Single-cell multiomic profiling of human lungs reveals cell-type-specific and age-dynamic control of SARS-CoV2 host genes

Contemporary and emerging technologies for research in children's rare and interstitial lung disease

Although recent decades have seen the identification, classification and discovery of the genetic basis of many children's interstitial and rare lung disease (chILD) disorders, detailed understanding of pathogenesis and specific therapies are still lacking for most of them. Fortunately, a revolution of technological advancements has created new opportunities to address these critical knowledge gaps. High-throughput sequencing has facilitated analysis of transcription of thousands of genes in thousands of single cells, creating tremendous breakthroughs in understanding normal and diseased cellular biology. Spatial techniques allow analysis of transcriptomes and proteomes at the subcellular level in the context of tissue architecture, in many cases even in formalin-fixed, paraffin-embedded specimens. Gene editing techniques allow creation of "humanized" animal models in a shorter time frame, for improved knowledge and preclinical therapeutic testing. Regenerative medicine approaches and bioengineering advancements facilitate the creation of patient-derived induced pluripotent stem cells and their differentiation into tissue-specific cell types which can be studied in multicellular "organoids" or "organ-on-a-chip" approaches. These technologies, singly and in combination, are already being applied to gain new biological insights into chILD disorders. The time is ripe to systematically apply these technologies to chILD, together with sophisticated data science approaches, to improve both biological understanding and disease-specific therapy.

Quercetin and taxifolin inhibits TMPRSS2 activity and its interaction with EGFR in paclitaxel-resistant breast cancer cells: An in silico and in vitro study

Transmembrane protease/serine (TMPRSS2), a type II transmembrane serine protease, plays a crucial role in different stages of cancer. Recent studies have reported that the triggering epidermal growth factor receptor (EGFR) activation through protease action promotes metastasis. However, there are no reports on the interaction of TMPRSS2 with EGFR, especially in triple-negative triple negative (TNBC). The current study investigates the unexplored interaction between TMPRSS2 and EGFR, which are key partners mediating metastasis. This interaction is explored for potential targeting using quercetin (QUE) and taxifolin (TAX). TMPRSS2 expression patterns in breast cancer (BC) tissues and subtypes have been predicted, with the prognostic significance assessed using the GENT2.0 database. Validation of TMPRSS2 expression was performed in normal and TNBC tissues, including drug-resistant cell lines, utilizing GEO datasets. TMPRSS2 was further validated as a predictive biomarker for FDA-approved chemotherapeutics through transcriptomic data from BC patients. The study demonstrated the association of TMPRSS2 with EGFR through in silico analysis and validates the findings in TNBC cohorts using the TIMER2.0 web server and the TCGA dataset through C-Bioportal. Molecular docking and molecular dynamic simulation studies identified QUE and TAX as best leads targeting TMPRSS2. They inhibited cell-free TMPRSS2 activity like clinical inhibitor of TMPRSS2, Camostat mesylate. In cell-based assays focused on paclitaxel-resistant TNBC (TNBC/PR), QUE and TAX demonstrated potent inhibitory activity against extracellular and membrane-bound TMPRSS2, with low IC50 values. Furthermore, ELISA and cell-based AlphaLISA assays demonstrated that QUE and TAX inhibit the interaction of TMPRSS2 with EGFR. Additionally, QUE and TAX exhibited significant inhibition of proliferation and cell cycle accompanied by notable alterations in the morphology of TNBC/PR cells. This study provides valuable insights into potential of QUE and TAX targeting TMPRSS2 overexpressing TNBC.

Transcriptomics Analysis Identifies the Decline in the Alveolar Type II Stem Cell Niche in Aged Human Lungs

Aging poses a global public health challenge, which is linked to the rise of age-related lung diseases. The precise understanding of the molecular and genetic changes in the aging lung that elevate the risk of acute and chronic lung diseases remains incomplete. Alveolar type II (AT2) cells are stem cells that maintain epithelial homeostasis and repair the lung after injury. AT2 progenitor function decreases with aging. The maintenance of AT2 function requires niche support from other cell types, but little has been done to characterize alveolar alterations with aging in the AT2 niche. To systematically profile the genetic changes associated with age, we present a single-cell transcriptional atlas comprising nearly half a million cells from the healthy lungs of human subjects spanning various ages, sexes, and smoking statuses. Most annotated cell lineages in aged lungs exhibit dysregulated genetic programs. Specifically, the aged AT2 cells demonstrate loss of epithelial identities, heightened inflammaging characterized by increased expression of AP-1 (Activator Protein-1) transcription factor and chemokine genes, and significantly increased cellular senescence. Furthermore, the aged mesenchymal cells display a remarkable decrease in collagen and elastin transcription and a loss of support to epithelial cell stemness. The decline of the AT2 niche is further exacerbated by a dysregulated genetic program in macrophages and dysregulated communications between AT2 and macrophages in aged human lungs. These findings highlight the dysregulations observed in both AT2 stem cells and their supportive niche cells, potentially contributing to the increased susceptibility of aged populations to lung diseases.

A therapy for suppressing canonical and noncanonical SARS-CoV-2 viral entry and an intrinsic intrapulmonary inflammatory response

The prevalence of "long COVID" is just one of the conundrums highlighting how little we know about the lung's response to viral infection, particularly to syndromecoronavirus-2 (SARS-CoV-2), for which the lung is the point of entry. We used an in vitro human lung system to enable a prospective, unbiased, sequential single-cell level analysis of pulmonary cell responses to infection by multiple SARS-CoV-2 strains. Starting with human induced pluripotent stem cells and emulating lung organogenesis, we generated and infected three-dimensional, multi-cell-type-containing lung organoids (LOs) and gained several unexpected insights. First, SARS-CoV-2 tropism is much broader than previously believed: Many lung cell types are infectable, if not through a canonical receptor-mediated route (e.g., via Angiotensin-converting encyme 2(ACE2)) then via a noncanonical "backdoor" route (via macropinocytosis, a form of endocytosis). Food and Drug Administration (FDA)-approved endocytosis blockers can abrogate such entry, suggesting adjunctive therapies. Regardless of the route of entry, the virus triggers a lung-autonomous, pulmonary epithelial cell-intrinsic, innate immune response involving interferons and cytokine/chemokine production in the absence of hematopoietic derivatives. The virus can spread rapidly throughout human LOs resulting in mitochondrial apoptosis mediated by the prosurvival protein Bcl-xL. This host cytopathic response to the virus may help explain persistent inflammatory signatures in a dysfunctional pulmonary environment of long COVID. The host response to the virus is, in significant part, dependent on pulmonary Surfactant Protein-B, which plays an unanticipated role in signal transduction, viral resistance, dampening of systemic inflammatory cytokine production, and minimizing apoptosis. Exogenous surfactant, in fact, can be broadly therapeutic.

