Lung Single-Cell Signaling Interaction Map Reveals Basophil Role in Macrophage Imprinting

Integrative analysis of bulk and single-cell RNA sequencing reveals the gene expression profile and the critical signaling pathways of type II CPAM

BACKGROUD

Type II congenital pulmonary airway malformation (CPAM) is a rare pulmonary microcystic developmental malformation. Surgical excision is the primary treatment for CPAM, although maternal steroids and betamethasone have proven effective in reducing microcystic CPAM. Disturbed intercellular communication may contribute to the development of CPAM. This study aims to investigate the expression profile and analyze intercellular communication networks to identify genes potentially associated with type II CPAM pathogenesis and therapeutic targets.

METHODS

RNA sequencing (RNA-seq) was performed on samples extracted from both the cystic area and the adjacent normal tissue post-surgery in CPAM patients. Iterative weighted gene correlation network analysis (iWGCNA) was used to identify genes specifically expressed in type II CPAM. Single-cell RNA-seq (scRNA-seq) was integrated to unveil the heterogeneity in cell populations and analyze the communication and interaction within epithelial cell sub-populations.

RESULTS

A total of 2,618 differentially expressed genes were identified, primarily enriched in cilium-related biological process and inflammatory response process. Key genes such as EDN1, GPR17, FPR2, and CHRM1, involved in the G protein-coupled receptor (GPCR) signaling pathway and playing roles in cell differentiation, apoptosis, calcium homeostasis, and the immune response, were highlighted based on the protein-protein interaction network. Type II CPAM-associated modules, including ciliary function-related genes, were identified using iWGCNA. By integrating scRNA-seq data, AGR3 (related to calcium homeostasis) and SLC11A1 (immune related) were identified as the only two differently expressed genes in epithelial cells of CPAM. Cell communication analysis revealed that alveolar type 1 (AT1) and alveolar type 2 (AT2) cells were the predominant communication cells for outgoing and incoming signals in epithelial cells. The ligands and receptors between epithelial cell subtypes included COLLAGEN genes enriched in PI3K-AKT singaling and involved in epithelial to mesenchymal transition.

CONCLUSIONS

In summary, by integrating bulk RNA-seq data of type II CPAM with scRNA-seq data, the gene expression profile and critical signaling pathways such as GPCR signaling and PI3K-AKT signaling pathways were revealed. Abnormally expressed genes in these pathways may disrupt epithelial-mesenchymal transition and contribute to the development of CPAM. Given the effectiveness of prenatal treatments of microcystic CPAM using maternal steroids and maternal betamethasone administration, targeting the genes and signaling pathways involved in the development of CPAM presents a promising therapeutic strategy.

Cytokines and chemokines skin gene expression in correlation with immune cells in blood and severity in equine insect bite hypersensitivity

Background

Insect bite hypersensitivity (IBH) is the most frequent skin allergy of horses and is highly debilitating, especially in the chronic phase. IBH is caused by IgE-mediated hypersensitivity reactions to culicoides midge bites and an imbalanced immune response that reduces the welfare of affected horses.

Objective

In the present study, we investigated the pathological mechanisms of IBH, aiming to understand the immune cell modulation in acute allergic skin lesions of IBH horses with the goal of finding possible biomarkers for a diagnostic approach to monitor treatment success.

Methods

By qPCR, we quantified the gene expression of cytokines, chemokines, and immune receptors in skin punch biopsies of IBH with different severity levels and healthy horses simultaneously in tandem with the analysis of immune cell counts in the blood.

Results

Our data show an increase in blood eosinophils, monocytes, and basophils with a concomitant, significant increase in associated cytokine, chemokine, and immune cell receptor mRNA expression levels in the lesional skin of IBH horses. Moreover, IL-5Ra, CCR5, IFN-γ, and IL-31Ra were strongly associated with IBH severity, while IL-31 and IL-33 were rather associated with a milder form of IBH. In addition, our data show a strong correlation of basophil cell count in blood with IL-31Ra, IL-5, IL-5Ra, IFN-γ, HRH2, HRH4, CCR3, CCR5, IL-12b, IL-10, IL-1β, and CCL26 mRNA expression in skin punch biopsies of IBH horses.

Conclusion

In summary, several cytokines and chemokines have been found to be associated with disease severity, hence contributing to IBH pathology. These molecules can be used as potential biomarkers to monitor the onset and progression of the disease or even to evaluate and monitor the efficacy of new therapeutic treatments for IBH skin allergy. To our knowledge, this is the first study that investigated immune cells together with a large set of genes related to their biological function, including correlation to disease severity, in a large cohort of healthy and IBH horses.

Building and analyzing metacells in single-cell genomics data

The advent of high-throughput single-cell genomics technologies has fundamentally transformed biological sciences. Currently, millions of cells from complex biological tissues can be phenotypically profiled across multiple modalities. The scaling of computational methods to analyze and visualize such data is a constant challenge, and tools need to be regularly updated, if not redesigned, to cope with ever-growing numbers of cells. Over the last few years, metacells have been introduced to reduce the size and complexity of single-cell genomics data while preserving biologically relevant information and improving interpretability. Here, we review recent studies that capitalize on the concept of metacells-and the many variants in nomenclature that have been used. We further outline how and when metacells should (or should not) be used to analyze single-cell genomics data and what should be considered when analyzing such data at the metacell level. To facilitate the exploration of metacells, we provide a comprehensive tutorial on the construction and analysis of metacells from single-cell RNA-seq data ( https://github.com/GfellerLab/MetacellAnalysisTutorial ) as well as a fully integrated pipeline to rapidly build, visualize and evaluate metacells with different methods ( https://github.com/GfellerLab/MetacellAnalysisToolkit ).

Basophil differentiation, heterogeneity, and functional implications

Basophils, rare granulocytes, have long been acknowledged for their roles in type 2 immune responses. However, the mechanisms by which basophils adapt their functions to diverse mammalian microenvironments remain unclear. Recent advancements in specific research tools and single-cell-based technologies have greatly enhanced our understanding of basophils. Several studies have shown that basophils play a role in maintaining homeostasis but can also contribute to pathology in various tissues and organs, including skin, lung, and others. Here, we provide an overview of recent basophil research, including cell development, characteristics, and functions. Based on an increasing understanding of basophil biology, we suggest that the precise targeting of basophil features might be beneficial in alleviating certain pathologies such as asthma, atopic dermatitis (AD), and others.

BASOPHILS ACTIVATE PRURICEPTOR-LIKE VAGAL SENSORY NEURONS

Vagal sensory neurons convey sensations from internal organs along the vagus nerve to the brainstem. Pruriceptors are a subtype of neurons that transmit itch and induce pruritus. Despite extensive research on the molecular mechanisms of itch, studies focusing on pruriceptors in the vagal ganglia still need to be explored. In this study, we characterized vagal pruriceptor neurons by their responsiveness to pruritogens such as lysophosphatidic acid, β-alanine, chloroquine, and the cytokine oncostatin M. We discovered that lung-resident basophils produce oncostatin M and that its release can be induced by engagement of FcεRIα. Oncostatin M then sensitizes multiple populations of vagal sensory neurons, including Tac1+ and MrgprA3+ neurons in the jugular ganglia. Finally, we observed an increase in oncostatin M release in mice sensitized to the house dust mite Dermatophagoides pteronyssinus or to the fungal allergen Alternaria alternata, highlighting a novel mechanism through which basophils and vagal sensory neurons may communicate during type I hypersensitivity diseases such as allergic asthma.

