Exploration of the potential common pathogenic mechanisms in COVID-19 and silicosis by using bioinformatics and system biology.

Silicosis is an occupational lung disease that is common worldwide. In recent years, coronavirus disease 2019 (COVID-19) has provided daunting challenges to public healthcare systems globally. Although multiple studies have shown a close link between COVID-19 and other respiratory diseases, the inter-relational mechanisms between COVID-19 and silicosis remain unclear. This study aimed to explore the shared molecular mechanisms and drug targets of COVID-19 and silicosis. Gene expression profiling identified four modules that were most closely associated with both diseases. Furthermore, we performed functional analysis and constructed a protein-protein interaction network. Seven hub genes (budding uninhibited by benzimidazoles 1 [BUB1], protein regulator of cytokinesis 1 [PRC1], kinesin family member C1 [KIFC1], ribonucleotide reductase regulatory subunit M2 [RRM2], cyclin-dependent kinase inhibitor 3 [CDKN3], Cyclin B2 [CCNB2], and minichromosome maintenance complex component 6 [MCM6]) were involved in the interaction between COVID-19 and silicosis. We investigated how diverse microRNAs and transcription factors regulate these seven genes. Subsequently, the correlation between the hub genes and infiltrating immune cells was explored. Further in-depth analyses were performed based on single-cell transcriptomic data from COVID-19, and the expression of hub-shared genes was characterized and located in multiple cell clusters. Finally, molecular docking results reveal small molecular compounds that may improve COVID-19 and silicosis. The current study reveals the common pathogenesis of COVID-19 and silicosis, which may provide a novel reference for further research.

Single-cell analysis of adult human heart across healthy and cardiovascular disease patients reveals the cellular landscape underlying SARS-CoV-2 invasion of myocardial tissue through ACE2.

BACKGROUND: The distribution of ACE2 and accessory proteases (ANAD17 and CTSL) in cardiovascular tissue and the host cell receptor binding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are crucial to understanding the virus's cell invasion, which may play a significant role in determining the viral tropism and its clinical manifestations. METHODS: We conducted a comprehensive analysis of the cell type-specific expression of ACE2, ADAM17, and CTSL in myocardial tissue from 10 patients using RNA sequencing. Our study included a meta-analysis of 2 heart single-cell RNA-sequencing studies with a total of 90,024 cells from 250 heart samples of 10 individuals. We used co-expression analysis to locate specific cell types that SARS-CoV-2 may invade. RESULTS: Our results revealed cell-type specific associations between male gender and the expression levels of ACE2, ADAM17, and CTSL, including pericytes and fibroblasts. AGT, CALM3, PCSK5, NRP1, and LMAN were identified as potential accessory proteases that might facilitate viral invasion. Enrichment analysis highlighted the extracellular matrix interaction pathway, adherent plaque pathway, vascular smooth muscle contraction inflammatory response, and oxidative stress as potential immune pathways involved in viral infection, providing potential molecular targets for therapeutic intervention. We also found specific high expression of IFITM3 and AGT in pericytes and differences in the IFN-II signaling pathway and PAR signaling pathway in fibroblasts from different cardiovascular comorbidities. CONCLUSIONS: Our data indicated possible high-risk groups for COVID-19 and provided emerging avenues for future investigations of its pathogenesis. TRIAL REGISTRATION: (Not applicable).

Genomic Tools in Clinical Epidemiology

The advent of high-throughput technologies, including next-generation sequencing (NGSs), is currently revolutionizing our understanding of several aspects in biological and medical sciences. Particularly, genomic, transcriptomic, epigenomic, and interactomic studies are having a profound impact on the progress of clinical epidemiology. This science is improving public health practices by linking the knowledge from the etiology, distribution, and risk factors during the appearance and progress of infectious and chronic diseases. In this sense, genomic tools have been incorporated in epidemiological studies for the identification of rare genetic variants, genetic and environmental risk factors, and accurate biomarkers for the diagnosis and treatment of several diseases. In this chapter, we aim to highlight the influence that genomics is having on different epidemiological traits by illustrating some examples about the control of the COVID-19 pandemic and the diagnoses, screening, and treatment of chronic diseases such as the infection caused by Helicobacter pylori, cancer, and rheumatoid arthritis. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Identification of genes related to immune enhancement caused by heterologous ChAdOx1-BNT162b2 vaccines in lymphocytes at single-cell resolution with machine learning methods.

