COVID-19 immune features revealed by a large-scale single-cell transcriptome atlas

Single-Cell Transcriptomics Reveals a Pivotal Role of DOCK2 in Sjögren Disease

OBJECTIVE

Sjögren disease (SjD) is an autoimmune condition characterized by the dysfunction of the salivary and lacrimal glands. The study aimed to decipher the pathogenic cell populations and their immunologic pathways in the salivary glands. We further determined the therapeutic effect of inhibiting dedicator of cytokinesis 2 (DOCK2) shared by novel clusters of CD8+ T cells in an SjD mouse model.

METHODS

This study employed single-cell RNA sequencing to examine the composition and dynamics of immune cells in the salivary glands of SjD mice. By analyzing the transcriptomic data and employing clustering analysis, a specific target was identified, leading to the treatment of mice with a targeted inhibitor.

RESULTS

The results showed diverse immune cell types, including B cells, CD4+ T cells, CD8+ T cells, macrophages, and natural killer cells. We identified specific clusters possessing phenotypic characteristics of immune cell subpopulations, thereby showing specific genes/pathways associated with the disease. The most striking finding was the elevated expression of DOCK2 in CD8+ T cells in the SjD model. This discovery is significant because subsequent treatment with a DOCK2 inhibitor 4-[3-(2-Chlorophenyl)-2-propen-1-ylidene]-1-phenyl-3,5-pyrazolidinedione (CPYPP) led to a marked amelioration of SjD signs.

CONCLUSION

The effectiveness of DOCK2 inhibition in alleviating SjD signs highlights the potential of DOCK2 as a therapeutic target, opening new avenues for treatment strategies that could modulate the immune response more effectively in SjD.

Identification and evaluation of candidate COVID-19 critical genes and medicinal drugs related to plasma cells

The ongoing COVID-19 pandemic, caused by the SARS-CoV-2 virus, represents one of the most significant global health crises in recent history. Despite extensive research into the immune mechanisms and therapeutic options for COVID-19, there remains a paucity of studies focusing on plasma cells. In this study, we utilized the DESeq2 package to identify differentially expressed genes (DEGs) between COVID-19 patients and controls using datasets GSE157103 and GSE152641. We employed the xCell algorithm to perform immune infiltration analyses, revealing notably elevated levels of plasma cells in COVID-19 patients compared to healthy individuals. Subsequently, we applied the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm to identify COVID-19 related plasma cell module genes. Further, positive cluster biomarker genes for plasma cells were extracted from single-cell RNA sequencing data (GSE171524), leading to the identification of 122 shared genes implicated in critical biological processes such as cell cycle regulation and viral infection pathways. We constructed a robust protein-protein interaction (PPI) network comprising 89 genes using Cytoscape, and identified 20 hub genes through cytoHubba. These genes were validated in external datasets (GSE152418 and GSE179627). Additionally, we identified three potential small molecules (GSK-1070916, BRD-K89997465, and idarubicin) that target key hub genes in the network, suggesting a novel therapeutic approach. These compounds were characterized by their ability to down-regulate AURKB, KIF11, and TOP2A effectively, as evidenced by their low free binding energies determined through computational analyses using cMAP and AutoDock. This study marks the first comprehensive exploration of plasma cells' role in COVID-19, offering new insights and potential therapeutic targets. It underscores the importance of a systematic approach to understanding and treating COVID-19, expanding the current body of knowledge and providing a foundation for future research.

Harnessing high-throughput OMICS in emerging zoonotic virus preparedness and response activities

Emerging and re-emerging viruses pose unpredictable and significant challenges to global health. Emerging zoonotic infectious diseases, which are transmitted between humans and non-human animals, have been estimated to be responsible for nearly two-thirds of emerging infectious disease events and emergence events attributed to these pathogens have been increasing in frequency with the potential for high global health and economic burdens. In this review we will focus on the application of highthroughput OMICS approaches to emerging zoonotic virus investigtations. We highlight the key contributions of transcriptome and proteome investigations to emerging zoonotic virus preparedness and response activities with a focus on SARS-CoV-2, avian influenza virus subtype H5N1, and Orthoebolavirus investigations.

SARS-CoV-2 infection induces hyaluronan production in vitro and hyaluronan levels in COVID-19 patients relate to morbidity and long-term lung impairment: a prospective cohort study

We previously demonstrated that the lungs of deceased COVID-19 patients were filled with a clear hydrogel consisting of hyaluronan (HA). In this translational study, we investigated the role of HA at all stages of COVID-19 disease to map the consequences of elevated HA on morbidity and identify the mechanism of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-induced HA production. A reduced alveolar surface area was observed in the lungs of deceased COVID-19 patients compared to healthy controls, as visualized by a 3D rendering of lung morphology using light-sheet fluorescence microscopy. We confirmed the presence of HA in lung biopsies and found large quantities of proinflammatory fragmented HA. The association of systemic HA in blood plasma and disease severity was assessed in patients with mild (WHO Clinical Progression Scale, WHO-CPS, 1-5) and severe COVID-19 (WHO-CPS, 6-9) during the acute and convalescent phases and related to lung function. We found that systemic levels of HA were high during acute COVID-19 disease, remained elevated during convalescence, and were associated with a reduced diffusion capacity. In vitro 3D-lung models, differentiated from primary human bronchial epithelial cells, were used to study the effects of SARS-CoV-2 infection on HA metabolism, and transcriptomic analyses revealed a dysregulation of HA synthases and hyaluronidases, both contributing to increased HA in apical secretions. Furthermore, corticosteroid treatment reduced the inflammation and downregulated HA synthases. Our findings demonstrate that HA plays a role in COVID-19 morbidity and that sustained elevated HA concentrations may contribute to long-term respiratory impairment.IMPORTANCEThis study provides insights into the role of hyaluronan (HA) in the severity and long-term impact of COVID-19 on lung function. Through extensive morphological examination of lung tissues and a multicenter study, we identified that HA levels are significantly elevated in COVID-19 patients, correlating with a reduced lung diffusion capacity during convalescence. Using a 3D-lung model, we further uncovered how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 infection causes a dysregulated HA metabolism, leading to increased HA production. Our findings provide valuable insights into the pathogenesis of SARS-CoV-2 and suggest that targeting HA metabolism could offer new therapeutic avenues for managing COVID-19, particularly to prevent long-term lung impairment. Additionally, HA holds potential as a biomarker for predicting disease severity, which could guide personalized treatment strategies.

Altered immune cell in human severe acute pancreatitis revealed by single-cell RNA sequencing

Background

Severe acute pancreatitis (SAP) is characterized by inflammation, with inflammatory immune cells playing a pivotal role in disease progression. This study aims to understand variations in specific immune cell subtypes in SAP, uncover their mechanisms of action, and identify potential biological markers for predicting Acute Pancreatitis (AP) severity.

Methods

We collected peripheral blood from 7 untreated SAP patients and employed single-cell RNA sequencing for the first time to construct a transcriptome atlas of peripheral blood mononuclear cells (PBMCs) in SAP. Integrating SAP transcriptomic data with 6 healthy controls from the GEO database facilitated the analysis of immune cell roles in SAP. We obtained comprehensive transcriptomic datasets from AP samples in the GEO database and identified potential biomarkers associated with AP severity using the "Scissor" tool in single-cell transcriptomic data.

Results

This study presents the inaugural construction of a peripheral blood single-cell atlas for SAP patients, identifying 20 cell subtypes. Notably, there was a significant decrease in effector T cell subsets and a noteworthy increase in monocytes compared to healthy controls. Moreover, we identified a novel monocyte subpopulation expressing high levels of PPBP and PF4 which was significantly elevated in SAP. The proportion of monocyte subpopulations with high CCL3 expression was also markedly increased compared to healthy controls, as verified by flow cytometry. Additionally, cell communication analysis revealed insights into immune and inflammation-related signaling pathways in SAP patient monocytes. Finally, our findings suggest that the subpopulation with high CCL3 expression, along with upregulated pro-inflammatory genes such as S100A12, IL1B, and CCL3, holds promise as biomarkers for predicting AP severity.

Conclusion

This study reveals monocytes' crucial role in SAP initiation and progression, characterized by distinct pro-inflammatory features intricately linked to AP severity. A monocyte subpopulation with elevated PPBP and CCL3 levels emerges as a potential biomarker and therapeutic target.