A systems biology-based identification and in vivo functional screening of Alzheimer's disease risk genes reveal modulators of memory function

Genome-wide association studies (GWASs) have uncovered over 75 genomic loci associated with risk for late-onset Alzheimer's disease (LOAD), but identification of the underlying causal genes remains challenging. Studies of induced pluripotent stem cell (iPSC)-derived neurons from LOAD patients have demonstrated the existence of neuronal cell-intrinsic functional defects. Here, we searched for genetic contributions to neuronal dysfunction in LOAD using an integrative systems approach that incorporated multi-evidence-based gene mapping and network-analysis-based prioritization. A systematic perturbation screening of candidate risk genes in Caenorhabditis elegans (C. elegans) revealed that neuronal knockdown of the LOAD risk gene orthologs vha-10 (ATP6V1G2), cmd-1 (CALM3), amph-1 (BIN1), ephx-1 (NGEF), and pho-5 (ACP2) alters short-/intermediate-term memory function, the cognitive domain affected earliest during LOAD progression. These results highlight the impact of LOAD risk genes on evolutionarily conserved memory function, as mediated through neuronal endosomal dysfunction, and identify new targets for further mechanistic interrogation.

Cell type-specific expression of angiotensin receptors in the human lung with implications for health, aging, and chronic disease

The renin-angiotensin system is a highly characterized integrative pathway in mammalian homeostasis whose clinical spectrum has been expanded to lung disorders such as chronic obstructive pulmonary disease (COPD)-emphysema, idiopathic pulmonary fibrosis (IPF), and COVID pathogenesis. Despite this widespread interest, specific localization of this receptor family in the mammalian lung is limited, partially due to the imprecision of available antibody reagents. In this study, we establish the expression pattern of the two predominant angiotensin receptors in the human lung, AGTR1 and AGTR2, using complementary and comprehensive bulk and single-cell RNA-sequence datasets that are publicly available. We show these two receptors have distinct localization patterns and developmental trajectories in the human lung, pericytes for AGTR1 and a subtype of alveolar epithelial type 2 cells for AGTR2. In the context of disease, we further pinpoint AGTR2 localization to the COPD-associated subpopulation of alveolar epithelial type 2 (AT2B) and AGTR1 localization to fibroblasts, where their expression is upregulated in individuals with COPD, but not in individuals with IPF. Finally, we examine the genetic variation of the angiotensin receptors, finding AGTR2 associated with lung phenotype (i.e., cystic fibrosis) via rs1403543. Together, our findings provide a critical foundation for delineating this pathway's role in lung homeostasis and constructing rational approaches for targeting specific lung disorders.

Bayesian-frequentist hybrid inference framework for single cell RNA-seq analyses

BACKGROUND

Single cell RNA sequencing technology (scRNA-seq) has been proven useful in understanding cell-specific disease mechanisms. However, identifying genes of interest remains a key challenge. Pseudo-bulk methods that pool scRNA-seq counts in the same biological replicates have been commonly used to identify differentially expressed genes. However, such methods may lack power due to the limited sample size of scRNA-seq datasets, which can be prohibitively expensive.

RESULTS

Motivated by this, we proposed to use the Bayesian-frequentist hybrid (BFH) framework to increase the power and we showed in simulated scenario, the proposed BFH would be an optimal method when compared with other popular single cell differential expression methods if both FDR and power were considered. As an example, the method was applied to an idiopathic pulmonary fibrosis (IPF) case study.

CONCLUSION

In our IPF example, we demonstrated that with a proper informative prior, the BFH approach identified more genes of interest. Furthermore, these genes were reasonable based on the current knowledge of IPF. Thus, the BFH offers a unique and flexible framework for future scRNA-seq analyses.

Identification of endothelial and mesenchymal FOXF1 enhancers involved in alveolar capillary dysplasia

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.

Micro-patterned culture of iPSC-derived alveolar and airway cells distinguishes SARS-CoV-2 variants

The emergence of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) variants necessitated a rapid evaluation system for their pathogenesis. Lung epithelial cells are their entry points; however, in addition to their limited source, the culture of human alveolar epithelial cells is especially complicated. Induced pluripotent stem cells (iPSCs) are an alternative source of human primary stem cells. Here, we report a model for distinguishing SARS-CoV-2 variants at high resolution, using separately induced iPSC-derived alveolar and airway cells in micro-patterned culture plates. The position-specific signals induced the apical-out alveolar type 2 and multiciliated airway cells at the periphery and center of the colonies, respectively. The infection studies in each lineage enabled profiling of the pathogenesis of SARS-CoV-2 variants: infection efficiency, tropism to alveolar and airway lineages, and their responses. These results indicate that this culture system is suitable for predicting the pathogenesis of emergent SARS-CoV-2 variants.

Single-cell analytical technologies: uncovering the mechanisms behind variations in immune responses

The immune landscape varies among individuals. It determines the immune response and results in surprisingly diverse symptoms, even in response to similar external stimuli. However, the detailed mechanisms underlying such diverse immune responses have remained mostly elusive. The utilization of recently developed single-cell multimodal analysis platforms has started to answer this question. Emerging studies have elucidated several molecular networks that may explain diversity with respect to age or other factors. An elaborate interplay between inherent physical conditions and environmental conditions has been demonstrated. Furthermore, the importance of modifications by the epigenome resulting in transcriptome variation among individuals is gradually being revealed. Accordingly, epigenomes and transcriptomes are direct indicators of the medical history and dynamic interactions with environmental factors. Coronavirus disease 2019 (COVID-19) has recently become one of the most remarkable examples of the necessity of in-depth analyses of diverse responses with respect to various factors to improve treatment in severe cases and to prevent viral transmission from asymptomatic carriers. In fact, determining why some patients develop serious symptoms is still a pressing issue. Here, we review the current "state of the art" in single-cell analytical technologies and their broad applications to healthy individuals and representative diseases, including COVID-19.

Identification of a distal enhancer regulating hedgehog interacting protein gene in human lung epithelial cells

BACKGROUND

An intergenic region at chromosome 4q31 is one of the most significant regions associated with COPD susceptibility and lung function in GWAS. In this region, the implicated causal gene HHIP has a unique epithelial expression pattern in adult human lungs, in contrast to dominant expression in fibroblasts in murine lungs. However, the mechanism underlying the species-dependent cell type-specific regulation of HHIP remains largely unknown.

METHODS

We employed snATAC-seq analysis to identify open chromatin regions within the COPD GWAS region in various human lung cell types. ChIP-quantitative PCR, reporter assays, chromatin conformation capture assays and Hi-C assays were conducted to characterize the regulatory element in this region. CRISPR/Cas9-editing was performed in BEAS-2B cells to generate single colonies with stable knockout of the regulatory element. RT-PCR and Western blot assays were used to evaluate expression of HHIP and epithelial-mesenchymal transition (EMT)-related marker genes.

FINDINGS

We identified a distal enhancer within the COPD 4q31 GWAS locus that regulates HHIP transcription at baseline and after TGFβ treatment in a SMAD3-dependent, but Hedgehog-independent manner in human bronchial epithelial cells. The distal enhancer also maintains chromatin topological domains near 4q31 locus and HHIP gene. Reduced HHIP expression led to increased EMT induced by TGFβ in human bronchial epithelial cells.

