Profiling cellular heterogeneity in asthma with single cell multiparameter CyTOF

Abstract

Asthma is a chronic inflammatory disease of the airways that afflicts over 30 million individuals in the United States and over 300 million individuals worldwide. The inflammatory response in the airways is often characterized by the analysis of sputum, which contains multiple types of cells including neutrophils, macrophages, lymphocytes, and rare bronchial epithelial cells. Subtyping patients using microscopy of the sputum has identified both neutrophilic and eosinophilic infiltrates in airway inflammation. However, with the extensive heterogeneity among these cell types, a higher resolution understanding of the inflammatory cell types present in the sputum is needed to dissect the heterogeneity of disease. Improved recognition of the distinct phenotypes and sources of inflammation in asthmatic granulocytes may identify relevant pathways for clinical management or investigation of novel therapeutic mediators. Here, we employed mass cytometry or cytometry by time-of-flight to quantify frequency and define functional status of sputum derived airway cells in asthmatic patients and healthy controls. This in-depth single cell analysis method identified multiple distinct subtypes of airway immune cells, especially in neutrophils. Significance was discovered by statistical analysis as well as a data-driven unbiased clustering approach. Our multidimensional assessment method identifies differences in cellular function and supports identification of cellular status that may contribute to diverse clinical responses. This technical advance is relevant for studies of pathogenesis and may provide meaningful insights to advance our knowledge of asthmatic inflammation.

Keywords: dendritic cell; eosinophil; inflammation; mass cytometry; neutrophil.

Figure 1.. Frequency of cells from sputum.

Induced sputum samples from asthmatic (AS, n=18) and healthy control (HC, n= 9) subjects were labeled fresh on the day of collection with metal-conjugated antibodies and analyzed by mass cytometry. (A) Cell yield mean ± sem, NS (B) Frequency of cell subsets (C) Frequency of macrophage subsets. Data shown is median with interquartile range; Wilcoxon signed rank test, * P<0.01.

Figure 2.. Frequencies of sputum cell sub-populations in asthmatics and healthy controls.

Induced sputum samples from asthmatic (AS, n=18) and healthy control (HC, n= 9) subjects were labeled fresh on the day of collection with metal-conjugated antibodies and analyzed by mass cytometry. Frequency of immune cell subsets displayed using Boolean analysis (A) and median values in each population by group (B).

Figure 3.. Functional analysis of asthmatic and healthy control granulocyte populations.

Induced sputum samples were labeled fresh on the day of collection with metal-conjugated antibodies and analyzed by mass cytometry. Analysis by FlowSOM clustering heatmap of the median expression levels of functional markers of granulocyte subsets for AS (n=4) and HC (n=3).

Figure 4.. Functional clustering of asthmatic and healthy control granulocyte populations.

Induced sputum samples were labeled fresh on the day of collection with metal-conjugated antibodies and analyzed by mass cytometry. Visualization of FlowSOM clusters by Tsne for neutrophil clusters from all samples (A) and separated for AS (B) andHC (C).