Deciphering breast cancer dynamics: insights from single-cell and spatial profiling in the multi-omics era

As one of the most common tumors in women, the pathogenesis and tumor heterogeneity of breast cancer have long been the focal point of research, with the emergence of tumor metastasis and drug resistance posing persistent clinical challenges. The emergence of single-cell sequencing (SCS) technology has introduced novel approaches for gaining comprehensive insights into the biological behavior of malignant tumors. SCS is a high-throughput technology that has rapidly developed in the past decade, providing high-throughput molecular insights at the individual cell level. Furthermore, the advent of multitemporal point sampling and spatial omics also greatly enhances our understanding of cellular dynamics at both temporal and spatial levels. The paper provides a comprehensive overview of the historical development of SCS, and highlights the most recent advancements in utilizing SCS and spatial omics for breast cancer research. The findings from these studies will serve as valuable references for future advancements in basic research, clinical diagnosis, and treatment of breast cancer.

Unraveling the spatial organization and development of human thymocytes through integration of spatial transcriptomics and single-cell multi-omics profiling

The structural components of the thymus are essential for guiding T cell development, but a thorough spatial view is still absent. Here we develop the TSO-his tool, designed to integrate multimodal data from single-cell and spatial transcriptomics to decipher the intricate structure of human thymus. Specifically, we characterize dynamic changes in cell types and critical markers, identifying ELOVL4 as a mediator of CD4+ T cell positive selection in the cortex. Utilizing the mapping function of TSO-his, we reconstruct thymic spatial architecture at single-cell resolution and recapitulates classical cell types and their essential co-localization for T cell development; additionally, previously unknown co-localization relationships such as that of CD8αα with memory B cells and monocytes are identified. Incorporating VDJ sequencing data, we also delineate distinct intermediate thymocyte states during αβ T cell development. Overall, these insights enhance our understanding of thymic biology and may inform therapeutic interventions targeting T cell-mediated immune responses.

Single-cell transcriptomic analysis of radiation-induced lung injury in rat

Radiation-induced lung injury (RILI) frequently occurs as a complication following radiotherapy for chest tumors like lung and breast cancers. However, the precise underlying mechanisms of RILI remain unclear. In this study, we generated RILI models in rats treated with a single dose of 20 Gy and examined lung tissues by single-cell RNA sequencing (scRNA-seq) 2 weeks post-radiation. Analysis of lung tissues revealed 18 major cell populations, indicating an increase in cell-cell communication following radiation exposure. Neutrophils, macrophages, and monocytes displayed distinct subpopulations and uncovered potential for pro-inflammatory effects. Additionally, endothelial cells exhibited a highly inflammatory profile and the potential for reactive oxygen species (ROS) production. Furthermore, smooth muscle cells (SMC) showed a high propensity for extracellular matrix (ECM) deposition. Our findings broaden the current understanding of RILI and highlight potential avenues for further investigation and clinical applications.

Identification of Therapy-Induced Clonal Evolution and Resistance Pathways in Minimal Residual Clones in Multiple Myeloma through Single-Cell Sequencing

PURPOSE

In multiple myeloma (MM), therapy-induced clonal evolution is associated with treatment resistance and is one of the most important hindrances toward a cure for MM. To further understand the molecular mechanisms controlling the clonal evolution of MM, we applied single-cell RNA sequencing (scRNA-seq) to paired diagnostic and posttreatment bone marrow (BM) samples.

EXPERIMENTAL DESIGN

scRNA-seq was performed on 38 BM samples from patients with monoclonal gammopathy of undetermined significance (n = 1), MM patients at diagnosis (n = 19), MM posttreatment (n = 17), and one healthy donor (HD). The single-cell transcriptome data of malignant plasma cells (PC) and the surrounding immune microenvironment were analyzed.

RESULTS

Profiling by scRNA-seq data revealed three primary trajectories of transcriptional evolution after treatment: clonal elimination in patients with undetectable minimal residual disease (MRD-) and clonal stabilization and clonal selection in detectable MRD (MRD+) patients. We noted a metabolic shift toward fatty acid oxidation in cycling-resistant PCs, whereas selective PCs favored the NF-κB pathway. Intriguingly, when comparing the genetic and transcriptional dynamics, we found a significant correlation between genetic and nongenetic factors in driving the clonal evolution. Furthermore, we identified variations in cellular interactions between malignant PCs and the tumor microenvironment. Selective PCs showed the most robust cellular interactions with the tumor microenvironment.

CONCLUSIONS

These data suggest that MM cells could rapidly adapt to induction treatment through transcriptional adaptation, metabolic adaptation, and specialized immune evasion. Targeting therapy-induced resistance mechanisms may help to avert refractory disease in MM.

Robust identification of perturbed cell types in single-cell RNA-seq data

Single-cell transcriptomics has emerged as a powerful tool for understanding how different cells contribute to disease progression by identifying cell types that change across diseases or conditions. However, detecting changing cell types is challenging due to individual-to-individual and cohort-to-cohort variability and naive approaches based on current computational tools lead to false positive findings. To address this, we propose a computational tool, scDist, based on a mixed-effects model that provides a statistically rigorous and computationally efficient approach for detecting transcriptomic differences. By accurately recapitulating known immune cell relationships and mitigating false positives induced by individual and cohort variation, we demonstrate that scDist outperforms current methods in both simulated and real datasets, even with limited sample sizes. Through the analysis of COVID-19 and immunotherapy datasets, scDist uncovers transcriptomic perturbations in dendritic cells, plasmacytoid dendritic cells, and FCER1G+NK cells, that provide new insights into disease mechanisms and treatment responses. As single-cell datasets continue to expand, our faster and statistically rigorous method offers a robust and versatile tool for a wide range of research and clinical applications, enabling the investigation of cellular perturbations with implications for human health and disease.

Interferon-responsive neutrophils and macrophages extricate SARS-CoV-2 Omicron critical patients from the nasty fate of sepsis

The SARS-CoV-2 Omicron variant is characterized by its high transmissibility, which has caused a worldwide epidemiological event. Yet, it turns ominous once the disease progression degenerates into severe pneumonia and sepsis, presenting a horrendous lethality. To elucidate the alveolar immune or inflammatory landscapes of Omicron critical-ill patients, we performed single-cell RNA-sequencing (scRNA-seq) of bronchoalveolar lavage fluid (BALF) from the patients with critical pneumonia caused by Omicron infection, and analyzed the correlation between the clinical severity scores and different immune cell subpopulations. In the BALF of Omicron critical patients, the alveolar violent myeloid inflammatory environment was determined. ISG15+ neutrophils and CXCL10+ macrophages, both expressed the interferon-stimulated genes (ISGs), were negatively correlated with clinical pulmonary infection score, while septic CST7+ neutrophils and inflammatory VCAN+ macrophages were positively correlated with sequential organ failure assessment. The percentages of ISG15+ neutrophils were associated with more protective alveolar epithelial cells, and may reshape CD4+ T cells to the exhaustive phenotype, thus preventing immune injuries. The CXCL10+ macrophages may promote plasmablast/plasma cell survival and activation as well as the production of specific antibodies. As compared to the previous BALF scRNA-seq data from SARS-CoV-2 wild-type/Alpha critical patients, the subsets of neutrophils and macrophages with pro-inflammatory and immunoregulatory features presented obvious distinctions, suggesting an immune disparity in Omicron variants. Overall, this study provides a BALF single-cell atlas of Omicron critical patients, and suggests that alveolar interferon-responsive neutrophils and macrophages may extricate SARS-CoV-2 Omicron critical patients from the nasty fate of sepsis.

Antibodies utilizing VL6-57 light chains target a convergent cryptic epitope on SARS-CoV-2 spike protein and potentially drive the genesis of Omicron variants

Continued evolution of SARS-CoV-2 generates variants to challenge antibody immunity established by infection and vaccination. A connection between population immunity and genesis of virus variants has long been suggested but its molecular basis remains poorly understood. Here, we identify a class of SARS-CoV-2 neutralizing public antibodies defined by their shared usage of VL6-57 light chains. Although heavy chains of diverse genotypes are utilized, convergent HCDR3 rearrangements have been observed among these public antibodies to cooperate with germline VL6-57 LCDRs to target a convergent epitope defined by RBD residues S371-S373-S375. Antibody repertoire analysis identifies that this class of VL6-57 antibodies is present in SARS-CoV-2-naive individuals and is clonally expanded in most COVID-19 patients. We confirm that Omicron-specific substitutions at S371, S373 and S375 mediate escape of antibodies of the VL6-57 class. These findings support that this class of public antibodies constitutes a potential immune pressure promoting the introduction of S371L/F-S373P-S375F in Omicron variants. The results provide further molecular evidence to support that antigenic evolution of SARS-CoV-2 is driven by antibody mediated population immunity.

