Single-cell transcriptome identifies FCGR3B upregulated subtype of alveolar macrophages in patients with critical COVID-19

Application of Macrophage Subtype Analysis in Acute Lung Injury/Acute Respiratory Distress Syndrome

Acute lung injury (ALI)/acute respiratory distress syndrome (ARDS) is a common critical illness. Supportive therapy is still the main strategy for ALI/ARDS. Macrophages are the predominant immune cells in the lungs and play a pivotal role in maintaining homeostasis, regulating metabolism, and facilitating tissue repair. During ALI/ARDS, these versatile cells undergo polarization into distinct subtypes with significant variations in transcriptional profiles, developmental trajectory, phenotype, and functionality. This review discusses developments in the analysis of alveolar macrophage subtypes in the study of ALI/ARDS, and the potential value of targeting new macrophage subtypes in the diagnosis, prognostic evaluation, and treatment of ALI/ARDS.

Single-cell Profiling of Intrahepatic Immune Cells Reveals an Expansion of Tissue-resident Cytotoxic CD4+ T Lymphocyte Subset Associated With Pathogenesis of Alcoholic-associated Liver Diseases

BACKGROUND & AIMS

The immunological mechanisms underpinning the pathogenesis of alcoholic-associated liver disease (ALD) remain incompletely elucidated. This study aims to explore the transcriptomic profiles of hepatic immune cells in ALD compared with healthy individuals and those with metabolic dysfunction-associated steatotic liver disease (MASLD).

METHODS

We utilized single-cell RNA sequencing to analyze liver samples from healthy subjects and patients with MASLD and ALD, focusing on the immune cell landscapes within the liver. Key alterations in immune cell subsets were further validated using liver biopsy samples from additional patient cohorts.

RESULTS

We observed a significant accumulation of CD4+ T cells in livers of patients with ALD, surpassing the prevalence of CD8+ T cells, in contrast to patients with MASLD and healthy counterparts, whereas natural killer (NK) cells and γδT cells exhibited reduced intrahepatic infiltration. In-depth transcriptional and developmental trajectory analyses unveiled that a distinct CD4+ subset characterized by granzyme K (GZMK) expression, displaying a tissue-resident signature and terminal effector state, prominently enriched among CD4+ T cells infiltrating the livers of patients with ALD. Subsequent examination of an independent ALD patient cohort corroborated the substantial enrichment of GZMK+CD4+ T lymphocytes, primarily within liver fibrotic zones, suggesting their potential involvement in disease progression. Additionally, we noted shifts in myeloid populations, with expanded APOE+ macrophage and FCGR3B+ monocyte subsets in ALD samples relative to MASLD and healthy tissues.

CONCLUSIONS

In summary, this study unravels the intricate cellular diversity within hepatic immune cell populations, highlighting the pivotal immune pathogenic role of the GZMK+CD4+ T lymphocyte subset in ALD pathogenesis.

Integrated serum proteomic and N-glycoproteomic characterization of dengue patients

Dengue fever is a mosquito-borne viral disease caused by the dengue virus (DENV). It poses a public health threat globally and, while most people with dengue have mild symptoms or are asymptomatic, approximately 5% of affected individuals develop severe disease and need hospital care. However, knowledge of the molecular mechanisms underlying dengue infection and the interaction between the virus and its host remains limited. In the present study, we performed a quantitative proteomic and N-glycoproteomic analysis of serum from 19 patients with dengue and 11 healthy people. The results revealed distinct proteomic and N-glycoproteomic landscapes between the two groups. Notably, we report for the first time the changes in the serum N glycosylation pattern following dengue infection and provide abundant information on glycoproteins, glycosylation sites, and intact N-glycopeptides using recently developed site-specific glycoproteomic approaches. Furthermore, a series of key functional pathways in proteomic and N-glycoproteomic were identified. Collectively, our findings significantly improve understanding of host and DENV interactions and the general pathogenesis and pathology of DENV, laying a foundation for functional studies of glycosylation and glycan structures in dengue infection.

