Danopoulos, S. | Search bioRxiv

bioRxiv2023

A Trisomy 21 Lung Cell Atlas

Trisomy 21 (T21), resulting in Down Syndrome (DS), is the most prevalent chromosomal abnormality worldwide. While pulmonary disease is a major cause of morbidity and mortality in DS, the ontogeny of pulmonary complications remains poorly understood. We recently demonstrated that T21 lung anomalies, including airway branching and vascular lymphatic abnormalities, are initiated in utero. Here, we aimed to describe molecular changes at the single cell level in prenatal T21 lungs. Our results demonstrate differences in the proportion of cell populations and detail changes in gene expression at the time of initiation of histopathological abnormalities. Notably, we identify shifts in the distribution of alveolar epithelial progenitors, widespread induction of key extracellular matrix molecules in mesenchymal cells and hyper-activation of IFN signaling in endothelial cells. This single cell atlas of T21 lungs greatly expands our understanding of antecedents to pulmonary complications and should facilitate efforts to mitigate respiratory disease in DS.

developmental biology↗

bioRxiv2020

Single cell transcriptomic profiling identifies molecular phenotypes of newborn human lung cells

RationaleWhile animal model studies have extensively defined mechanisms controlling cell diversity in the developing mammalian lung, the limited data available from late stage human lung development represents a significant knowledge gap. The NHLBI Molecular Atlas of Lung Development Program (LungMAP) seeks to fill this gap by creating a structural, cellular and molecular atlas of the human and mouse lung. MethodsSingle cell RNA sequencing generated transcriptional profiles of 5500 cells obtained from two one-day old human lungs (born at gestational ages of 39 and 31 weeks) from the LungMAP Human Tissue Core Biorepository at the University of Rochester. Frozen single cell isolates were captured, and library preparation was completed on the Chromium 10X system. Data was analyzed in Seurat, and cellular annotation was performed using the ToppGene functional analysis tool. Single cell sequence data from 32000 postnatal day 1, 3, 7 and 10 mouse lung (n = 2 at each time point) cells generated by the LungMAP Research Center at Cincinnati Childrens Hospital and Medical Center, using Dropseq platform, was integrated with the human data. In situ hybridization was used to confirm the spatial location of cellular phenotypes. ResultsTranscriptional interrogation of donor newborn human lung cells identified distinct clusters representing multiple populations of epithelial, endothelial, fibroblasts, pericytes, smooth muscle, and immune cells and signature genes for each of these populations were identified. Computational integration of newborn human and postnatal mouse lung development cellular transcriptomes facilitated the identification of distinct cellular lineages among all the major cell types. Integration of the human and mouse cellular transcriptomes also demonstrated cell type-specific differences in developmental states of the newborn human lung cells. In particular, matrix fibroblasts could be separated into those representative of younger cells (n=393), or older cells (n=158). This is the first comprehensive molecular map of the cellular landscape of neonatal human lung, including biomarkers for cells at distinct states of development. Our results indicate that integrated single cell RNA profiling of human and mouse lung will help identify common and species-specific mechanisms of lung development and respiratory disease.

genomics↗