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The respiratory system undergoes a diversity of structural, biochemical, and functional changes necessary for adaptation to air breathing at birth. To identify the heterogeneity of pulmonary cell types and dynamic changes in gene expression mediating adaptation to respiration, here we perform single cell RNA analyses of mouse lung on postnatal day 1. Using an iterative cell type identification strategy we unbiasedly identify the heterogeneity of murine pulmonary cell types. We identify distinct populations of epithelial, endothelial, mesenchymal, and immune cells, each containing distinct subpopulations. Furthermore we compare temporal changes in RNA expression patterns before and after birth to identify signaling pathways selectively activated in specific pulmonary cell types, including activation of cell stress and the unfolded protein response during perinatal adaptation of the lung. The present data provide a single cell view of the adaptation to air breathing after birth. The respiratory system is transformed in terms of functional change at birth to adapt to breathing air. Here, the authors examine the molecular changes behind the first breath in the mouse by Drop-seq based RNA sequencing, identifying activation of the unfolded protein response as a perinatal adaptation of the lung.

Accurate cell type identification is a key and rate-limiting step in single-cell data analysis. Single-cell references with comprehensive cell types, reproducible and functionally validated cell identities, and common nomenclatures are much needed by the research community for automated cell type annotation, data integration, and data sharing. Here, we develop a computational pipeline utilizing the LungMAP CellCards as a dictionary to consolidate single-cell transcriptomic datasets of 104 human lungs and 17 mouse lung samples to construct LungMAP single-cell reference (CellRef) for both normal human and mouse lungs. CellRefs define 48 human and 40 mouse lung cell types catalogued from diverse anatomic locations and developmental time points. We demonstrate the accuracy and stability of LungMAP CellRefs and their utility for automated cell type annotation of both normal and diseased lungs using multiple independent methods and testing data. We develop user-friendly web interfaces for easy access and maximal utilization of the LungMAP CellRefs. Accurate cell-type identification is vital for single-cell analysis. Here, the authors develop a computational pipeline called “LungMAP CellRef” for efficient, automated cell-type annotation of normal and disease human and mouse lung single-cell datasets.

Despite high expectations for lung tumoroids, they have not been applied in the clinic due to the difficulty of their long-term culture. Here, however, using AO (airway organoid) media developed by the Clevers laboratory, we succeeded in generating 3 lung tumoroid lines for long-term culture (>13 months) from 41 lung cancer cases (primary or metastatic). Use of nutlin-3a was key to selecting lung tumoroids that harbor mutant p53 in order to eliminate normal lung epithelial organoids. Next-generation sequencing (NGS) analysis indicated that each lung tumoroid carried BRAF G469A , TPM3-ROS1 or EGFR L858R /RB1 E737* , respectively. Targeted therapies using small molecule drugs (trametinib/erlotinib for BRAF G469A , crizotinib/entrectinib for TPM3-ROS1 and ABT-263/YM-155 for EGFR L858R /RB1 E737* ) significantly suppressed the growth of each lung tumoroid line. AO media was superior to 3 different media developed by other laboratories. Our experience indicates that long-term lung tumoroid culture is feasible, allowing us to identify NGS-based therapeutic targets and determine the responsiveness to corresponding small molecule drugs.

Respiratory failure associated with COVID-19 has placed focus on the lungs. Here, we present single-nucleus accessible chromatin profiles of 90,980 nuclei and matched single-nucleus transcriptomes of 46,500 nuclei in non-diseased lungs from donors of ~30 weeks gestation,~3 years and ~30 years. We mapped candidate cis -regulatory elements (cCREs) and linked them to putative target genes. We identified distal cCREs with age-increased activity linked to SARS-CoV-2 host entry gene TMPRSS2 in alveolar type 2 cells, which had immune regulatory signatures and harbored variants associated with respiratory traits. At the 3p21.31 COVID-19 risk locus, a candidate variant overlapped a distal cCRE linked to SLC6A20 , a gene expressed in alveolar cells and with known functional association with the SARS-CoV-2 receptor ACE2. Our findings provide insight into regulatory logic underlying genes implicated in COVID-19 in individual lung cell types across age. More broadly, these datasets will facilitate interpretation of risk loci for lung diseases.

