Dynamic blood single-cell immune responses in patients with COVID-19

Selectively T cell phosphorylation activation of azvudine in the thymus tissue with immune protection effect

Thymus is the important immune organ, responsible for T cell development and differentiation. The lower circulating T counts have been observed in patients who died from COVID-19 compared with survivors. Azvudine, also known as FNC, is a thymus-homing anti-SARS-CoV-2 drug in treating COVID-19 patients. In this study, single-cell transcriptome, proteomics, and parallel reaction monitoring (PRM) were applied to insight into the activation process of FNC in rat and SARS-CoV-2 rhesus monkey thymus. The results indicated that thymic immune cells possess a robust metabolic capacity for cytidine-analogue drugs such as FNC. Key enzymes involved in the FNC phosphorylation process, such as Dck, Cmpk1, and Nme2, were highly expressed in CD4+ T cells, CD8+ T cells, and DP (CD4+ CD8+) cells. Additionally, FNC could upregulate multiple phosphorylated kinases in various cell types while downregulating the phosphatases, phosphoribosyl transferases, and deaminases, respectively. The robust phosphorylation capacity of the thymus for cytidine analogue drug FNC, and the activation effect of FNC on the NAs metabolism system potentially contribute to its enrichment in the thymus and immune protection effect. This suggests that it is crucial to consider the expression level of phosphorylation kinases when evaluating NA drug properties, as an important factor during antiviral drug design.

Critical COVID-19, Victivallaceae abundance, and celiac disease: A mediation Mendelian randomization study

Celiac disease exhibits a higher prevalence among patients with coronavirus disease 2019. However, the potential influence of COVID-19 on celiac disease remains uncertain. Considering the significant association between gut microbiota alterations, COVID-19 and celiac disease, the two-step Mendelian randomization method was employed to investigate the genetic causality between COVID-19 and celiac disease, with gut microbiota as the potential mediators. We employed the genome-wide association study to select genetic instrumental variables associated with the exposure. Subsequently, these variables were utilized to evaluate the impact of COVID-19 on the risk of celiac disease and its potential influence on gut microbiota. Employing a two-step Mendelian randomization approach enabled the examination of potential causal relationships, encompassing: 1) the effects of COVID-19 infection, hospitalized COVID-19 and critical COVID-19 on the risk of celiac disease; 2) the influence of gut microbiota on celiac disease; and 3) the mediating impact of the gut microbiota between COVID-19 and the risk of celiac disease. Our findings revealed a significant association between critical COVID-19 and an elevated risk of celiac disease (inverse variance weighted [IVW]: P = 0.035). Furthermore, we observed an inverse correlation between critical COVID-19 and the abundance of Victivallaceae (IVW: P = 0.045). Notably, an increased Victivallaceae abundance exhibits a protective effect against the risk of celiac disease (IVW: P = 0.016). In conclusion, our analysis provides genetic evidence supporting the causal connection between critical COVID-19 and lower Victivallaceae abundance, thereby increasing the risk of celiac disease.

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.

Longitudinal Mapping of Personal Biotic and Abiotic Exposomes and Transcriptome in Underwater Confined Space Using Wearable Passive Samplers

Silicone-based passive samplers, commonly paired with gas chromatography-mass spectrometry (GC-MS) analysis, are increasingly utilized for personal exposure assessments. However, its compatibility with the biotic exposome remains underexplored. In this study, we introduce the wearable silicone-based AirPie passive sampler, coupled with nontargeted liquid chromatography with high-resolution tandem mass spectrometry (LC-HRMS/MS), GC-HRMS, and metagenomic shotgun sequencing methods, offering a comprehensive view of personalized airborne biotic and abiotic exposomes. We applied the AirPie samplers to 19 participants in a unique deep underwater confined environment, annotating 4,390 chemical and 2,955 microbial exposures, integrated with corresponding transcriptomic data. We observed significant shifts in environmental exposure and gene expression upon entering this unique environment. We noted increased exposure to pollutants, such as benzenoids, polycyclic aromatic hydrocarbons (PAHs), opportunistic pathogens, and associated antibiotic-resistance genes (ARGs). Transcriptomic analyses revealed the activation of neurodegenerative disease-related pathways, mostly related to chemical exposure, and the repression of immune-related pathways, linked to both biological and chemical exposures. In summary, we provided a comprehensive, longitudinal exposome map of the unique environment and underscored the intricate linkages between external exposures and human health. We believe that the AirPie sampler and associated analytical methods will have broad applications in exposome and precision medicine.

Clinical and immunologic features of co-infection in COVID-19 patients, along with potential traditional Chinese medicine treatments

Objectives

With the increasing number of people worldwide infected with SARS-CoV-2, the likelihood of co-infection and/or comorbidities is rising. The impact of these co-infections on the patient's immune system remains unclear. This study aims to investigate the immunological characteristics of secondary infections in hospitalized COVID-19 patients, and preliminarily predict potential therapeutic effects of traditional Chinese medicine and their derivatives for the treatment of co-infections.

Methods

In this retrospective cohort study, we included 131 hospitalized patients with laboratory-confirmed COVID-19, of whom there were 64 mild and 67 severe cases. We analyzed clinical characteristics and immunologic data, including circulating immune cell numbers, levels of inflammatory factors and viral load, comparing COVID-19 patients with and without co-infection.

Results

Among 131 hospitalized COVID-19 patients, 41 (31.3%) were co-infection positive, with 33 (80.5%) having severe disease and 14 (34.1%) of them resulting in fatalities. Co-infected patients exhibited significantly higher severity and mortality rates compared to non-co-infected counterparts. Co-infected patients had significantly lower absolute counts of lymphocytes, total T lymphocytes, CD4+ T cells, CD8+ T cells and B lymphocytes, while levels of hs-CRP, PCT and IL-6 were significantly elevated compared to non-co-infected patients. Additionally, the viral load of co-infected patients was significantly higher than non-co-infected patients.

Conclusion

Co-infection emerges as a dangerous factor for COVID-19 patients, elevating the risk of severe pneumonia and mortality. Co-infection suppresses the host's immune response by reducing the number of lymphocytes and increasing inflammation, thereby diminishing the antiviral and anti-infective effects of the immune system, which promotes the severity of the disease. Therefore, it is crucial to implement infection prevention measures to minimize the spread of co-infections among COVID-19 hospitalized patients. Additionally, changes in these biomarkers provide a theoretical basis for the effective treatment of co-infections with traditional Chinese medicine.

Genetic correlations, shared risk genes and immunity landscapes between COVID-19 and venous thromboembolism: evidence from GWAS and bulk transcriptome data

BACKGROUND

Patients with coronavirus disease 2019 (COVID-19) were vulnerable to venous thromboembolism (VTE), which further increases the risk of unfavorable outcomes. However, neither genetic correlations nor shared genes underlying COVID-19 and VTE are well understood.

OBJECTIVE

This study aimed to characterize genetic correlations and common pathogenic mechanisms between COVID-19 and VTE.

METHODS

We used linkage disequilibrium score (LDSC) regression and Mendelian Randomization (MR) analysis to investigate the genetic associations and causal effects between COVID-19 and VTE, respectively. Then, the COVID-19 and VTE-related datasets were obtained from the Gene Expression Omnibus (GEO) database and analyzed by bioinformatics and systems biology approaches with R software, including weighted gene co-expression network analysis (WGCNA), enrichment analysis, and single-cell transcriptome sequencing analysis. The miRNA-genes and transcription factor (TF)-genes interaction networks were conducted by NetworkAnalyst. We performed the secondary analysis of the ATAC-seq and Chip-seq datasets to address the epigenetic-regulating relationship of the shared genes.

RESULTS

This study demonstrated positive correlations between VTE and COVID-19 by LDSC and bidirectional MR analysis. A total of 26 potential shared genes were discovered from the COVID-19 dataset (GSE196822) and the VTE dataset (GSE19151), with 19 genes showing positive associations and 7 genes exhibiting negative associations with these diseases. After incorporating two additional datasets, GSE164805 (COVID-19) and GSE48000 (VTE), two hub genes TP53I3 and SLPI were identified and showed up-regulation and diagnostic capabilities in both illnesses. Furthermore, this study illustrated the landscapes of immune processes in COVID-19 and VTE, revealing the downregulation in effector memory CD8+ T cells and activated B cells. The single-cell sequencing analysis suggested that the hub genes were predominantly expressed in the monocytes of COVID-19 patients at high levels. Additionally, we identified common regulators of hub genes, including five miRNAs (miR-1-3p, miR-203a-3p, miR-210-3p, miR-603, and miR-124-3p) and one transcription factor (RELA).

CONCLUSIONS

Collectively, our results highlighted the significant correlations between COVID-19 and VTE and pinpointed TP53I3 and SLPI as hub genes that potentially link the severity of both conditions. The hub genes and their common regulators might present an opportunity for the simultaneous treatment of these two diseases.

