ABSTRACT
To (re)define tissue architecture of the lung and airways at the cellular and molecular level, we profiled five proximal-to-distal locations of healthy human lungs in depth using multi-omic single cell/nuclei and Visium Spatial Transcriptomics. Using computational data integration and analysis, we extend beyond the suspension cell paradigm of lung atlases to date, to define and discover macro and micro-anatomical tissue compartments. We describe novel cell types and states in vascular, stromal and nerve bundle microenvironments. From our spatial transcriptomics, we discover and validate a novel survival niche for IgA plasma cells in the airway submucosal glands (SMG). In this niche we define a supporting role for SMG epithelial cells in mucosal immunity through recruitment and maintenance of IgA plasma, B and CD4 T cells locally at the airway SMG. We identify an immune-supporting role for SMG duct and serous cells with distinct signalling circuits to recruit B cells and IgA plasma cells, promoting longevity and antibody secretion through expression of CCL28, APRIL and IL6. We find high expression of MHC-II in SMG duct and serous cells, which are localised closely with memory CD4 T cells, suggesting local modulation of antigen specific immune responses locally at the glands. This new tissue microenvironment, which we term the “gland-associated immune niche” (GAIN) has major implications for respiratory immunity and infection response. Our single cell and spatial data is available for download and query at lungcellatlas.org.
ABSTRACT
Common genetic variants modulate the cellular response to viruses and are implicated in a range of immune pathologies, including infectious and autoimmune diseases. The transcriptional antiviral response is known to vary between infected cells from a single individual, yet how genetic variants across individuals modulate the antiviral response (and its cell-to-cell variability) is not well understood. Here, we triggered the antiviral response in human fibroblasts from 68 healthy donors, and profiled tens of thousands of cells using single-cell RNA-seq. We developed GASPACHO (GAuSsian Processes for Association mapping leveraging Cell HeterOgeneity), the first statistical approach designed to identify dynamic eQTLs across a transcriptional trajectory of cell populations, without aggregating single-cell data into pseudo-bulk. This allows us to uncover the underlying architecture and variability of antiviral response across responding cells, and to identify more than two thousands eQTLs modulating the dynamic changes during this response. Many of these eQTLs colocalise with risk loci identified in GWAS of infectious and autoimmune diseases. As a case study, we focus on a COVID-19 susceptibility locus, colocalised with the antiviral OAS1 splicing QTL. We validated it in blood cells from a patient cohort and in the infected nasal cells of a patient with the risk allele, demonstrating the utility of GASPACHO to fine-map and functionally characterise a genetic locus. In summary, our novel analytical approach provides a new framework for delineation of the genetic variants that shape a wide spectrum of transcriptional responses at single-cell resolution.