‘LungGENS’, our previously developed web tool for mapping single-cell gene expression in the developing lung, has been well received by the pulmonary research community. With continued support from the ‘LungMAP’ consortium, we extended the scope of the LungGENS database to accommodate transcriptomics data from pulmonary tissues and cells from human and mouse at different stages of lung development. Lung Gene Expression Analysis (LGEA) web portal is an extended version of LungGENS useful for the analysis, display and interpretation of gene expression patterns obtained from single cells, sorted cell populations and whole lung tissues. The LGEA web portal is freely available at http://research.cchmc.org/pbge/lunggens/mainportal.html.

Mutations in the FOXF1 gene, a key transcriptional regulator of pulmonary vascular development, cause Alveolar Capillary Dysplasia with Misalignment of Pulmonary Veins, a lethal lung disease affecting newborns and infants. Identification of new FOXF1 upstream regulatory elements is critical to explain why frequent non-coding FOXF1 deletions are linked to the disease. Herein, we use multiome single-nuclei RNA and ATAC sequencing of mouse and human patient lungs to identify four conserved endothelial and mesenchymal FOXF1 enhancers. We demonstrate that endothelial FOXF1 enhancers are autoactivated, whereas mesenchymal FOXF1 enhancers are regulated by EBF1 and GLI1. The cell-specificity of FOXF1 enhancers is validated by disrupting these enhancers in mouse embryonic stem cells using CRISPR/Cpf1 genome editing followed by lineage-tracing of mutant embryonic stem cells in mouse embryos using blastocyst complementation. This study resolves an important clinical question why frequent non-coding FOXF1 deletions that interfere with endothelial and mesenchymal enhancers can lead to the disease. Mutations in FOXF1 , a key transcriptional regulator of pulmonary vascular development, cause Alveolar Capillary Dysplasia with Misalignment of Pulmonary Veins. Here, the authors discovered four genomic regions that control cell type-specific activity of Foxf1 during lung development and show that disrupting these regions via genetic deletions leads to alveolar capillary dysplasia.

While the critical role of NKX2-1 and its transcriptional targets in lung morphogenesis and pulmonary epithelial cell differentiation is increasingly known, mechanisms by which chromatin accessibility alters the epigenetic landscape and how NKX2-1 interacts with other co-activators required for alveolar epithelial cell differentiation and function are not well understood. Combined deletion of the histone methyl transferases Prdm3 and Prdm16 in early lung endoderm causes perinatal lethality due to respiratory failure from loss of AT2 cells and the accumulation of partially differentiated AT1 cells. Combination of single-cell RNA-seq, bulk ATAC-seq, and CUT&RUN data demonstrate that PRDM3 and PRDM16 regulate chromatin accessibility at NKX2-1 transcriptional targets critical for perinatal AT2 cell differentiation and surfactant homeostasis. Lineage specific deletion of PRDM3/16 in AT2 cells leads to lineage infidelity, with PRDM3/16 null cells acquiring partial AT1 fate. Together, these data demonstrate that NKX2-1-dependent regulation of alveolar epithelial cell differentiation is mediated by epigenomic modulation via PRDM3/16. Growth and differentiation of pulmonary epithelial cells is precisely controlled to form the alveoli that create the gas exchange region of the lung. Here, the authors demonstrate that epigenetic modulation of the genome by PRDM3/16 mediates NKX2-1 activity to control alveolar cell fate and differentiation during embryonic and perinatal lung development.