The widely used ChAdOx1 nCoV-19 (ChAd) vector and BNT162b2 (BNT) mRNA vaccines have been shown to induce robust immune responses. Recent studies demonstrated that the immune responses of people who received one dose of ChAdOx1 and one dose of BNT were better than those of people who received vaccines with two homologous ChAdOx1 or two BNT doses. However, how heterologous vaccines function has not been extensively investigated. In this study, single-cell RNA sequencing data from three classes of samples: volunteers vaccinated with heterologous ChAdOx1-BNT and volunteers vaccinated with homologous ChAd-ChAd and BNT-BNT vaccinations after 7 days were divided into three types of immune cells (3654 B, 8212 CD4+ T, and 5608 CD8+ T cells). To identify differences in gene expression in various cell types induced by vaccines administered through different vaccination strategies, multiple advanced feature selection methods (max-relevance and min-redundancy, Monte Carlo feature selection, least absolute shrinkage and selection operator, light gradient boosting machine, and permutation feature importance) and classification algorithms (decision tree and random forest) were integrated into a computational framework. Feature selection methods were in charge of analyzing the importance of gene features, yielding multiple gene lists. These lists were fed into incremental feature selection, incorporating decision tree and random forest, to extract essential genes, classification rules and build efficient classifiers. Highly ranked genes include PLCG2, whose differential expression is important to the B cell immune pathway and is positively correlated with immune cells, such as CD8+ T cells, and B2M, which is associated with thymic T cell differentiation. This study gave an important contribution to the mechanistic explanation of results showing the stronger immune response of a heterologous ChAdOx1-BNT vaccination schedule than two doses of either BNT or ChAdOx1, offering a theoretical foundation for vaccine modification.

Lung development and regeneration: newly defined cell types and progenitor status.

The lung is the most critical organ of the respiratory system supporting gas exchange. Constant interaction with the external environment makes the lung vulnerable to injury. Thus, a deeper understanding of cellular and molecular processes underlying lung development programs and evaluation of progenitor status within the lung is an essential part of lung regenerative medicine. In this review, we aim to discuss the current understanding of lung development process and regenerative capability. We highlight the advances brought by multi-omics approaches, single-cell transcriptome, in particular, that can help us further dissect the cellular player and molecular signaling underlying those processes.

Boosters for adeno-associated virus vector (AAV) (r)evolution.

Adeno-associated virus (AAV) is one of the most exciting and most versatile templates for engineering of gene-delivery vectors for use in human gene therapy, owing to the existence of numerous naturally occurring capsid variants and their amenability to directed molecular evolution. As a result, the field has witnessed an explosion of novel "designer" AAV capsids and ensuing vectors over the last two decades, which have been isolated from comprehensive capsid libraries generated through technologies such as DNA shuffling or peptide display, and stratified under stringent positive and/or negative selection pressures. Here, we briefly highlight a panel of recent, innovative and transformative methodologies that we consider to have exceptional potential to advance directed AAV capsid evolution and to thereby accelerate AAV vector revolution. These avenues comprise original technologies for (i) barcoding and high-throughput screening of individual AAV variants or entire capsid libraries, (ii) selection of transduction-competent AAV vectors on the DNA level, (iii) enrichment of expression-competent AAV variants on the RNA level, as well as (iv) high-resolution stratification of focused AAV capsid libraries on the single-cell level. Together with other emerging AAV engineering stratagems, such as rational design or machine learning, these pioneering techniques promise to provide an urgently needed booster for AAV (r)evolution.

