Airway cell-cell communication in smoking through integration of spatial and single-cell transcriptomics

Cigarette smoking has a significant impact on global health. Although cessation has positive health benefits, some molecular changes to intercellular communications may persist in the lung. In this study we created a workflow to generate hypotheses by predicting altered cell-cell communication in smoker lungs using single-cell and spatial transcriptomic data.

We integrated publicly available lung single-cell transcriptomic data (n = 104) with spatial transcriptomic data (n = 2) from never-smoker and current-smoker airway samples to create spatial transcriptomic data at virtual single-cell resolution by mapping individual cells from our lung scRNA-seq dataset to spots in the spatial transcriptomic data. Cell-cell communications altered in smoking were identified using these integrated transcriptomic data.

We identified pathways altered in two current-smoker samples compared with two never-smoker samples, including the overexpressed collagen pathway. We observed increased collagen pathway activity involving the ligands COL1A1 and COL1A2 in adventitial fibroblasts and decreased activity involving COL1A2 and COL6A3 in pericytes and myofibroblasts, respectively. We also identified other pathways with structural (e.g. Fibronectin-1), immune-related (e.g. MHC-II), growth factor (e.g. Pleiotrophin) and immunophilin (e.g. Cyclophilin A) roles.

In this study we inferred spatially proximal cell-cell communication between interacting cell types from spatial transcriptomics at virtual single-cell resolution to identify lung intercellular signaling altered in smoking. Our findings further implicate several pathways previously identified, and provide additional molecular context to inform future functional experiments and therapeutic avenues to mitigate pathogenic effects of smoking.