INTERPRETATION

A distal enhancer regulates HHIP expression both under homeostatic condition and upon TGFβ treatment in human bronchial epithelial cells. The interaction between HHIP and TGFβ signalling possibly contributes to COPD pathogenesis.

FUNDING

Supported by NIH grants R01HL127200, R01HL148667 and R01HL162783 (to X. Z).

Epithelial stem cells and niches in lung alveolar regeneration and diseases

Alveoli serve as the functional units of the lungs, responsible for the critical task of blood-gas exchange. Comprising type I (AT1) and type II (AT2) cells, the alveolar epithelium is continuously subject to external aggressors like pathogens and airborne particles. As such, preserving lung function requires both the homeostatic renewal and reparative regeneration of this epithelial layer. Dysfunctions in these processes contribute to various lung diseases. Recent research has pinpointed specific cell subgroups that act as potential stem or progenitor cells for the alveolar epithelium during both homeostasis and regeneration. Additionally, endothelial cells, fibroblasts, and immune cells synergistically establish a nurturing microenvironment-or "niche"-that modulates these epithelial stem cells. This review aims to consolidate the latest findings on the identities of these stem cells and the components of their niche, as well as the molecular mechanisms that govern them. Additionally, this article highlights diseases that arise due to perturbations in stem cell-niche interactions. We also discuss recent technical innovations that have catalyzed these discoveries. Specifically, this review underscores the heterogeneity, plasticity, and dynamic regulation of these stem cell-niche systems. It is our aspiration that a deeper understanding of the fundamental cellular and molecular mechanisms underlying alveolar homeostasis and regeneration will open avenues for identifying novel therapeutic targets for conditions such as chronic obstructive pulmonary disease (COPD), fibrosis, coronavirus disease 2019 (COVID-19), and lung cancer.

Single-Cell Transcriptomic Profiling Identifies Molecular Phenotypes of Newborn Human Lung Cells

While animal model studies have extensively defined the mechanisms controlling cell diversity in the developing mammalian lung, there exists a significant knowledge gap with regards to late-stage human lung development. 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. Transcriptomic profiling at the single-cell level created a cellular atlas of newborn human lungs. Frozen single-cell isolates obtained from two newborn human lungs from the LungMAP Human Tissue Core Biorepository, 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. Transcriptional interrogation of 5500 newborn human lung cells identified distinct clusters representing multiple populations of epithelial, endothelial, fibroblasts, pericytes, smooth muscle, immune cells and their gene signatures. Computational integration of data from newborn human cells and with 32,000 cells from postnatal days 1 through 10 mouse lungs generated by the LungMAP Cincinnati Research Center facilitated the identification of distinct cellular lineages among all the major cell types. Integration of the newborn human and mouse cellular transcriptomes also demonstrated cell type-specific differences in maturation states of newborn human lung cells. Specifically, newborn human lung matrix fibroblasts could be separated into those representative of younger cells (n = 393), or older cells (n = 158). Cells with each molecular profile were spatially resolved within newborn human lung tissue. This is the first comprehensive molecular map of the cellular landscape of neonatal human lung, including biomarkers for cells at distinct states of maturity.

Dictionary learning for integrative, multimodal and scalable single-cell analysis

Mapping single-cell sequencing profiles to comprehensive reference datasets provides a powerful alternative to unsupervised analysis. However, most reference datasets are constructed from single-cell RNA-sequencing data and cannot be used to annotate datasets that do not measure gene expression. Here we introduce 'bridge integration', a method to integrate single-cell datasets across modalities using a multiomic dataset as a molecular bridge. Each cell in the multiomic dataset constitutes an element in a 'dictionary', which is used to reconstruct unimodal datasets and transform them into a shared space. Our procedure accurately integrates transcriptomic data with independent single-cell measurements of chromatin accessibility, histone modifications, DNA methylation and protein levels. Moreover, we demonstrate how dictionary learning can be combined with sketching techniques to improve computational scalability and harmonize 8.6 million human immune cell profiles from sequencing and mass cytometry experiments. Our approach, implemented in version 5 of our Seurat toolkit ( http://www.satijalab.org/seurat ), broadens the utility of single-cell reference datasets and facilitates comparisons across diverse molecular modalities.

Comparative Pathogenesis of Severe Acute Respiratory Syndrome Coronaviruses

Over the last two decades the world has witnessed the global spread of two genetically related highly pathogenic coronaviruses, severe acute respiratory syndrome coronavirus (SARS-CoV) and SARS-CoV-2. However, the impact of these outbreaks differed significantly with respect to the hospitalizations and fatalities seen worldwide. While many studies have been performed recently on SARS-CoV-2, a comparative pathogenesis analysis with SARS-CoV may further provide critical insights into the mechanisms of disease that drive coronavirus-induced respiratory disease. In this review, we comprehensively describe clinical and experimental observations related to transmission and pathogenesis of SARS-CoV-2 in comparison with SARS-CoV, focusing on human, animal, and in vitro studies. By deciphering the similarities and disparities of SARS-CoV and SARS-CoV-2, in terms of transmission and pathogenesis mechanisms, we offer insights into the divergent characteristics of these two viruses. This information may also be relevant to assessing potential novel introductions of genetically related highly pathogenic coronaviruses.

Early human lung immune cell development and its role in epithelial cell fate

Studies of human lung development have focused on epithelial and mesenchymal cell types and function, but much less is known about the developing lung immune cells, even though the airways are a major site of mucosal immunity after birth. An unanswered question is whether tissue-resident immune cells play a role in shaping the tissue as it develops in utero. Here, we profiled human embryonic and fetal lung immune cells using scRNA-seq, smFISH, and immunohistochemistry. At the embryonic stage, we observed an early wave of innate immune cells, including innate lymphoid cells, natural killer cells, myeloid cells, and lineage progenitors. By the canalicular stage, we detected naive T lymphocytes expressing high levels of cytotoxicity genes and the presence of mature B lymphocytes, including B-1 cells. Our analysis suggests that fetal lungs provide a niche for full B cell maturation. Given the presence and diversity of immune cells during development, we also investigated their possible effect on epithelial maturation. We found that IL-1β drives epithelial progenitor exit from self-renewal and differentiation to basal cells in vitro. In vivo, IL-1β-producing myeloid cells were found throughout the lung and adjacent to epithelial tips, suggesting that immune cells may direct human lung epithelial development.

Single-Cell Profiling of Premature Neonate Airways Reveals a Continuum of Myeloid Differentiation

Single-cell genomic technologies hold great potential to advance our understanding of lung development and disease. A major limitation lies in accessing intact cells from primary lung tissues for profiling human airway health. Sampling methods such as endotracheal aspiration that are compatible with clinical interventions could enable longitudinal studies, the enrollment of large cohorts, and the development of novel diagnostics. To explore single-cell RNA sequencing profiling of the cell types present at birth in the airway lumen of extremely premature neonates (<28 wk gestation), we isolated cells from endotracheal aspirates collected from intubated neonates within the first hour after birth. We generated data on 10 subjects, providing a rich view of airway luminal biology at a critical developmental period. Our results show that cells present in the airways of premature neonates primarily represent a continuum of myeloid differentiation, including fetal monocytes (25% of total), intermediate myeloid populations (48%), and macrophages (2.6%). Applying trajectory analysis to the myeloid populations, we identified two trajectories consistent with the developmental stages of interstitial and alveolar macrophages, as well as a third trajectory presenting an alternative pathway bridging the distinct macrophage precursors. The three trajectories share many dynamic genes (N = 5,451), but also have distinct transcriptional changes (259 alveolar-specific, 666 interstitial-specific, and 285 bridging-specific). Overall, our results define cells isolated within the so-called "golden hour of birth" in extremely premature neonate airways, representing complex lung biology, and can be used in studies of human development and disease.