Intense impact of IL-1β expressing inflammatory macrophages in acute aortic dissection

There is no treatment for acute aortic dissection (AAD) targeting inflammatory cells. We aimed to identify the new therapeutic targets associated with inflammatory cells. We characterized the specific distribution of myeloid cells of both human type A AAD samples and a murine AAD model generated using angiotensin II (ANGII) and β-aminopropionitrile (BAPN) by single-cell RNA sequencing (scRNA-seq). We also examined the effect of an anti-interleukin-1β (IL-1β) antibody in the murine AAD model. IL1B+ inflammatory macrophages and classical monocytes were increased in human AAD samples. Trajectory analysis demonstrated that IL1B+ inflammatory macrophages differentiated from S100A8/9/12+ classical monocytes uniquely observed in the aorta of AAD. We found increased infiltration of neutrophils and monocytes with the expression of inflammatory cytokines in the aorta and accumulation of inflammatory macrophages before the onset of macroscopic AAD in the murine AAD model. In blocking experiments using an anti-IL-1β antibody, it improved survival of murine AAD model by preventing elastin degradation. We observed the accumulation of inflammatory macrophages expressing IL-1β in both human AAD samples and in a murine AAD model. Anti-IL-1β antibody could improve the mortality rate in mice, suggesting that it may be a treatment option for AAD.

Single-cell reconstruction and mutation enrichment analysis identifies dysregulated cardiomyocyte and endothelial cells in congenital heart disease

Congenital heart disease (CHD) is one of the most prevalent neonatal congenital anomalies. To catalog the putative candidate CHD risk genes, we collected 16,349 variants [single-nucleotide variants (SNVs) and Indels] impacting 8,308 genes in 3,166 CHD cases for a comprehensive meta-analysis. Using American College of Medical Genetics (ACMG) guidelines, we excluded the 0.1% of benign/likely benign variants and the resulting dataset consisted of 83% predicted loss of function variants and 17% missense variants. Seventeen percent were de novo variants. A stepwise analysis identified 90 variant-enriched CHD genes, of which six (GPATCH1, NYNRIN, TCLD2, CEP95, MAP3K19, and TTC36) were novel candidate CHD genes. Single-cell transcriptome cluster reconstruction analysis on six CHD tissues and four controls revealed upregulation of the top 10 frequently mutated genes primarily in cardiomyocytes. NOTCH1 (highest number of variants) and MYH6 (highest number of recurrent variants) expression was elevated in endocardial cells and cardiomyocytes, respectively, and 60% of these gene variants were associated with tetralogy of Fallot and coarctation of the aorta, respectively. Pseudobulk analysis using the single-cell transcriptome revealed significant (P < 0.05) upregulation of both NOTCH1 (endocardial cells) and MYH6 (cardiomyocytes) in the control heart data. We observed nine different subpopulations of CHD heart cardiomyocytes of which only four were observed in the control heart. This is the first comprehensive meta-analysis combining genomics and CHD single-cell transcriptomics, identifying the most frequently mutated CHD genes, and demonstrating CHD gene heterogeneity, suggesting that multiple genes contribute to the phenotypic heterogeneity of CHD. Cardiomyocytes and endocardial cells are identified as major CHD-related cell types.NEW & NOTEWORTHY Congential heart disease (CHD) is one of the most prevalent neonatal congenital anomalies. We present a comprehensive analysis combining genomics and CHD single-cell transcriptome. Our study identifies 90 potential candidate CHD risk genes of which 6 are novel. The risk genes have heterogenous expression suggestive of multiple genes contributing to the phenotypic heterogeneity of CHD. Cardiomyocytes and endocardial cells are identified as major CHD-related cell types.

Study on Potential Differentially Expressed Genes in Idiopathic Pulmonary Fibrosis by Bioinformatics and Next-Generation Sequencing Data Analysis