Immune characteristics of kidney transplant recipients with acute respiratory distress syndrome induced by COVID-19 at single-cell resolution

BACKGROUND

COVID-19-induced acute respiratory distress syndrome (ARDS) can result in tissue damage and multiple organ dysfunction, especially in kidney transplant recipients (KTRs) receiving immunosuppressive drugs. Presently, single-cell research on COVID-19-induced ARDS is considerably advanced, yet knowledge about ARDS in KTRs is still constrained.

METHODS

Single-cell RNA sequencing (scRNA-seq) analysis was performed to construct a comprehensive single-cell immune landscape of the peripheral blood mononuclear cells (PBMCs) of eight patients with COVID-19-induced ARDS, five KTRs with COVID-19-induced ARDS, and five healthy individuals. Subsequently, we conducted a comprehensive bioinformatics analysis, including cell clustering, enrichment analysis, trajectory analysis, gene regulatory network analysis, and cell-cell interaction analysis, to investigate the heterogeneity of the immune microenvironment in KTRs with ARDS.

RESULT

Our study revealed that KTRs exhibit significant heterogeneity with COVID-19-induced ARDS compared with those of other individuals, with significant reductions in T cells, as well as an abnormal proliferation of B cells and monocytes. In the context of dual influences from immunosuppression and viral infection, KTRs exhibited more specific plasma cells, along with significant enrichment of dysfunctional GZMB and XAF1 double-positive effector T cells and IFI27-positive monocytes. Additionally, robust communication existed among T cells and monocytes in cytokine signaling. These effects impede the process of immune reconstitution in KTR patients.

CONCLUSION

Our findings suggest that KTRs with COVID-19-induced ARDS show elevated antibody levels, impaired T cell differentiation, and dysregulation of innate immunity. In summary, this study provides a theoretical foundation for a comprehensive understanding of COVID-19-induced ARDS in KTRs.

Longitudinal single cell atlas identifies complex temporal relationship between type I interferon response and COVID-19 severity

Due to the paucity of longitudinal molecular studies of COVID-19, particularly those covering the early stages of infection (Days 1-8 symptom onset), our understanding of host response over the disease course is limited. We perform longitudinal single cell RNA-seq on 286 blood samples from 108 age- and sex-matched COVID-19 patients, including 73 with early samples. We examine discrete cell subtypes and continuous cell states longitudinally, and we identify upregulation of type I IFN-stimulated genes (ISGs) as the predominant early signature of subsequent worsening of symptoms, which we validate in an independent cohort and corroborate by plasma markers. However, ISG expression is dynamic in progressors, spiking early and then rapidly receding to the level of severity-matched non-progressors. In contrast, cross-sectional analysis shows that ISG expression is deficient and IFN suppressors such as SOCS3 are upregulated in severe and critical COVID-19. We validate the latter in four independent cohorts, and SOCS3 inhibition reduces SARS-CoV-2 replication in vitro. In summary, we identify complexity in type I IFN response to COVID-19, as well as a potential avenue for host-directed therapy.

Ferroptosis in cardiovascular diseases: role and mechanism

In multicellular organisms, regulatory cell death is a crucial aspect of growth and development. Ferroptosis, which was postulated roughly ten years ago, is a mode of cell death that differs from apoptosis, autophagy, and pyrodeath. This distinct pattern of cell death is triggered by an imbalance between oxidants and antioxidants and strongly associated with the metabolism of iron, lipids, amino acids, and glutathione. A growing body of research has implicated ferroptosis in the incidence and progression of many organ traumas and degenerative diseases. Recently, ferroptosis has gained attention as a crucial regulatory mechanism underlying the initiation and development of a variety of cardiovascular diseases, including myocardial ischemia/reperfusion injury, cardiomyopathy, arrhythmia, chemotherapy, and Corona Virus-2-induced cardiac injury. Pharmacological therapies that inhibit ferroptosis have great potential for the management of cardiovascular disorders. This review discusses the prevalence and regulatory mechanisms of ferroptosis, effect of ferroptosis on the immune system, significance of ferroptosis in cardiovascular diseases, and potential therapeutic value of regulating ferroptosis in a variety of heart diseases.

Crosstalk of ferroptosis and oxidative stress in infectious diseases

Ferroptosis is a type of programmed cell death that pathogens can leverage to enhance their replication, transmission, and pathogenicity. Hosts typically combat pathogenic infections by utilizing oxidative stress as a defense mechanism. Nonetheless, some pathogens can trigger considerable oxidative stress while infecting, inducing an intense inflammatory response in the host's immune system and activating cell death. The process of ferroptosis is closely linked to oxidative stress, with their interaction exerting a substantial impact on the outcome of infectious diseases. This article presents an overview of the interrelated mechanisms of both Ferroptosis and oxidative stress in infectious diseases, identifying potential targets for treating such diseases in the context of their interaction.

γδ T cells: origin and fate, subsets, diseases and immunotherapy

The intricacy of diseases, shaped by intrinsic processes like immune system exhaustion and hyperactivation, highlights the potential of immune renormalization as a promising strategy in disease treatment. In recent years, our primary focus has centered on γδ T cell-based immunotherapy, particularly pioneering the use of allogeneic Vδ2+ γδ T cells for treating late-stage solid tumors and tuberculosis patients. However, we recognize untapped potential and optimization opportunities to fully harness γδ T cell effector functions in immunotherapy. This review aims to thoroughly examine γδ T cell immunology and its role in diseases. Initially, we elucidate functional differences between γδ T cells and their αβ T cell counterparts. We also provide an overview of major milestones in γδ T cell research since their discovery in 1984. Furthermore, we delve into the intricate biological processes governing their origin, development, fate decisions, and T cell receptor (TCR) rearrangement within the thymus. By examining the mechanisms underlying the anti-tumor functions of distinct γδ T cell subtypes based on γδTCR structure or cytokine release, we emphasize the importance of accurate subtyping in understanding γδ T cell function. We also explore the microenvironment-dependent functions of γδ T cell subsets, particularly in infectious diseases, autoimmune conditions, hematological malignancies, and solid tumors. Finally, we propose future strategies for utilizing allogeneic γδ T cells in tumor immunotherapy. Through this comprehensive review, we aim to provide readers with a holistic understanding of the molecular fundamentals and translational research frontiers of γδ T cells, ultimately contributing to further advancements in harnessing the therapeutic potential of γδ T cells.

Differential activation of programmed cell death in patients with severe SARS-CoV-2 infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes severe lower airway disease and death in a subset of patients. Knowledge on the relative contribution of programmed cell death (PCD) to lung pathology is limited to few human autopsy studies with small sample size/scope, in vitro cell culture, and experimental model systems. In this study, we sought to identify, localize, and quantify activation of apoptosis, ferroptosis, pyroptosis, and necroptosis in FFPE lung tissues from patients that died from severe SARS-CoV-2 infection (n = 28) relative to uninfected controls (n = 13). Immunofluorescence (IF) staining, whole-slide imaging, and Image J software was used to localize and quantify expression of SARS-CoV-2 nucleoprotein and the following PCD protein markers: cleaved Caspase-3, pMLKL, cleaved Gasdermin D, and CD71, respectively. IF showed differential activation of each PCD pathway in infected lungs and dichotomous staining for SARS-CoV-2 nucleoprotein enabling distinction between high (n = 9) vs low viral burden (n = 19). No differences were observed in apoptosis and ferroptosis in SARS-CoV-2 infected lungs relative to uninfected controls. However, both pyroptosis and necroptosis were significantly increased in SARS-CoV-2-infected lungs. Increased pyroptosis was observed in SARS-CoV-2 infected lungs, irrespective of viral burden, suggesting an inflammation-driven mechanism. In contrast, necroptosis exhibited a very strong positive correlation with viral burden (R2 = 0.9925), suggesting a direct SARS-CoV-2 mediated effect. These data indicate a possible novel mechanism for viral-mediated necroptosis and a potential role for both lytic programmed cell death pathways, necroptosis and pyroptosis, in mediating infection outcome.

NK cell subsets and dysfunction during viral infection: a new avenue for therapeutics?

In the setting of viral challenge, natural killer (NK) cells play an important role as an early immune responder against infection. During this response, significant changes in the NK cell population occur, particularly in terms of their frequency, location, and subtype prevalence. In this review, changes in the NK cell repertoire associated with several pathogenic viral infections are summarized, with a particular focus placed on changes that contribute to NK cell dysregulation in these settings. This dysregulation, in turn, can contribute to host pathology either by causing NK cells to be hyperresponsive or hyporesponsive. Hyperresponsive NK cells mediate significant host cell death and contribute to generating a hyperinflammatory environment. Hyporesponsive NK cell populations shift toward exhaustion and often fail to limit viral pathogenesis, possibly enabling viral persistence. Several emerging therapeutic approaches aimed at addressing NK cell dysregulation have arisen in the last three decades in the setting of cancer and may prove to hold promise in treating viral diseases. However, the application of such therapeutics to treat viral infections remains critically underexplored. This review briefly explores several therapeutic approaches, including the administration of TGF-β inhibitors, immune checkpoint inhibitors, adoptive NK cell therapies, CAR NK cells, and NK cell engagers among other therapeutics.