Scupa: Single-cell unified polarization assessment of immune cells using the single-cell foundation model

Immune cells undergo cytokine-driven polarization in respond to diverse stimuli. This process significantly modulates their transcriptional profiles and functional states. Although single-cell RNA sequencing (scRNA-seq) has advanced our understanding of immune responses across various diseases or conditions, currently there lacks a method to systematically examine cytokine effects and immune cell polarization. To address this gap, we developed Single-cell unified polarization assessment (Scupa), the first computational method for comprehensive immune cell polarization analysis. Scupa is trained on data from the Immune Dictionary, which characterizes 66 cytokine-driven polarization states across 14 immune cell types. By leveraging the cell embeddings from the Universal Cell Embeddings model, Scupa effectively identifies polarized cells in new datasets generated from different species and experimental conditions. Applications of Scupa in independent datasets demonstrated its accuracy in classifying polarized cells and further revealed distinct polarization profiles in tumor-infiltrating myeloid cells across cancers. Scupa complements conventional single-cell data analysis by providing new insights into immune cell polarization, and it holds promise for assessing molecular effects or identifying therapeutic targets in cytokine-based therapies.

SARS-CoV2 infection in whole lung primarily targets macrophages that display subset-specific responses

Deciphering the initial steps of SARS-CoV-2 infection, that influence COVID-19 outcomes, is challenging because animal models do not always reproduce human biological processes and in vitro systems do not recapitulate the histoarchitecture and cellular composition of respiratory tissues. To address this, we developed an innovative ex vivo model of whole human lung infection with SARS-CoV-2, leveraging a lung transplantation technique. Through single-cell RNA-seq, we identified that alveolar and monocyte-derived macrophages (AMs and MoMacs) were initial targets of the virus. Exposure of isolated lung AMs, MoMacs, classical monocytes and non-classical monocytes (ncMos) to SARS-CoV-2 variants revealed that while all subsets responded, MoMacs produced higher levels of inflammatory cytokines than AMs, and ncMos contributed the least. A Wuhan lineage appeared to be more potent than a D614G virus, in a dose-dependent manner. Amidst the ambiguity in the literature regarding the initial SARS-CoV-2 cell target, our study reveals that AMs and MoMacs are dominant primary entry points for the virus, and suggests that their responses may conduct subsequent injury, depending on their abundance, the viral strain and dose. Interfering on virus interaction with lung macrophages should be considered in prophylactic strategies.

A Novel Human Extravascular Monocyte Subset with Antiviral Functions Is Crucial for Resolving Lung Tissue Infection

The recurring emergence of novel respiratory viruses has highlighted our poor understanding of the human immune mechanisms governing the resolution of lung infection in an immunologically naïve context. Using SARS-CoV-2 as a prototypical emerging respiratory virus, we leveraged mice co-engrafted with a genetically matched fetal lung xenograft (fLX) and a human immune system (BLT-L mice) to investigate such mechanisms. While BLT-L mice effectively resolve SARS-CoV-2 infection following acute viral replication in fLX, viral clearance is robustly abrogated through systemic depletion of CD4+, but not CD3+ or CD8+ cells, resulting in persistent infection. Leveraging single-cell transcriptomics to uncover the CD4-expressing subsets driving infection resolution, we identified a novel subset of lung extravascular inflammatory monocytes (ExiMO) with antiviral functions. ExiMO are the dominant CD163-expressing myeloid population emerging in fLX upon acute infection and derive from recruited circulating CD4+ monocytes. They are highly enriched in viral RNA and elicit a robust antiviral response before vanishing from tissues when infection resolves. Notably, systemic CD4+ cell depletion results in impaired recruitment of CD163+ cells into fLX and leads to a state of immune tolerance and chronic infection defined by the absence of ExiMO antiviral responses. Together, our study uncovers ExiMO as major sentinels driving SARS-CoV-2 infection resolution in human lung tissues without pre-existing immunity. This work expands our understanding of lung extravascular monocytes and unravels novel facets of the cellular determinants governing our vulnerability to viral respiratory pathogens.

Identification of a Novel ECM Remodeling Macrophage Subset in AKI to CKD Transition by Integrative Spatial and Single-Cell Analysis

The transition from acute kidney injury (AKI) to chronic kidney disease (CKD) is a critical clinical issue. Although previous studies have suggested macrophages as a key player in promoting inflammation and fibrosis during this transition, the heterogeneity and dynamic characterization of macrophages are still poorly understood. Here, we used integrated single-cell RNA sequencing and spatial transcriptomic to characterize the spatiotemporal heterogeneity of macrophages in murine AKI-to-CKD model of unilateral ischemia-reperfusion injury. A marked increase in macrophage infiltration at day 1 was followed by a second peak at day 14 post AKI. Spatiotemporal profiling revealed that injured tubules and macrophages co-localized early after AKI, whereas in late chronic stages had spatial proximity to fibroblasts. Further pseudotime analysis revealed two distinct lineages of macrophages in this transition: renal resident macrophages differentiated into the pro-repair subsets, whereas infiltrating monocyte-derived macrophages contributed to chronic inflammation and fibrosis. A novel macrophage subset, extracellular matrix remodeling-associated macrophages (EAMs) originating from monocytes, linked to renal fibrogenesis and communicated with fibroblasts via insulin-like growth factors (IGF) signalling. In sum, our study identified the spatiotemporal dynamics of macrophage heterogeneity with a unique subset of EAMs in AKI-to-CKD transition, which could be a potential therapeutic target for preventing CKD development.

Age-associated clonal B cells drive B cell lymphoma in mice

Although cancer is an age-related disease, how the processes of aging contribute to cancer progression is not well understood. In this study, we uncovered how mouse B cell lymphoma develops as a consequence of a naturally aged system. We show here that this malignancy is associated with an age-associated clonal B cell (ACBC) population that likely originates from age-associated B cells. Driven by c-Myc activation, promoter hypermethylation and somatic mutations, IgM+ ACBCs clonally expand independently of germinal centers and show increased biological age. ACBCs become self-sufficient and support malignancy when transferred into young recipients. Inhibition of mTOR or c-Myc in old mice attenuates pre-malignant changes in B cells during aging. Although the etiology of mouse and human B cell lymphomas is considered distinct, epigenetic changes in transformed mouse B cells are enriched for changes observed in human B cell lymphomas. Together, our findings characterize the spontaneous progression of cancer during aging through both cell-intrinsic and microenvironmental changes and suggest interventions for its prevention.

S100a8/A9 proteins: critical regulators of inflammation in cardiovascular diseases

Neutrophil hyperexpression is recognized as a key prognostic factor for inflammation and is closely related to the emergence of a wide range of cardiovascular disorders. In recent years, S100 calcium binding protein A8/A9 (S100A8/A9) derived from neutrophils has attracted increasing attention as an important warning protein for cardiovascular disease. This article evaluates the utility of S100A8/A9 protein as a biomarker and therapeutic target for diagnosing cardiovascular diseases, considering its structural features, fundamental biological properties, and its multifaceted influence on cardiovascular conditions including atherosclerosis, myocardial infarction, myocardial ischemia/reperfusion injury, and heart failure.

Computational identification of mitochondrial dysfunction biomarkers in severe SARS-CoV-2 infection: Facilitating therapeutic applications of phytomedicine

BACKGROUND

Currently, SARS-CoV-2 has not disappeared and continues to prevail worldwide, with the ongoing risk of mutations and the potential for severe COVID-19. The impairment of monocyte mitochondrial function caused by SARS-CoV-2, leading to a metabolic and immune dysregulation, is a crucial factor in the development of severe COVID-19.

PURPOSE

Discover effective phytomedicines based on mitochondrial-related biomarkers in severe SARS-CoV-2 infection.

METHODS

Firstly, differential gene analysis and gene set enrichment analysis (GSEA) were conducted on monocytes datasets to identify genes and pathways distinguishing severe patients from uninfected individuals. Then, GO and KEGG enrichment analysis on the differentially expressed genes (DEGs) obtained. Take the DEGs and intersect them with the MitoCarta 3.0 gene set to obtain the differentially expressed mitochondrial-related genes (DE-MRGs). Subsequently, machine learning algorithms were employed to screen potential mitochondrial dysfunction biomarkers for severe COVID-19 based on score values. ROC curves were then plotted to assess the distinguish capability of the biomarkers, followed by validation using two additional independent datasets. Next, the effects of the identified biomarkers on metabolic pathways and immune cells were explored through Gene Set Variation Analysis (GSVA) and CIBERSORT. Finally, potential nature products for severe COVID-19 were screened from the expression profile dataset based on dysregulated mitochondrial-related genes, followed by in vitro experimental validation.

