Homo Sapiens Nasal Inferior Turbinates of house dust mite-induced allergic rhinitis and controls
To elucidate the epithelial cell diversity within the nasal inferior turbinates, a comprehensive investigation was conducted comparing control subjects to individuals with house dust mite-induced allergic rhinitis. This study aimed to delineate the differential expression profiles and phenotypic variations of epithelial cells in response to allergic rhinitis. This research elucidated distinct subpopulations and rare cell types of epithelial cells within the nasal turbinates, discerning alterations induced by allergic rhinitis. Furthermore, by interrogating transcriptomic signatures, the investigation provided novel insights into the cellular dynamics and immune responses underlying allergic rhinitis pathogenesis Overall design: Single cell suspension of surgically collected inferior turbinates were obtained by enzymatic digestion using liberase (87.5 µg/ml, 5401127001, Roche) and DNase I (300 µg/ml, 10104159001, Roche) in RPMI with 10% FBS for 30' with additional mechanical disruption using a 16G needle after both 15' and 30' of enzymatic digestion. Digestion was stopped by adding EDTA (20 mM, 15575020, Invitrogen), whereafter red blood cells were lysed using 9.9% NaCl solution. Negative selection for immune, myeloid and fibroblast was performed using anti-CD45 (11153D, Invitrogen), anti-CD15 (11137D, Invitrogen) and anti-CD31 (11155D, Invitrogen) dynabeads, respectively. Cells were resuspended in PBS and filtered through a 70 µm cell strainer (542070, Greiner). Cells were loaded on the 10X Genomics Chromium 3' device (3' V2, 10X Genomics, Pleasanton, California, USA), and afterwards RNA libraries were constructed and sequenced using the NovaSeq 6000 S4 Reagent Kit V1.5 (20028312, Illumina) and using the NovaSeq 6000 device (Illumina, San Diego, California, USA). Raw sequencing files were cleaned, mapped to the human reference genome, filtered, normalized, demultiplexed and counted using fastaq-mcf, fastQC, Cell Ranger and fastMnM, after which data was analyzed using different R tools, such as Seurat, Harmony and Bioconductor in R 4.2.1 (36–41).