The temporal progression of lung immune remodeling during breast cancer metastasis

Tumor metastasis requires systemic remodeling of distant organ microenvironments that impacts immune cell phenotypes, population structure, and intercellular communication. However, our understanding of immune phenotypic dynamics in the metastatic niche remains incomplete. Here, we longitudinally assayed lung immune transcriptional profiles in the polyomavirus middle T antigen (PyMT) and 4T1 metastatic breast cancer models from primary tumorigenesis, through pre-metastatic niche formation, to the final stages of metastatic outgrowth at single-cell resolution. Computational analyses of these data revealed a TLR-NFκB inflammatory program enacted by both peripherally derived and tissue-resident myeloid cells that correlated with pre-metastatic niche formation and mirrored CD14+ "activated" myeloid cells in the primary tumor. Moreover, we observed that primary tumor and metastatic niche natural killer (NK) cells are differentially regulated in mice and human patient samples, with the metastatic niche featuring elevated cytotoxic NK cell proportions. Finally, we identified cell-type-specific dynamic regulation of IGF1 and CCL6 signaling during metastatic progression that represents anti-metastatic immunotherapy candidate pathways.

A complex immune communication between eicosanoids and pulmonary macrophages

Respiratory viral infections represent a constant threat for human health and urge for a better understanding of the pulmonary immune response to prevent disease severity. Macrophages are at the center of pulmonary immunity, where they play a pivotal role in orchestrating beneficial and/or pathological outcomes during infection. Eicosanoids, the host bioactive lipid mediators, have re-emerged as important regulators of pulmonary immunity during respiratory viral infections. In this review, we summarize the current knowledge linking eicosanoids' and pulmonary macrophages' homeostatic and antimicrobial functions and discuss eicosanoids as emerging targets for immunotherapy in viral infection.

Apolipoprotein E controls Dectin-1-dependent development of monocyte-derived alveolar macrophages upon pulmonary β-glucan-induced inflammatory adaptation

The lung is constantly exposed to the outside world and optimal adaptation of immune responses is crucial for efficient pathogen clearance. However, mechanisms that lead to lung-associated macrophages' functional and developmental adaptation remain elusive. To reveal such mechanisms, we developed a reductionist model of environmental intranasal β-glucan exposure, allowing for the detailed interrogation of molecular mechanisms of pulmonary macrophage adaptation. Employing single-cell transcriptomics, high-dimensional imaging and flow cytometric characterization paired with in vivo and ex vivo challenge models, we reveal that pulmonary low-grade inflammation results in the development of apolipoprotein E (ApoE)-dependent monocyte-derived alveolar macrophages (ApoE+CD11b+ AMs). ApoE+CD11b+ AMs expressed high levels of CD11b, ApoE, Gpnmb and Ccl6, were glycolytic, highly phagocytic and produced large amounts of interleukin-6 upon restimulation. Functional differences were cell intrinsic, and myeloid cell-specific ApoE ablation inhibited Ly6c+ monocyte to ApoE+CD11b+ AM differentiation dependent on macrophage colony-stimulating factor secretion, promoting ApoE+CD11b+ AM cell death and thus impeding ApoE+CD11b+ AM maintenance. In vivo, β-glucan-elicited ApoE+CD11b+ AMs limited the bacterial burden of Legionella pneumophilia after infection and improved the disease outcome in vivo and ex vivo in a murine lung fibrosis model. Collectively these data identify ApoE+CD11b+ AMs generated upon environmental cues, under the control of ApoE signaling, as an essential determinant for lung adaptation enhancing tissue resilience.

IL-33 controls IL-22-dependent antibacterial defense by modulating the microbiota

IL-22 plays a critical role in defending against mucosal infections, but how IL-22 production is regulated is incompletely understood. Here, we show that mice lacking IL-33 or its receptor ST2 (IL-1RL1) were more resistant to Streptococcus pneumoniae lung infection than wild-type animals and that single-nucleotide polymorphisms in IL33 and IL1RL1 were associated with pneumococcal pneumonia in humans. The effect of IL-33 on S. pneumoniae infection was mediated by negative regulation of IL-22 production in innate lymphoid cells (ILCs) but independent of ILC2s as well as IL-4 and IL-13 signaling. Moreover, IL-33's influence on IL-22-dependent antibacterial defense was dependent on housing conditions of the mice and mediated by IL-33's modulatory effect on the gut microbiota. Collectively, we provide insight into the bidirectional crosstalk between the innate immune system and the microbiota. We conclude that both genetic and environmental factors influence the gut microbiota, thereby impacting the efficacy of antibacterial immune defense and susceptibility to pneumonia.

Novel insights into the ontogeny of basophils

Basophils are the least common granulocytes, accounting for <1% of peripheral blood leukocytes. In the last 20 years, analytical tools for mouse basophils have been developed, and we now recognize that basophils play critical roles in various immune reactions, including the development of allergic inflammation and protective immunity against parasites. Moreover, the combined use of flow cytometric analyses and knockout mice has uncovered several progenitor cells committed to basophils in mice. Recently, advancements in single-cell RNA sequencing (scRNA-seq) technologies have challenged the classical view of the differentiation of various hematopoietic cell lineages. This is also true for basophil differentiation, and studies using scRNA-seq analysis have provided novel insights into basophil differentiation, including the association of basophil differentiation with that of erythrocyte/megakaryocyte and the discovery of novel basophil progenitor cells in the mouse bone marrow. In this review, we summarize the recent findings of basophil ontogeny in both mice and humans, mainly focusing on studies using scRNA-seq analyses.

Sepsis-trained macrophages promote antitumoral tissue-resident T cells

Sepsis induces immune alterations, which last for months after the resolution of illness. The effect of this immunological reprogramming on the risk of developing cancer is unclear. Here we use a national claims database to show that sepsis survivors had a lower cumulative incidence of cancers than matched nonsevere infection survivors. We identify a chemokine network released from sepsis-trained resident macrophages that triggers tissue residency of T cells via CCR2 and CXCR6 stimulations as the immune mechanism responsible for this decreased risk of de novo tumor development after sepsis cure. While nonseptic inflammation does not provoke this network, laminarin injection could therapeutically reproduce the protective sepsis effect. This chemokine network and CXCR6 tissue-resident T cell accumulation were detected in humans with sepsis and were associated with prolonged survival in humans with cancer. These findings identify a therapeutically relevant antitumor consequence of sepsis-induced trained immunity.

