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Studies comparing single cell RNA-Seq (scRNA-Seq) data between conditions mainly focus on differences in the proportion of cell types or on differentially expressed genes. In many cases these differences are driven by changes in cell interactions which are challenging to infer without spatial information. To determine cell-cell interactions that differ between conditions we developed the Cell Interaction Network Inference (CINS) pipeline. CINS combines Bayesian network analysis with regression-based modeling to identify differential cell type interactions and the proteins that underlie them. We tested CINS on a disease case control and on an aging mouse dataset. In both cases CINS correctly identifies cell type interactions and the ligands involved in these interactions improving on prior methods suggested for cell interaction predictions. We performed additional mouse aging scRNA-Seq experiments which further support the interactions identified by CINS. 

Abstract Engineered whole lungs may one day expand therapeutic options for patients with end-stage lung disease. However, the feasibility of ex vivo lung regeneration remains limited by the inability to recapitulate mature, functional alveolar epithelium. Here, we modulate multimodal components of the alveolar epithelial type 2 cell (AEC2) niche in decellularized lung scaffolds in order to guide AEC2 behavior for epithelial regeneration. First, endothelial cells coordinate with fibroblasts, in the presence of soluble growth and maturation factors, to promote alveolar scaffold population with surfactant-secreting AEC2s. Subsequent withdrawal of Wnt and FGF agonism synergizes with tidal-magnitude mechanical strain to induce the differentiation of AEC2s to squamous type 1 AECs (AEC1s) in cultured alveoli, in situ. These results outline a rational strategy to engineer an epithelium of AEC2s and AEC1s contained within epithelial-mesenchymal-endothelial alveolar-like units, and highlight the critical interplay amongst cellular, biochemical, and mechanical niche cues within the reconstituting alveolus. 

Although epithelial-mesenchymal transition (EMT) is a common feature of fibrotic lung disease, its role in fibrogenesis is controversial. Recently, aberrant basaloid cells were identified in fibrotic lung tissue as a novel epithelial cell type displaying a partial EMT phenotype. The developmental origin of these cells remains unknown. To elucidate the role of EMT in the development of aberrant basaloid cells from the bronchial epithelium, we mapped EMT-induced transcriptional changes at the population and single-cell levels. Human bronchial epithelial cells grown as submerged or air-liquid interface (ALI) cultures with or without EMT induction were analyzed by bulk and single-cell RNA-Sequencing. Comparison of submerged and ALI cultures revealed differential expression of 8,247 protein coding (PC) and 1,621 long noncoding RNA (lncRNA) genes and revealed epithelial cell-type-specific lncRNAs. Similarly, EMT induction in ALI cultures resulted in robust transcriptional reprogramming of 6,020 PC and 907 lncRNA genes. Although there was no evidence for fibroblast/myofibroblast conversion following EMT induction, cells displayed a partial EMT gene signature and an aberrant basaloid-like cell phenotype. The substantial transcriptional differences between submerged and ALI cultures highlight that care must be taken when interpreting data from submerged cultures. This work supports that lung epithelial EMT does not generate fibroblasts/myofibroblasts and confirms ALI cultures provide a physiologically relevant system to study aberrant basaloid-like cells and mechanisms of EMT. We provide a catalog of PC and lncRNA genes and an interactive browser ( https://bronc-epi-in-vitro.cells.ucsc.edu/ ) of single-cell RNA-Seq data for further exploration of potential roles in the lung epithelium in health and lung disease. 

Abstract Patients with chronic lung disease (CLD) have an increased risk for severe coronavirus disease-19 (COVID-19) and poor outcomes. Here, we analyze the transcriptomes of 611,398 single cells isolated from healthy and CLD lungs to identify molecular characteristics of lung cells that may account for worse COVID-19 outcomes in patients with chronic lung diseases. We observe a similar cellular distribution and relative expression of SARS-CoV-2 entry factors in control and CLD lungs. CLD AT2 cells express higher levels of genes linked directly to the efficiency of viral replication and the innate immune response. Additionally, we identify basal differences in inflammatory gene expression programs that highlight how CLD alters the inflammatory microenvironment encountered upon viral exposure to the peripheral lung. Our study indicates that CLD is accompanied by changes in cell-type-specific gene expression programs that prime the lung epithelium for and influence the innate and adaptive immune responses to SARS-CoV-2 infection.