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with reduced quality of life and earlier mortality, but its pathogenesis and key genes are still unclear. In this investigation, bioinformatics was used to deeply analyze the pathogenesis of IPF and related key genes, so as to investigate the potential molecular pathogenesis of IPF and provide guidance for clinical treatment. Next-generation sequencing dataset GSE213001 was obtained from Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) were identified between IPF and normal control group. The DEGs between IPF and normal control group were screened with the DESeq2 package of R language. The Gene Ontology (GO) and REACTOME pathway enrichment analyses of the DEGs were performed. Using the g:Profiler, the function and pathway enrichment analyses of DEGs were performed. Then, a protein-protein interaction (PPI) network was constructed via the Integrated Interactions Database (IID) database. Cytoscape with Network Analyzer was used to identify the hub genes. miRNet and NetworkAnalyst databaseswereused to construct the targeted microRNAs (miRNAs), transcription factors (TFs), and small drug molecules. Finally, receiver operating characteristic (ROC) curve analysis was used to validate the hub genes. A total of 958 DEGs were screened out in this study, including 479 up regulated genes and 479 down regulated genes. Most of the DEGs were significantly enriched in response to stimulus, GPCR ligand binding, microtubule-based process, and defective GALNT3 causes HFTC. In combination with the results of the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network, hub genes including LRRK2, BMI1, EBP, MNDA, KBTBD7, KRT15, OTX1, TEKT4, SPAG8, and EFHC2 were selected. Cyclothiazide and rotigotinethe are predicted small drug molecules for IPF treatment. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of IPF, and provide a novel strategy for clinical therapy.

Genetic analysis of potential biomarkers and therapeutic targets in age-related hearing loss

Age-related hearing loss (ARHL) or presbycusis is the phenomenon of hearing loss due to the aging of auditory organs with age. It seriously affects the cognitive function and quality of life of the elderly. This study is based on comprehensive bioinformatic and machine learning methods to identify the critical genes of ARHL and explore its therapy targets and pathological mechanisms. The ARHL and normal samples were from GSE49543 datasets of the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was applied to obtain significant modules. The Limma R-package was used to identify differentially expressed genes (DEGs). The 15 common genes of the practical module and DEGs were screened. Functional enrichment analysis suggested that these genes were mainly associated with inflammation, immune response, and infection. Cytoscape software created the protein-protein interaction (PPI) layouts and cytoHubba, support vector machine-recursive feature elimination (SVM-RFE), and random forests (RF) algorithms screened hub genes. After validating the hub gene expressions in GSE6045 and GSE154833 datasets, Clec4n, Mpeg1, and Fcgr3 are highly expressed in ARHL and have higher diagnostic efficacy for ARHL, so they were identified as hub genes. In conclusion, Clec4n, Mpeg1, and Fcgr3 play essential roles in developing ARHL, and they might become vital targets in ARHL diagnosis and anti-inflammatory therapy.

Cell-specific MAPT gene expression is preserved in neuronal and glial tau cytopathologies in progressive supranuclear palsy

Microtubule-associated protein tau (MAPT) aggregates in neurons, astrocytes and oligodendrocytes in a number of neurodegenerative diseases, including progressive supranuclear palsy (PSP). Tau is a target of therapy and the strategy includes either the elimination of pathological tau aggregates or reducing MAPT expression, and thus the amount of tau protein made to prevent its aggregation. Disease-associated tau affects brain regions in a sequential manner that includes cell-to-cell spreading. Involvement of glial cells that show tau aggregates is interpreted as glial cells taking up misfolded tau assuming that glial cells do not express enough MAPT. Although studies have evaluated MAPT expression in human brain tissue homogenates, it is not clear whether MAPT expression is compromised in cells accumulating pathological tau. To address these perplexing aspects of disease pathogenesis, this study used RNAscope combined with immunofluorescence (AT8), and single-nuclear(sn) RNAseq to systematically map and quantify MAPT expression dynamics across different cell types and brain regions in controls (n = 3) and evaluated whether tau cytopathology affects MAPT expression in PSP (n = 3). MAPT transcripts were detected in neurons, astrocytes and oligodendrocytes, and varied between brain regions and within each cell type, and were preserved in all cell types with tau aggregates in PSP. These results propose a complex scenario in all cell types, where, in addition to the ingested misfolded tau, the preserved cellular MAPT expression provides a pool for local protein production that can (1) be phosphorylated and aggregated, or (2) feed the seeding of ingested misfolded tau by providing physiological tau, both accentuating the pathological process. Since tau cytopathology does not compromise MAPT gene expression in PSP, a complete loss of tau protein expression as an early pathogenic component is less likely. These observations provide rationale for a dual approach to therapy by decreasing cellular MAPT expression and targeting removal of misfolded tau.