How Mycobacterium tuberculosis builds a home: Single-cell analysis reveals M. tuberculosis ESX-1-mediated accumulation of anti-inflammatory macrophages in infected mouse lungs

Mycobacterium tuberculosis (MTB) infects and replicates in lung mononuclear phagocytes (MNPs) with astounding ability to evade elimination. ESX-1, a type VII secretion system, acts as a virulence determinant that contributes to MTB's ability to survive within MNPs, but its effect on MNP recruitment and/or differentiation remains unknown. Here, using single-cell RNA sequencing, we studied the role of ESX-1 in MNP heterogeneity and response in mice and murine bone marrow-derived macrophages (BMDM). We found that ESX-1 is required for MTB to recruit diverse MNP subsets with high MTB burden. Further, MTB induces an anti-inflammatory signature in MNPs and BMDM in an ESX-1 dependent manner. Similarly, spatial transcriptomics revealed an upregulation of anti-inflammatory signals in MTB lesions, where monocyte-derived macrophages concentrate near MTB-infected cells. Together, our findings suggest that MTB ESX-1 mediates the recruitment and differentiation of anti-inflammatory MNPs, which MTB can infect and manipulate for survival.

Single cell atlas of human gastric muscle immune cells and macrophage-driven changes in idiopathic gastroparesis

Gastrointestinal immune cells, particularly muscularis macrophages (MM) interact with the enteric nervous system and influence gastrointestinal motility. Here we determine the human gastric muscle immunome and its changes in patients with idiopathic gastroparesis (IG). Single cell sequencing was performed on 26,000 CD45+ cells obtained from the gastric tissue of 20 subjects. We demonstrate 11 immune cell clusters with T cells being most abundant followed by myeloid cells. The proportions of cells belonging to the 11 clusters were similar between IG and controls. However, 9/11 clusters showed 578-11,429 differentially expressed genes. In IG, MM had decreased expression of tissue-protective and microglial genes and increased the expression of monocyte trafficking and stromal activating genes. Furthermore, in IG, IL12 mediated JAK-STAT signaling involved in the activation of tissue-resident macrophages and Eph-ephrin signaling involved in monocyte chemotaxis were upregulated. Patients with IG had a greater abundance of monocyte-like cells. These data further link immune dysregulation to the pathophysiology of gastroparesis.

Comparative analysis of cell-cell communication at single-cell resolution

Inference of cell-cell communication from single-cell RNA sequencing data is a powerful technique to uncover intercellular communication pathways, yet existing methods perform this analysis at the level of the cell type or cluster, discarding single-cell-level information. Here we present Scriabin, a flexible and scalable framework for comparative analysis of cell-cell communication at single-cell resolution that is performed without cell aggregation or downsampling. We use multiple published atlas-scale datasets, genetic perturbation screens and direct experimental validation to show that Scriabin accurately recovers expected cell-cell communication edges and identifies communication networks that can be obscured by agglomerative methods. Additionally, we use spatial transcriptomic data to show that Scriabin can uncover spatial features of interaction from dissociated data alone. Finally, we demonstrate applications to longitudinal datasets to follow communication pathways operating between timepoints. Our approach represents a broadly applicable strategy to reveal the full structure of niche-phenotype relationships in health and disease.

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.

Scalable nonparametric clustering with unified marker gene selection for single-cell RNA-seq data

Clustering is commonly used in single-cell RNA-sequencing (scRNA-seq) pipelines to characterize cellular heterogeneity. However, current methods face two main limitations. First, they require user-specified heuristics which add time and complexity to bioinformatic workflows; second, they rely on post-selective differential expression analyses to identify marker genes driving cluster differences, which has been shown to be subject to inflated false discovery rates. We address these challenges by introducing nonparametric clustering of single-cell populations (NCLUSION): an infinite mixture model that leverages Bayesian sparse priors to identify marker genes while simultaneously performing clustering on single-cell expression data. NCLUSION uses a scalable variational inference algorithm to perform these analyses on datasets with up to millions of cells. By analyzing publicly available scRNA-seq studies, we demonstrate that NCLUSION (i) matches the performance of other state-of-the-art clustering techniques with significantly reduced runtime and (ii) provides statistically robust and biologically relevant transcriptomic signatures for each of the clusters it identifies. Overall, NCLUSION represents a reliable hypothesis-generating tool for understanding patterns of expression variation present in single-cell populations.

MDIC3: Matrix decomposition to infer cell-cell communication

Crosstalk among cells is vital for maintaining the biological function and intactness of systems. Most existing methods for investigating cell-cell communications are based on ligand-receptor (L-R) expression, and they focus on the study between two cells. Thus, the final communication inference results are particularly sensitive to the completeness and accuracy of the prior biological knowledge. Because existing L-R research focuses mainly on humans, most existing methods can only examine cell-cell communication for humans. As far as we know, there is currently no effective method to overcome this species limitation. Here, we propose MDIC3 (matrix decomposition to infer cell-cell communication), an unsupervised tool to investigate cell-cell communication in any species, and the results are not limited by specific L-R pairs or signaling pathways. By comparing it with existing methods for the inference of cell-cell communication, MDIC3 obtained better performance in both humans and mice.

The ontogenesis and heterogeneity of basophils

Basophils are the rarest leukocytes, but they have essential roles in protection against helminths, allergic disorders, autoimmune diseases, and some cancers. For years, the clinical significance of basophils has been neglected because of the lack of proper experimental tools to study them. The development of basophil-specific antibodies and animal models, along with genomic advances like single-cell transcriptomics, has greatly enhanced our understanding of basophil biology. Recent discoveries regarding basophils prompted us to write this review, emphasizing the basophil developmental pathway. In it, we chronologically examine the steps of basophil development in various species, which reveals the apparent advent of basophils predating IgE and basophil's IgE-independent regulatory role in primitive vertebrates. Then, we cover studies of basophil development in adult bone marrow, and compare those of murine and human basophils, introducing newly identified basophil progenitors and mature basophil subsets, as well as the transcription factors that regulate the transitions between them. Last, we discuss the heterogeneity of tissue-resident basophils, which may develop through extramedullary hematopoiesis. We expect that this review will contribute to a deeper understanding of basophil biology from the intricate aspects of basophil development and differentiation, offering valuable insights for both researchers and clinicians.

Lung single-cell RNA profiling reveals response of pulmonary capillary to sepsis-induced acute lung injury

Background

Sepsis-induced acute lung injury (ALI) poses a significant threat to human health. Endothelial cells, especially pulmonary capillaries, are the primary barriers against sepsis in the lungs. Therefore, investigating endothelial cell function is essential to understand the pathophysiological processes of sepsis-induced ALI.

Methods

We downloaded single-cell RNA-seq expression data from GEO with accession number GSE207651. The mice underwent cecal ligation and puncture (CLP) surgery, and lung tissue samples were collected at 0, 24, and 48 h. The cells were annotated using the CellMarker database and FindAllMarkers functions. GO enrichment analyses were performed using the Metascape software. Gene set enrichment Analysis (GSEA) and variation Analysis (GSVA) were performed to identify differential signaling pathways. Differential expression genes were collected with the "FindMarkers" function. The R package AUCell was used to score individual cells for pathway activities. The Cellchat package was used to explore intracellular communication.

Results

Granulocytes increased significantly as the duration of endotoxemia increased. However, the number of T cells, NK cells, and B cells declined. Pulmonary capillary cells were grouped into three sub-clusters. Capillary-3 cells were enriched in the sham group, but declined sharply in the CLP.24 group. Capillary-1 cells peaked in the CLP.24 group, while Capillary-2 cells were enriched in the CLP.48 group. Furthermore, we found that Cd74+ Capillary-3 cells mainly participated in immune interactions. Plat+ Capillary-1 and Clec1a+ Capillary-2 are involved in various physiological processes. Regarding cell-cell interactions, Plat+ Capillary-1 plays the most critical role in granulocyte adherence to capillaries during ALI. Cd74+ Capillary cells expressing high levels of major histocompatibility complex (MHC) and mainly interacted with Cd8a+ T cells in the sham group.