RESULTS

There are 1812 DEGs and 17 dysregulated mitochondrial processes between severe COVID-19 patients and uninfected individuals. A total of 77 DE-MRGs were identified, and the potential biomarkers were identified as RECQL4, PYCR1, PIF1, POLQ, and GLDC. In both the training and validation sets, the area under the ROC curve (AUC) for these five biomarkers was greater than 0.9. And they did not show significant changes in mild to moderate patients (p > 0.05), indicating their ability to effectively distinguish severe COVID-19. These biomarkers exhibit a highly significant correlation with the dysregulated metabolic processes (p < 0.05) and immune cell imbalance (p < 0.05) in severe patients, as demonstrated by GSVA and CIBERSORT algorithms. Curcumin has the highest score in the predictive model based on transcriptomic data from 496 natural compounds (p = 0.02; ES = 0.90). Pre-treatment with curcumin for 8 h has been shown to alleviate mitochondrial membrane potential damage caused by the SARS-CoV-2 S1 protein (p < 0.05) and reduce elevated levels of reactive oxygen species (ROS) (p < 0.01).

CONCLUSION

The results of this study indicate a significant correlation between severe SARS-CoV-2 infection and mitochondrial dysfunction. The proposed mitochondrial dysfunction biomarkers identified in this study are associated with the disease progression, metabolic and immune changes in severe SARS-CoV-2 infected patients. Curcumin has a potential role in preventing severe COVID-19 by protecting mitochondrial function. Our findings provide new strategies for predicting the prognosis and enabling early intervention in SARS-CoV-2 infection.

Immunological characterization and comparison of children with COVID-19 from their adult counterparts at single-cell resolution

Introduction

The immunological characteristics that could protect children with coronavirus disease 2019 (COVID-19) from severe or fatal illnesses have not been fully understood yet.

Methods

Here, we performed single-cell RNA sequencing (scRNA-seq) analysis on peripheral blood samples of 15 children (8 with COVID-19) and compared them to 18 adults (13 with COVID-19).

Results

The child-adult integrated single cell data indicated that children with the disease presented a restrained response to type I interferon in most of the major immune cell types, along with suppression of upstream interferon regulatory factor and toll-like receptor expression in monocytes, which was confirmed by in vitro interferon stimulation assays. Unlike adult patients, children with COVID-19 showed lower frequencies of activated proinflammatory CD14+ monocytes, possibly explaining the rareness of cytokine storm in them. Notably, natural killer (NK) cells in pediatric patients displayed potent cytotoxicity with a rich expression of cytotoxic molecules and upregulated cytotoxic pathways, whereas the cellular senescence, along with the Notch signaling pathway, was significantly downregulated in NK cells, all suggesting more robust cytotoxicity in NK cells of children than adult patients that was further confirmed by CD107a degranulation assays. Lastly, a modest adaptive immune response was evident with more naïve T cells but less activated and proliferated T cells while less naïve B cells but more activated B cells in children over adult patients.

Conclusion

Conclusively, this preliminary study revealed distinct cell frequency and activation status of major immune cell types, particularly more robust NK cell cytotoxicity in PBMC that might help protect children from severe COVID-19.

Recent infection with SARS-CoV-2 in donors was associated with a higher incidence of acute graft-versus-host disease in recipients undergoing allogeneic haematopoietic stem cell transplantation

The global pandemic has resulted in the common occurrence of SARS-CoV-2 infection in the population. In the post-pandemic era, it is imperative to understand the influence of donor SARS-CoV-2 infection on outcomes after allogeneic haematopoietic stem cell transplantation (allo-HSCT). We retrospectively analysed allo-HSCTs from donors with mild SARS-CoV-2 infection or early recovery stage (ERS) (group 1, n = 65) and late recovery stage (group 2, n = 120). Additionally, we included allo-HSCT from donors without prior SARS-CoV-2 infection as group 0 (n = 194). Transplants from donors with different SARS-CoV-2 infection status had comparable primary engraftment and survival rates. However, group 1 had higher incidences of acute graft-versus-host disease (aGvHD), grade II-IV (41.5% vs. 28.1% in group 0 [p = 0.014] and 30.6% in group 2 [p = 0.067]) and grade III-IV (22.2% vs. 9.6% [p = 0.004] in group 0 and 12.2% in group 2 [p = 0.049]). Conversely, the risk of aGvHD in group 2 was similar to that in group 0 (p > 0.5). Multivariable analysis identified group 1 associated with grade II-IV (hazard ratio [HR] 2.307, p = 0.010) and grade III-IV (HR 2.962, p = 0.001) aGvHD, which yielded no significant risk factors for survival. In conclusion, we preliminarily demonstrated donors in the active infection state or ERS of mild SARS-CoV-2 infection were associated with higher incidences of aGvHD in transplants from related donors.

Single-cell landscape of peripheral immune response in patients with anti-melanoma differentiation-associated gene 5 dermatomyositis

OBJECTIVE

Anti-melanoma differentiation-associated gene 5 (Anti-MDA5)-positive DM is a rare but life-threatening autoimmune disorder that is associated with a high risk of developing rapidly progressive interstitial lung disease. Current empirical therapies offer limited benefit in terms of patient survival, as little is known about the aetiology of anti-MDA5 DM. To best understand its immune landscape, we applied single-cell RNA sequencing (scRNA-seq) to peripheral blood samples from DM patients and healthy controls.

METHODS

Peripheral blood mononuclear cells (PBMCs) from eight DM patients (including three distinct subtypes of DM) and two healthy donors were sequenced using the 10X Genomics platform. Additional scRNA-seq data for four healthy donors were incorporated for further bioinformatic analysis.

RESULTS

Aberrantly increased proportions of CD14+ monocytes and plasma cells were observed in anti-MDA5 DM PBMC samples. Moreover, we found an overactivated type I IFN response and antiviral immunity in both innate and adaptive immune cells derived from anti-MDA5 DM patients that was positively correlated with disease severity. Importantly, a unique subset of CD14+ monocytes that highly expressed IFN alpha-inducible protein 27 (IFI27), a biomarker for viral infection, and IFN induced with helicase C domain 1 (IFIH1, which encodes MDA5) was specifically identified in anti-MDA5 DM samples for the first time.

CONCLUSION

Our study has illustrated the peripheral immune cell atlas of a number of DM subtypes, has provided compelling evidence for a viral infection-derived origin for anti-MDA5 DM, and has indicated potential targets for innovative therapeutic interventions.

Cytotoxic Lymphocyte-Monocyte Complex Reflects the Dynamics of Coronavirus Disease 2019 Systemic Immune Response

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes a variety of clinical manifestations, many of which originate from altered immune responses, either locally or systemically. Immune cell cross-talk occurs mainly in lymphoid organs. However, systemic cell interaction specific to coronavirus disease 2019 has not been well characterized. Here, by employing single-cell RNA sequencing and imaging flow cytometry analysis, we unraveled, in peripheral blood, a heterogeneous group of cell complexes formed by the adherence of CD14+ monocytes to different cytotoxic lymphocytes, including SARS-CoV-2-specific CD8+ T cells, γδ T cells, and natural killer T cells. These lymphocytes attached to CD14+ monocytes that showed enhanced inflammasome activation and pyroptosis-induced cell death in progression stage; in contrast, in the convalescent phase, CD14+ monocytes with elevated antigen presentation potential were targeted by cytotoxic lymphocytes, thereby restricting the excessive immune activation. Collectively, our study reports previously unrecognized cell-cell interplay in the SARS-CoV-2-specific immune response, providing new insight into the intricacy of dynamic immune cell interaction representing antiviral defense.

ReCIDE: robust estimation of cell type proportions by integrating single-reference-based deconvolutions

In this study, we introduce Robust estimation of Cell type proportions by Integrating single-reference-based DEconvolutions (ReCIDE), an innovative framework for robust estimation of cell type proportions by integrating single-reference-based deconvolutions. ReCIDE outperforms existing approaches in benchmark and real datasets, particularly excelling in estimating rare cell type proportions. Through exploratory analysis on public bulk data of triple-negative breast cancer (TNBC) patients using ReCIDE, we demonstrate a significant correlation between the prognosis of TNBC patients and the proportions of both T cell and perivascular-like cell subtypes. Built upon this discovery, we develop a prognostic assessment model for TNBC patients. Our contribution presents a novel framework for enhancing deconvolution accuracy, showcasing its effectiveness in medical research.

