections, including SARS-CoV-2.
  • Coronaviruses disrupt mitochondrial function in multiple cell types, including airway epithelial cells and cardiomyocytes.

Purpose of the Study:

  • To elucidate the mechanisms by which coronaviruses induce mitochondrial damage and its consequences.
  • To explore the role of mitochondrial dysfunction in COVID-19 pathogenesis and potential therapeutic targets.

Main Methods:

  • Analysis of transcriptomic changes in nuclear-encoded mitochondrial genes.
  • Investigation of viral protein interactions with host mitochondrial proteins.
  • Assessment of mitochondrial function markers (depolarization, MTP opening, ETC activity, ATP synthesis, fission, apoptosis).

Main Results:

  • SARS-CoV-2 infection rapidly alters gene expression, downregulating electron transport chain and ATP synthesis components.
  • Viral proteins alone can induce mitochondrial depolarization, MTP opening, and apoptosis.
  • Coronavirus infection impairs hypoxic pulmonary vasoconstriction (HPV) by suppressing mitochondrial oxygen sensing, contributing to hypoxemia in COVID-19.

Conclusions:

  • Coronavirus-induced mitochondriopathy contributes to cellular damage, apoptosis, and impaired physiological responses like HPV.
  • Mitochondrial dysfunction is a key factor in COVID-19 pathogenesis and may underlie long COVID symptoms.
  • Targeting apoptosis pathways and restoring HPV show therapeutic potential in preclinical models.

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