Context-aware single-cell multiome approach identified cell-type specific lung cancer susceptibility genes

Genome-wide association studies (GWAS) identified over fifty loci associated with lung cancer risk. However, the genetic mechanisms and target genes underlying these loci are largely unknown, as most risk-associated-variants might regulate gene expression in a context-specific manner. Here, we generated a barcode-shared transcriptome and chromatin accessibility map of 117,911 human lung cells from age/sex-matched ever- and never-smokers to profile context-specific gene regulation. Accessible chromatin peak detection identified cell-type-specific candidate cis-regulatory elements (cCREs) from each lung cell type. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs prioritized the variants for 68% of the GWAS loci, a subset of which was also supported by transcription factor abundance and footprinting. cCRE colocalization and single-cell based trait relevance score nominated epithelial and immune cells as the main cell groups contributing to lung cancer susceptibility. Notably, cCREs of rare proliferating epithelial cell types, such as AT2-proliferating (0.13%) and basal cells (1.8%), overlapped with CCVs, including those in TERT. A multi-level cCRE-gene linking system identified candidate susceptibility genes from 57% of lung cancer loci, including those not detected in tissue- or cell-line-based approaches. cCRE-gene linkage uncovered that adjacent genes expressed in different cell types are correlated with distinct subsets of coinherited CCVs, including JAML and MPZL3 at the 11q23.3 locus. Our data revealed the cell types and contexts where the lung cancer susceptibility genes are functional.

Multimodal deep learning approaches for single-cell multi-omics data integration

Integrating single-cell multi-omics data is a challenging task that has led to new insights into complex cellular systems. Various computational methods have been proposed to effectively integrate these rapidly accumulating datasets, including deep learning. However, despite the proven success of deep learning in integrating multi-omics data and its better performance over classical computational methods, there has been no systematic study of its application to single-cell multi-omics data integration. To fill this gap, we conducted a literature review to explore the use of multimodal deep learning techniques in single-cell multi-omics data integration, taking into account recent studies from multiple perspectives. Specifically, we first summarized different modalities found in single-cell multi-omics data. We then reviewed current deep learning techniques for processing multimodal data and categorized deep learning-based integration methods for single-cell multi-omics data according to data modality, deep learning architecture, fusion strategy, key tasks and downstream analysis. Finally, we provided insights into using these deep learning models to integrate multi-omics data and better understand single-cell biological mechanisms.

Single Cell Multiomics Identifies Cells and Genetic Networks Underlying Alveolar Capillary Dysplasia

Rationale: Alveolar capillary dysplasia with misalignment of pulmonary veins (ACDMPV) is a lethal developmental disorder of lung morphogenesis caused by insufficiency of FOXF1 (forkhead box F1) transcription factor function. The cellular and transcriptional mechanisms by which FOXF1 deficiency disrupts human lung formation are unknown. Objectives: To identify cell types, gene networks, and cell-cell interactions underlying the pathogenesis of ACDMPV. Methods: We used single-nucleus RNA and assay for transposase-accessible chromatin sequencing, immunofluorescence confocal microscopy, and RNA in situ hybridization to identify cell types and molecular networks influenced by FOXF1 in ACDMPV lungs. Measurements and Main Results: Pathogenic single-nucleotide variants and copy-number variant deletions involving the FOXF1 gene locus in all subjects with ACDMPV (n = 6) were accompanied by marked changes in lung structure, including deficient alveolar development and a paucity of pulmonary microvasculature. Single-nucleus RNA and assay for transposase-accessible chromatin sequencing identified alterations in cell number and gene expression in endothelial cells (ECs), pericytes, fibroblasts, and epithelial cells in ACDMPV lungs. Distinct cell-autonomous roles for FOXF1 in capillary ECs and pericytes were identified. Pathogenic variants involving the FOXF1 gene locus disrupt gene expression in EC progenitors, inhibiting the differentiation or survival of capillary 2 ECs and cell-cell interactions necessary for both pulmonary vasculogenesis and alveolar type 1 cell differentiation. Loss of the pulmonary microvasculature was associated with increased VEGFA (vascular endothelial growth factor A) signaling and marked expansion of systemic bronchial ECs expressing COL15A1 (collagen type XV α 1 chain). Conclusions: Distinct FOXF1 gene regulatory networks were identified in subsets of pulmonary endothelial and fibroblast progenitors, providing both cellular and molecular targets for the development of therapies for ACDMPV and other diffuse lung diseases of infancy.

Multiomic Investigations into Lung Health and Disease

Diseases of the lung account for more than 5 million deaths worldwide and are a healthcare burden. Improving clinical outcomes, including mortality and quality of life, involves a holistic understanding of the disease, which can be provided by the integration of lung multi-omics data. An enhanced understanding of comprehensive multiomic datasets provides opportunities to leverage those datasets to inform the treatment and prevention of lung diseases by classifying severity, prognostication, and discovery of biomarkers. The main objective of this review is to summarize the use of multiomics investigations in lung disease, including multiomics integration and the use of machine learning computational methods. This review also discusses lung disease models, including animal models, organoids, and single-cell lines, to study multiomics in lung health and disease. We provide examples of lung diseases where multi-omics investigations have provided deeper insight into etiopathogenesis and have resulted in improved preventative and therapeutic interventions.

Preserved perception-action integration in adolescents after a COVID-19 infection

Evidence is accumulating that the Coronavirus disease (COVID-19) can bring forth deficits in executive functioning via alterations in the dopaminergic system. Importantly, dopaminergic pathways have been shown to modulate how actions and perceptions are integrated within the brain. Such alterations in event file binding could thus underlie the cognitive deficits developing after a COVID-19 infection. We examined action-perception integration in a group of young people (11-19 years of age) that had been infected with COVID-19 before study participation (n = 34) and compared them to a group of uninfected healthy controls (n = 29) on the behavioral (i.e., task accuracy, reaction time) and neurophysiological (EEG) level using an established event file binding paradigm. Groups did not differ from each other regarding demographic variables or in reporting psychiatric symptoms. Overall, multiple lines of evidence (behavioral and neurophysiological) suggest that action-perception integration is preserved in adolescents who suffered from COVID-19 prior to study participation. Event file binding processes were intact in both groups on all levels. While cognitive impairments can occur following a COVID-19 infection, the study demonstrates that action-perception integration as one of the basic building blocks of cognition seems to be largely unaffected in adolescents with a rather mild course of the disease.