Reduction in ACE2 expression in peripheral blood mononuclear cells during COVID-19 - implications for post COVID-19 conditions

BACKGROUND

Severe COVID-19 is uncommon, restricted to 19% of the total population. In response to the first virus wave (alpha variant of SARS-CoV-2), we investigated whether a biomarker indicated severity of disease and, in particular, if variable expression of angiotensin converting enzyme 2 (ACE2) in blood might clarify this difference in risk and of post COVID -19 conditions (PCC).

METHODS

The IRB-approved study compared patients hospitalized with severe COVID-19 to healthy controls. Severe infection was defined requiring oxygen or increased oxygen need from baseline at admission with positive COVID-19 PCR. A single blood sample was obtained from patients within a day of admission. ACE2 RNA expression in blood cells was measured by an RT-PCR assay. Plasma ACE1 and ACE2 enzyme activities were quantified by fluorescent peptides. Plasma TIMP-1, PIIINP and MMP-9 antigens were quantified by ELISA. Data were entered into REDCap and analyzed using STATA v 14 and GraphPad Prism v 10.

RESULTS

Forty-eight patients and 72 healthy controls were recruited during the pandemic. ACE2 RNA expression in peripheral blood mononuclear cells (PBMC) was rarely detected acutely during severe COVID-19 but common in controls (OR for undetected ACE2: 12.4 [95% CI: 2.62-76.1]). ACE2 RNA expression in PBMC did not determine plasma ACE1 and ACE2 activity, suggesting alternative cell-signaling pathways. Markers of fibrosis (TIMP-1 and PIIINP) and vasculopathy (MMP-9) were additionally elevated. ACE2 RNA expression during severe COVID-19 often responded within hours to convalescent plasma. Analogous to oncogenesis, we speculate that potent, persistent, cryptic processes following COVID-19 (the renin-angiotensin system (RAS), fibrosis and vasculopathy) initiate or promote post-COVID-19 conditions (PCC) in susceptible individuals.

CONCLUSIONS

This work elucidates biological and temporal plausibility for ACE2, TIMP1, PIIINP and MMP-9 in the pathogenesis of PCC. Intersection of these independent systems is uncommon and may in part explain the rarity of PCC.

Integrating single-nucleus RNA sequencing and spatial transcriptomics to elucidate a specialized subpopulation of astrocytes, microglia and vascular cells in brains of mouse model of lipopolysaccharide-induced sepsis-associated encephalopathy

BACKGROUND

Understanding the mechanism behind sepsis-associated encephalopathy (SAE) remains a formidable task. This study endeavors to shed light on the complex cellular and molecular alterations that occur in the brains of a mouse model with SAE, ultimately unraveling the underlying mechanisms of this condition.

METHODS

We established a murine model using intraperitoneal injection of lipopolysaccharide (LPS) in wild type and Anxa1-/- mice and collected brain tissues for analysis at 0-hour, 12-hour, 24-hour, and 72-hour post-injection. Utilizing advanced techniques such as single-nucleus RNA sequencing (snRNA-seq) and Stereo-seq, we conducted a comprehensive characterization of the cellular responses and molecular patterns within the brain.

RESULTS

Our study uncovered notable temporal differences in the response to LPS challenge between Anxa1-/- (annexin A1 knockout) and wild type mice, specifically at the 12-hour and 24-hour time points following injection. We observed a significant increase in the proportion of Astro-2 and Micro-2 cells in these mice. These cells exhibited a colocalization pattern with the vascular subtype Vas-1, forming a distinct region known as V1A2M2, where Astro-2 and Micro-2 cells surrounded Vas-1. Moreover, through further analysis, we discovered significant upregulation of ligands and receptors such as Timp1-Cd63, Timp1-Itgb1, Timp1-Lrp1, as well as Ccl2-Ackr1 and Cxcl2-Ackr1 within this region. In addition, we observed a notable increase in the expression of Cd14-Itgb1, Cd14-Tlr2, and Cd14-C3ar1 in regions enriched with Micro-2 cells. Additionally, Cxcl10-Sdc4 showed broad upregulation in brain regions containing both Micro-2 and Astro-2 cells. Notably, upon LPS challenge, there was an observed increase in Anxa1 expression in the mouse brain. Furthermore, our study revealed a noteworthy increase in mortality rates following Anxa1 knockdown. However, we did not observe substantial differences in the types, numbers, or distribution of other brain cells between Anxa1-/- and wildtype mice over time. Nevertheless, when comparing the 24-hour post LPS injection time point, we observed a significant decrease in the proportion and distribution of Micro-2 and Astro-2 cells in the vicinity of blood vessels in Anxa1-/- mice. Additionally, we noted reduced expression levels of several ligand-receptor pairs including Cd14-Tlr2, Cd14-C3ar1, Cd14-Itgb1, Cxcl10-Sdc4, Ccl2-Ackr1, and Cxcl2-Ackr1.

CONCLUSIONS

By combining snRNA-seq and Stereo-seq techniques, our study successfully identified a distinctive cellular colocalization, referred to as a special pathological niche, comprising Astro-2, Micro-2, and Vas-1 cells. Furthermore, we observed an upregulation of ligand-receptor pairs within this niche. These findings suggest a potential association between this cellular arrangement and the underlying mechanisms contributing to SAE or the increased mortality observed in Anxa1 knockdown mice.

Single-cell sequencing: Current applications in various tuberculosis specimen types

Tuberculosis (TB) is a chronic disease caused by Mycobacterium tuberculosis (M.tb) and responsible for millions of deaths worldwide each year. It has a complex pathogenesis that primarily affects the lungs but can also impact systemic organs. In recent years, single-cell sequencing technology has been utilized to characterize the composition and proportion of immune cell subpopulations associated with the pathogenesis of TB disease since it has a high resolution that surpasses conventional techniques. This paper reviews the current use of single-cell sequencing technologies in TB research and their application in analysing specimens from various sources of TB, primarily peripheral blood and lung specimens. The focus is on how these technologies can reveal dynamic changes in immune cell subpopulations, genes and proteins during disease progression after M.tb infection. Based on the current findings, single-cell sequencing has significant potential clinical value in the field of TB research. Next, we will focus on the real-world applications of the potential targets identified through single-cell sequencing for diagnostics, therapeutics and the development of effective vaccines.

Exploring the immune characteristions of CRKP pneumonia at single-cell level

The immune dysregulation associated with carbapenem-resistant Klebsiella pneumoniae (CRKP) severity was investigated through single-cell RNA sequencing (scRNA-seq) of 5 peripheral blood samples from 3 patients with moderate and severe CRKP pneumonia. Additionally, scRNA-seq datasets from two individuals with COVID-19 were included for comparative analysis. The dynamic characterization and functional properties of each immune cell type were examined by delineating the transcriptional profiles of immune cells throughout the transition from moderate to severe conditions. Overall, most immune cells in CRKP patients exhibited a robust interferon-α response and inflammatory reaction compared to healthy controls, mirroring observations in COVID-19 patients. Furthermore, cell signatures associated with NK cells, macrophages, and monocytes were identified in CRKP progression including PTPRCAP for NK cells, C1QB for macrophages, and S100A12 for both macrophages and monocytes. In summary, this study offers a comprehensive scRNA-seq resource for illustrating the dynamic immune response patterns during CRKP progression, thereby shedding light on the associations between CRKP and COVID-19.

Single-cell analysis reveals lasting immunological consequences of influenza infection and respiratory immunization in the pig lung

The pig is a natural host for influenza viruses and integrally involved in virus evolution through interspecies transmissions between humans and swine. Swine have many physiological, anatomical, and immunological similarities to humans, and are an excellent model for human influenza. Here, we employed single cell RNA-sequencing (scRNA-seq) and flow cytometry to characterize the major leukocyte subsets in bronchoalveolar lavage (BAL), twenty-one days after H1N1pdm09 infection or respiratory immunization with an adenoviral vector vaccine expressing hemagglutinin and nucleoprotein with or without IL-1β. Mapping scRNA-seq clusters from BAL onto those previously described in peripheral blood facilitated annotation and highlighted differences between tissue resident and circulating immune cells. ScRNA-seq data and functional assays revealed lasting impacts of immune challenge on BAL populations. First, mucosal administration of IL-1β reduced the number of functionally active Treg cells. Second, influenza infection upregulated IFI6 in BAL cells and decreased their susceptibility to virus replication in vitro. Our data provide a reference map of porcine BAL cells and reveal lasting immunological consequences of influenza infection and respiratory immunization in a highly relevant large animal model for respiratory virus infection.