Conclusion

Plat+ capillaries are involved in the innate immune response through their interaction with neutrophils via ICAM-1 adhesion during endotoxemia, while Cd74+ capillaries epxressed high level of MHC proteins play a role in adaptive immune response through their interaction with T cells. However, it remains unclear whether the function of Cd74+ capillaries leans towards immunity or tolerance, and further studies are needed to confirm this.

Hyperoxia prevents the dynamic neonatal increases in lung mesenchymal cell diversity

Rapid expansion of the pulmonary microvasculature through angiogenesis drives alveolarization, the final stage of lung development that occurs postnatally and dramatically increases lung gas-exchange surface area. Disruption of pulmonary angiogenesis induces long-term structural and physiologic lung abnormalities, including bronchopulmonary dysplasia, a disease characterized by compromised alveolarization. Although endothelial cells are primary determinants of pulmonary angiogenesis, mesenchymal cells (MC) play a critical and dual role in angiogenesis and alveolarization. Therefore, we performed single cell transcriptomics and in-situ imaging of the developing lung to profile mesenchymal cells during alveolarization and in the context of lung injury. Specific mesenchymal cell subtypes were present at birth with increasing diversity during alveolarization even while expressing a distinct transcriptomic profile from more mature correlates. Hyperoxia arrested the transcriptomic progression of the MC, revealed differential cell subtype vulnerability with pericytes and myofibroblasts most affected, altered cell to cell communication, and led to the emergence of Acta1 expressing cells. These insights hold the promise of targeted treatment for neonatal lung disease, which remains a major cause of infant morbidity and mortality across the world.

Exploring Immune Cell Diversity in the Lacrimal Glands of Healthy Mice: A Single-Cell RNA-Sequencing Atlas

The lacrimal gland is responsible for maintaining the health of the ocular surface through the production of tears. However, our understanding of the immune system within the lacrimal gland is currently limited. Therefore, in this study, we utilized single-cell RNA sequencing and bioinformatic analysis to identify and analyze immune cells and molecules present in the lacrimal glands of normal mice. A total of 34,891 cells were obtained from the lacrimal glands of mice and classified into 18 distinct cell clusters using Seurat clustering. Within these cell populations, 26 different immune cell subpopulations were identified, including T cells, innate lymphocytes, macrophages, mast cells, dendritic cells, and B cells. Network analysis revealed complex cell-cell interactions between these immune cells, with particularly significant interactions observed among T cells, macrophages, plasma cells, and dendritic cells. Interestingly, T cells were found to be the main source of ligands for the Thy1 signaling pathway, while M2 macrophages were identified as the primary target of this pathway. Moreover, some of these immune cells were validated using immunohistological techniques. Collectively, these findings highlight the abundance and interactions of immune cells and provide valuable insights into the complexity of the lacrimal gland immune system and its relevance to associated diseases.

CellCommuNet: an atlas of cell-cell communication networks from single-cell RNA sequencing of human and mouse tissues in normal and disease states

Cell-cell communication, as a basic feature of multicellular organisms, is crucial for maintaining the biological functions and microenvironmental homeostasis of cells, organs, and whole organisms. Alterations in cell-cell communication contribute to many diseases, including cancers. Single-cell RNA sequencing (scRNA-seq) provides a powerful method for studying cell-cell communication by enabling the analysis of ligand-receptor interactions. Here, we introduce CellCommuNet (http://www.inbirg.com/cellcommunet/), a comprehensive data resource for exploring cell-cell communication networks in scRNA-seq data from human and mouse tissues in normal and disease states. CellCommuNet currently includes 376 single datasets from multiple sources, and 118 comparison datasets between disease and normal samples originating from the same study. CellCommuNet provides information on the strength of communication between cells and related signalling pathways and facilitates the exploration of differences in cell-cell communication between healthy and disease states. Users can also search for specific signalling pathways, ligand-receptor pairs, and cell types of interest. CellCommuNet provides interactive graphics illustrating cell-cell communication in different states, enabling differential analysis of communication strength between disease and control samples. This comprehensive database aims to be a valuable resource for biologists studying cell-cell communication networks.

Combined Host-Pathogen Fate Mapping to Investigate Lung Macrophages in Viral Infection

Macrophage identity, as defined by epigenetic, transcriptional, proteomic, and functional programs, is greatly impacted by cues originating from the microenvironment. As a consequence, immunophenotyping based on surface marker expression is established and reliable in homeostatic conditions, whereas environmental challenges, in particular infections, severely hamper the determination of identity states. This has become more evident with recent discoveries that macrophage-inherent plasticity may go beyond limits of lineage-defining immunophenotypes. Therefore, transgenic fate mapping tools, such as the phage-derived loxP-cre-system, are essential for the analysis of macrophage adaptation in the tissue under extreme environmental conditions, for example, upon encounter with pathogens. In this chapter, we describe an advanced application of the loxP-cre-system during infection. Here, the host encodes a cell type-specific cre-recombinase, while the pathogen harbors a STOP-floxed fluorescent reporter gene. As an instructive example for the versatility of the system, we demonstrate that alveolar macrophages are predominantly targeted after respiratory tract infection with mouse cytomegalovirus (MCMV). Combined host-pathogen fate mapping not only enables to distinguish between infected and non-infected (bystander) macrophages but also spurs exploration of phenotypic adaptation and tracing of cellular localization in the context of MCMV infection. Moreover, we provide a gating strategy for resolving the diversity of pulmonary immune cell populations.

An IL-4 signalling axis in bone marrow drives pro-tumorigenic myelopoiesis

Myeloid cells are known to suppress antitumour immunity1. However, the molecular drivers of immunosuppressive myeloid cell states are not well defined. Here we used single-cell RNA sequencing of human and mouse non-small cell lung cancer (NSCLC) lesions, and found that in both species the type 2 cytokine interleukin-4 (IL-4) was predicted to be the primary driver of the tumour-infiltrating monocyte-derived macrophage phenotype. Using a panel of conditional knockout mice, we found that only deletion of the IL-4 receptor IL-4Rα in early myeloid progenitors in bone marrow reduced tumour burden, whereas deletion of IL-4Rα in downstream mature myeloid cells had no effect. Mechanistically, IL-4 derived from bone marrow basophils and eosinophils acted on granulocyte-monocyte progenitors to transcriptionally programme the development of immunosuppressive tumour-promoting myeloid cells. Consequentially, depletion of basophils profoundly reduced tumour burden and normalized myelopoiesis. We subsequently initiated a clinical trial of the IL-4Rα blocking antibody dupilumab2-5 given in conjunction with PD-1/PD-L1 checkpoint blockade in patients with relapsed or refractory NSCLC who had progressed on PD-1/PD-L1 blockade alone (ClinicalTrials.gov identifier NCT05013450 ). Dupilumab supplementation reduced circulating monocytes, expanded tumour-infiltrating CD8 T cells, and in one out of six patients, drove a near-complete clinical response two months after treatment. Our study defines a central role for IL-4 in controlling immunosuppressive myelopoiesis in cancer, identifies a novel combination therapy for immune checkpoint blockade in humans, and highlights cancer as a systemic malady that requires therapeutic strategies beyond the primary disease site.