Interpreting non-coding disease-associated human variants using single-cell epigenomics

Genome-wide association studies (GWAS) have linked hundreds of thousands of sequence variants in the human genome to common traits and diseases. However, translating this knowledge into a mechanistic understanding of disease-relevant biology remains challenging, largely because such variants are predominantly in non-protein-coding sequences that still lack functional annotation at cell-type resolution. Recent advances in single-cell epigenomics assays have enabled the generation of cell type-, subtype- and state-resolved maps of the epigenome in heterogeneous human tissues. These maps have facilitated cell type-specific annotation of candidate cis-regulatory elements and their gene targets in the human genome, enhancing our ability to interpret the genetic basis of common traits and diseases.

Guided construction of single cell reference for human and mouse 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.

A transcriptional cell atlas identifies the decline in the AT2 niche in aged human lungs

Aging poses a global public health challenge, associated with molecular and physiological changes in the lungs. It increases susceptibility to acute and chronic lung diseases, yet the underlying molecular and cellular drivers in aged populations are not fully appreciated. To systematically profile the genetic changes associated with age, we present a single-cell transcriptional atlas comprising nearly half a million cells from the healthy lungs of human subjects spanning various ages, sexes, and smoking statuses. Most annotated cell lineages in aged lungs exhibit dysregulated genetic programs. Specifically, the aged alveolar epithelial cells, including both alveolar type II (AT2) and type I (AT1) cells, demonstrate loss of epithelial identities, heightened inflammaging characterized by increased expression of AP-1 transcription factor and chemokine genes, and significantly increased cellular senescence. Furthermore, the aged mesenchymal cells display a remarkable decrease in Collagen and Elastin transcription. The decline of the AT2 niche is further exacerbated by a weakened endothelial cell phenotype and a dysregulated genetic program in macrophages. These findings highlight the dysregulation observed in both AT2 stem cells and their supportive niche cells, potentially contributing to the increased susceptibility of aged populations to lung diseases.

Regionally distinct progenitor cells in the lower airway give rise to neuroendocrine and multiciliated cells in the developing human lung

Using scRNA-seq and microscopy, we describe a cell that is enriched in the lower airways of the developing human lung and identified by the unique coexpression of SCGB3A2/SFTPB/CFTR. To functionally interrogate these cells, we apply a single-cell barcode-based lineage tracing method, called CellTagging, to track the fate of SCGB3A2/SFTPB/CFTR cells during airway organoid differentiation in vitro. Lineage tracing reveals that these cells have a distinct differentiation potential from basal cells, giving rise predominantly to pulmonary neuroendocrine cells and a subset of multiciliated cells distinguished by high C6 and low MUC16 expression. Lineage tracing results are supported by studies using organoids and isolated cells from the lower noncartilaginous airway. We conclude that SCGB3A2/SFTPB/CFTR cells are enriched in the lower airways of the developing human lung and contribute to the epithelial diversity and heterogeneity in this region.

An integrated cell atlas of the lung in health and disease

Single-cell technologies have transformed our understanding of human tissues. Yet, studies typically capture only a limited number of donors and disagree on cell type definitions. Integrating many single-cell datasets can address these limitations of individual studies and capture the variability present in the population. Here we present the integrated Human Lung Cell Atlas (HLCA), combining 49 datasets of the human respiratory system into a single atlas spanning over 2.4 million cells from 486 individuals. The HLCA presents a consensus cell type re-annotation with matching marker genes, including annotations of rare and previously undescribed cell types. Leveraging the number and diversity of individuals in the HLCA, we identify gene modules that are associated with demographic covariates such as age, sex and body mass index, as well as gene modules changing expression along the proximal-to-distal axis of the bronchial tree. Mapping new data to the HLCA enables rapid data annotation and interpretation. Using the HLCA as a reference for the study of disease, we identify shared cell states across multiple lung diseases, including SPP1+ profibrotic monocyte-derived macrophages in COVID-19, pulmonary fibrosis and lung carcinoma. Overall, the HLCA serves as an example for the development and use of large-scale, cross-dataset organ atlases within the Human Cell Atlas.

Genetic Variants within SARS-CoV-2 Human Receptor Genes May Contribute to Variable Disease Outcomes in Different Ethnicities

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has evolved into a global pandemic, with an alarming infectivity and mortality rate. Studies have examined genetic effects on SARS-CoV-2 disease susceptibility and severity within Eurasian populations. These studies identified contrasting effects on the severity of disease between African populations. Genetic factors can explain some of the diversity observed within SARS-CoV-2 disease susceptibility and severity. Single nucleotide polymorphisms (SNPs) within the SARS-CoV-2 receptor genes have demonstrated detrimental and protective effects across ethnic groups. For example, the TT genotype of rs2285666 (Angiotensin-converting enzyme 2 (ACE2)) is associated with the severity of SARS-CoV-2 disease, which is found at higher frequency within Asian individuals compared to African and European individuals. In this study, we examined four SARS-CoV-2 receptors, ACE2, Transmembrane serine protease 2 (TMPRSS2), Neuropilin-1 (NRP1), and Basigin (CD147). A total of 42 SNPs located within the four receptors were reviewed: ACE2 (12), TMPRSS2 (10), BSG (CD147) (5), and NRP1 (15). These SNPs may be determining factors for the decreased disease severity observed within African individuals. Furthermore, we highlight the absence of genetic studies within the African population and emphasize the importance of further research. This review provides a comprehensive summary of specific variants within the SARS-CoV-2 receptor genes, which can offer a better understanding of the pathology of the SARS-CoV-2 pandemic and identify novel potential therapeutic targets.

Cell-Specific Mechanisms in the Heart of COVID-19 Patients

From the onset of the pandemic, evidence of cardiac involvement in acute COVID-19 abounded. Cardiac presentations ranged from arrhythmias to ischemia, myopericarditis/myocarditis, ventricular dysfunction to acute heart failure, and even cardiogenic shock. Elevated serum cardiac troponin levels were prevalent among hospitalized patients with COVID-19; the higher the magnitude of troponin elevation, the greater the COVID-19 illness severity and in-hospital death risk. Whether these consequences were due to direct SARS-CoV-2 infection of cardiac cells or secondary to inflammatory responses steered early cardiac autopsy studies. SARS-CoV-2 was reportedly detected in endothelial cells, cardiac myocytes, and within the extracellular space. However, findings were inconsistent and different methodologies had their limitations. Initial autopsy reports suggested that SARS-CoV-2 myocarditis was common, setting off studies to find and phenotype inflammatory infiltrates in the heart. Nonetheless, subsequent studies rarely detected myocarditis. Microthrombi, cardiomyocyte necrosis, and inflammatory infiltrates without cardiomyocyte damage were much more common. In vitro and ex vivo experimental platforms have assessed the cellular tropism of SARS-CoV-2 and elucidated mechanisms of viral entry into and replication within cardiac cells. Data point to pericytes as the primary target of SARS-CoV-2 in the heart. Infection of pericytes can account for the observed pericyte and endothelial cell death, innate immune response, and immunothrombosis commonly observed in COVID-19 hearts. These processes are bidirectional and synergistic, rendering a definitive order of events elusive. Single-cell/nucleus analyses of COVID-19 myocardial tissue and isolated cardiac cells have provided granular data about the cellular composition and cell type-specific transcriptomic signatures of COVID-19 and microthrombi-positive COVID-19 hearts. Still, much remains unknown and more in vivo studies are needed. This review seeks to provide an overview of the current understanding of COVID-19 cardiac pathophysiology. Cell type-specific mechanisms and the studies that provided such insights will be highlighted. Given the unprecedented pace of COVID-19 research, more mechanistic details are sure to emerge since the writing of this review. Importantly, our current knowledge offers significant clues about the cardiac pathophysiology of long COVID-19, the increased postrecovery risk of cardiac events, and thus, the future landscape of cardiovascular disease.