The role of cell death in SARS-CoV-2 infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), showing high infectiousness, resulted in an ongoing pandemic termed coronavirus disease 2019 (COVID-19). COVID-19 cases often experience acute respiratory distress syndrome, which has caused millions of deaths. Apart from triggering inflammatory and immune responses, many viral infections can cause programmed cell death in infected cells. Cell death mechanisms have a vital role in maintaining a suitable environment to achieve normal cell functionality. Nonetheless, these processes are dysregulated, potentially contributing to disease pathogenesis. Over the past decades, multiple cell death pathways are becoming better understood. Growing evidence suggests that the induction of cell death by the coronavirus may significantly contributes to viral infection and pathogenicity. However, the interaction of SARS-CoV-2 with cell death, together with its associated mechanisms, is yet to be elucidated. In this review, we summarize the existing evidence concerning the molecular modulation of cell death in SARS-CoV-2 infection as well as viral-host interactions, which may shed new light on antiviral therapy against SARS-CoV-2.

Intracellular peptides in SARS-CoV-2-infected patients

Intracellular peptides (InPeps) generated by the orchestrated action of the proteasome and intracellular peptidases have biological and pharmacological significance. Here, human plasma relative concentration of specific InPeps was compared between 175 patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and 45 SARS-CoV-2 non-infected patients; 2,466 unique peptides were identified, of which 67% were InPeps. The results revealed differences of a specific group of peptides in human plasma comparing non-infected individuals to patients infected by SARS-CoV-2, following the results of the semi-quantitative analyses by isotope-labeled electrospray mass spectrometry. The protein-protein interactions networks enriched pathways, drawn by genes encoding the proteins from which the peptides originated, revealed the presence of the coronavirus disease/COVID-19 network solely in the group of patients fatally infected by SARS-CoV-2. Thus, modulation of the relative plasma levels of specific InPeps could be employed as a predictive tool for disease outcome.

Transcriptome from Paired Samples Improves the Power of Comprehensive COVID-19 Host-Viral Characterization

Previous transcriptome profiling studies showed significantly upregulated genes and altered biological pathways in acute COVID-19. However, changes in the transcriptional signatures during a defined time frame are not yet examined and described. The aims of this study included viral metagenomics and evaluation of the total expression in time-matched and tissue-matched paired COVID-19 samples with the analysis of the host splicing profile to reveal potential therapeutic targets. Prospective analysis of paired nasopharyngeal swabs (NPS) and blood (BL) samples from 18 COVID-19 patients with acute and resolved infection performed using Kallisto, Suppa2, Centrifuge, EdgeR, PantherDB, and L1000CDS2 tools. In NPS, we discovered 6 genes with changed splicing and 40 differentially expressed genes (DEG) that yielded 88 altered pathways. Blood samples yielded 15 alternatively spliced genes. Although the unpaired DEG analysis failed, pairing identified 78 genes and 242 altered pathways with meaningful clinical interpretation and new candidate drug combinations with up to 65% overlap. Metagenomics analyses showed SARS-CoV-2 dominance during and after the acute infection, with a significant reduction in NPS (0.008 vs. 0.002, p = 0.019). Even though both NPS and BL give meaningful insights into expression changes, this is the first demonstration of how the power of blood analysis is vastly maximized by pairing. The obtained results essentially showed that pairing is a determinant between a failed and a comprehensive study. Finally, the bioinformatics results prove to be a comprehensive tool for full-action insights, drug development, and infectious disease research when designed properly.

Single-cell RNA sequencing reveals the transcriptomic characteristics of peripheral blood mononuclear cells in hepatitis B vaccine non-responders

The emergence of a vaccine against hepatitis B has proven to be an important milestone in the prevention of this disease; however, 5%-10% of vaccinated individuals do not generate an immune response to the vaccine, and its molecular mechanism has not been clarified. In this study, single-cell RNA sequencing was performed on peripheral blood mononuclear cells (PBMCs) from three volunteers with a high immune response (HR) and three with no immune response (NR) to the hepatitis B vaccine. We found that the antigen-presenting activity scores of various antigen-presenting cells, the mitogen-activated protein kinase (MAPK) pathway activity scores of naive B cells, and the cell activity scores of three types of effector T cells were significantly decreased, whereas the cytotoxicity scores of CD3highCD16lowKLRG1high natural killer T (NKT) cells were significantly increased in the NR group compared with those in the HR group. Additionally, the expression levels of some classical molecules associated with distinct signaling pathways-including HLA-B, HLA-DRB5, BLNK, BLK, IL4R, SCIMP, JUN, CEBPB, NDFIP1, and TXNIP-were significantly reduced in corresponding subsets of PBMCs from the NR group relative to those of the HR group. Furthermore, the expression of several cytotoxicity-related effector molecules, such as GNLY, NKG7, GZMB, GZMM, KLRC1, KLRD1, PRF1, CST7, and CTSW, was significantly higher in CD3highCD16lowKLRG1high NKT cells derived from non-responders. Our study provides a molecular basis for the lack of response to the hepatitis B vaccine, including defective antigen presentation, decreased T cell activity, and reduced IL-4 secretion, as well as novel insight into the role of NKT cells in the immune response to the hepatitis B vaccine.

The use of RNA-based treatments in the field of cancer immunotherapy

Over the past several decades, mRNA vaccines have evolved from a theoretical concept to a clinical reality. These vaccines offer several advantages over traditional vaccine techniques, including their high potency, rapid development, low-cost manufacturing, and safe administration. However, until recently, concerns over the instability and inefficient distribution of mRNA in vivo have limited their utility. Fortunately, recent technological advancements have mostly resolved these concerns, resulting in the development of numerous mRNA vaccination platforms for infectious diseases and various types of cancer. These platforms have shown promising outcomes in both animal models and humans. This study highlights the potential of mRNA vaccines as a promising alternative approach to conventional vaccine techniques and cancer treatment. This review article aims to provide a thorough and detailed examination of mRNA vaccines, including their mechanisms of action and potential applications in cancer immunotherapy. Additionally, the article will analyze the current state of mRNA vaccine technology and highlight future directions for the development and implementation of this promising vaccine platform as a mainstream therapeutic option. The review will also discuss potential challenges and limitations of mRNA vaccines, such as their stability and in vivo distribution, and suggest ways to overcome these issues. By providing a comprehensive overview and critical analysis of mRNA vaccines, this review aims to contribute to the advancement of this innovative approach to cancer treatment.

Effect of antiviral and immunomodulatory treatment on a cytokine profile in patients with COVID-19

Background

The severity of COVID-19 is associated with an elevated level of a variety of inflammatory mediators. Increasing evidence suggests that the Th17 response contributes to the severity of COVID-19 pneumonia, whereas Th22 response plays a regulatory role in SARS-CoV-2 infection. Two main types of available COVID-19 treatments are antivirals and immunomodulatory drugs; however, their effect on a cytokine profile is yet to be determined.

Methods

This study aim to analyse a cytokine profile in peripheral blood from patients with COVID-19 (n=44) undergoing antiviral or/and immunomodulatory treatment and healthy controls (n=20). Circulating CD4+ and CD8+ T cells and their intracellular expression of IL-17A and IL-22 were assessed by flow cytometry.

Results

Initial results showed an overexpression of IL-17F, IL-17A, CCL5/RANTES, GM-CSF, IL-4, IL-10, CXCL-10/IP-10 and IL-6 in COVID-19 patients compared to healthy controls. Treatment with remdesivir resulted in a significant decline in concentrations of IL-6, IL-10, IFN-alpha and CXCL10/IP-10. Immunomodulatory treatment contributed to a significant downregulation of IL-10, IFN-alpha, CXCL10/IP-10 and B7-H3 as well as upregulation of IL-22 and IL-1 beta. A combination of an antiviral and immunomodulatory treatment resulted in a significant decrease in IL-17F, IL-10, IFN-alpha, CXCL10/IP-10 and B7-H3 levels as well as an increase in IL-17A and IL-1 beta. We found significantly higher percentage of both CD4+ and CD8+ T cells producing IL-17A and CD4+ T cells producing IL-22 in patients with COVID-19.

