Intracellular organelles remodeling in myocardial endotheliocytes in COVID-19: an autopsy-based study.
Nataliya BgatovaSergey SavchenkoAlexei LamanovIuliia S TaskaevaBoris AyzikovichValentina GritcingerAndrey LetyaginMaksim KorolevPublished in: Ultrastructural pathology (2023)
It is known that the unfavorable outcome in patients infected with SARS-CoV-2 may be associated with the development of complications caused by heart damage due to the direct virus action. The mechanism of these cardiovascular injuries caused by SARS-CoV-2 infection has not been fully understood; however, the study of COVID-19-associated myocardial microcirculatory dysfunction can represent the useful strategy to solving this challenge. Thus, here we aimed to study the ultrastructural organization of endothelial cells of myocardial capillaries in patients with COVID-19. The morphology of endotheliocytes of the myocardial blood capillaries in patients with COVID-19 was studied on cardiac autopsy material using transmission electron microscopy. The endotheliocytes of myocardial capillaries in patients with COVID-19 were characterized by the abundant rough endoplasmic reticulum (ER) membranes, the Golgi complex, and free polysomal complexes of ribosomes and lipids. The presence of double membrane vesicles with virions and zippered ER was detected in the cytoplasm of endotheliocytes. The revealed endothelial ultrastructural changes indicate the remodeling of intracellular membranes during SARS-CoV-2 infection. Our findings confirm the formation of virus-induced structures in myocardial endothelial cells considered critical for viral replication and assembly. The data may elucidate the mechanisms of endothelial dysfunction development in patients with COVID-19 to provide potential targets for drug therapy.
Keyphrases
- sars cov
- left ventricular
- endoplasmic reticulum
- endothelial cells
- respiratory syndrome coronavirus
- electron microscopy
- coronavirus disease
- high glucose
- heart failure
- ejection fraction
- newly diagnosed
- estrogen receptor
- stem cells
- emergency department
- single cell
- electronic health record
- breast cancer cells
- diabetic rats
- big data
- atrial fibrillation
- machine learning
- human health
- data analysis
- chemotherapy induced