Inflammation in Prostate Cancer: Exploring the Promising Role of Phenolic Compounds as an Innovative Therapeutic Approach

Prostate cancer (PCa) remains a significant global health concern, being a major cause of cancer morbidity and mortality worldwide. Furthermore, profound understanding of the disease is needed. Prostate inflammation caused by external or genetic factors is a central player in prostate carcinogenesis. However, the mechanisms underlying inflammation-driven PCa remain poorly understood. This review dissects the diagnosis methods for PCa and the pathophysiological mechanisms underlying the disease, clarifying the dynamic interplay between inflammation and leukocytes in promoting tumour development and spread. It provides updates on recent advances in elucidating and treating prostate carcinogenesis, and opens new insights for the use of bioactive compounds in PCa. Polyphenols, with their noteworthy antioxidant and anti-inflammatory properties, along with their synergistic potential when combined with conventional treatments, offer promising prospects for innovative therapeutic strategies. Evidence from the use of polyphenols and polyphenol-based nanoparticles in PCa revealed their positive effects in controlling tumour growth, proliferation, and metastasis. By consolidating the diverse features of PCa research, this review aims to contribute to increased understanding of the disease and stimulate further research into the role of polyphenols and polyphenol-based nanoparticles in its management.

Lymphatic muscle cells are unique cells that undergo aging induced changes

Lymphatic muscle cells (LMCs) within the wall of collecting lymphatic vessels exhibit tonic and autonomous phasic contractions, which drive active lymph transport to maintain tissue-fluid homeostasis and support immune surveillance. Damage to LMCs disrupts lymphatic function and is related to various diseases. Despite their importance, knowledge of the transcriptional signatures in LMCs and how they relate to lymphatic function in normal and disease contexts is largely missing. We have generated a comprehensive transcriptional single-cell atlas-including LMCs-of collecting lymphatic vessels in mouse dermis at various ages. We identified genes that distinguish LMCs from other types of muscle cells, characterized the phenotypical and transcriptomic changes in LMCs in aged vessels, and uncovered a pro-inflammatory microenvironment that suppresses the contractile apparatus in advanced-aged LMCs. Our findings provide a valuable resource to accelerate future research for the identification of potential drug targets on LMCs to preserve lymphatic vessel function as well as supporting studies to identify genetic causes of primary lymphedema currently with unknown molecular explanation.

Sctensor detects many-to-many cell-cell interactions from single cell RNA-sequencing data

BACKGROUND

Complex biological systems are described as a multitude of cell-cell interactions (CCIs). Recent single-cell RNA-sequencing studies focus on CCIs based on ligand-receptor (L-R) gene co-expression but the analytical methods are not appropriate to detect many-to-many CCIs.

RESULTS

In this work, we propose scTensor, a novel method for extracting representative triadic relationships (or hypergraphs), which include ligand-expression, receptor-expression, and related L-R pairs.

CONCLUSIONS

Through extensive studies with simulated and empirical datasets, we have shown that scTensor can detect some hypergraphs that cannot be detected using conventional CCI detection methods, especially when they include many-to-many relationships. scTensor is implemented as a freely available R/Bioconductor package.

Macrophage-driven cardiac inflammation and healing: insights from homeostasis and myocardial infarction

Early and prompt reperfusion therapy has markedly improved the survival rates among patients enduring myocardial infarction (MI). Nonetheless, the resulting adverse remodeling and the subsequent onset of heart failure remain formidable clinical management challenges and represent a primary cause of disability in MI patients worldwide. Macrophages play a crucial role in immune system regulation and wield a profound influence over the inflammatory repair process following MI, thereby dictating the degree of myocardial injury and the subsequent pathological remodeling. Despite numerous previous biological studies that established the classical polarization model for macrophages, classifying them as either M1 pro-inflammatory or M2 pro-reparative macrophages, this simplistic categorization falls short of meeting the precision medicine standards, hindering the translational advancement of clinical research. Recently, advances in single-cell sequencing technology have facilitated a more profound exploration of macrophage heterogeneity and plasticity, opening avenues for the development of targeted interventions to address macrophage-related factors in the aftermath of MI. In this review, we provide a summary of macrophage origins, tissue distribution, classification, and surface markers. Furthermore, we delve into the multifaceted roles of macrophages in maintaining cardiac homeostasis and regulating inflammation during the post-MI period.

Single-nuclei RNA-seq reveals skin cell responses to Aeromonas hydrophila infection in Chinese longsnout catfish Leiocassis longirostris

As the primary natural barrier that protects against adverse environmental conditions, the skin plays a crucial role in the innate immune response of fish, particularly in relation to bacterial infections. However, due to the diverse functionality and intricate anatomical and cellular composition of the skin, deciphering the immune response of the host is a challenging task. In this study, single nuclei RNA-sequencing (snRNA-seq) was performed on skin biopsies obtained from Chinese longsnout catfish (Leiocassis longirostris), comparing Aeromonas hydrophila-infected subjects to healthy control subjects. A total of 19,581 single nuclei cells were sequenced using 10x Genomics (10,400 in the control group and 9,181 in the treated group). Based on expressed unique transcriptional profiles, 33 cell clusters were identified and classified into 12 cell types including keratinocyte (KC), fibroblast (FB), endothelial cells (EC), secretory cells (SC), immune cells, smooth muscle cells (SMC), and other cells such as pericyte (PC), brush cell (BC), red blood cell (RBC), neuroendocrine cell (NDC), neuron cells (NC), and melanocyte (MC). Among these, three clusters of KCs, namely, KC1, KC2, and KC5 exhibited significant expansion after A. hydrophila infection. Analysis of pathway enrichment revealed that KC1 was primarily involved in environmental signal transduction, KC2 was primarily involved in endocrine function, and KC5 was primarily involved in metabolism. Finally, our findings suggest that neutrophils may play a crucial role in combating A. hydrophila infections. In summary, this study not only provides the first detailed comprehensive map of all cell types present in the skin of teleost fish but also sheds light on the immune response mechanism of the skin following A. hydrophila infection in Chinese longsnout catfish.

Th2-dependent disappearance and phenotypic conversion of mouse alveolar macrophages

Alveolar macrophages (alvMs) play an important role for maintenance of lung function by constant removal of cellular debris in the alveolar space. They further contribute to defense against microbial or viral infections and limit tissue damage during acute lung injury. alvMs arise from embryonic progenitor cells, seed the alveoli before birth, and have life-long self-renewing capacity. However, recruited monocytes may also help to restore the alvM population after depletion caused by toxins or influenza virus infection. At present, the population dynamics and cellular plasticity of alvMs during allergic lung inflammation is poorly defined. To address this point, we used a mouse model of Aspergillus fumigatus-induced allergic lung inflammation and observed that Th2-derived IL-4 and IL-13 caused almost complete disappearance of alvMs. This effect required STAT6 expression in alvMs and also occurred in various other settings of type 2 immunity-mediated lung inflammation or administration of IL-4 complexes to the lung. In addition, Th2 cells promoted conversion of alvMs to alternatively activated macrophages and multinucleated giant cells. Given the well-established role of alvMs for maintenance of lung function, this process may have implications for resolution of inflammation and tissue homeostasis in allergic asthma.