Conclusion

Administration of antiviral or/and immunomodulatory treatment resulted in a significant downregulation of pro-inflammatory cytokine expression and an upregulation of T cell absolute counts in most cases, thus showing effectiveness of treatment in COVID-19. SARS-CoV-2 infection induced cytokine overexpression in hospitalized patients with COVID-19 as well as lymphopenia, particularly a decrease in CD4+ and CD8+ T cell counts. Moreover, despite the reduced counts of CD4+ and CD8+ T cells, both subsets showed overactivation and increased expression of IL-17A and IL-22, thus targeting Th17 response might alleviate inflammatory response in severe disease.

Transcriptome Changes of Hematopoietic Stem and Progenitor Cells in the Peripheral Blood of COVID-19 Patients by scRNA-seq

Coronavirus disease 2019 (COVID-19) threatens public health all over the world. It is well-accepted that the immune cells in peripheral blood are widely involved in the pathological process of COVID-19. However, hematopoietic stem and progenitor cells (HSPCs), as the main source of peripheral immune cells, have not been well studied during COVID-19 infection. We comprehensively revealed the transcriptome changes of peripheral blood HSPCs after COVID-19 infection and vaccination by single-cell RNA-seq. Compared with healthy individuals, the proportion of HSPCs in COVID-19 patients significantly increased. The increase in the proportion of HSPCs might be partly attributed to the enhancement of the HSPCs proliferation upon COVID-19 infection. However, the stemness damage of HSPCs is reflected by the decrease of differentiation signal, which can be used as a potential specific indicator of the severity and duration of COVID-19 infection. Type I interferon (IFN-I) and translation signals in HSPCs were mostly activated and inhibited after COVID-19 infection, respectively. In addition, the response of COVID-19 vaccination to the body is mild, while the secondary vaccination strengthens the immune response of primary vaccination. In conclusion, our study provides new insights into understanding the immune mechanism of COVID-19 infection.

Differential Activation of Programmed Cell Death in Patients with Severe SARS-CoV-2 Infection

SARS-CoV-2 (SARS-2) causes severe lower airway disease and death in a subset of patients. Knowledge on the relative contribution of programmed cell death (PCD) to lung pathology is limited to few human autopsy studies with small sample size/scope, in vitro cell culture, and experimental model systems. In this study, we sought to identify, localize, and quantify activation of apoptosis, ferroptosis, pyroptosis, and necroptosis in FFPE lung tissues from patients that died from severe SARS-2 infection (n=28) relative to uninfected controls (n=13). Immunofluorescence (IF) staining, whole-slide imaging, and Image J software was used to localize and quantify expression of SARS-2 nucleoprotein and the following PCD protein markers: cleaved Caspase-3, pMLKL, cleaved Gasdermin D, and CD71, respectively. IF showed differential activation of each PCD pathway in SARS-2 infected lungs and dichotomous staining for SARS-2 nucleoprotein enabling distinction between high (n=9) vs low viral burden (n= 19). No differences were observed in apoptosis and ferroptosis in SARS-2 infected lungs relative to uninfected controls. However, both pyroptosis and necroptosis were significantly increased in SARS-2 infected lungs. Increased pyroptosis was observed in SARS-2 infected lungs, irrespective of viral burden, suggesting an inflammation-driven mechanism. In contrast, necroptosis exhibited a very strong positive correlation with viral burden (R2=0.9925), suggesting a direct SARS-2 mediated effect. These data indicate a possible novel mechanism for viral-mediated necroptosis and a potential role for both lytic programmed cell death pathways, necroptosis and pyroptosis, in mediating infection outcome.

Explainable artificial intelligence model for identifying COVID-19 gene biomarkers

AIM

COVID-19 has revealed the need for fast and reliable methods to assist clinicians in diagnosing the disease. This article presents a model that applies explainable artificial intelligence (XAI) methods based on machine learning techniques on COVID-19 metagenomic next-generation sequencing (mNGS) samples.

METHODS

In the data set used in the study, there are 15,979 gene expressions of 234 patients with COVID-19 negative 141 (60.3%) and COVID-19 positive 93 (39.7%). The least absolute shrinkage and selection operator (LASSO) method was applied to select genes associated with COVID-19. Support Vector Machine - Synthetic Minority Oversampling Technique (SVM-SMOTE) method was used to handle the class imbalance problem. Logistics regression (LR), SVM, random forest (RF), and extreme gradient boosting (XGBoost) methods were constructed to predict COVID-19. An explainable approach based on local interpretable model-agnostic explanations (LIME) and SHAPley Additive exPlanations (SHAP) methods was applied to determine COVID-19- associated biomarker candidate genes and improve the final model's interpretability.

RESULTS

For the diagnosis of COVID-19, the XGBoost (accuracy: 0.930) model outperformed the RF (accuracy: 0.912), SVM (accuracy: 0.877), and LR (accuracy: 0.912) models. As a result of the SHAP, the three most important genes associated with COVID-19 were IFI27, LGR6, and FAM83A. The results of LIME showed that especially the high level of IFI27 gene expression contributed to increasing the probability of positive class.

CONCLUSIONS

The proposed model (XGBoost) was able to predict COVID-19 successfully. The results show that machine learning combined with LIME and SHAP can explain the biomarker prediction for COVID-19 and provide clinicians with an intuitive understanding and interpretability of the impact of risk factors in the model.

Single-cell RNA-seq revealing the immune features of donor liver during liver transplantation

Immune cells, including T and B cells, are key factors in the success of liver transplantation. And the repertoire of T cells and B cells plays an essential function in mechanism of the immune response associated with organ transplantation. An exploration of their expression and distribution in donor organs could contribute to a better understanding of the altered immune microenvironment in grafts. In this study, using single-cell 5' RNA sequence and single-cell T cell receptor (TCR)/B cell receptor (BCR) repertoire sequence, we profiled immune cells and TCR/BCR repertoire in three pairs of donor livers pre- and post-transplantation. By annotating different immune cell types, we investigated the functional properties of monocytes/Kupffer cells, T cells and B cells in grafts. Bioinformatic characterization of differentially expressed genes (DEGs) between the transcriptomes of these cell subclusters were performed to explore the role of immune cells in inflammatory response or rejection. In addition, we also observed shifts in TCR/BCR repertoire after transplantation. In conclusion, we profiled the immune cell transcriptomics and TCR/BCR immune repertoire of liver grafts during transplantation, which may offer novel strategies for monitoring recipient immune function and treatment of rejection after liver transplantation.

The Evolution of Single-Cell RNA Sequencing Technology and Application: Progress and Perspectives

As an emerging sequencing technology, single-cell RNA sequencing (scRNA-Seq) has become a powerful tool for describing cell subpopulation classification and cell heterogeneity by achieving high-throughput and multidimensional analysis of individual cells and circumventing the shortcomings of traditional sequencing for detecting the average transcript level of cell populations. It has been applied to life science and medicine research fields such as tracking dynamic cell differentiation, revealing sensitive effector cells, and key molecular events of diseases. This review focuses on the recent technological innovations in scRNA-Seq, highlighting the latest research results with scRNA-Seq as the core technology in frontier research areas such as embryology, histology, oncology, and immunology. In addition, this review outlines the prospects for its innovative application in traditional Chinese medicine (TCM) research and discusses the key issues currently being addressed by scRNA-Seq and its great potential for exploring disease diagnostic targets and uncovering drug therapeutic targets in combination with multiomics technologies.

Evaluation of both expression and serum protein levels of caspase-8 and mitogen-activated protein kinase 1 genes in patients with different severities of COVID-19 infection

AIM

The current study aimed to evaluate the effects of caspase-8 (CASP8) and mitogen-activated protein kinase 1 (MAPK1) gene expression levels and their products on preventing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.

METHODS

A total of 40 patients (men, 15 [37.5%]; women, 25 [62.5%]) with COVID-19 infection were included in the current study. The patients were divided into four main groups based on disease severity: mild (n = 7), moderate (n = 10), severe (n = 14), and critical (n = 9). Individuals aged < 18 years and pregnant women were excluded. Patients were classified according to the World Health Organization (WHO) classification system (WHO/2019-nCoV/clinical/2021.1).

RESULTS

Considering all groups, statistically significant differences were detected among all groups for both CASP8^2-ΔΔCt (p = 0.006) and MAPK1 2^-ΔΔCt values (p = 0.015). Moreover, statistically significant differences were detected between mild and moderate (p = 0.013), moderate and critical (p = 0.018), and severe and critical (p = 0.023) groups for lymphocytes.

CONCLUSION

The CASP8/MAPK1 expression levels and/or its products are essential in preventing injury caused by COVID-19 infection. They play crucial roles in maintaining cellular homeostasis and viability. Furthermore, CASP8/MAPK1 levels can provide information about disease severity.