Single cell RNA-seq resolution revealed CCR1+/SELL+/XAF+ CD14 monocytes mediated vascular endothelial cell injuries in Kawasaki disease and COVID-19.

INTRODUCTION: The COVID-19 pandemic provide the opportunities to explore the numerous similarities in clinical symptoms with Kawasaki disease (KD), including severe vasculitis. Despite this, the underlying mechanisms of vascular injury in both KD and COVID-19 remain elusive. To identify these mechanisms, this study employs single-cell RNA sequencing to explore the molecular mechanisms of immune responses in vasculitis, and validate the results through in vitro experiments. METHOD: The single-cell RNA sequencing (scRNA-seq) analysis of peripheral blood mononuclear cells (PBMCs) was carried out to investigate the molecular mechanisms of immune responses in vasculitis in KD and COVID-19. The analysis was performed on PBMCs from six children diagnosed with complete KD, three age-matched KD healthy controls (KHC), six COVID-19 patients (COV), three influenza patients (FLU), and four healthy controls (CHC). The results from the scRNA-seq analysis were validated through flow cytometry and immunofluorescence experiments on additional human samples. Subsequently, monocyte adhesion assays, immunofluorescence, and quantitative polymerase chain reaction (qPCR) were used to analyze the damages to endothelial cells post-interaction with monocytes in HUVEC and THP1 cultures. RESULTS: The scRNA-seq analysis revealed the potential cellular types involved and the alterations in genetic transcriptions in the inflammatory responses. The findings indicated that while the immune cell compositions had been altered in KD and COV patients, and the ratio of CD14+ monocytes were both elevated in KD and COV. While the CD14+ monocytes share a large scale of same differentiated expressed geens between KD and COV. The differential activation of CD14 and CD16 monocytes was found to respond to both endothelial and epithelial dysfunctions. Furthermore, SELL+/CCR1+/XAF1+ CD14 monocytes were seen to enhance the adhesion and damage to endothelial cells. The results also showed that different types of B cells were involved in both KD and COV, while only the activation of T cells was recorded in KD. CONCLUSION: In conclusion, our study demonstrated the role of the innate immune response in the regulation of endothelial dysfunction in both KD and COVID-19. Additionally, our findings indicate that the adaptive immunity activation differs between KD and COVID-19. Our results demonstrate that monocytes in COVID-19 exhibit adhesion to both endothelial cells and alveolar epithelial cells, thus providing insight into the mechanisms and shared phenotypes between KD and COVID-19.

Urokinase System in Pathogenesis of Pulmonary Fibrosis: A Hidden Threat of COVID-19.

Pulmonary fibrosis is a common and threatening post-COVID-19 complication with poorly resolved molecular mechanisms and no established treatment. The plasminogen activator system, including urokinase (uPA) and urokinase receptor (uPAR), is involved in the pathogenesis of COVID-19 and contributes to the development of lung injury and post-COVID-19 pulmonary fibrosis, although their cellular and molecular underpinnings still remain obscure. The aim of the current study was to assess the role of uPA and uPAR in the pathogenesis of pulmonary fibrosis. We analyzed uPA and uPAR expression in human lung tissues from COVID-19 patients with pulmonary fibrosis using single-cell RNA-seq and immunohistochemistry. We modeled lung fibrosis in Plau-/- and Plaur-/- mice upon bleomycin instillation and explored the effect of uPAR downregulation in A549 and BEAS-2B lung epithelial cells. We found that uPAR expression drastically decreased in the epithelial airway basal cells and monocyte/macrophage cells, whereas uPA accumulation significantly increased in tissue samples of COVID-19 patients. Lung injury and fibrosis in Plaur-/- vs. WT mice upon bleomycin instillation revealed that uPAR deficiency resulted in pro-fibrogenic uPA accumulation, IL-6 and ACE2 upregulation in lung tissues and was associated with severe fibrosis, weight loss and poor survival. uPAR downregulation in A549 and BEAS-2B was linked to an increased N-cadherin expression, indicating the onset of epithelial-mesenchymal transition and potentially contributing to pulmonary fibrosis. Here for the first time, we demonstrate that plasminogen treatment reversed lung fibrosis in Plaur-/- mice: the intravenous injection of 1 mg of plasminogen on the 21st day of bleomycin-induced fibrosis resulted in a more than a two-fold decrease in the area of lung fibrosis as compared to non-treated mice as evaluated by the 42nd day. The expression and function of the plasminogen activator system are dysregulated upon COVID-19 infection, leading to excessive pulmonary fibrosis and worsening the prognosis. The potential of plasminogen as a life-saving treatment for non-resolving post-COVID-19 pulmonary fibrosis warrants further investigation.