Enhlink infers distal and context-specific enhancer-promoter linkages

Enhancers play a crucial role in regulating gene expression and their functional status can be queried with cell type precision using using single-cell (sc)ATAC-seq. To facilitate analysis of such data, we developed Enhlink, a novel computational approach that leverages single-cell signals to infer linkages between regulatory DNA sequences, such as enhancers and promoters. Enhlink uses an ensemble strategy that integrates cell-level technical covariates to control for batch effects and biological covariates to infer robust condition-specific links and their associated p-values. It can integrate simultaneous gene expression and chromatin accessibility measurements of individual cells profiled by multi-omic experiments for increased specificity. We evaluated Enhlink using simulated and real scATAC-seq data, including those paired with physical enhancer-promoter links enumerated by promoter capture Hi-C and with multi-omic scATAC-/RNA-seq data we generated from the mouse striatum. These examples demonstrated that our method outperforms popular alternative strategies. In conjunction with eQTL analysis, Enhlink revealed a putative super-enhancer regulating key cell type-specific markers of striatal neurons. Taken together, our analyses demonstrate that Enhlink is accurate, powerful, and provides features that can lead to novel biological insights.

scRAA: the development of a robust and automatic annotation procedure for single-cell RNA sequencing data

A critical task in single-cell RNA sequencing (scRNA-Seq) data analysis is to identify cell types from heterogeneous tissues. While the majority of classification methods demonstrated high performance in scRNA-Seq annotation problems, a robust and accurate solution is desired to generate reliable outcomes for downstream analyses, for instance, marker genes identification, differentially expressed genes, and pathway analysis. It is hard to establish a universally good metric. Thus, a universally good classification method for all kinds of scenarios does not exist. In addition, reference and query data in cell classification are usually from different experimental batches, and failure to consider batch effects may result in misleading conclusions. To overcome this bottleneck, we propose a robust ensemble approach to classify cells and utilize a batch correction method between reference and query data. We simulated four scenarios that comprise simple to complex batch effect and account for varying cell-type proportions. We further tested our approach on both lung and pancreas data. We found improved prediction accuracy and robust performance across simulation scenarios and real data. The incorporation of batch effect correction between reference and query, and the ensemble approach improve cell-type prediction accuracy while maintaining robustness. We demonstrated these through simulated and real scRNA-Seq data.

Single-cell multiomic analysis identifies a HOX-PBX gene network regulating the survival of lymphangioleiomyomatosis cells

Lymphangioleiomyomatosis (LAM) is a rare, progressive lung disease that predominantly affects women. LAM cells carry TSC1/TSC2 mutations, causing mTORC1 hyperactivation and uncontrolled cell growth. mTORC1 inhibitors stabilize lung function; however, sustained efficacy requires long-term administration, and some patients fail to tolerate or respond to therapy. Although the genetic basis of LAM is known, mechanisms underlying LAM pathogenesis remain elusive. We integrated single-cell RNA sequencing and single-nuclei ATAC-seq of LAM lungs to construct a gene regulatory network controlling the transcriptional program of LAM cells. We identified activation of uterine-specific HOX-PBX transcriptional programs in pulmonary LAMCORE cells as regulators of cell survival depending upon HOXD11-PBX1 dimerization. Accordingly, blockage of HOXD11-PBX1 dimerization by HXR9 suppressed LAM cell survival in vitro and in vivo. PBX1 regulated STAT1/3, increased the expression of antiapoptotic genes, and promoted LAM cell survival in vitro. The HOX-PBX gene network provides promising targets for treatment of LAM/TSC mTORC1-hyperactive cancers.

An update in club cell biology and its potential relevance to chronic obstructive pulmonary disease

Club cells are found in human small airways where they play an important role in immune defense, xenobiotic metabolism, and repair after injury. Over the past few years, data from single-cell RNA sequencing (scRNA-seq) studies has generated new insights into club cell heterogeneity and function. In this review, we integrate findings from scRNA-seq experiments with earlier in vitro, in vivo, and microscopy studies and highlight the many ways club cells contribute to airway homeostasis. We then discuss evidence for loss of club cells or club cell products in the airways of patients with chronic obstructive pulmonary disease (COPD) and discuss potential mechanisms through which this might occur.

Gut distress and intervention via communications of SARS-CoV-2 with mucosal exposome

Acute coronavirus disease 2019 (COVID-19) has been associated with prevalent gastrointestinal distress, characterized by fecal shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA or persistent antigen presence in the gut. Using a meta-analysis, the present review addressed gastrointestinal symptoms, such as nausea, vomiting, abdominal pain, and diarrhea. Despite limited data on the gut-lung axis, viral transmission to the gut and its influence on gut mucosa and microbial community were found to be associated by means of various biochemical mechanisms. Notably, the prolonged presence of viral antigens and disrupted mucosal immunity may increase gut microbial and inflammatory risks, leading to acute pathological outcomes or post-acute COVID-19 symptoms. Patients with COVID-19 exhibit lower bacterial diversity and a higher relative abundance of opportunistic pathogens in their gut microbiota than healthy controls. Considering the dysbiotic changes during infection, remodeling or supplementation with beneficial microbial communities may counteract adverse outcomes in the gut and other organs in patients with COVID-19. Moreover, nutritional status, such as vitamin D deficiency, has been associated with disease severity in patients with COVID-19 via the regulation of the gut microbial community and host immunity. The nutritional and microbiological interventions improve the gut exposome including the host immunity, gut microbiota, and nutritional status, contributing to defense against acute or post-acute COVID-19 in the gut-lung axis.

Estradiol Augments Tumor-Induced Neutrophil Production to Promote Tumor Cell Actions in Lymphangioleiomyomatosis Models

Lymphangioleiomyomatosis (LAM) is a rare cystic lung disease caused by smooth muscle cell-like tumors containing tuberous sclerosis (TSC) gene mutations and found almost exclusively in females. Patient studies suggest LAM progression is estrogen dependent, an observation supported by in vivo mouse models. However, in vitro data using TSC-null cell lines demonstrate modest estradiol (E2) responses, suggesting E2 effects in vivo may involve pathways independent of direct tumor stimulation. We previously reported tumor-dependent neutrophil expansion and promotion of TSC2-null tumor growth in an E2-sensitive LAM mouse model. We therefore hypothesized that E2 stimulates tumor growth in part by promoting neutrophil production. Here we report that E2-enhanced lung colonization of TSC2-null cells is indeed dependent on neutrophils. We demonstrate that E2 induces granulopoiesis via estrogen receptor α in male and female bone marrow cultures. With our novel TSC2-null mouse myometrial cell line, we show that factors released from these cells drive E2-sensitive neutrophil production. Last, we analyzed single-cell RNA sequencing data from LAM patients and demonstrate the presence of tumor-activated neutrophils. Our data suggest a powerful positive feedback loop whereby E2 and tumor factors induce neutrophil expansion, which in turn intensifies tumor growth and production of neutrophil-stimulating factors, resulting in continued TSC2-null tumor growth.