Single-cell RNA sequencing reveals the molecular features of peripheral blood immune cells in children, adults and centenarians

Peripheral blood immune cells have different molecular characteristics at different stages of the whole lifespan. Knowledge of circulating immune cell types and states from children to centenarians remains incomplete. We profiled peripheral blood mononuclear cells (PBMCs) of multiple age groups with single-cell RNA sequencing (scRNA-seq), involving the age ranges of 1-12 (G1), 20-30(G2), 30-60(G3), 60-80(G4), and >110 years (G5). The proportion and states of myeloid cells change significantly from G1 to G2. We identified a novel CD8⁺CCR7⁺GZMB⁺ cytotoxic T cell subtype specific in G1, expressing naive and cytotoxic genes, and validated by flow cytometry. CD8⁺ T cells showed significant changes in the early stage (G1 to G2), while CD4⁺ T cells changed in the late stage (G4 to G5). Moreover, the intercellular crosstalk among PBMCs in G1 is very dynamic. Susceptibility genes for a variety of autoimmune diseases (AIDs) have different cell-specific expression localization, and the expression of susceptibility genes for AIDs changes with age. Notably, the CD3⁺ undefined T cells clearly expressed susceptibility genes for multiple AIDs, especially in G3. ETS1 and FLI1, susceptibility genes associated with systemic lupus erythematosus, were differentially expressed in CD4⁺ and CD8⁺ effector cells in G1 and G3. These results provided a valuable basis for future research on the unique immune system of the whole lifespan and AIDs.

IFI27 transcription is an early predictor for COVID-19 outcomes, a multi-cohort observational study

Purpose

Robust biomarkers that predict disease outcomes amongst COVID-19 patients are necessary for both patient triage and resource prioritisation. Numerous candidate biomarkers have been proposed for COVID-19. However, at present, there is no consensus on the best diagnostic approach to predict outcomes in infected patients. Moreover, it is not clear whether such tools would apply to other potentially pandemic pathogens and therefore of use as stockpile for future pandemic preparedness.

Methods

We conducted a multi-cohort observational study to investigate the biology and the prognostic role of interferon alpha-inducible protein 27 (IFI27) in COVID-19 patients.

Results

We show that IFI27 is expressed in the respiratory tract of COVID-19 patients and elevated IFI27 expression in the lower respiratory tract is associated with the presence of a high viral load. We further demonstrate that the systemic host response, as measured by blood IFI27 expression, is associated with COVID-19 infection. For clinical outcome prediction (e.g., respiratory failure), IFI27 expression displays a high sensitivity (0.95) and specificity (0.83), outperforming other known predictors of COVID-19 outcomes. Furthermore, IFI27 is upregulated in the blood of infected patients in response to other respiratory viruses. For example, in the pandemic H1N1/09 influenza virus infection, IFI27-like genes were highly upregulated in the blood samples of severely infected patients.

Conclusion

These data suggest that prognostic biomarkers targeting the family of IFI27 genes could potentially supplement conventional diagnostic tools in future virus pandemics, independent of whether such pandemics are caused by a coronavirus, an influenza virus or another as yet-to-be discovered respiratory virus.

The IFN-stimulated gene IFI27 counteracts innate immune responses after viral infections by interfering with RIG-I signaling

The recognition of viral nucleic acids by host pattern recognition receptors (PRRs) is critical for initiating innate immune responses against viral infections. These innate immune responses are mediated by the induction of interferons (IFNs), IFN-stimulated genes (ISGs) and pro-inflammatory cytokines. However, regulatory mechanisms are critical to avoid excessive or long-lasting innate immune responses that may cause detrimental hyperinflammation. Here, we identified a novel regulatory function of the ISG, IFN alpha inducible protein 27 (IFI27) in counteracting the innate immune responses triggered by cytoplasmic RNA recognition and binding. Our model systems included three unrelated viral infections caused by Influenza A virus (IAV), Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2), and Sendai virus (SeV), and transfection with an analog of double-stranded (ds) RNA. Furthermore, we found that IFI27 has a positive effect on IAV and SARS-CoV-2 replication, most likely due to its ability to counteract host-induced antiviral responses, including in vivo. We also show that IFI27 interacts with nucleic acids and PRR retinoic acid-inducible gene I (RIG-I), being the interaction of IFI27 with RIG-I most likely mediated through RNA binding. Interestingly, our results indicate that interaction of IFI27 with RIG-I impairs RIG-I activation, providing a molecular mechanism for the effect of IFI27 on modulating innate immune responses. Our study identifies a molecular mechanism that may explain the effect of IFI27 in counterbalancing innate immune responses to RNA viral infections and preventing excessive innate immune responses. Therefore, this study will have important implications in drug design to control viral infections and viral-induced pathology.

B cell receptor repertoire analysis from autopsy samples of COVID-19 patients

Neutralizing antibodies against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are being developed world over. We investigated the possibility of producing artificial antibodies from the formalin fixation and paraffin-embedding (FFPE) lung lobes of a patient who died by coronavirus disease 2019 (COVID-19). The B-cell receptors repertoire in the lung tissue where SARS-CoV-2 was detected were considered to have highly sensitive virus-neutralizing activity, and artificial antibodies were produced by combining the most frequently detected heavy and light chains. Some neutralizing effects against the SARS-CoV-2 were observed, and mixing two different artificial antibodies had a higher tendency to suppress the virus. The neutralizing effects were similar to the immunoglobulin G obtained from healthy donors who had received a COVID-19 mRNA vaccine. Therefore, the use of FFPE lung tissue, which preserves the condition of direct virus sensitization, to generate artificial antibodies may be useful against future unknown infectious diseases.

Single-cell multiomics revealed the dynamics of antigen presentation, immune response and T cell activation in the COVID-19 positive and recovered individuals

Introduction

Despite numerous efforts to describe COVID-19's immunological landscape, there is still a gap in our understanding of the virus's infections after-effects, especially in the recovered patients. This would be important to understand as we now have huge number of global populations infected by the SARS-CoV-2 as well as variables inclusive of VOCs, reinfections, and vaccination breakthroughs. Furthermore, single-cell transcriptome alone is often insufficient to understand the complex human host immune landscape underlying differential disease severity and clinical outcome.

Methods

By combining single-cell multi-omics (Whole Transcriptome Analysis plus Antibody-seq) and machine learning-based analysis, we aim to better understand the functional aspects of cellular and immunological heterogeneity in the COVID-19 positive, recovered and the healthy individuals.

Results

Based on single-cell transcriptome and surface marker study of 163,197 cells (124,726 cells after data QC) from the 33 individuals (healthy=4, COVID-19 positive=16, and COVID-19 recovered=13), we observed a reduced MHC Class-I-mediated antigen presentation and dysregulated MHC Class-II-mediated antigen presentation in the COVID-19 patients, with restoration of the process in the recovered individuals. B-cell maturation process was also impaired in the positive and the recovered individuals. Importantly, we discovered that a subset of the naive T-cells from the healthy individuals were absent from the recovered individuals, suggesting a post-infection inflammatory stage. Both COVID-19 positive patients and the recovered individuals exhibited a CD40-CD40LG-mediated inflammatory response in the monocytes and T-cell subsets. T-cells, NK-cells, and monocyte-mediated elevation of immunological, stress and antiviral responses were also seen in the COVID-19 positive and the recovered individuals, along with an abnormal T-cell activation, inflammatory response, and faster cellular transition of T cell subtypes in the COVID-19 patients. Importantly, above immune findings were used for a Bayesian network model, which significantly revealed FOS, CXCL8, IL1β, CST3, PSAP, CD45 and CD74 as COVID-19 severity predictors.

Discussion

In conclusion, COVID-19 recovered individuals exhibited a hyper-activated inflammatory response with the loss of B cell maturation, suggesting an impeded post-infection stage, necessitating further research to delineate the dynamic immune response associated with the COVID-19. To our knowledge this is first multi-omic study trying to understand the differential and dynamic immune response underlying the sample subtypes.

When ferroptosis meets pathogenic infections

Apoptosis, necrosis, or autophagy are diverse types of regulated cell death (RCD), recognized as the strategies that host cells use to defend against pathogens such as viruses, bacteria, or fungi. Pathogens can induce or block different types of host cell RCD, promoting propagation or evading host immune surveillance. Ferroptosis is a newly identified RCD. Evidence has demonstrated how pathogens regulate ferroptosis to promote their replication, dissemination, and pathogenesis. However, the interaction between ferroptosis and pathogenic infections still needs to be completely elucidated. This review summarizes the advances in the interaction between pathogenic infections and host ferroptotic processes, focusing on the underlying mechanisms of how pathogens exploit ferroptosis, and discussing possible therapeutic measures against pathogen-associated diseases in a ferroptosis-dependent manner.

Whole-transcriptome analyses of sheep embryonic testicular cells infected with the bluetongue virus

Introduction

bluetongue virus (BTV) infection triggers dramatic and complex changes in the host's transcriptional profile to favor its own survival and reproduction. However, there is no whole-transcriptome study of susceptible animal cells with BTV infection, which impedes the in-depth and systematical understanding of the comprehensive characterization of BTV-host interactome, as well as BTV infection and pathogenic mechanisms.

