SARS-CoV-2 cellular tropism and direct multiorgan failure in COVID-19 patients: Bioinformatic predictions, experimental observations, and open questions.
Anna A ValyaevaAnastasia A ZharikovaEugene V ShevalPublished in: Cell biology international (2022)
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19), has led to an unprecedented public health emergency worldwide. While common cold symptoms are observed in mild cases, COVID-19 is accompanied by multiorgan failure in severe patients. Organ damage in COVID-19 patients is partially associated with the indirect effects of SARS-CoV-2 infection (e.g., systemic inflammation, hypoxic-ischemic damage, coagulopathy), but early processes in COVID-19 patients that trigger a chain of indirect effects are connected with the direct infection of cells by the virus. To understand the virus transmission routes and the reasons for the wide-spectrum of complications and severe outcomes of COVID-19, it is important to identify the cells targeted by SARS-CoV-2. This review summarizes the major steps of investigation and the most recent findings regarding SARS-CoV-2 cellular tropism and the possible connection between the early stages of infection and multiorgan failure in COVID-19. The SARS-CoV-2 pandemic is the first epidemic in which data extracted from single-cell RNA-seq (scRNA-seq) gene expression data sets have been widely used to predict cellular tropism. The analysis presented here indicates that the SARS-CoV-2 cellular tropism predictions are accurate enough for estimating the potential susceptibility of different cells to SARS-CoV-2 infection; however, it appears that not all susceptible cells may be infected in patients with COVID-19.
Keyphrases
- sars cov
- respiratory syndrome coronavirus
- coronavirus disease
- induced apoptosis
- single cell
- rna seq
- public health
- cell cycle arrest
- gene expression
- healthcare
- endoplasmic reticulum stress
- electronic health record
- signaling pathway
- emergency department
- high resolution
- type diabetes
- newly diagnosed
- ejection fraction
- cell death
- dna methylation
- high throughput
- big data
- cell proliferation
- drug delivery
- depressive symptoms
- insulin resistance
- glycemic control