Defining and identifying cell sub-crosstalk pairs for characterizing cell-cell communication patterns

Current cell-cell communication analysis focuses on quantifying intercellular interactions at cell type level. In the tissue microenvironment, one type of cells could be divided into multiple cell subgroups that function differently and communicate with other cell types or subgroups via different ligand-receptor-mediated signaling pathways. Given two cell types, we define a cell sub-crosstalk pair (CSCP) as a combination of two cell subgroups with strong and similar intercellular crosstalk signals and identify CSCPs based on coupled non-negative matrix factorization. Using single-cell spatial transcriptomics data of mouse olfactory bulb and visual cortex, we find that cells of different types within CSCPs are significantly spatially closer with each other than those in the whole single-cell spatial map. To demonstrate the utility of CSCPs, we apply 13 cell-cell communication analysis methods to sampled single-cell transcriptomics datasets at CSCP level and reveal ligand-receptor interactions masked at cell type level. Furthermore, by analyzing single-cell transcriptomics data from 29 breast cancer patients with different immunotherapy responses, we find that CSCPs are useful predictive features to discriminate patients responding to anti-PD-1 therapy from non-responders. Taken together, partitioning a cell type pair into CSCPs enables fine-grained characterization of cell-cell communication in tissue and tumor microenvironments.

A single-cell atlas of West African lungfish respiratory system reveals evolutionary adaptations to terrestrialization

The six species of lungfish possess both lungs and gills and are the closest extant relatives of tetrapods. Here, we report a single-cell transcriptome atlas of the West African lungfish (Protopterus annectens). This species manifests the most extreme form of terrestrialization, a life history strategy to survive dry periods that can last for years, characterized by dormancy and reversible adaptive changes of the gills and lungs. Our atlas highlights the cell type diversity of the West African lungfish, including gene expression consistent with phenotype changes of terrestrialization. Comparison with terrestrial tetrapods and ray-finned fishes reveals broad homology between the swim bladder and lung cell types as well as shared and idiosyncratic changes of the external gills of the West African lungfish and the internal gills of Atlantic salmon. The single-cell atlas presented here provides a valuable resource for further exploration of the respiratory system evolution in vertebrates and the diversity of lungfish terrestrialization.

Deciphering ligand-receptor-mediated intercellular communication based on ensemble deep learning and the joint scoring strategy from single-cell transcriptomic data

BACKGROUND

Cell-cell communication in a tumor microenvironment is vital to tumorigenesis, tumor progression and therapy. Intercellular communication inference helps understand molecular mechanisms of tumor growth, progression and metastasis.

METHODS

Focusing on ligand-receptor co-expressions, in this study, we developed an ensemble deep learning framework, CellComNet, to decipher ligand-receptor-mediated cell-cell communication from single-cell transcriptomic data. First, credible LRIs are captured by integrating data arrangement, feature extraction, dimension reduction, and LRI classification based on an ensemble of heterogeneous Newton boosting machine and deep neural network. Next, known and identified LRIs are screened based on single-cell RNA sequencing (scRNA-seq) data in certain tissues. Finally, cell-cell communication is inferred by incorporating scRNA-seq data, the screened LRIs, a joint scoring strategy that combines expression thresholding and expression product of ligands and receptors.

RESULTS

The proposed CellComNet framework was compared with four competing protein-protein interaction prediction models (PIPR, XGBoost, DNNXGB, and OR-RCNN) and obtained the best AUCs and AUPRs on four LRI datasets, elucidating the optimal LRI classification ability. CellComNet was further applied to analyze intercellular communication in human melanoma and head and neck squamous cell carcinoma (HNSCC) tissues. The results demonstrate that cancer-associated fibroblasts highly communicate with melanoma cells and endothelial cells strong communicate with HNSCC cells.

CONCLUSIONS

The proposed CellComNet framework efficiently identified credible LRIs and significantly improved cell-cell communication inference performance. We anticipate that CellComNet can contribute to anticancer drug design and tumor-targeted therapy.

A Comparison of Cell-Cell Interaction Prediction Tools Based on scRNA-seq Data

Computational prediction of cell-cell interactions (CCIs) is becoming increasingly important for understanding disease development and progression. We present a benchmark study of available CCI prediction tools based on single-cell RNA sequencing (scRNA-seq) data. By comparing prediction outputs with a manually curated gold standard for idiopathic pulmonary fibrosis (IPF), we evaluated prediction performance and processing time of several CCI prediction tools, including CCInx, CellChat, CellPhoneDB, iTALK, NATMI, scMLnet, SingleCellSignalR, and an ensemble of tools. According to our results, CellPhoneDB and NATMI are the best performer CCI prediction tools, among the ones analyzed, when we define a CCI as a source-target-ligand-receptor tetrad. In addition, we recommend specific tools according to different types of research projects and discuss the possible future paths in the field.

Liver in infections: a single-cell and spatial transcriptomics perspective

The liver is an immune organ that plays a vital role in the detection, capture, and clearance of pathogens and foreign antigens that invade the human body. During acute and chronic infections, the liver transforms from a tolerant to an active immune state. The defence mechanism of the liver mainly depends on a complicated network of intrahepatic and translocated immune cells and non-immune cells. Therefore, a comprehensive liver cell atlas in both healthy and diseased states is needed for new therapeutic target development and disease intervention improvement. With the development of high-throughput single-cell technology, we can now decipher heterogeneity, differentiation, and intercellular communication at the single-cell level in sophisticated organs and complicated diseases. In this concise review, we aimed to summarise the advancement of emerging high-throughput single-cell technologies and re-define our understanding of liver function towards infections, including hepatitis B virus, hepatitis C virus, Plasmodium, schistosomiasis, endotoxemia, and corona virus disease 2019 (COVID-19). We also unravel previously unknown pathogenic pathways and disease mechanisms for the development of new therapeutic targets. As high-throughput single-cell technologies mature, their integration into spatial transcriptomics, multiomics, and clinical data analysis will aid in patient stratification and in developing effective treatment plans for patients with or without liver injury due to infectious diseases.

Signaling is the pathway to macrophage function

Tissue and inflammatory contexts are well appreciated to shape macrophage function to promote health or disease. However, there has been minimal progress towards understanding how these contexts modify signaling-to-transcription networks. Integration of mechanistic modeling and data-driven approaches will be crucial for investigating how cell state impacts macrophage decision-making.

The Neonatal Immune System and Respiratory Pathogens

Neonates are more susceptible to some pathogens, particularly those that cause infection in the respiratory tract. This is often attributed to an incompletely developed immune system, but recent work demonstrates effective neonatal immune responses to some infection. The emerging view is that neonates have a distinctly different immune response that is well-adapted to deal with unique immunological challenges of the transition from a relatively sterile uterus to a microbe-rich world, tending to suppress potentially dangerous inflammatory responses. Problematically, few animal models allow a mechanistic examination of the roles and effects of various immune functions in this critical transition period. This limits our understanding of neonatal immunity, and therefore our ability to rationally design and develop vaccines and therapeutics to best protect newborns. This review summarizes what is known of the neonatal immune system, focusing on protection against respiratory pathogens and describes challenges of various animal models. Highlighting recent advances in the mouse model, we identify knowledge gaps to be addressed.