Methods

to systematically understand these changes, we performed whole-transcriptome sequencing in BTV serotype 1 (BTV-1)-infected and mock-infected sheep embryonic testicular cells, and subsequently conducted bioinformatics differential analyses.

Results

there were 1504 differentially expressed mRNAs, 78 differentially expressed microRNAs, 872 differentially expressed long non-coding RNAs, and 59 differentially expressed circular RNAs identified in total. Annotation from the Gene Ontology, enrichment from the Kyoto Encyclopedia of Genes and Genomes, and construction of competing endogenous RNA networks revealed differentially expressed RNAs primarily related to virus-sensing and signaling transduction pathways, antiviral and immune responses, inflammation, and development and metabolism related pathways. Furthermore, a protein-protein interaction network analysis found that BTV may contribute to abnormal spermatogenesis by reducing steroid biosynthesis. Finally, real-time quantitative PCR and western blotting results showed that the expression trends of differentially expressed RNAs were consistent with the whole-transcriptome sequencing data.

Discussion

this study provides more insights of comprehensive characterization of BTV-host interactome, and BTV infection and pathogenic mechanisms.

Immune-profiling of SARS-CoV-2 viremic patients reveals dysregulated innate immune responses

SARS-CoV-2 plasma viremia has been associated with severe disease and death in COVID-19. However, the effects of viremia on immune responses in blood cells remain unclear. The current study comprehensively examined transcriptional signatures of PBMCs involving T cells, B cells, NK cells, monocytes, myeloid dendritic cells (mDCs), and plasmacytoid dendritic cells (pDCs) respectively, from three different groups including individuals with moderate (nM), or severe disease with (vS) or without (nS) detectable plasma viral load. Whole transcriptome analysis demonstrated that all seven immune cell subsets were associated with disease severity regardless of cell type. Supervised clustering analysis demonstrated that mDCs and pDCs gene signatures could distinguish disease severity. Notably, transcriptional signatures of the vS group were enriched in pathways related to DNA repair, E2F targets, and G2M checkpoints; in contrast, transcriptional signatures of the nM group were enriched in interferon responses. Moreover, we observed an impaired induction of interferon responses accompanied by imbalanced cell-intrinsic immune sensing and an excessive inflammatory response in patients with severe disease (nS and vS). In sum, our study provides detailed insights into the systemic immune response to SARS-CoV-2 infection and reveals profound alterations in seven major immune cells in COVID-19 patients.

A machine learning approach utilizing DNA methylation as an accurate classifier of COVID-19 disease severity

Since the onset of the COVID-19 pandemic, increasing cases with variable outcomes continue globally because of variants and despite vaccines and therapies. There is a need to identify at-risk individuals early that would benefit from timely medical interventions. DNA methylation provides an opportunity to identify an epigenetic signature of individuals at increased risk. We utilized machine learning to identify DNA methylation signatures of COVID-19 disease from data available through NCBI Gene Expression Omnibus. A training cohort of 460 individuals (164 COVID-19-infected and 296 non-infected) and an external validation dataset of 128 individuals (102 COVID-19-infected and 26 non-COVID-associated pneumonia) were reanalyzed. Data was processed using ChAMP and beta values were logit transformed. The JADBio AutoML platform was leveraged to identify a methylation signature associated with severe COVID-19 disease. We identified a random forest classification model from 4 unique methylation sites with the power to discern individuals with severe COVID-19 disease. The average area under the curve of receiver operator characteristic (AUC-ROC) of the model was 0.933 and the average area under the precision-recall curve (AUC-PRC) was 0.965. When applied to our external validation, this model produced an AUC-ROC of 0.898 and an AUC-PRC of 0.864. These results further our understanding of the utility of DNA methylation in COVID-19 disease pathology and serve as a platform to inform future COVID-19 related studies.

Development of Single-Cell Transcriptomics and Its Application in COVID-19

Over the last three years, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related health crisis has claimed over six million lives and caused USD 12 trillion losses to the global economy. SARS-CoV-2 continuously mutates and evolves with a high basic reproduction number (R0), resulting in a variety of clinical manifestations ranging from asymptomatic infection to acute respiratory distress syndrome (ARDS) and even death. To gain a better understanding of coronavirus disease 2019 (COVID-19), it is critical to investigate the components that cause various clinical manifestations. Single-cell sequencing has substantial advantages in terms of identifying differentially expressed genes among individual cells, which can provide a better understanding of the various physiological and pathological processes. This article reviewed the use of single-cell transcriptomics in COVID-19 research, examined the immune response disparities generated by SARS-CoV-2, and offered insights regarding how to improve COVID-19 diagnosis and treatment plans.

Comprehensive analysis of immune responses in CLL patients after heterologous COVID-19 vaccination

Patients with chronic lymphocytic leukemia (CLL) treated with B-cell pathway inhibitors and anti-CD20 antibodies exhibit low humoral response rate (RR) following SARS-CoV-2 vaccination. To investigate the relationship between the initial transcriptional response to vaccination with ensuing B and T cell immune responses, we performed a comprehensive immune transcriptome analysis flanked by antibody and T cell assays in peripheral blood prospectively collected from 15 CLL/SLL patients vaccinated with heterologous BNT162b2/ChAdOx1 with follow up at a single institution. The two-dose antibody RR was 40% increasing to 53% after booster. Patients on BTKi, venetoclax ± anti-CD20 antibody within 12 months of vaccination responded less well than those under BTKi alone. The two-dose T cell RR was 80% increasing to 93% after booster. Transcriptome studies revealed that seven patients showed interferon-mediated signaling activation within 2 days and one at 7 days after vaccination. Increasing counts of COVID-19 specific IGHV genes correlated with B-cell reconstitution and improved humoral RR. T cell responses in CLL patients appeared after vaccination regardless of treatment status. A higher humoral RR was associated with BTKi treatment and B-cell reconstitution. Boosting was particularly effective when intrinsic immune status was improved by CLL-treatment.

Combining single-cell RNA sequencing of peripheral blood mononuclear cells and exosomal transcriptome to reveal the cellular and genetic profiles in COPD

Background

It has been a long-held consensus that immune reactions primarily mediate the pathology of chronic obstructive pulmonary disease (COPD), and that exosomes may participate in immune regulation in COPD. However, the relationship between exosomes and peripheral immune status in patients with COPD remains unclear.

Methods

In this study, we sequenced plasma exosomes and performed single-cell RNA sequencing on peripheral blood mononuclear cells (PBMCs) from patients with COPD and healthy controls. Finally, we constructed competing endogenous RNA (ceRNA) and protein–protein interaction (PPI) networks to delineate the interactions between PBMCs and exosomes within COPD.

Results

We identified 135 mRNAs, 132 lncRNAs, and 359 circRNAs from exosomes that were differentially expressed in six patients with COPD compared with four healthy controls. Functional enrichment analyses revealed that many of these differentially expressed RNAs were involved in immune responses including defending viral infection and cytokine–cytokine receptor interaction. We also identified 18 distinct cell clusters of PBMCs in one patient and one control by using an unsupervised cluster analysis called uniform manifold approximation and projection (UMAP). According to resultant cell identification, it was likely that the proportions of monocytes, dendritic cells, and natural killer cells increased in the COPD patient we tested, meanwhile the proportions of B cells, CD4 + T cells, and naïve CD8 + T cells declined. Notably, CD8 + T effector memory CD45RA + (Temra) cell and CD8 + effector memory T (Tem) cell levels were elevated in patient with COPD, which were marked by their lower capacity to differentiate due to their terminal differentiation state and lower reactive capacity to viral pathogens.

Conclusions

We generated exosomal RNA profiling and single-cell transcriptomic profiling of PBMCs in COPD, described possible connection between impaired immune function and COPD development, and finally determined the possible role of exosomes in mediating local and systemic immune reactions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02182-8.

Delineating COVID-19 immunological features using single-cell RNA sequencing

Understanding the molecular mechanisms of coronavirus disease 2019 (COVID-19) pathogenesis and immune response is vital for developing therapies. Single-cell RNA sequencing has been applied to delineate the cellular heterogeneity of the host response toward COVID-19 in multiple tissues and organs. Here, we review the applications and findings from over 80 original COVID-19 single-cell RNA sequencing studies as well as many secondary analysis studies. We describe that single-cell RNA sequencing reveals multiple features of COVID-19 patients with different severity, including cell populations with proportional alteration, COVID-19-induced genes and pathways, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection in single cells, and adaptation of immune repertoire. We also collect published single-cell RNA sequencing datasets from original studies. Finally, we discuss the limitations in current studies and perspectives for future advance.

