Abstract :
[en] Single cell RNA sequencing (scRNA-seq) is a powerful transcriptomic technique to analyse cell expression profiles across various tissues or conditions, and to identify new cell subpopulations. It has been extensively used in human and mouse studies, and more recently for identification of cellular subpopulations in the bronchoalveolar lavage fluid of dogs. To date, the molecular state of all cell types in canine lung tissue has not been profiled. Such study will help to determine specific cell markers, often lacking in the canine species, and will also provide the foundation for further comparisons with specific lung diseases at single-cell level, such as canine pulmonary fibrosis or neoplasia. In this context, we had a particular interest in fibroblast subpopulations and their expression profiles. Indeed, molecules expressed by fibroblasts (and by cancer-associated fibroblasts) are of potential interest for further development of early markers of disease and of novel molecular fibroblast-targeting therapies.
We performed droplet-based scRNA-seq on fresh healthy lung biopsies from three dogs. Two biopsies were collected from dogs euthanized for unrelated reasons, and one was collected from the tumour-free area of a lung lobe resected for primary adenocarcinoma. Biopsies were systematically collected at the peripheral part of the right caudal lobe. Tissues were dissociated to obtain single-cell suspensions, which were loaded into the Chromium Controller (10x Genomics). Clustering, visualization and gene profiling was achieved using the Seurat package in R. Distinct cell populations were identified based on canonical or literature-described cell markers.
A total of 22,424 cells were sequenced. Four main cell compartments were identified and individually investigated: epithelial cells (EPCAM+, 5 subpopulations), immune cells (PTPRC+, 17 subpopulations), endothelial cells (PECAM1+, 5 subpopulations) and mesenchymal cells (EPCAM-/PTPRC-/PECAM1-, 10 subpopulations). Clustering resolution was high enough to consistently discriminate different cell subpopulations within classical cell types such as fibroblasts, smooth muscle cells, lymphocytes or macrophages, for example. Among fibroblasts, cluster analysis highlighted subpopulations already identified in humans such as alveolar or adventitial fibroblasts. Differential gene expression profiles were defined for all 37 cell subpopulations, thus identifying new specific cell markers for all cells of the canine lung.
This is the first report of scRNA-seq analysis of canine lung tissue, expanding our knowledge of canine distal lung cell subpopulations. This study provides the foundation for comparisons with specific lung diseases at single-cell level, such as canine pulmonary fibrosis or canine pulmonary neoplasia, for which development of emerging therapies are cruelly required.
