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Lower respiratory tract single-cell RNA sequencing and neutrophil extracellular trap profiling of COVID-19-associated pulmonary aspergillosis: a single centre, retrospective, observational study

By: Simon Feys, Sam Vanmassenhove, Sirima Kraisin, Karen Yu, Cato Jacobs, Bram Boeckx, and others. Show all authors here



COVID-19-associated pulmonary aspergillosis (CAPA) is a severe superinfection with the fungus Aspergillus affecting patients who are critically ill with COVID-19. Patients admitted to the intensive care unit with COVID-19 who develop CAPA show an increased mortality rate of approximately 50%, which is more or less twice as much as those without CAPA. The reason why patients with severe COVID-19 (or other severe viral lung infections) develop aspergillosis is not clear, as this fungal infection is typically encountered in patients with a severely malfunctioning immune system. To explore how severe COVID-19 affects the immune system, predisposing to aspergillosis, we performed the following study.


We characterized the immune cell landscape of the lumen of the lower respiratory tract of patients mechanically ventilated because of COVID-19, comparing patients with versus without aspergillosis, using single-cell RNA sequencing on bronchoalveolar lavage samples. Single-cell RNA sequencing allows us to identify the transcriptome (i.e. the specific genes that are being expressed) from single cells in a sample. The computational resources provided by the VSC were instrumental in this research, allowing us to store large raw single-cell RNA datasets and map them to the transcriptome in parallel. This quick processing of raw data greatly reduced the time between sample collection and downstream analysis of the data.


The computational resources provided by the VSC were instrumental in this research, allowing us to store large raw single-cell RNA datasets and map them to the transcriptome in parallel. This quick processing of raw data greatly reduced the time between sample collection and downstream analysis of the data.

We observed that patients with CAPA had significantly lower neutrophil fractions than patients with COVID-19 only. Neutrophils are the most important immune cells to attack Aspergillus. Strikingly, those neutrophils that were still found in patients with CAPA were characterized by expression of genes linked to antigen presentation. This is atypical for neutrophils, but has been described to happen in animal models of fungal infection. These “hybrid” neutrophils (hybrid because they are in some ways similar to the antigen-presenting dendritic cell) were previously shown to be more potent killers of fungi. Patients with CAPA also showed depletion of mucosal-associated invariant T-cells, reduced T helper 1 and T helper 17 differentiation, which are all cells that play a role in the adaptive immunity against fungal infections, and transcriptional defects in specific aspects of antifungal immunity in macrophages and monocytes.


In a partially separate cohort, we showed that levels of neutrophil extracellular traps (NETs) are significantly higher in CAPA patients compared to patients with COVID-19 only. As NETs are the product of neutrophils expelling their DNA, often leading to neutrophil death, this may explain the lower observed neutrophil fractions in the single-cell RNA sequencing patient group. We showed that higher NET levels were associated with increased 90-day survival in patients with CAPA specifically, implying a beneficial role for NETs in CAPA.



Figure 1

A: Swimmer plot of patients included in the single-cell RNA-sequencing (scRNA-seq) study. B-C: uniform manifold approximations and projection (UMAP) plots showing all clustered cells. D: Boxplots showing major cell type fractions in CAPA vs. COVID-19-only. E-F: UMAPs of the neutrophil subclusters (E) and pseudotime trajectory (F). G: boxplot showing H3Cit-DNA (a form of NETs) levels in CAPA vs. COVID-19-only. H: Kaplan-Meier plots for CAPA and COVID-19-only patients, subdivided according to H3Cit-DNA levels.



Figure 2

Observations and derived hypotheses generated through this research.


 

Read the full publication in the Lancet journals here

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