Influenza vaccination and single cell multiomics reveal sex dimorphic immune imprints of prior mild COVID-19

Viral infections can have profound and durable functional impacts on the immune system. There is an urgent need to characterize the long-term immune effects of SARS-CoV-2 infection given the persistence of symptoms in some individuals and the continued threat of novel variants. Here we use systems immunology, including longitudinal multimodal single cell analysis (surface proteins, transcriptome, and V(D)J sequences) from 33 previously healthy individuals after recovery from mild, non-hospitalized COVID-19 and 40 age- and sex-matched healthy controls with no history of COVID-19 to comparatively assess the post-infection immune status (mean: 151 days after diagnosis) and subsequent innate and adaptive responses to seasonal influenza vaccination. Identification of both sex-specific and -independent temporally stable changes, including signatures of T-cell activation and repression of innate defense/immune receptor genes (e.g., Toll-like receptors) in monocytes, suggest that mild COVID-19 can establish new post-recovery immunological set-points. COVID-19-recovered males had higher innate, influenza-specific plasmablast, and antibody responses after vaccination compared to healthy males and COVID-19-recovered females, partly attributable to elevated pre-vaccination frequencies of a GPR56 expressing CD8+ T-cell subset in male recoverees that are "poised" to produce higher levels of IFNγ upon inflammatory stimulation. Intriguingly, by day 1 post-vaccination in COVID-19-recovered subjects, the expression of the repressed genes in monocytes increased and moved towards the pre-vaccination baseline of healthy controls, suggesting that the acute inflammation induced by vaccination could partly reset the immune states established by mild COVID-19. Our study reveals sex-dimorphic immune imprints and in vivo functional impacts of mild COVID-19 in humans, suggesting that prior COVID-19, and possibly respiratory viral infections in general, could change future responses to vaccination and in turn, vaccines could help reset the immune system after COVID-19, both in an antigen-agnostic manner.

Identification of key molecules in COVID-19 patients significantly correlated with clinical outcomes by analyzing transcriptomic data

Background

Although several key molecules have been identified to modulate SARS-CoV-2 invasion of human host cells, the molecules correlated with outcomes in COVID-19 caused by SARS-CoV-2 infection remain insufficiently explored.

Methods

This study analyzed three RNA-Seq gene expression profiling datasets for COVID-19 and identified differentially expressed genes (DEGs) between COVID-19 patients and normal people, commonly in the three datasets. Furthermore, this study explored the correlation between the expression of these genes and clinical features in COVID-19 patients.

Results

This analysis identified 13 genes significantly upregulated in COVID-19 patients’ leukocyte and SARS-CoV-2-infected nasopharyngeal tissue compared to normal tissue. These genes included OAS1, OAS2, OAS3, OASL, HERC6, SERPING1, IFI6, IFI44, IFI44L, CMPK2, RSAD2, EPSTI1, and CXCL10, all of which are involved in antiviral immune regulation. We found that these genes’ downregulation was associated with worse clinical outcomes in COVID-19 patients, such as intensive care unit (ICU) admission, mechanical ventilatory support (MVS) requirement, elevated D-dimer levels, and increased viral loads. Furthermore, this analysis identified two COVID-19 clusters based on the expression profiles of the 13 genes, termed COV-C1 and COV-C2. Compared with COV-C1, COV-C2 more highly expressed the 13 genes, had stronger antiviral immune responses, were younger, and displayed more favorable clinical outcomes.

Conclusions

A strong antiviral immune response is essential in reducing severity of COVID-19.

The link between ferroptosis and airway inflammatory diseases: A novel target for treatment

Ferroptosis is an iron-dependent mode of cell death characterized by intracellular lipid peroxide accumulation and a redox reaction imbalance. Compared with other modes of cell death, ferroptosis has specific biological and morphological features. The iron-dependent lipid peroxidation accumulation is manifested explicitly in the abnormal metabolism of intracellular lipid oxides catalyzed by excessive iron ions with the production of many reactive oxygen species and over-oxidization of polyunsaturated fatty acids. Recent studies have shown that various diseases, which include intestinal diseases and cancer, are associated with ferroptosis, but few studies are related to airway inflammatory diseases. This review provides a comprehensive analysis of the primary damage mechanisms of ferroptosis and summarizes the relationship between ferroptosis and airway inflammatory diseases. In addition to common acute and chronic airway inflammatory diseases, we also focus on the progress of research on COVID-19 in relation to ferroptosis. New therapeutic approaches and current issues to be addressed in the treatment of inflammatory airway diseases using ferroptosis are further proposed.

Identifying novel host-based diagnostic biomarker panels for COVID-19: a whole-blood/nasopharyngeal transcriptome meta-analysis

BACKGROUND

Regardless of improvements in controlling the COVID-19 pandemic, the lack of comprehensive insight into SARS-COV-2 pathogenesis is still a sophisticated challenge. In order to deal with this challenge, we utilized advanced bioinformatics and machine learning algorithms to reveal more characteristics of SARS-COV-2 pathogenesis and introduce novel host response-based diagnostic biomarker panels.

METHODS

In the present study, eight published RNA-Seq datasets related to whole-blood (WB) and nasopharyngeal (NP) swab samples of patients with COVID-19, other viral and non-viral acute respiratory illnesses (ARIs), and healthy controls (HCs) were integrated. To define COVID-19 meta-signatures, Gene Ontology and pathway enrichment analyses were applied to compare COVID-19 with other similar diseases. Additionally, CIBERSORTx was executed in WB samples to detect the immune cell landscape. Furthermore, the optimum WB- and NP-based diagnostic biomarkers were identified via all the combinations of 3 to 9 selected features and the 2-phases machine learning (ML) method which implemented k-fold cross validation and independent test set validation.

RESULTS

The host gene meta-signatures obtained for SARS-COV-2 infection were different in the WB and NP samples. The gene ontology and enrichment results of the WB dataset represented the enhancement in inflammatory host response, cell cycle, and interferon signature in COVID-19 patients. Furthermore, NP samples of COVID-19 in comparison with HC and non-viral ARIs showed the significant upregulation of genes associated with cytokine production and defense response to the virus. In contrast, these pathways in COVID-19 compared to other viral ARIs were strikingly attenuated. Notably, immune cell proportions of WB samples altered in COVID-19 versus HC. Moreover, the optimum WB- and NP-based diagnostic panels after two phases of ML-based validation included 6 and 8 markers with an accuracy of 97% and 88%, respectively.

CONCLUSIONS

Based on the distinct gene expression profiles of WB and NP, our results indicated that SARS-COV-2 function is body-site-specific, although according to the common signature in WB and NP COVID-19 samples versus controls, this virus also induces a global and systematic host response to some extent. We also introduced and validated WB- and NP-based diagnostic biomarkers using ML methods which can be applied as a complementary tool to diagnose the COVID-19 infection from non-COVID cases.

Identification of COVID-19-Specific Immune Markers Using a Machine Learning Method

Notably, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a tight relationship with the immune system. Human resistance to COVID-19 infection comprises two stages. The first stage is immune defense, while the second stage is extensive inflammation. This process is further divided into innate and adaptive immunity during the immune defense phase. These two stages involve various immune cells, including CD4⁺ T cells, CD8⁺ T cells, monocytes, dendritic cells, B cells, and natural killer cells. Various immune cells are involved and make up the complex and unique immune system response to COVID-19, providing characteristics that set it apart from other respiratory infectious diseases. In the present study, we identified cell markers for differentiating COVID-19 from common inflammatory responses, non-COVID-19 severe respiratory diseases, and healthy populations based on single-cell profiling of the gene expression of six immune cell types by using Boruta and mRMR feature selection methods. Some features such as IFI44L in B cells, S100A8 in monocytes, and NCR2 in natural killer cells are involved in the innate immune response of COVID-19. Other features such as ZFP36L2 in CD4⁺ T cells can regulate the inflammatory process of COVID-19. Subsequently, the IFS method was used to determine the best feature subsets and classifiers in the six immune cell types for two classification algorithms. Furthermore, we established the quantitative rules used to distinguish the disease status. The results of this study can provide theoretical support for a more in-depth investigation of COVID-19 pathogenesis and intervention strategies.

Landscape of B Cell Receptor Repertoires in COVID-19 Patients Revealed Through CDR3 Sequencing of Immunoglobulin Heavy and Light Chains

The outbreak and persistence of coronavirus disease 2019 (COVID-19) threaten human health. B cells play a vital role in fighting the infections caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Despite many studies on the immune responses in COVID-19 patients, it is still unclear how B cell receptor (BCR) constituents, including immunoglobulin heavy (IGHs) and light chains (IGLs), respond to SARS-CoV-2 in patients with varying symptoms. In this study, we conducted complementarity-determining region 3 (CDR3) sequencing of BCR IGHs and IGLs from the peripheral blood of COVID-19 patients and healthy donors. The results showed significantly reduced clonal diversity, more expanded clones, and longer CDR3 lengths of IGH and IGL in COVID-19 patients than those in healthy individuals. The IGLs had a much higher percentage of VJ skew usage (47.83% IGLV and 42.86% IGLJ were significantly regulated) than the IGHs (12.09% IGHV and 0% IGHJ) between the healthy individuals and patients, which indicated the importance of BCR light chains. Furthermore, we found a largely expanded IGLV3-25 gene cluster mostly pairing with IGLJ1 and ILGJ2 in COVID-19 patients and a newly identified upregulated IGLJ1 gene and IGLJ2+IGLV13-21 recombination, both of which are potential sources of SARS-CoV-2-targeting antibodies. Our findings on specific immune B-cell signatures associated with COVID-19 have clinical implications for vaccine and biomarker development for disease diagnosis.