Organotypic human lung bud microarrays identify BMP-dependent SARS-CoV-2 infection in lung cells

Although lung disease is the primary clinical outcome in COVID-19 patients, how SARS-CoV-2 induces lung pathology remains elusive. Here we describe a high-throughput platform to generate self-organizing and commensurate human lung buds derived from hESCs cultured on micropatterned substrates. Lung buds resemble human fetal lungs and display proximodistal patterning of alveolar and airway tissue directed by KGF. These lung buds are susceptible to infection by SARS-CoV-2 and endemic coronaviruses and can be used to track cell type-specific cytopathic effects in hundreds of lung buds in parallel. Transcriptomic comparisons of infected lung buds and postmortem tissue of COVID-19 patients identified an induction of BMP signaling pathway. BMP activity renders lung cells more susceptible to SARS-CoV-2 infection and its pharmacological inhibition impairs infection by this virus. These data highlight the rapid and scalable access to disease-relevant tissue using lung buds that recapitulate key features of human lung morphogenesis and viral infection biology.

Molecular Function and Contribution of TBX4 in Development and Disease

Over the past decade, recognition of the profound impact of the TBX4 (T-box 4) gene, which encodes a member of the evolutionarily conserved family of T-box-containing transcription factors, on respiratory diseases has emerged. The developmental importance of TBX4 is emphasized by the association of TBX4 variants with congenital disorders involving respiratory and skeletal structures; however, the exact role of TBX4 in human development remains incompletely understood. Here, we discuss the developmental, tissue-specific, and pathological TBX4 functions identified through human and animal studies and review the published TBX4 variants resulting in variable disease phenotypes. We also outline future research directions to fill the gaps in our understanding of TBX4 function and of how TBX4 disruption affects development.

Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk

Lung-function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry genome-wide association meta-analysis of lung function to date, comprising 580,869 participants, we identified 1,020 independent association signals implicating 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies for selected associated variants as well as trait and pathway-specific genetic risk scores to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies.

The lung employs an intrinsic surfactant-mediated inflammatory response for viral defense

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) causes an acute respiratory distress syndrome (ARDS) that resembles surfactant deficient RDS. Using a novel multi-cell type, human induced pluripotent stem cell (hiPSC)-derived lung organoid (LO) system, validated against primary lung cells, we found that inflammatory cytokine/chemokine production and interferon (IFN) responses are dynamically regulated autonomously within the lung following SARS-CoV-2 infection, an intrinsic defense mechanism mediated by surfactant proteins (SP). Single cell RNA sequencing revealed broad infectability of most lung cell types through canonical (ACE2) and non-canonical (endocytotic) viral entry routes. SARS-CoV-2 triggers rapid apoptosis, impairing viral dissemination. In the absence of surfactant protein B (SP-B), resistance to infection was impaired and cytokine/chemokine production and IFN responses were modulated. Exogenous surfactant, recombinant SP-B, or genomic correction of the SP-B deletion restored resistance to SARS-CoV-2 and improved viability.

Decision level integration of unimodal and multimodal single cell data with scTriangulate

Decisively delineating cell identities from uni- and multimodal single-cell datasets is complicated by diverse modalities, clustering methods, and reference atlases. We describe scTriangulate, a computational framework to mix-and-match multiple clustering results, modalities, associated algorithms, and resolutions to achieve an optimal solution. Rather than ensemble approaches which select the "consensus", scTriangulate picks the most stable solution through coalitional iteration. When evaluated on diverse multimodal technologies, scTriangulate outperforms alternative approaches to identify high-confidence cell-populations and modality-specific subtypes. Unlike existing integration strategies that rely on modality-specific joint embedding or geometric graphs, scTriangulate makes no assumption about the distributions of raw underlying values. As a result, this approach can solve unprecedented integration challenges, including the ability to automate reference cell-atlas construction, resolve clonal architecture within molecularly defined cell-populations and subdivide clusters to discover splicing-defined disease subtypes. scTriangulate is a flexible strategy for unified integration of single-cell or multimodal clustering solutions, from nearly unlimited sources.

Towards precision medicine: Omics approach for COVID-19

The coronavirus disease 2019 (COVID-19) pandemic had a devastating impact on human society. Beginning with genome surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the development of omics technologies brought a clearer understanding of the complex SARS-CoV-2 and COVID-19. Here, we reviewed how omics, including genomics, proteomics, single-cell multi-omics, and clinical phenomics, play roles in answering biological and clinical questions about COVID-19. Large-scale sequencing and advanced analysis methods facilitate COVID-19 discovery from virus evolution and severity risk prediction to potential treatment identification. Omics would indicate precise and globalized prevention and medicine for the COVID-19 pandemic under the utilization of big data capability and phenotypes refinement. Furthermore, decoding the evolution rule of SARS-CoV-2 by deep learning models is promising to forecast new variants and achieve more precise data to predict future pandemics and prevent them on time.

c-JUN-mediated transcriptional responses in lymphatic endothelial cells are required for lung fluid clearance at birth

Fluid clearance mediated by lymphatic vessels is known to be essential for lung inflation and gas-exchange function during the transition from prenatal to postnatal life, yet the molecular mechanisms that regulate lymphatic function remain unclear. Here, we profiled the molecular features of lymphatic endothelial cells (LECs) in embryonic and postnatal day (P) 0 lungs by single-cell RNA-sequencing analysis. We identified that the expression of c-JUN is transiently upregulated in P0 LECs. Conditional knockout of Jun in LECs impairs the opening of lung lymphatic vessels at birth, leading to fluid retention in the lungs and neonatal death. We further demonstrated that increased mechanical pressure induces the expression of c-JUN in LECs. c-JUN regulates the opening of lymphatic vessels by modulating the remodeling of the actin cytoskeleton in LECs. Our study established the essential regulatory function of c-JUN-mediated transcriptional responses in facilitating lung lymphatic fluid clearance at birth.