Peripheral immune landscape for hypercytokinemia in myasthenic crisis utilizing single-cell transcriptomics

BACKGROUND

Myasthenia gravis (MG) is the most prevalent autoimmune disorder affecting the neuromuscular junction. A rapid deterioration in respiratory muscle can lead to a myasthenic crisis (MC), which represents a life-threatening condition with high mortality in MG. Multiple CD4+ T subsets and hypercytokinemia have been identified in the peripheral pro-inflammatory milieu during the crisis. However, the pathogenesis is complicated due to the many types of cells involved, leaving the underlying mechanism largely unexplored.

METHODS

We conducted single-cell transcriptomic and immune repertoire sequencing on 33,577 peripheral blood mononuclear cells (PBMCs) from two acetylcholine receptor antibody-positive (AChR +) MG patients during MC and again three months post-MC. We followed the Scanpy workflow for quality control, dimension reduction, and clustering of the single-cell data. Subsequently, we annotated high-resolution cell types utilizing transfer-learning models derived from publicly available single-cell immune datasets. RNA velocity calculations from unspliced and spliced mRNAs were applied to infer cellular state progression. We analyzed cell communication and MG-relevant cytokines and chemokines to identify potential inflammation initiators.

RESULTS

We identified a unique subset of monocytes, termed monocytes 3 (FCGR3B+ monocytes), which exhibited significant differential expression of pro-inflammatory signaling pathways during and after the crisis. In line with the activated innate immune state indicated by MC, a high neutrophil-lymphocyte ratio (NLR) was confirmed in an additional 22 AChR + MC patients in subsequent hemogram analysis and was associated with MG-relevant clinical scores. Furthermore, oligoclonal expansions were identified in age-associated B cells exhibiting high autoimmune activity, and in CD4+ and CD8+ T cells demonstrating persistent T exhaustion.

CONCLUSIONS

In summary, our integrated analysis of single-cell transcriptomics and TCR/BCR sequencing has underscored the role of innate immune activation which is associated with hypercytokinemia in MC. The identification of a specific monocyte cluster that dominates the peripheral immune profile may provide some hints into the etiology and pathology of MC. However, future functional studies are required to explore causality.

Identification of the Genetic Influence of SARS-CoV-2 Infections on IgA Nephropathy Based on Bioinformatics Method

INTRODUCTION

Coronavirus disease-2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. It was initially detected in Wuhan, China, in December 2019. In March 2020, the World Health Organization (WHO) declared COVID-19 a global pandemic. Compared to healthy individuals, patients with IgA nephropathy (IgAN) are at a higher risk of SARS-CoV-2 infection. However, the potential mechanisms remain unclear. This study explores the underlying molecular mechanisms and therapeutic agents for the management of IgAN and COVID-19 using the bioinformatics and system biology way.

METHODS

We first downloaded GSE73953 and GSE164805 from the Gene Expression Omnibus (GEO) database to obtain common differentially expressed genes (DEGs). Then, we performed the functional enrichment analysis, pathway analysis, protein-protein interaction (PPI) analysis, gene regulatory networks analysis, and potential drug analysis on these common DEGs.

RESULTS

We acquired 312 common DEGs from the IgAN and COVID-19 datasets and used various bioinformatics tools and statistical analyses to construct the PPI network to extract hub genes. Besides, we performed gene ontology (GO) and pathway analyses to reveal the common correlation between IgAN and COVID-19. Finally, on the basis of common DEGs, we determined the interactions between DEGs-miRNAs, the transcription factor-genes (TFs-genes), protein-drug, and gene-disease networks.

CONCLUSION

We successfully identified hub genes that may act as biomarkers of COVID-19 and IgAN and also screened out some potential drugs to provide new ideas for COVID-19 and IgAN treatment.

Screening and identification of tissue-infiltrating immune cells and genes for patients with emphysema phenotype of COPD

Objective

To study the tissue-infiltrating immune cells of the emphysema phenotype of chronic obstructive pulmonary disease (COPD) and find the molecular mechanism related to the development of emphysema to offer potential targets for more precise treatment of patients with COPD.

