Single-cell transcriptomic profiling of eosinophils and airway immune cells in childhood asthma

Background

Single-cell RNA sequencing has transformed our understanding of cellular heterogeneity but remains inadequate in capturing granulocytes, particularly in tissue compartments, owing to technical limitations.

Objective

To enhance granulocyte recovery in single-cell RNA sequencing, we used nasal lavage samples from children with asthma, leveraging the 10× Genomics Flex platform combined with a customized data processing pipeline.

Methods

Nasal lavage samples were processed without prior manipulation to avoid technical artifacts such as lysis or stimulation. Granulocyte recovery was optimized by using fixation to preserve cell quality and advanced computational techniques to separate cells with a low RNA content from background noise. Cell-type proportions were validated against histologic and bulk RNA data.

Results

The optimized approach achieved more than a16-fold increase in eosinophil detection versus in standard methods. This method successfully captured eosinophils, neutrophils, and other major cell types in proportions consistent with histologic and bulk RNA assessments, with no biased loss of cell types. Phenotypic comparisons between children with high-eosinophil and low-eosinophil asthma uncovered significant transcriptional differences, cell composition, and distinct biologic pathways in granulocytes, immune cells, and epithelial cells. Additionally, distinct subpopulations of eosinophils and neutrophils with unique functional profiles were identified; the identified subpopulations were uniquely associated with high- and low-eosinophil asthma phenotypes, highlighting the complexity of airway granulocyte inflammation.

Conclusions

This study provides a framework for efficient capture of granulocytes in tissue compartments, overcoming traditional limitations. The resulting data set serves as a valuable resource for understanding airway granulocyte biology and inflammation, enabling detailed exploration of asthma pathogenesis. Furthermore, this approach facilitates large-scale, multicenter translational studies and advances personalized therapeutic strategies for airway diseases.