Culture impact on the transcriptomic programs of primary and iPSC-derived human alveolar type 2 cells

Dysfunction of alveolar epithelial type 2 cells (AEC2s), the facultative progenitors of lung alveoli, is implicated in pulmonary disease pathogenesis, highlighting the importance of human in vitro models. However, AEC2-like cells in culture have yet to be directly compared to their in vivo counterparts at single-cell resolution. Here, we performed head-to-head comparisons among the transcriptomes of primary (1°) adult human AEC2s, their cultured progeny, and human induced pluripotent stem cell-derived AEC2s (iAEC2s). We found each population occupied a distinct transcriptomic space with cultured AEC2s (1° and iAEC2s) exhibiting similarities to and differences from freshly purified 1° cells. Across each cell type, we found an inverse relationship between proliferative and maturation states, with preculture 1° AEC2s being most quiescent/mature and iAEC2s being most proliferative/least mature. Cultures of either type of human AEC2s did not generate detectable alveolar type 1 cells in these defined conditions; however, a subset of iAEC2s cocultured with fibroblasts acquired a transitional cell state described in mice and humans to arise during fibrosis or following injury. Hence, we provide direct comparisons of the transcriptomic programs of 1° and engineered AEC2s, 2 in vitro models that can be harnessed to study human lung health and disease.

Risk Factors of Severe COVID-19: A Review of Host, Viral and Environmental Factors

The clinical course and outcome of COVID-19 are highly variable, ranging from asymptomatic infections to severe disease and death. Understanding the risk factors of severe COVID-19 is relevant both in the clinical setting and at the epidemiological level. Here, we provide an overview of host, viral and environmental factors that have been shown or (in some cases) hypothesized to be associated with severe clinical outcomes. The factors considered in detail include the age and frailty, genetic polymorphisms, biological sex (and pregnancy), co- and superinfections, non-communicable comorbidities, immunological history, microbiota, and lifestyle of the patient; viral genetic variation and infecting dose; socioeconomic factors; and air pollution. For each category, we compile (sometimes conflicting) evidence for the association of the factor with COVID-19 outcomes (including the strength of the effect) and outline possible action mechanisms. We also discuss the complex interactions between the various risk factors.

Multi-omic association study identifies DNA methylation-mediated genotype and smoking exposure effects on lung function in children living in urban settings

Impaired lung function in early life is associated with the subsequent development of chronic respiratory disease. Most genetic associations with lung function have been identified in adults of European descent and therefore may not represent those most relevant to pediatric populations and populations of different ancestries. In this study, we performed genome-wide association analyses of lung function in a multiethnic cohort of children (n = 1,035) living in low-income urban neighborhoods. We identified one novel locus at the TDRD9 gene in chromosome 14q32.33 associated with percent predicted forced expiratory volume in one second (FEV1) (p = 2.4x10-9; βz = -0.31, 95% CI = -0.41- -0.21). Mendelian randomization and mediation analyses revealed that this genetic effect on FEV1 was partially mediated by DNA methylation levels at this locus in airway epithelial cells, which were also associated with environmental tobacco smoke exposure (p = 0.015). Promoter-enhancer interactions in airway epithelial cells revealed chromatin interaction loops between FEV1-associated variants in TDRD9 and the promoter region of the PPP1R13B gene, a stimulator of p53-mediated apoptosis. Expression of PPP1R13B in airway epithelial cells was significantly associated the FEV1 risk alleles (p = 1.3x10-5; β = 0.12, 95% CI = 0.06-0.17). These combined results highlight a potential novel mechanism for reduced lung function in urban youth resulting from both genetics and smoking exposure.

Characterizing cis-regulatory elements using single-cell epigenomics

Cell type-specific gene expression patterns and dynamics during development or in disease are controlled by cis-regulatory elements (CREs), such as promoters and enhancers. Distinct classes of CREs can be characterized by their epigenomic features, including DNA methylation, chromatin accessibility, combinations of histone modifications and conformation of local chromatin. Tremendous progress has been made in cataloguing CREs in the human genome using bulk transcriptomic and epigenomic methods. However, single-cell epigenomic and multi-omic technologies have the potential to provide deeper insight into cell type-specific gene regulatory programmes as well as into how they change during development, in response to environmental cues and through disease pathogenesis. Here, we highlight recent advances in single-cell epigenomic methods and analytical tools and discuss their readiness for human tissue profiling.

Use of Antiandrogens as Therapeutic Agents in COVID-19 Patients

COVID-19, caused by the severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), is estimated to have caused over 6.5 million deaths worldwide. The emergence of fast-evolving SARS-CoV-2 variants of concern alongside increased transmissibility and/or virulence, as well as immune and vaccine escape capabilities, highlight the urgent need for more effective antivirals to combat the disease in the long run along with regularly updated vaccine boosters. One of the early risk factors identified during the COVID-19 pandemic was that men are more likely to become infected by the virus, more likely to develop severe disease and exhibit a higher likelihood of hospitalisation and mortality rates compared to women. An association exists between SARS-CoV-2 infectiveness and disease severity with sex steroid hormones and, in particular, androgens. Several studies underlined the importance of the androgen-mediated regulation of the host protease TMPRSS2 and the cell entry protein ACE2, as well as the key role of these factors in the entry of the virus into target cells. In this context, modulating androgen signalling is a promising strategy to block viral infection, and antiandrogens could be used as a preventative measure at the pre- or early hospitalisation stage of COVID-19 disease. Different antiandrogens, including commercial drugs used to treat metastatic castration-sensitive prostate cancer and other conditions, have been tested as antivirals with varying success. In this review, we summarise the most recent updates concerning the use of antiandrogens as prophylactic and therapeutic options for COVID-19.

Does autonomous macrophage-driven inflammation promote alveolar damage in COVID-19?

SARS-CoV-2 has caused devastating effects with over 550 million infections by July 2022 and approximately 6.4 million deaths [1]. Societal and economic impacts will reverberate for years, with continuous evolution of SARS-CoV-2 as it persistently spreads through the human population as exemplified by reduced activity of vaccines and monoclonals against Omicron BA.4 or BA.5 subvariants [2]. A greater understanding of pathogenesis and more tailored therapeutic approaches are therefore essential.

Towards an artificial human lung: modelling organ-like complexity to aid mechanistic understanding

Respiratory diseases account for over 5 million deaths yearly and are a huge burden to healthcare systems worldwide. Murine models have been of paramount importance to decode human lung biology in vivo, but their genetic, anatomical, physiological and immunological differences with humans significantly hamper successful translation of research into clinical practice. Thus, to clearly understand human lung physiology, development, homeostasis and mechanistic dysregulation that may lead to disease, it is essential to develop models that accurately recreate the extraordinary complexity of the human pulmonary architecture and biology. Recent advances in micro-engineering technology and tissue engineering have allowed the development of more sophisticated models intending to bridge the gap between the native lung and its replicates in vitro Alongside advanced culture techniques, remarkable technological growth in downstream analyses has significantly increased the predictive power of human biology-based in vitro models by allowing capture and quantification of complex signals. Refined integrated multi-omics readouts could lead to an acceleration of the translational pipeline from in vitro experimental settings to drug development and clinical testing in the future. This review highlights the range and complexity of state-of-the-art lung models for different areas of the respiratory system, from nasal to large airways, small airways and alveoli, with consideration of various aspects of disease states and their potential applications, including pre-clinical drug testing. We explore how development of optimised physiologically relevant in vitro human lung models could accelerate the identification of novel therapeutics with increased potential to translate successfully from the bench to the patient's bedside.