SARS-CoV-2 cellular tropism and direct multiorgan failure in COVID-19 patients: Bioinformatic predictions, experimental observations, and open questions.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19), has led to an unprecedented public health emergency worldwide. While common cold symptoms are observed in mild cases, COVID-19 is accompanied by multiorgan failure in severe patients. Organ damage in COVID-19 patients is partially associated with the indirect effects of SARS-CoV-2 infection (e.g., systemic inflammation, hypoxic-ischemic damage, coagulopathy), but early processes in COVID-19 patients that trigger a chain of indirect effects are connected with the direct infection of cells by the virus. To understand the virus transmission routes and the reasons for the wide-spectrum of complications and severe outcomes of COVID-19, it is important to identify the cells targeted by SARS-CoV-2. This review summarizes the major steps of investigation and the most recent findings regarding SARS-CoV-2 cellular tropism and the possible connection between the early stages of infection and multiorgan failure in COVID-19. The SARS-CoV-2 pandemic is the first epidemic in which data extracted from single-cell RNA-seq (scRNA-seq) gene expression data sets have been widely used to predict cellular tropism. The analysis presented here indicates that the SARS-CoV-2 cellular tropism predictions are accurate enough for estimating the potential susceptibility of different cells to SARS-CoV-2 infection; however, it appears that not all susceptible cells may be infected in patients with COVID-19.

Immune response and homeostasis mechanism following administration of BBIBP-CorV SARS-CoV-2 inactivated vaccine.

The BBIBP-CorV severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) inactivated vaccine has been authorized for emergency use and widely distributed. We used single-cell transcriptome sequencing to characterize the dynamics of immune responses to the BBIBP-CorV inactivated vaccine. In addition to the expected induction of humoral immunity, we found that the inactivated vaccine induced multiple, comprehensive immune responses, including significantly increased proportions of CD16+ monocytes and activation of monocyte antigen presentation pathways; T cell activation pathway upregulation in CD8+ T cells, along with increased activation of CD4+ T cells; significant enhancement of cell-cell communications between innate and adaptive immunity; and the induction of regulatory CD4+ T cells and co-inhibitory interactions to maintain immune homeostasis after vaccination. Additionally, comparative analysis revealed higher neutralizing antibody levels, distinct expansion of naive T cells, a shared increased proportion of regulatory CD4+ T cells, and upregulated expression of functional genes in booster dose recipients with a longer interval after the second vaccination. Our research will support a comprehensive understanding of the systemic immune responses elicited by the BBIBP-CorV inactivated vaccine, which will facilitate the formulation of better vaccination strategies and the design of new vaccines.

Data analysis guidelines for single-cell RNA-seq in biomedical studies and clinical applications.

