| Literature DB >> 36225927 |
Olga Krysko1, Joshua H Bourne2, Elena Kondakova3, Elena A Galova4, Katharine Whitworth2, Maddy L Newby5, Claus Bachert1, Harriet Hill6, Max Crispin5, Zania Stamataki6, Adam F Cunningham6, Matthew Pugh6, Abdullah O Khan2, Julie Rayes2, Maria Vedunova3, Dmitri V Krysko3,7,8, Alexander Brill2.
Abstract
Background: The systemic inflammatory response post-SARS-CoV-2 infection increases pro-inflammatory cytokine production, multi-organ damage, and mortality rates. Mast cells (MC) modulate thrombo-inflammatory disease progression (e.g., deep vein thrombosis) and the inflammatory response post-infection. Objective: To enhance our understanding of the contribution of MC and their proteases in SARS-CoV-2 infection and the pathogenesis of the disease, which might help to identify novel therapeutic targets.Entities:
Keywords: COVID-19; LUVA cells; mast cells; protease; von Willebrand factor
Mesh:
Substances:
Year: 2022 PMID: 36225927 PMCID: PMC9548604 DOI: 10.3389/fimmu.2022.968981
Source DB: PubMed Journal: Front Immunol ISSN: 1664-3224 Impact factor: 8.786
Demographics and baseline characteristics of patients included in the study.
| controls | moderate | severe | |
|---|---|---|---|
| (n=17 ) | (n=30) | (n=30) | |
| Age, years | 54,7±19,7 | 47,7±16,2 | 59,1±15,9 |
| Gender | 7M/10F | 7M/23F | 11M/19F |
| Body mass index | 25,09±3,6 | 27,8±4,7 | 31,6±4,9 |
| Hypertension (n,%) | 4 (23%) | 16 (53%) | 24 (80%) |
| Diabetes (n,%) | 1 (6%) | 1 (3%) | 13 (43%) |
| Cardiovascular disease (n,%) | 3 (17%) | 4 (13%) | 14 (46%) |
| Malignancy (n,%) | 0 (0) | 4 (13%) | 5 (16%) |
| Stroke (n,%) | 0 (0) | 1 (3%) | 3 (10%) |
| Chronic lung diseases (n,%) | 0 (0) | 2 (6%) | 2 (6%) |
| Arrhythmia (n,%) | 0 (0) | 4 (13%) | 1 (3%) |
| Rheumatoid arthritis (n,%) | 1 (6%) | 0 (0%) | 1 (3%) |
The number (n) of the patients in each group is provided with description of their age, gender, and comorbidities. For demographic characteristics data are presented as median ± standard deviation.
Figure 1MC degranulation markers in patient serum are increased relative to clinical severity of patients post-SARS-CoV-2 infection. The presence of (A) CMA1, (B) CPA3 and (C) TPSB2 in patient serum was determined by ELISA. Healthy controls (n=17) were used to compare to patients post-SARS-CoV-2 infection with moderate (admission to hospital; n=30), or severe (admission to ICU; n=30) clinical outcome. Statistical significance was determined using a one-way ANOVA with Kruskal-Wallis multiple comparison test. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.
Correlation analysis of MC protease levels in serum with demographical and clinical characteristics of patients with COVID-19.
| CMA1 | CPA3 | TPSB2 | |||||
|---|---|---|---|---|---|---|---|
| Pearson’s r | p-value | Pearson’s r | p-value | Pearson’s r | p-value | ||
|
| 0.147 | 0.261 | 0.209 | 0.11 | 0.127 | 0.335 | |
|
| 0.109 | 0.417 | 0.121 | 0.368 | 0.281 | 0,033 | |
|
| 0.187 | 0.153 | 0.244 | 0.06 | 0.3 | 0,020 | |
|
| 0.174 | 0.183 | 0.3 | 0,020 | 0.125 | 0.341 | |
|
| 0.561 | <0,0001 | 0.452 | <0,0001 | 0.465 | <0,0001 | |
|
| 0.591 | <0,0001 | 0.577 | <0,0001 | 0.503 | <0,0001 | |
|
| 0.586 | <0,0001 | 0.561 | <0,0001 | 0.472 | <0,0001 | |
|
| |||||||
|
| -0.076 | 0.564 | -0.214 | 0.102 | -0.399 | 0,002 | |
Pearson correlation coefficient and two-tailed p values were calculated for the selected datasets using GraphPad Prism 9.0.
Figure 2MC recruitment and degranulation is increased in the lungs of patients post-SARS-CoV-2 infection. The lungs of patients deceased post-SARS-CoV-2 infection were frozen, sectioned to 6 μm and labelled by immunofluorescence, before imaging using an epifluorescence microscope. Lungs of non-SARS-CoV-2-linked deaths were used as a control. (A) MCs were identified by tryptase (magenta) in the lungs of deceased non-SARS-CoV-2 (n=3) or COVID-19 patients (n=8); (B) Quantification of MC numbers; (C) Non-degranulated (controls, left panel) and degranulated (COVID-19, middle panel) MCs; right panel represents non-degranulated MC (arrows) and granules (arrowheads) releasing from a MC in the process of degranulation; (D) Quantification of MC granules identified as tryptase-positive objects with the area of <50 µm2; (E) Ratio between the numbers of cell-free granules and MCs; (F) Correlation between the numbers of MCs and cell-free granules; (G) Quantification of the average of MC area. Images were analyzed using ImageJ. Horizontal lines represent mean. Statistical significance was determined using the unpaired Student’s t-test.
Figure 3Neither viral proteins nor the SARS-CoV-2 virus directly induce MC degranulation, and SARS-CoV-2 virus does not penetrates MC. LUVA cells were cultured in the presence or absence of compound 48/80 (10 µg/ml) or spike protein or nucleocapsid protein (1-10 µM; A–D), or SARS-CoV-2 (E–H) for 1 h in a CO2-free humidified atmosphere at 37°C. Cells were analyzed for the expression of (A, E) avidin, (B, F) CD203c, (C, G) CD63, or ACE-2 (D, H) using a CytoFlex flow cytometer and quantified using FlowJo v10. Statistical significance was determined using a one-way ANOVA with Tukey’s multiple comparisons test. *p<0.05, ****p<0.0001. ns, not significant. LUVA cells were incubated without or with (first and second rows, respectively) ARS-CoV-2 virus for 24 h, 48 h or 72 h, after which cells were seeded on a polylysine-coated polystyrene wells and stained for nuclei (blue), nucleocapsid protein (red), and spike protein (green) to evaluate virus entry into the cells (I). Vero cells (third row) served as a control of both virus penetration and quality of the antibodies. No dissemination of the virus inside cells was observed at all time points, which is confirmed by quantitation of the fluorescence (J); C and V designate control and virus for Vero cells. Staining of cell samples for avidin and CD203c revealed no degranulation (K). Scale bar 200 um, n = 3 for each time point.
Figure 4Correlation between MC-related parameters and lung VWF levels. The levels of VWF in the lungs were determined as fluorescence intensity in arbitrary units. (A) and (B), representative images of VWF staining in the lungs of non-COVID-19 and COVID-19 patients, respectively. Correlations of VWF levels with (C) MC numbers, (D) cell-free granule numbers and (E) granule/MC number ratio are presented. Pearson r coefficient was calculated using MS Excel.