Target-Oriented Reference Construction for supervised cell-type identification in scRNA-seq

Cell-type identification is the most crucial step in single cell RNA-seq (scRNA-seq) data analysis, for which the supervised cell-type identification method is a desired solution due to the accuracy and efficiency. The performance of such methods is highly dependent on the quality of the reference data. Even though there are many supervised cell-type identification tools, there is no method for selecting and constructing reference data. Here we develop Target-Oriented Reference Construction (TORC), a widely applicable strategy for constructing reference given target dataset in scRNA-seq supervised cell-type identification. TORC alleviates the differences in data distribution and cell-type composition between reference and target. Extensive benchmarks on simulated and real data analyses demonstrate consistent improvements in cell-type identification from TORC. TORC is freely available at https://github.com/weix21/TORC.

T-Cell Epitope Mapping of SARS-CoV-2 Reveals Coordinated IFN-γ Production and Clonal Expansion of T Cells Facilitates Recovery from COVID-19

BACKGROUND

T-cell responses can be protective or detrimental during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection; however, the underlying mechanism is poorly understood.

METHODS

In this study, we screened 144 15-mer peptides spanning the SARS-CoV-2 spike, nucleocapsid (NP), M, ORF8, ORF10, and ORF3a proteins and 39 reported SARS-CoV-1 peptides in peripheral blood mononuclear cells (PBMCs) from nine laboratory-confirmed coronavirus disease 2019 (COVID-19) patients (five moderate and four severe cases) and nine healthy donors (HDs) collected before the COVID-19 pandemic. T-cell responses were monitored by IFN-γ and IL-17A production using ELISA, and the positive samples were sequenced for the T cell receptor (TCR) β chain. The positive T-cell responses to individual SARS-CoV-2 peptides were validated by flow cytometry.

RESULTS

COVID-19 patients with moderate disease produced more IFN-γ than HDs and patients with severe disease (moderate vs. HDs, p < 0.0001; moderate vs. severe, p < 0.0001) but less IL-17A than those with severe disease (p < 0.0001). A positive correlation was observed between IFN-γ production and T-cell clonal expansion in patients with moderate COVID-19 (r = 0.3370, p = 0.0214) but not in those with severe COVID-19 (r = -0.1700, p = 0.2480). Using flow cytometry, we identified that a conserved peptide of the M protein (Peptide-120, P120) was a dominant epitope recognized by CD8+ T cells in patients with moderate disease.

CONCLUSION

Coordinated IFN-γ production and clonal expansion of SARS-CoV-2-specific T cells are associated with disease resolution in COVID-19. Our findings contribute to a better understanding of T-cell-mediated immunity in COVID-19 and may inform future strategies for managing and preventing severe outcomes of SARS-CoV-2 infection.

Comparative analysis of dynamic transcriptomes reveals specific COVID-19 features and pathogenesis of immunocompromised populations

A dysfunction of human host genes and proteins in coronavirus infectious disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a key factor impacting clinical symptoms and outcomes. Yet, a detailed understanding of human host immune responses is still incomplete. Here, we applied RNA sequencing to 94 samples of COVID-19 patients with and without hematological tumors as well as COVID-19 uninfected non-tumor individuals to obtain a comprehensive transcriptome landscape of both hematological tumor patients and non-tumor individuals. In our analysis, we further accounted for the human-SARS-CoV-2 protein interactome, human protein interactome, and human protein complex subnetworks to understand the mechanisms of SARS-CoV-2 infection and host immune responses. Our data sets enabled us to identify important SARS-CoV-2 (non-)targeted differentially expressed genes and complexes post-SARS-CoV-2 infection in both hematological tumor and non-tumor individuals. We found several unique differentially expressed genes, complexes, and functions/pathways such as blood coagulation (APOE, SERPINE1, SERPINE2, and TFPI), lipoprotein particle remodeling (APOC2, APOE, and CETP), and pro-B cell differentiation (IGHM, VPREB1, and IGLL1) during COVID-19 infection in patients with hematological tumors. In particular, APOE, a gene that is associated with both blood coagulation and lipoprotein particle remodeling, is not only upregulated in hematological tumor patients post-SARS-CoV-2 infection but also significantly expressed in acute dead patients with hematological tumors, providing clues for the design of future therapeutic strategies specifically targeting COVID-19 in patients with hematological tumors. Our data provide a rich resource for understanding the specific pathogenesis of COVID-19 in immunocompromised patients, such as those with hematological malignancies, and developing effective therapeutics for COVID-19.

IMPORTANCE

A majority of previous studies focused on the characterization of coronavirus infectious disease 2019 (COVID-19) disease severity in people with normal immunity, while the characterization of COVID-19 in immunocompromised populations is still limited. Our study profiles changes in the transcriptome landscape post-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in hematological tumor patients and non-tumor individuals. Furthermore, our integrative and comparative systems biology analysis of the interactome, complexome, and transcriptome provides new insights into the tumor-specific pathogenesis of COVID-19. Our findings confirm that SARS-CoV-2 potentially tends to target more non-functional host proteins to indirectly affect host immune responses in hematological tumor patients. The identified unique genes, complexes, functions/pathways, and expression patterns post-SARS-CoV-2 infection in patients with hematological tumors increase our understanding of how SARS-CoV-2 manipulates the host molecular mechanism. Our observed differential genes/complexes and clinical indicators of normal/long infection and deceased COVID-19 patients provide clues for understanding the mechanism of COVID-19 progression in hematological tumors. Finally, our study provides an important data resource that supports the increasing value of the application of publicly accessible data sets to public health.

A Regularized Bayesian Dirichlet-multinomial Regression Model for Integrating Single-cell-level Omics and Patient-level Clinical Study Data

The abundance of various cell types can vary significantly among patients with varying phenotypes and even those with the same phenotype. Recent scientific advancements provide mounting evidence that other clinical variables, such as age, gender, and lifestyle habits, can also influence the abundance of certain cell types. However, current methods for integrating single-cell-level omics data with clinical variables are inadequate. In this study, we propose a regularized Bayesian Dirichlet-multinomial regression framework to investigate the relationship between single-cell RNA sequencing data and patient-level clinical data. Additionally, the model employs a novel hierarchical tree structure to identify such relationships at different cell-type levels. Our model successfully uncovers significant associations between specific cell types and clinical variables across three distinct diseases: pulmonary fibrosis, COVID-19, and non-small cell lung cancer. This integrative analysis provides biological insights and could potentially inform clinical interventions for various diseases.

Interstitial macrophages are a focus of viral takeover and inflammation in COVID-19 initiation in human lung

Early stages of deadly respiratory diseases including COVID-19 are challenging to elucidate in humans. Here, we define cellular tropism and transcriptomic effects of SARS-CoV-2 virus by productively infecting healthy human lung tissue and using scRNA-seq to reconstruct the transcriptional program in "infection pseudotime" for individual lung cell types. SARS-CoV-2 predominantly infected activated interstitial macrophages (IMs), which can accumulate thousands of viral RNA molecules, taking over 60% of the cell transcriptome and forming dense viral RNA bodies while inducing host profibrotic (TGFB1, SPP1) and inflammatory (early interferon response, CCL2/7/8/13, CXCL10, and IL6/10) programs and destroying host cell architecture. Infected alveolar macrophages (AMs) showed none of these extreme responses. Spike-dependent viral entry into AMs used ACE2 and Sialoadhesin/CD169, whereas IM entry used DC-SIGN/CD209. These results identify activated IMs as a prominent site of viral takeover, the focus of inflammation and fibrosis, and suggest targeting CD209 to prevent early pathology in COVID-19 pneumonia. This approach can be generalized to any human lung infection and to evaluate therapeutics.

Innate Immunity in Protection and Pathogenesis During Coronavirus Infections and COVID-19

The COVID-19 pandemic was caused by the recently emerged β-coronavirus SARS-CoV-2. SARS-CoV-2 has had a catastrophic impact, resulting in nearly 7 million fatalities worldwide to date. The innate immune system is the first line of defense against infections, including the detection and response to SARS-CoV-2. Here, we discuss the innate immune mechanisms that sense coronaviruses, with a focus on SARS-CoV-2 infection and how these protective responses can become detrimental in severe cases of COVID-19, contributing to cytokine storm, inflammation, long-COVID, and other complications. We also highlight the complex cross talk among cytokines and the cellular components of the innate immune system, which can aid in viral clearance but also contribute to inflammatory cell death, cytokine storm, and organ damage in severe COVID-19 pathogenesis. Furthermore, we discuss how SARS-CoV-2 evades key protective innate immune mechanisms to enhance its virulence and pathogenicity, as well as how innate immunity can be therapeutically targeted as part of the vaccination and treatment strategy. Overall, we highlight how a comprehensive understanding of innate immune mechanisms has been crucial in the fight against SARS-CoV-2 infections and the development of novel host-directed immunotherapeutic strategies for various diseases.