Methods

Combined analyses of COPD emphysema phenotype lung tissue-related datasets, GSE47460 and GSE1122, were performed. CIBERSORT was used to assess the distribution of tissue-infiltrating immune cells. Weighted gene co-expression network analysis (WGCNA) was used to select immune key genes closely related to clinical features. Rt-qPCR experiments were used for the validation of key genes. Emphysema risk prediction models were constructed by logistic regression analysis and a nomogram was developed.

Results

In this study, three immune cells significantly associated with clinical features of emphysema (FEV1 post-bronchodilator % predicted, GOLD Stage, and DLCO) were found. The proportion of neutrophils (p=0.025) infiltrating in the emphysema phenotype was significantly increased compared with the non-emphysema phenotype, while the proportions of M2 macrophages (p=0.004) and resting mast cells (p=0.01) were significantly decreased. Five immune-related differentially expressed genes (DEGs) were found. WGCNA and clinical lung tissue validation of patients with emphysema phenotype were performed to further screen immune-related genes closely related to clinical features. A key gene (SERPINA3) was selected and included in the emphysema risk prediction model. Compared with the traditional clinical prediction model (AUC=0.923), the combined prediction model, including SERPINA3 and resting mast cells (AUC=0.941), had better discrimination power and higher net benefit.

Conclusion

This study comprehensively analyzed the tissue-infiltrating immune cells significantly associated with emphysema phenotype, including M2 macrophages, neutrophils, and resting mast cells, and identified SERPINA3 as a key immune-related gene.

ARDS in the Time of Corona: Context and Perspective

For more than 2 years, COVID-19 has been holding the world at awe with new waves of infections, novel mutants, and still limited (albeit improved) means to combat SARS-CoV-2-induced respiratory failure, the most common and fatal presentation of severe COVID-19. In the present perspective, we draw from the successes and—mostly—failures in previous acute respiratory distress syndrome (ARDS) work and the experiences from COVID-19 to define conceptual barriers that have so far hindered therapeutic breakthroughs in this deadly disease, and to open up new avenues of thinking and thus, ultimately of therapy.

A Landscape Study on COVID-19 Immunity at the Single-Cell Level

Since 2019, the coronavirus (COVID-19) has outbroken continuously, spreading internationally and threatening the public health. However, it was unknown how the disorder at the single-cell level was associated with the pathogenesis of COVID-19. This study presented the disorders of macrophages, epithelial cells, CD8⁺ T cells, and natural killer (NK) cells at the single-cell level in the courses of COVID-19 and analyzed the immune response to cytokine storm. Compared with the healthy group, patients with COVID-19 had higher proportions of macrophages and lower proportions of T and NK cells, especially proportions of macrophages and epithelial cells with an increase during patients’ conditions from mild to severe. This study suggested that there were high levels of pro-inflammatory and chemokine expressions in cells of COVID-19 and analyzed cell subsets to explore its changes and pathways. It was worth noting that several subsets of macrophages, epithelial cells, CD8 T cells, and NK cells were involved in inflammation pathways, including interleukin-17 (IL-17) signaling pathway and tumor necrosis factor (TNF) signaling pathway. Moreover, the pathways interacting COVID-19 and cytokine receptor with each other were remarkably enriched. In addition, these cell subsets played important roles in inflammation, and their abnormal functions may cause COVID-19. In conclusion, this study provided an immune outlook for COVID-19 at the single-cell level and revealed different pathways in immune response of COVID-19 single cells.

Analyzing single cell transcriptome data from severe COVID-19 patients

We describe the protocol for identifying COVID-19 severity specific cell types and their regulatory marker genes using single-cell transcriptomics data. We construct COVID-19 comorbid disease-associated gene list using multiple databases and literature resources. Next, we identify specific cell type where comorbid genes are upregulated. We further characterize the identified cell type using gene enrichment analysis. We detect upregulation of marker gene restricted to severe COVID-19 cell type and validate our findings using in silico, in vivo, and in vitro cellular models.

For complete details on the use and execution of this protocol, please refer to Nassir et al. (2021b).

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Step-by-step protocol for single cell transcriptome data clustering and analysis

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Customized cell type marker identification pipeline

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Identification of clusters with enrichment of COVID-19 comorbidity associated genes

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Gene expression studies from nasopharyngeal swabs and spike protein simulated cells