The application of single-cell RNA sequencing (scRNA-seq) in biomedical research has advanced our understanding of the pathogenesis of disease and provided valuable insights into new diagnostic and therapeutic strategies. With the expansion of capacity for high-throughput scRNA-seq, including clinical samples, the analysis of these huge volumes of data has become a daunting prospect for researchers entering this field. Here, we review the workflow for typical scRNA-seq data analysis, covering raw data processing and quality control, basic data analysis applicable for almost all scRNA-seq data sets, and advanced data analysis that should be tailored to specific scientific questions. While summarizing the current methods for each analysis step, we also provide an online repository of software and wrapped-up scripts to support the implementation. Recommendations and caveats are pointed out for some specific analysis tasks and approaches. We hope this resource will be helpful to researchers engaging with scRNA-seq, in particular for emerging clinical applications.

Network analysis between neuron dysfunction and neuroimmune response based on neural single-cell transcriptome of COVID-19 patients.

Despite global vaccination efforts, COVID-19 breakthrough infections caused by variant virus continue to occur frequently, long-term sequelae of COVID-19 infection like neuronal dysfunction emerge as a noteworthy issue. Neuroimmune disorder induced by Inflammatory factor storm was considered as a possible reason, however, little was known about the functional factors affecting neuroimmune response to this virus. Here, using medial prefrontal cortex single cell data of COVID-19 patients, expression pattern analysis indicated that some immune-related pathway genes expressed specifically, including genes associated with T cell receptor, TNF signaling in microglia and Cytokine-cytokine receptor interaction and HIF-1 signaling pathway genes in astrocytes. Besides the well-known immune-related cell type microglia, we also observed immune-related factors like IL17D, TNFRSF1A and TLR4 expressed in Astrocytes. Based on the ligand-receptor relationship of immune-related factors, crosstalk landscape among cell clusters were analyzed. The findings indicated that astrocytes collaborated with microglia and affect excitatory neurons, participating in the process of immune response and neuronal dysfunction. Moreover, subset of astrocytes specific immune factors (hinged neuroimmune genes) were proved to correlate with Covid-19 infection and ventilator-associated pneumonia using multi-tissue RNA-seq and scRNA-seq data. Function characterization clarified that hinged neuroimmune genes were involved in activation of inflammation and hypoxia signaling pathways, which could lead to hyper-responses related neurological sequelae. Finally, a risk model was constructed and testified in RNA-seq and scRNA data of peripheral blood.

Dissecting CD8+ T cell pathology of severe SARS-CoV-2 infection by single-cell immunoprofiling.

Introduction: SARS-CoV-2 infection results in varying disease severity, ranging from asymptomatic infection to severe illness. A detailed understanding of the immune response to SARS-CoV-2 is critical to unravel the causative factors underlying differences in disease severity and to develop optimal vaccines against new SARS-CoV-2 variants. Methods: We combined single-cell RNA and T cell receptor sequencing with CITE-seq antibodies to characterize the CD8+ T cell response to SARS-CoV-2 infection at high resolution and compared responses between mild and severe COVID-19. Results: We observed increased CD8+ T cell exhaustion in severe SARS-CoV-2 infection and identified a population of NK-like, terminally differentiated CD8+ effector T cells characterized by expression of FCGR3A (encoding CD16). Further characterization of NK-like CD8+ T cells revealed heterogeneity among CD16+ NK-like CD8+ T cells and profound differences in cytotoxicity, exhaustion, and NK-like differentiation between mild and severe disease conditions. Discussion: We propose a model in which differences in the surrounding inflammatory milieu lead to crucial differences in NK-like differentiation of CD8+ effector T cells, ultimately resulting in the appearance of NK-like CD8+ T cell populations of different functionality and pathogenicity. Our in-depth characterization of the CD8+ T cell-mediated response to SARS-CoV-2 infection provides a basis for further investigation of the importance of NK-like CD8+ T cells in COVID-19 severity.

Single-cell RNA-sequencing in asthma research.