Basophils beyond allergic and parasitic diseases

Basophils bind IgE via FcεRI-αβγ2, which they uniquely share only with mast cells. In doing so, they can rapidly release mediators that are hallmark of allergic disease. This fundamental similarity, along with some morphological features shared by the two cell types, has long brought into question the biological significance that basophils mediate beyond that of mast cells. Unlike mast cells, which mature and reside in tissues, basophils are released into circulation from the bone marrow (constituting 1% of leukocytes), only to infiltrate tissues under specific inflammatory conditions. Evidence is emerging that basophils mediate non-redundant roles in allergic disease and, unsuspectingly, are implicated in a variety of other pathologies [e.g., myocardial infarction, autoimmunity, chronic obstructive pulmonary disease, fibrosis, cancer, etc.]. Recent findings strengthen the notion that these cells mediate protection from parasitic infections, whereas related studies implicate basophils promoting wound healing. Central to these functions is the substantial evidence that human and mouse basophils are increasingly implicated as important sources of IL-4 and IL-13. Nonetheless, much remains unclear regarding the role of basophils in pathology vs. homeostasis. In this review, we discuss the dichotomous (protective and/or harmful) roles of basophils in a wide spectrum of non-allergic disorders.

IL-4 and IL-13: Regulators and Effectors of Wound Repair

Type 2 immunity mediates protective responses to helminths and pathological responses to allergens, but it also has broad roles in the maintenance of tissue integrity, including wound repair. Type 2 cytokines are known to promote fibrosis, an overzealous repair response, but their contribution to healthy wound repair is less well understood. This review discusses the evidence that the canonical type 2 cytokines, IL-4 and IL-13, are integral to the tissue repair process through two main pathways. First, essential for the progression of effective tissue repair, IL-4 and IL-13 suppress the initial inflammatory response to injury. Second, these cytokines regulate how the extracellular matrix is modified, broken down, and rebuilt for effective repair. IL-4 and/or IL-13 amplifies multiple aspects of the tissue repair response, but many of these pathways are highly redundant and can be induced by other signals. Therefore, the exact contribution of IL-4Rα signaling remains difficult to unravel.

scTenifoldXct: A semi-supervised method for predicting cell-cell interactions and mapping cellular communication graphs

We present scTenifoldXct, a semi-supervised computational tool for detecting ligand-receptor (LR)-mediated cell-cell interactions and mapping cellular communication graphs. Our method is based on manifold alignment, using LR pairs as inter-data correspondences to embed ligand and receptor genes expressed in interacting cells into a unified latent space. Neural networks are employed to minimize the distance between corresponding genes while preserving the structure of gene regression networks. We apply scTenifoldXct to real datasets for testing and demonstrate that our method detects interactions with high consistency compared with other methods. More importantly, scTenifoldXct uncovers weak but biologically relevant interactions overlooked by other methods. We also demonstrate how scTenifoldXct can be used to compare different samples, such as healthy vs. diseased and wild type vs. knockout, to identify differential interactions, thereby revealing functional implications associated with changes in cellular communication status.

Perinatal origins of bronchopulmonary dysplasia-deciphering normal and impaired lung development cell by cell

Bronchopulmonary dysplasia (BPD) is a multifactorial disease occurring as a consequence of premature birth, as well as antenatal and postnatal injury to the developing lung. BPD morbidity and severity depend on a complex interplay between prenatal and postnatal inflammation, mechanical ventilation, and oxygen therapy as well as associated prematurity-related complications. These initial hits result in ill-explored aberrant immune and reparative response, activation of pro-fibrotic and anti-angiogenic factors, which further perpetuate the injury. Histologically, the disease presents primarily by impaired lung development and an arrest in lung microvascular maturation. Consequently, BPD leads to respiratory complications beyond the neonatal period and may result in premature aging of the lung. While the numerous prenatal and postnatal stimuli contributing to BPD pathogenesis are relatively well known, the specific cell populations driving the injury, as well as underlying mechanisms are still not well understood. Recently, an effort to gain a more detailed insight into the cellular composition of the developing lung and its progenitor populations has unfold. Here, we provide an overview of the current knowledge regarding perinatal origin of BPD and discuss underlying mechanisms, as well as novel approaches to study the perturbed lung development.

Novel insights into Hodgkin lymphoma biology by single-cell analysis

The emergence and rapid development of single-cell technologies mark a paradigm shift in cancer research. Various technology implementations represent powerful tools to understand cellular heterogeneity, identify minor cell populations that were previously hard to detect and define, and make inferences about cell-to-cell interactions at single-cell resolution. Applied to lymphoma, recent advances in single-cell RNA sequencing have broadened opportunities to delineate previously underappreciated heterogeneity of malignant cell differentiation states and presumed cell of origin, and to describe the composition and cellular subsets in the ecosystem of the tumor microenvironment (TME). Clinical deployment of an expanding armamentarium of immunotherapy options that rely on targets and immune cell interactions in the TME emphasizes the requirement for a deeper understanding of immune biology in lymphoma. In particular, classic Hodgkin lymphoma (CHL) can serve as a study paradigm because of its unique TME, featuring infrequent tumor cells among numerous nonmalignant immune cells with significant interpatient and intrapatient variability. Synergistic to advances in single-cell sequencing, multiplexed imaging techniques have added a new dimension to describing cellular cross talk in various lymphoma entities. Here, we comprehensively review recent progress using novel single-cell technologies with an emphasis on the TME biology of CHL as an application field. The described technologies, which are applicable to peripheral blood, fresh tissues, and formalin-fixed samples, hold the promise to accelerate biomarker discovery for novel immunotherapeutic approaches and to serve as future assay platforms for biomarker-informed treatment selection, including immunotherapies.

Single-Cell RNA Sequencing Analysis of Gene Regulatory Network Changes in the Development of Lung Adenocarcinoma

Lung cancer is a highly heterogeneous disease. Cancer cells and other cells within the tumor microenvironment interact to determine disease progression, as well as response to or escape from treatment. Understanding the regulatory relationship between cancer cells and their tumor microenvironment in lung adenocarcinoma is of great significance for exploring the heterogeneity of the tumor microenvironment and its role in the genesis and development of lung adenocarcinoma. This work uses public single-cell transcriptome data (distant normal, nLung; early LUAD, tLung; advanced LUAD, tL/B), to draft a cell map of lung adenocarcinoma from onset to progression, and provide a cell-cell communication view of lung adenocarcinoma in the different disease stages. Based on the analysis of cell populations, it was found that the proportion of macrophages was significantly reduced in the development of lung adenocarcinoma, and patients with lower proportions of macrophages exhibited poor prognosis. We therefore constructed a process to screen an intercellular gene regulatory network that reduces any error generated by single cell communication analysis and increases the credibility of selected cell communication signals. Based on the key regulatory signals in the macrophage-tumor cell regulatory network, we performed a pseudotime analysis of the macrophages and found that signal molecules (TIMP1, VEGFA, SPP1) are highly expressed in immunosuppression-associated macrophages. These molecules were also validated using an independent dataset and were significantly associated with poor prognosis. Our study provides an effective method for screening the key regulatory signals in the tumor microenvironment and the selected signal molecules may serve as a reference to guide the development of diagnostic biomarkers for risk stratification and therapeutic targets for lung adenocarcinoma.