Single-Cell Sequencing: High-Resolution Analysis of Cellular Heterogeneity in Autoimmune Diseases

Autoimmune diseases (AIDs) are complex in etiology and diverse in classification but clinically show similar symptoms such as joint pain and skin problems. As a result, the diagnosis is challenging, and usually, only broad treatments can be available. Consequently, the clinical responses in patients with different types of AIDs are unsatisfactory. Therefore, it is necessary to conduct more research to figure out the pathogenesis and therapeutic targets of AIDs. This requires research technologies with strong extraction and prediction capabilities. Single-cell sequencing technology analyses the genomic, epigenomic, or transcriptomic information at the single-cell level. It can define different cell types and states in greater detail, further revealing the molecular mechanisms that drive disease progression. These advantages enable cell biology research to achieve an unprecedented resolution and scale, bringing a whole new vision to life science research. In recent years, single-cell technology especially single-cell RNA sequencing (scRNA-seq) has been widely used in various disease research. In this paper, we present the innovations and applications of single-cell sequencing in the medical field and focus on the application contributing to the differential diagnosis and precise treatment of AIDs. Despite some limitations, single-cell sequencing has a wide range of applications in AIDs. We finally present a prospect for the development of single-cell sequencing. These ideas may provide some inspiration for subsequent research.

Heatstroke Comorbid with SARS-CoV-2 Infection: A Case Report and Literature Review

Background

Hyperthermia and multiple organ dysfunction syndrome (MODS) are the main characteristics of heatstroke and COVID-19. Differentiating between these illnesses is crucial during a summer COVID-19 pandemic, but cases of heatstroke comorbid with COVID-19 are rarely reported.

Case description

We report the first case of heatstroke comorbid with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection in a 52-year-old male. After receiving intravenous antibiotics, organ protection measures, and treatment for coagulation disorders, his fever and coma resolved. However, he developed dyspnea and cerebral hemorrhage after several days. This patient experienced a multi-pathogen pulmonary infection and an intractable coagulopathy that ultimately resulted in MODS and death.

Conclusion

The combination of heatstroke and SARS-CoV-2 infection exacerbated inflammation, immune abnormalities, and coagulation disorders. The interaction between inflammation and coagulation disturbances contributed to the underlying mechanism in this case, highlighting the importance of early anti-infection, treatment for coagulopathy, immune regulation, and organ protection as crucial interventions.

Deciphering Abnormal Platelet Subpopulations in COVID-19, Sepsis and Systemic Lupus Erythematosus through Machine Learning and Single-Cell Transcriptomics

This study focuses on understanding the transcriptional heterogeneity of activated platelets and its impact on diseases such as sepsis, COVID-19, and systemic lupus erythematosus (SLE). Recognizing the limited knowledge in this area, our research aims to dissect the complex transcriptional profiles of activated platelets to aid in developing targeted therapies for abnormal and pathogenic platelet subtypes. We analyzed single-cell transcriptional profiles from 47,977 platelets derived from 413 samples of patients with these diseases, utilizing Deep Neural Network (DNN) and eXtreme Gradient Boosting (XGB) to distinguish transcriptomic signatures predictive of fatal or survival outcomes. Our approach included source data annotations and platelet markers, along with SingleR and Seurat for comprehensive profiling. Additionally, we employed Uniform Manifold Approximation and Projection (UMAP) for effective dimensionality reduction and visualization, aiding in the identification of various platelet subtypes and their relation to disease severity and patient outcomes. Our results highlighted distinct platelet subpopulations that correlate with disease severity, revealing that changes in platelet transcription patterns can intensify endotheliopathy, increasing the risk of coagulation in fatal cases. Moreover, these changes may impact lymphocyte function, indicating a more extensive role for platelets in inflammatory and immune responses. This study identifies crucial biomarkers of platelet heterogeneity in serious health conditions, paving the way for innovative therapeutic approaches targeting platelet activation, which could improve patient outcomes in diseases characterized by altered platelet function.

The gonadal niche safeguards human fetal germline cell development following maternal SARS-CoV-2 infection

During pregnancy, germline development is vital for maintaining the continuation of species. Recent studies have shown increased pregnancy risks in COVID-19 patients at the perinatal stage. However, the potential consequence of infection for reproductive quality in developing fetuses remains unclear. Here, we analyze the transcriptome and DNA methylome of the fetal germline following maternal severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We find that infection at early gestational age, a critical period of human primordial germ cell specification and epigenetic reprogramming, trivially affects fetal germ cell (FGC) development. Additionally, FGC-niche communications are not compromised by maternal infection. Strikingly, both general and SARS-CoV-2-specific immune pathways are greatly activated in gonadal niche cells to protect FGCs from maternal infection. Notably, there occurs an "in advance" development tendency in FGCs after maternal infection. Our study provides insights into the impacts of maternal SARS-CoV-2 infection on fetal germline development and serves as potential clinical guidance for future pandemics.

Activation of CD14+ Monocytes via the IFN-γ Signaling Pathway Is Associated with Immune-Related Adverse Events in Hepatocellular Carcinoma Patients Receiving PD-1 Inhibition Combination Therapy

(1) Background: Immune-related adverse events (irAEs) are a series of unique organ-specific inflammatory toxicities observed in patients with hepatocellular carcinoma (HCC) undergoing PD-1 inhibition combination therapy. The specific underlying mechanisms remain unclear. (2) Methods: We recruited 71 patients with HCC undergoing PD-1 inhibition combination therapy. These patients were then divided into two groups based on irAE occurrence: 34 had irAEs and 37 did not. Using Olink proteomics, we analyzed the aberrant inflammation-related proteins (IRPs) in these patient groups. For single-cell RNA sequencing (scRNA-seq) analysis, we collected peripheral blood mononuclear cells (PBMCs) from two representative patients at the pretreatment, irAE occurrence, and resolution stages. (3) Results: Our study revealed distinct plasma protein signatures in HCC patients experiencing irAEs after PD-1 inhibition combination therapy. We clarified the relationship between monocyte activation and irAEs, identified a strongly associated CD14-MC-CCL3 monocyte subset, and explored the role of the IFN-γ signaling pathway in monocyte activation during irAEs. (4) Conclusions: The activation of monocytes induced by the IFN-γ signaling pathway is an important mechanism underlying the occurrence of irAEs in HCC patients receiving PD-1 inhibition combination therapy.

Joint multi-omics discriminant analysis with consistent representation learning using PANDA

Integrative multi-omics analysis provides deeper insight and enables better and more realistic modeling of the underlying biology and causes of diseases than does single omics analysis. Although several integrative multi-omics analysis methods have been proposed and demonstrated promising results in integrating distinct omics datasets, inconsistent distribution of the different omics data, which is caused by technology variations, poses a challenge for paired integrative multi-omics methods. In addition, the existing discriminant analysis-based integrative methods do not effectively exploit correlation and consistent discriminant structures, necessitating a compromise between correlation and discrimination in using these methods. Herein we present PAN-omics Discriminant Analysis (PANDA), a joint discriminant analysis method that seeks omics-specific discriminant common spaces by jointly learning consistent discriminant latent representations for each omics. PANDA jointly maximizes between-class and minimizes within-class omics variations in a common space and simultaneously models the relationships among omics at the consistency representation and cross-omics correlation levels, overcoming the need for compromise between discrimination and correlation as with the existing integrative multi-omics methods. Because of the consistency representation learning incorporated into the objective function of PANDA, this method seeks a common discriminant space to minimize the differences in distributions among omics, can lead to a more robust latent representations than other methods, and is against the inconsistency of the different omics. We compared PANDA to 10 other state-of-the-art multi-omics data integration methods using both simulated and real-world multi-omics datasets and found that PANDA consistently outperformed them while providing meaningful discriminant latent representations. PANDA is implemented using both R and MATLAB, with codes available at https://github.com/WuLabMDA/PANDA.

Single-cell analysis of anti-BCMA CAR T cell therapy in patients with central nervous system autoimmunity

Chimeric antigen receptor (CAR) T cell immunotherapy for the treatment of neurological autoimmune diseases is promising, but CAR T cell kinetics and immune alterations after treatment are poorly understood. Here, we performed single-cell multi-omics sequencing of paired cerebrospinal fluid (CSF) and blood samples from patients with neuromyelitis optica spectrum disorder (NMOSD) treated with anti-B cell maturation antigen (BCMA) CAR T cells. Proliferating cytotoxic-like CD8+ CAR T cell clones were identified as the main effectors in autoimmunity. Anti-BCMA CAR T cells with enhanced features of chemotaxis efficiently crossed the blood-CSF barrier, eliminated plasmablasts and plasma cells in the CSF, and suppressed neuroinflammation. The CD44-expressing early memory phenotype in infusion products was potentially associated with CAR T cell persistence in autoimmunity. Moreover, CAR T cells from patients with NMOSD displayed distinctive features of suppressed cytotoxicity compared with those from hematological malignancies. Thus, we provide mechanistic insights into CAR T cell function in patients with neurological autoimmune disease.