Asthma is a complex and heterogeneous disease with multicellular involvement, and knowledge gaps remain in our understanding of the pathogenesis of asthma. Efforts are still being made to investigate the immune pathogenesis of asthma in order to identify possible targets for prevention. Single cell RNA sequencing (scRNA-seq) technology is a useful tool for exploring heterogeneous diseases, identifying rare cell types and distinct cell subsets, enabling elucidation of key processes of cell differentiation, and understanding regulatory gene networks that predict immune function. In this article, we provide an overview of the importance of scRNA-seq for asthma research, followed by an in-depth discussion of the results in recent years, in order to provide new ideas for the pathogenesis, drug development and treatment of asthma.

Characteristics of lymphocyte subset alterations in COVID-19 patients with different levels of disease severity.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a respiratory disorder caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which had rapidly spread all over the world and caused public health emergencies in the past two years. Although the diagnosis and treatment for COVID-19 have been well defined, the immune cell characteristics and the key lymphocytes subset alterations in COVID-19 patients have not been thoroughly investigated. METHODS: The levels of immune cells including T cells, B cells, and natural killer (NK) cells in 548 hospitalized COVID-19 patients, and 30 types of lymphocyte subsets in 125 hospitalized COVID-19 patients admitted to Wuhan Huoshenshan Hospital of China were measured using flow cytometry. The relationship between lymphocytes subsets with the cytokine interleukin-6 (IL-6) and the characteristics of lymphocyte subsets in single-cell RNA sequencing (scRNA-seq) data obtained from peripheral blood mononuclear cells (PBMCs) were also analysed in COVID-19 patients. RESULTS: In this study, we found that patients with critical COVID-19 infection exhibited an overall decline in lymphocytes including CD4+ T cells, CD8+ T cells, total T cells, B cells, and NK cells compared to mild and severe patients. However, the number of lymphocyte subsets, such as CD21low CD38low B cells, effector T4 cells, and PD1+ depleted T8 cells, was moderately increased in critical COVID-19 patients compared to mild cases. Notably, except for effector memory T4 cells, plasma blasts and Tregs, the number of all lymphocyte subsets was markedly decreased in COVID-19 patients with IL-6 levels over 30-fold higher than those in healthy cases. Moreover, scRNA-seq data showed obvious differences in the distribution and numbers of lymphocyte subsets between COVID-19 patients and healthy persons, and subsets-specific marker genes of lymphocyte subsets including CD4, CD19, CCR7, and IL7R, were markedly decreased in COVID-19 patients compared with those in healthy cases. CONCLUSION: A comprehensive decrease in immune cell and lymphocyte subsets in critical COVID-19 patients, and peripheral lymphocyte subset alterations showed a clear association with clinical characteristics.

Multiomics analysis of male infertility†.

Infertility affects 8-12% of couples globally, and the male factor is a primary cause in ~50% of couples. Male infertility is a multifactorial reproductive disorder, which can be caused by paracrine and autocrine factors, hormones, genes, and epigenetic changes. Recent studies in rodents and most notably in humans using multiomics approach have yielded important insights into understanding the biology of spermatogenesis. Nonetheless, the etiology and pathogenesis of male infertility are still largely unknown. In this review, we summarized and critically evaluated findings based on the use of advanced technologies to compare normal and obstructive azoospermic versus nonobstructive azoospermic men, including whole-genome bisulfite sequencing, single-cell RNA-seq, whole-exome sequencing, and transposase-accessible chromatin using sequencing. It is obvious that the multiomics approach is the method of choice for basic research and clinical studies including clinical diagnosis of male infertility.

Self-supervised contrastive learning for integrative single cell RNA-seq data analysis.

We present a novel self-supervised Contrastive LEArning framework for single-cell ribonucleic acid (RNA)-sequencing (CLEAR) data representation and the downstream analysis. Compared with current methods, CLEAR overcomes the heterogeneity of the experimental data with a specifically designed representation learning task and thus can handle batch effects and dropout events simultaneously. It achieves superior performance on a broad range of fundamental tasks, including clustering, visualization, dropout correction, batch effect removal, and pseudo-time inference. The proposed method successfully identifies and illustrates inflammatory-related mechanisms in a COVID-19 disease study with 43 695 single cells from peripheral blood mononuclear cells.