Shaping of the alveolar landscape by respiratory infections and long-term consequences for lung immunity

Respiratory infections and especially viral infections, along with other extrinsic environmental factors, have been shown to profoundly affect macrophage populations in the lung. In particular, alveolar macrophages (AMs) are important sentinels during respiratory infections and their disappearance opens a niche for recruited monocytes (MOs) to differentiate into resident macrophages. Although this topic is still the focus of intense debate, the phenotype and function of AMs that recolonize the niche after an inflammatory insult, such as an infection, appear to be dictated in part by their origin, but also by local and/or systemic changes that may be imprinted at the epigenetic level. Phenotypic alterations following respiratory infections have the potential to shape lung immunity for the long-term, leading to beneficial responses such as protection against allergic airway inflammation or against other infections, but also to detrimental responses when associated with the development of immunopathologies. This review reports the persistence of virus-induced functional alterations in lung macrophages, and discusses the importance of this imprinting in explaining inter-individual and lifetime immune variation.

Role of GM-CSF in lung balance and disease

Granulocyte-macrophage colony-stimulating factor (GM-CSF) is a hematopoietic growth factor originally identified as a stimulus that induces the differentiation of bone marrow progenitor cells into granulocytes and macrophages. GM-CSF is now considered to be a multi-origin and pleiotropic cytokine. GM-CSF receptor signals activate JAK2 and induce nuclear signals through the JAK-STAT, MAPK, PI3K, and other pathways. In addition to promoting the metabolism of pulmonary surfactant and the maturation and differentiation of alveolar macrophages, GM-CSF plays a key role in interstitial lung disease, allergic lung disease, alcoholic lung disease, and pulmonary bacterial, fungal, and viral infections. This article reviews the latest knowledge on the relationship between GM-CSF and lung balance and lung disease, and indicates that there is much more to GM-CSF than its name suggests.

MicroRNA-223 Dampens Pulmonary Inflammation during Pneumococcal Pneumonia

Community-acquired pneumonia remains a major contributor to global communicable disease-mediated mortality. Neutrophils play a leading role in trying to contain bacterial lung infection, but they also drive detrimental pulmonary inflammation, when dysregulated. Here we aimed at understanding the role of microRNA-223 in orchestrating pulmonary inflammation during pneumococcal pneumonia. Serum microRNA-223 was measured in patients with pneumococcal pneumonia and in healthy subjects. Pulmonary inflammation in wild-type and microRNA-223-knockout mice was assessed in terms of disease course, histopathology, cellular recruitment and evaluation of inflammatory protein and gene signatures following pneumococcal infection. Low levels of serum microRNA-223 correlated with increased disease severity in pneumococcal pneumonia patients. Prolonged neutrophilic influx into the lungs and alveolar spaces was detected in pneumococci-infected microRNA-223-knockout mice, possibly accounting for aggravated histopathology and acute lung injury. Expression of microRNA-223 in wild-type mice was induced by pneumococcal infection in a time-dependent manner in whole lungs and lung neutrophils. Single-cell transcriptome analyses of murine lungs revealed a unique profile of antimicrobial and cellular maturation genes that are dysregulated in neutrophils lacking microRNA-223. Taken together, low levels of microRNA-223 in human pneumonia patient serum were associated with increased disease severity, whilst its absence provoked dysregulation of the neutrophil transcriptome in murine pneumococcal pneumonia.

Developmental diversity and unique sensitivity to injury of lung endothelial subtypes during postnatal growth

At birth, the lung is still immature, heightening susceptibility to injury but enhancing regenerative capacity. Angiogenesis drives postnatal lung development. Therefore, we profiled the transcriptional ontogeny and sensitivity to injury of pulmonary endothelial cells (EC) during early postnatal life. Although subtype speciation was evident at birth, immature lung EC exhibited transcriptomes distinct from mature counterparts, which progressed dynamically over time. Gradual, temporal changes in aerocyte capillary EC (CAP2) contrasted with more marked alterations in general capillary EC (CAP1) phenotype, including distinct CAP1 present only in the early alveolar lung expressing Peg3, a paternally imprinted transcription factor. Hyperoxia, an injury that impairs angiogenesis induced both common and unique endothelial gene signatures, dysregulated capillary EC crosstalk, and suppressed CAP1 proliferation while stimulating venous EC proliferation. These data highlight the diversity, transcriptomic evolution, and pleiotropic responses to injury of immature lung EC, possessing broad implications for lung development and injury across the lifespan.

Influence of lipid composition of messenger RNA-loaded lipid nanoparticles on the protein expression via intratracheal administration in mice

Intratracheal (i.t.) administration, which takes advantage of the specific structure of the respiratory system, can effectively deliver nanoparticles to the lung. Much remains unknown about the i.t. administration of messenger RNA (mRNA)-lipid nanoparticles (LNPs) and the effect of lipid composition. In this study, we administered minute amounts of mRNA-LNP solutions into mice intratracheally and investigated the effect of lipid composition on protein expression in the lungs. We first validated higher protein expression with mRNA-LNP compared to that with mRNA-PEI complex and naked mRNA. Then, we evaluated the influence of lipid composition of LNPs on the protein expression and found that: 1) decreasing the PEG molarity from 1.5% to 0.5% could significantly increase the protein expression; 2) replacing DMG-PEG with DSG-PEG could slightly increase the protein expression; 3) using DOPE instead of DSPC could increase protein expression by an order of magnitude. We successfully prepared an mRNA-LNP with optimal lipid compositions that led to robust protein expression following i.t. administration, thus providing meaningful insights into advanced development of mRNA-LNPs for therapeutic i.t. administration.

Deep learning in spatial transcriptomics: Learning from the next next-generation sequencing

Spatial transcriptomics (ST) technologies are rapidly becoming the extension of single-cell RNA sequencing (scRNAseq), holding the potential of profiling gene expression at a single-cell resolution while maintaining cellular compositions within a tissue. Having both expression profiles and tissue organization enables researchers to better understand cellular interactions and heterogeneity, providing insight into complex biological processes that would not be possible with traditional sequencing technologies. Data generated by ST technologies are inherently noisy, high-dimensional, sparse, and multi-modal (including histological images, count matrices, etc.), thus requiring specialized computational tools for accurate and robust analysis. However, many ST studies currently utilize traditional scRNAseq tools, which are inadequate for analyzing complex ST datasets. On the other hand, many of the existing ST-specific methods are built upon traditional statistical or machine learning frameworks, which have shown to be sub-optimal in many applications due to the scale, multi-modality, and limitations of spatially resolved data (such as spatial resolution, sensitivity, and gene coverage). Given these intricacies, researchers have developed deep learning (DL)-based models to alleviate ST-specific challenges. These methods include new state-of-the-art models in alignment, spatial reconstruction, and spatial clustering, among others. However, DL models for ST analysis are nascent and remain largely underexplored. In this review, we provide an overview of existing state-of-the-art tools for analyzing spatially resolved transcriptomics while delving deeper into the DL-based approaches. We discuss the new frontiers and the open questions in this field and highlight domains in which we anticipate transformational DL applications.