CircRNA: a rising therapeutic strategy for lung injury induced by pulmonary toxicants

Lung injury has been a serious medical problem that requires new therapeutic approaches and biomarkers. Circular RNAs (circRNAs) are non-coding RNAs (ncRNAs) that exist widely in eukaryotes. CircRNAs are single-stranded RNAs that form covalently closed loops. CircRNAs are significant gene regulators that have a role in the development, progression, and therapy of lung injury by controlling transcription, translating into protein, and sponging microRNAs (miRNAs) and proteins. Although the study of circRNAs in lung injury caused by pulmonary toxicants is just beginning, several studies have revealed their expression patterns. The function that circRNAs perform in relation to pulmonary toxicants (severe acute respiratory distress syndrome coronavirus-2 (SARS-CoV-2), drug abuse, PM2.5, and cigarette smoke) is the main topic of this review. A variety of circRNAs can serve as potential biomarkers of lung injury. In this review, the biogenesis, properties, and biological functions of circRNAs were concluded, and the relationship between circRNAs and pulmonary toxicants was discussed. It is expected that the new ideas and potential treatment targets that circRNAs provide would be beneficial to research into the molecular mechanisms behind lung injury.

Stem Cell Extracellular Vesicles as Anti-SARS-CoV-2 Immunomodulatory Therapeutics: A Systematic Review of Clinical and Preclinical Studies

BACKGROUND

COVID-19 rapidly escalated into a worldwide pandemic with elevated infectivity even from asymptomatic patients. Complications can lead to severe pneumonia and acute respiratory distress syndrome (ARDS), which are the main contributors to death. Because of their regenerative and immunomodulatory capacities, stem cells and their derived extracellular vesicles (EVs) are perceived as promising therapies against severe pulmonary conditions, including those associated with COVID-19. Herein, we evaluate the safety and efficacy of stem cell EVs in treating COVID-19 and complicating pneumonia, acute lung injury, and ARDS. We also cover relevant preclinical studies to recapitulate the current progress in stem cell EV-based therapy.

METHODS

Using PubMed, Cochrane Central Register of Controlled Trials, Scopus, and Web of Science, we searched for all English-language published studies (2000-2023) that used stem cell EVs as a therapy for COVID-19, ARDS, or pneumonia. The risk of bias (ROB) was assessed for all studies.

RESULTS

Forty-eight studies met our inclusion criteria. Various-sized EVs derived from different types of stem cells were reported as a potentially safe and effective therapy to attenuate the cytokine storm induced by COVID-19. EVs alleviated inflammation and regenerated the alveolar epithelium by decreasing apoptosis, proinflammatory cytokines, neutrophil infiltration, and M2 macrophage polarization. They also prevented fibrin production and promoted the production of anti-inflammatory cytokines and endothelial cell junction proteins.

CONCLUSION

Similar to their parental cells, stem cell EVs mediate lung tissue regeneration by targeting multiple pathways and thus hold promise in promoting the recovery of COVID-19 patients and improving the survival rate of severely affected patients.

A comparative analysis of TCR immune repertoire in COVID-19 patients

The coronavirus disease 2019 (COVID-19) has merged as a global health threat since its outbreak in December 2019. Despite widespread recognition, there has been a paucity of studies focusing on the T cell receptor (TCR) bias in adaptive immunity induced by SARS-CoV-2. This research conducted a comparative analysis of the TCR immune repertoire to identify notable αβ TCR bias sequences associated with the SARS-CoV-2 virus antigen. The present study encompassed 73 symptomatic COVID-19 patients, categorized as moderate/mild or severe/critical, along with 9 healthy controls. Our findings revealed specific TCR chains prominently utilized by moderate and severe patients, identified as TRAV30-J34-TRBV3-1-J2-7 and TRAV12-3-J6-TRBV28-J1-1, respectively. Additionally, our research explored critical TCR preferences in the bronchoalveolar lavage fluid (BALF) of COVID-19 patients at various disease stages. Indeed, monitoring the dynamics of immune repertoire changes in COVID-19 patients could serve as a crucial biomarker for predicting disease progression and recovery. Furthermore, the study explored TCR bias in both peripheral blood mononuclear cells (PBMCs) and BALF. The most common αβ VJ pair observed in BALF was TRAV12-3-J18-TRBV7-6-J2-7. In addition, a comparative analysis with the VDJdb database indicated that the HLA-A*02:01 allele exhibited the widest distribution and highest frequency in COVID-19 patients across different periods. This comprehensive examination provided a global characterization of the TCR immune repertoire in COVID-19 patients, contributing significantly to our understanding of TCR bias induced by SARS-CoV-2.

Single-cell immune repertoire analysis

Single-cell T cell and B cell antigen receptor-sequencing data analysis can potentially perform in-depth assessments of adaptive immune cells that inform on understanding immune cell development to tracking clonal expansion in disease and therapy. However, it has been extremely challenging to analyze and interpret T cells and B cells and their adaptive immune receptor repertoires at the single-cell level due to not only the complexity of the data but also the underlying biology. In this Review, we delve into the computational breakthroughs that have transformed the analysis of single-cell T cell and B cell antigen receptor-sequencing data.

Multi-omics analysis reveals COVID-19 vaccine induced attenuation of inflammatory responses during breakthrough disease

The immune mechanisms mediating COVID-19 vaccine attenuation of COVID-19 remain undescribed. We conducted comprehensive analyses detailing immune responses to SARS-CoV-2 virus in blood post-vaccination with ChAdOx1 nCoV-19 or a placebo. Samples from randomised placebo-controlled trials (NCT04324606 and NCT04400838) were taken at baseline, onset of COVID-19-like symptoms, and 7 days later, confirming COVID-19 using nucleic amplification test (NAAT test) via real-time PCR (RT-PCR). Serum cytokines were measured with multiplexed immunoassays. The transcriptome was analysed with long, short and small RNA sequencing. We found attenuation of RNA inflammatory signatures in ChAdOx1 nCoV-19 compared with placebo vaccinees and reduced levels of serum proteins associated with COVID-19 severity. KREMEN1, a putative alternative SARS-CoV-2 receptor, was downregulated in placebo compared with ChAdOx1 nCoV-19 vaccinees. Vaccination ameliorates reductions in cell counts across leukocyte populations and platelets noted at COVID-19 onset, without inducing potentially deleterious Th2-skewed immune responses. Multi-omics integration links a global reduction in miRNA expression at COVID-19 onset to increased pro-inflammatory responses at the mRNA level. This study reveals insights into the role of COVID-19 vaccines in mitigating disease severity by abrogating pro-inflammatory responses associated with severe COVID-19, affirming vaccine-mediated benefit in breakthrough infection, and highlighting the importance of clinically relevant endpoints in vaccine evaluation.

[Prevention and treatment of COVID-19 based on post-genomic pharmacological analysis: Systematic computer analysis of 290,000 scientific articles on COVID-19]

The COVID-19 pandemic has highlighted pressing challenges in biomedical research methodology. It has become obvious that the rapid and effective development of treatments for "new" viral infections is impossible without the coordination of interdisciplinary research and in-depth analysis of data obtained within the framework of the post-genomic paradigm. Presents the results of a systematic computer analysis of 290,000 scientific articles on COVID-19, with an emphasis on the results of post-genomic studies of SARS-CoV-2. The futility of the overly simplified approach, which considers only one "most important receptor protein", only one "key virus gene", etc., is shown. It is shown how post-genomic technologies will make it possible to find informative biomarkers of severe coronavirus infection, including those based on complex immune disorders associated with COVID-19.

Powerful and accurate detection of temporal gene expression patterns from multi-sample multi-stage single-cell transcriptomics data with TDEseq

We present a non-parametric statistical method called TDEseq that takes full advantage of smoothing splines basis functions to account for the dependence of multiple time points in scRNA-seq studies, and uses hierarchical structure linear additive mixed models to model the correlated cells within an individual. As a result, TDEseq demonstrates powerful performance in identifying four potential temporal expression patterns within a specific cell type. Extensive simulation studies and the analysis of four published scRNA-seq datasets show that TDEseq can produce well-calibrated p-values and up to 20% power gain over the existing methods for detecting temporal gene expression patterns.