Single-cell RNA-seq data analysis characterizing bronchoalveolar epithelial cells in patients with SARS-CoV-2 infection.

BACKGROUND: Angiotensin-converting enzyme 2 (ACE2) has been reported to be the main receptor for SARS-CoV-2 infection of host cells. Understanding the changes in bronchoalveolar epithelial cells after SARS-CoV-2 infection of host cells and the intercellular communication relationship between these epithelial cell changes and immune cells is of great significance for the development of therapeutic methods. METHODS: We explored the single-cell RNA sequence (scRNA-seq) of cells infected with bronchoalveolar lavage fluid (BaLF) of patients with different severities of SARS-CoV-2 and healthy people. RESULTS: We found 11 clusters of epithelial cells in the BaLF, and they were derived from the S group. In the S group, the proportion of cells with positive ACE2 expression was relatively high. ACE2 was relatively more expressed in epithelial cell clusters 1, 3, and 7. Clusters 4 and 5 represented the original state, and there were two differentiation directions: one was cluster 2, and the others were clusters 1, 3, and 6. Cluster 7 was the intermediate state. Clusters 1, 3, 6, and 7 had high similarities (> 0.9), and their main signaling pathways focused on inflammatory activation and immune response. Cluster 2 was relatively specific and was up-regulated in differential genes that were mainly related to apoptosis. The ligand-receptor expression pattern of TNFRSF10D-TNFSF10 showed a special inter-cell regulatory relationship between epithelial cell cluster 2 and macrophages. CONCLUSION: This study revealed the changes in epithelial cells derived from alveolar lavage fluid after SARS-CoV-2 infection and the communication relationship with other immune cells.

Single-Cell Gene Regulatory Network Analysis Reveals Potential Mechanisms of Action of Antimalarials Against SARS-CoV-2

The efficiency of antimalarials, chloroquine (CQ) and hydroxychloroquine (HCQ), in the prevention and treatment of coronavirus disease 2019 (COVID-19) is under intense debate. The mechanisms of action of antimalarials against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have not been fully elucidated. Here, we applied a network-based comparative analysis, implemented in our machine learning workflow-scTenifoldNet, to scRNA-seq data from COVID-19 patientswith different levels of severity. We found that genes of the Malaria pathway expressed in macrophages are significantly differentially regulated between patientswith moderate and severe symptoms. Our findings help reveal the mechanisms of action of CQ and HCQ during SARS-CoV-2 infection, providing new evidence to support the use of these antimalarial drugs in the treatment of COVID-19, especially for patients who are mildly affected or in the early stage of the infection.

Identification of COVID-19-Associated DNA Methylation Variations by Integrating Methylation Array and scRNA-Seq Data at Cell-Type Resolution.

Single-cell transcriptome studies have revealed immune dysfunction in COVID-19 patients, including lymphopenia, T cell exhaustion, and increased levels of pro-inflammatory cytokines, while DNA methylation plays an important role in the regulation of immune response and inflammatory response. The specific cell types of immune responses regulated by DNA methylation in COVID-19 patients will be better understood by exploring the COVID-19 DNA methylation variation at the cell-type level. Here, we developed an analytical pipeline to explore single-cell DNA methylation variations in COVID-19 patients by transferring bulk-tissue-level knowledge to the single-cell level. We discovered that the methylation variations in the whole blood of COVID-19 patients showed significant cell-type specificity with remarkable enrichment in gamma-delta T cells and presented a phenomenon of hypermethylation and low expression. Furthermore, we identified five genes whose methylation variations were associated with several cell types. Among them, S100A9, AHNAK, and CX3CR1 have been reported as potential COVID-19 biomarkers previously, and the others (TRAF3IP3 and LFNG) are closely associated with the immune and virus-related signaling pathways. We propose that they might serve as potential epigenetic biomarkers for COVID-19 and could play roles in important biological processes such as the immune response and antiviral activity.