Though invasive mucinous adenocarcinoma of the lung (IMA) is pathologically distinctive, the molecular mechanism driving IMA is not well understood, which hampers efforts to identify therapeutic targets. Here, by analyzing gene expression profiles of human and mouse IMA, we identified a Mucinous Lung Tumor Signature of 143 genes, which was unexpectedly enriched in mucin‐producing gastrointestinal, pancreatic, and breast cancers. The signature genes included transcription factors FOXA3, SPDEF, HNF4A, mucins MUC5AC, MUC5B, MUC3, and an inhibitory immune checkpoint VTCN1 / B7‐H4 (but not PD‐L1 / B7‐H1 ). Importantly, induction of FOXA3 or SPDEF along with mutant KRAS in lung epithelium was sufficient to develop benign or malignant mucinous lung tumors, respectively, in transgenic mice. FOXA3 and SPDEF induced MUC5AC and MUC5B, while HNF4A induced MUC3 in human mucinous lung cancer cells harboring a KRAS mutation. ChIP‐seq combined with CRISPR/Cas9 determined that upstream enhancer regions of the mucin genes MUC5AC and MUC5B , which were bound by SPDEF, were required for the expression of the mucin genes. Here, we report the molecular signature and gene regulatory network driving mucinous lung tumors. Synopsis Invasive mucinous adenocarcinoma of the lung (IMA) is now defined not only pathologically but also at the molecular level. A novel gene IMA signature characterizes human IMA cases that bear KRAS mutations. The immune checkpoint VTCN1/B7‐H4 but not PD‐L1/B7‐H1 correlates with mucinous markers. The anti‐mucous transcription factor NKX2‐1 induces PD‐L1/B7‐H1 and suppresses the pro‐mucous transcription factors FOXA3, SPDEF, and HNF4A. Distal enhancers bound by SPDEF are required for the expression of MUC5AC and MUC5B. Graphical Abstract Invasive mucinous adenocarcinoma of the lung (IMA) is now defined not only pathologically but also at the molecular level.

The transcription factor NKX2-1/TTF-1 is involved in lung pathophysiology, including breathing, innate defense and tumorigenesis. To understand the mechanism by which NKX2-1 regulates genes involved in such pathophysiology, we have previously performed ChIP-seq and identified genome-wide NKX2-1-binding sites, which revealed that NKX2-1 binds to not only proximal promoter regions but also multiple intra- and inter-genic regions of the genes regulated by NKX2-1. However, the roles of such regions, especially non-proximal ones, bound by NKX2-1 have not yet been determined. Here, using CRISPRi (CRISPR/dCas9-KRAB), we scrutinize the functional roles of 19 regions/sites bound by NKX2-1, which are located in genes involved in breathing and innate defense (SFTPB, LAMP3, SFTPA1, SFTPA2) and lung tumorigenesis (MYBPH, LMO3, CD274/PD-L1). Notably, the CRISPRi approach reveals that a portion of NKX2-1-binding sites are functionally indispensable while the rest are dispensable for the expression of the genes, indicating that functional roles of NKX2-1-binding sites are unequally yoked.The transcription factor NKX2-1 is a key regulator of lung pathophysiology, but the importance of its binding sites outside of proximal promoter regions is unclear. Here, William Stuart and Iris Fink-Baldauf et al. use CRISPRi to interrogate 19 NKX2-1 binding sites and identify specific sites important for breathing, innate immune defense, and tumorigenesis.

A major challenge in developmental biology is to understand the genetic and cellular processes/programs driving organ formation and differentiation of the diverse cell types that comprise the embryo. While recent studies using single cell transcriptome analysis illustrate the power to measure and understand cellular heterogeneity in complex biological systems, processing large amounts of RNA-seq data from heterogeneous cell populations creates the need for readily accessible tools for the analysis of single-cell RNA-seq (scRNA-seq) profiles. The present study presents a generally applicable analytic pipeline (SINCERA: a computational pipeline for SINgle CEll RNA-seq profiling Analysis) for processing scRNA-seq data from a whole organ or sorted cells. The pipeline supports the analysis for: 1) the distinction and identification of major cell types; 2) the identification of cell type specific gene signatures; and 3) the determination of driving forces of given cell types. We applied this pipeline to the RNA-seq analysis of single cells isolated from embryonic mouse lung at E16.5. Through the pipeline analysis, we distinguished major cell types of fetal mouse lung, including epithelial, endothelial, smooth muscle, pericyte, and fibroblast-like cell types, and identified cell type specific gene signatures, bioprocesses, and key regulators. SINCERA is implemented in R, licensed under the GNU General Public License v3, and freely available from CCHMC PBGE website, https://research.cchmc.org/pbge/sincera.html.