Cell deaths: Involvement in the pathogenesis and intervention therapy of COVID-19

The current pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has dramatically influenced various aspects of the world. It is urgent to thoroughly study pathology and underlying mechanisms for developing effective strategies to prevent and treat this threatening disease. It is universally acknowledged that cell death and cell autophagy are essential and crucial to maintaining host homeostasis and participating in disease pathogenesis. At present, more than twenty different types of cell death have been discovered, some parts of which have been fully understood, whereas some of which need more investigation. Increasing studies have indicated that cell death and cell autophagy caused by coronavirus might play an important role in virus infection and pathogenicity. However, the knowledge of the interactions and related mechanisms of SARS-CoV-2 between cell death and cell autophagy lacks systematic elucidation. Therefore, in this review, we comprehensively delineate how SARS-CoV-2 manipulates diverse cell death (including apoptosis, necroptosis, pyroptosis, ferroptosis, and NETosis) and cell autophagy for itself benefits, which is simultaneously involved in the occurrence and progression of COVID-19, aiming to provide a reasonable basis for the existing interventions and further development of novel therapies.

Long COVID: A proposed hypothesis-driven model of viral persistence for the pathophysiology of the syndrome

Background: Long COVID (coronavirus disease 2019) syndrome includes a group of patients who, after infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), exhibit lingering mild-to-moderate symptoms and develop medical complications that can have lasting health problems. In this report, we propose a model for the pathophysiology of the long COVID presentation based on increased proinflammatory cytokine production that results from the persistence of the SARS-CoV-2 virus or one of its molecular components. Associated with this hyperproduction of inflammatory cytokines is a heightened activity of nuclear factor κ B (NF-κB) and p38 mitogen-activated protein kinase signaling pathways that regulate cytokine production. Objective: The purpose of the present report was to review the causes of long COVID syndrome and suggest ways that can provide a basis for a better understanding of the clinical symptomatology for the of improved diagnostic and therapeutic procedures for the condition. Methods: Extensive research was conducted in medical literature data bases by applying terms such as "long COVID" associated with "persistence of the SARS-CoV-2 virus" "spike protein' "COVID-19" and "biologic therapies." Results and Conclusions: In this model of the long COVID syndrome, the persistence of SARS-CoV-2 is hypothesized to trigger a dysregulated immune system with subsequent heightened release of proinflammatory cytokines that lead to chronic low-grade inflammation and multiorgan symptomatology. The condition seems to have a genetic basis, which predisposes individuals to have a diminished immunologic capacity to completely clear the virus, with residual parts of the virus persisting. This persistence of virus and resultant hyperproduction of proinflammatory cytokines are proposed to form the basis of the syndrome.

Comparative Analysis of Long Non-Coding RNA Expression and Immune Response in Mild and Severe COVID-19

Background: Coronavirus disease 2019 (COVID-19) is a worldwide emergency, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Long non-coding RNAs (lncRNAs) do not encode proteins but could participate in immune response.

Methods: In our study, 39 COVID-19 patients were enrolled. The microarray of peripheral blood mononuclear cells from healthy and COVID-19 patients was applied to identify the expression profiles of lncRNAs and mRNAs. Identified differentially expressed (DE) lncRNAs were validated by qRT-PCR. Then, the lncRNA–mRNA network was constructed and visualized using Cytoscape (3.6.1) based on the Pearson correlation coefficient. The enrichment of DE mRNAs was analyzed using Metascape. The difference in frequencies of immune cells and cytokines was detected using CIBERSORT and ImmPort based on DE mRNAs.

Results: All patients with COVID-19 displayed lymphopenia, especially in T cells, and hyper-inflammatory responses, including IL-6 and TNF-α. Four immune-related lncRNAs in COVID-19 were found and further validated, including AC136475.9, CATG00000032642.1, G004246, and XLOC_013290. Functional analysis enriched in downregulation of the T-cell receptor and the antigen processing and presentation as well as increased apoptotic proteins, which could lead to T-cell cytopenia. In addition, they participated in monocyte remodeling, which contributed to releasing cytokines and chemokines and then recruiting more monocytes and aggravating the clinical severity of COVID-19 patients.

Conclusion: Taken together, four lncRNAs were in part of immune response in COVID-19, which was involved in the T-cell cytopenia by downregulating the antigen processing and presentation, the T-cell receptor, and an increased proportion of monocytes, with a distinct change in cytokines and chemokines.

Dynamic changes of SARS-CoV-2 specific IgM and IgG among population vaccinated with COVID-19 vaccine

To evaluate the dynamic changes of antibody levels in different groups after inoculation with the coronavirus disease 2019 (COVID-19) vaccine. The 1493 subjects who were tested for IgM and IgG against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at Qionglai Medical Center Hospital from June to October in 2021 were accepted for analyses of geometric mean titre (GMT) of IgG and IgM. The overall GMT of IgM and IgG in the population of Qionglai reached at a peak value at 1.497 (+3.810, −3.810) S/CO and 4.048 (+2.059, −2.059) S/CO in the second week, and then gradually decreased to 0.114 (+2.707, −2.707) and 1.885 (+1.506, −1.506) S/CO in the 11th–25th weeks, respectively. IgG was positive within 1 day, after that GMT increased continuously and peaked on the 13th day. There was a significant difference between male and female groups for titre of IgM during the prior 2 weeks and among three age groups for titre of IgG during the 2nd–3rd week after vaccination. The GMT level of IgG in the population vaccinated with the COVID-19 vaccine remained at a high level within 25 weeks and peaked on the 13th day, indicating that IgG could exist for a longer period and exhibiting positive SARS-CoV-2- defending effect.

A genetic variant in IL-6 lowering its expression is protective for critical patients with COVID-19

Critical coronavirus disease 2019 (COVID-19) is associated with high mortality and potential genetic factors have been reported to be involved in the development of critical COVID-19. We performed a genome-wide association study to identify the genetic factors responsible for developing critical COVID-19. 632 critical patients with COVID-19 and 3021 healthy controls from the Chinese population were recruited. First, we identified a genome-wide significant difference of IL-6 rs2069837 (p = 9.73 × 10⁻¹⁵, OR = 0.41) between 437 critical patients with COVID-19 and 2551 normal controls in the discovery cohort. When replicated these findings in a set of 195 patients with critical COVID-19 and 470 healthy controls, we detected significant association of rs2069837 with COVID-19 (p = 8.89 × 10⁻³, OR = 0.67). This variant surpassed the formal threshold for genome-wide significance (combined p = 4.64 × 10⁻¹⁶, OR = 0.49). Further analysis revealed that there was a significantly stronger expression of IL-6 in the serum from patients with critical COVID-19 than in that from patients with asymptomatic COVID-19. An in vitro assay showed that the A to G allele changes in rs2069837 within IL-6 obviously decreased the luciferase expression activity. When analyzing the effect of this variant on the IL-6 in the serum based on the rs2069837 genotype, we found that the A to G variation in rs2069837 decreased the expression of IL-6, especially in the male. Overall, we identified a genetic variant in IL-6 that protects against critical conditions with COVID-19 though decreasing IL-6 expression in the serum.

COVID-19 Biomarkers Recognition & Classification Using Intelligent Systems

Background:

SARS-CoV-2 has paralyzed mankind due to its high transmissibility and its associated mortality, causing millions of infections and deaths worldwide. The search for gene expression biomarkers from the host transcriptional response to infection may help understand the underlying mechanisms by which the virus causes COVID-19. This research proposes a smart methodology integrating different RNA-Seq datasets from SARS-CoV-2, other respiratory diseases, and healthy patients.

Methods:

The proposed pipeline exploits the functionality of the ‘KnowSeq’ R/Bioc package, integrating different data sources and attaining a significantly larger gene expression dataset, thus endowing the results with higher statistical significance and robustness in comparison with previous studies in the literature. A detailed preprocessing step was carried out to homogenize the samples and build a clinical decision system for SARS-CoV-2. It uses machine learning techniques such as feature selection algorithm and supervised classification system. This clinical decision system uses the most differentially expressed genes among different diseases (including SARS-Cov-2) to develop a four-class classifier.

Results:

The multiclass classifier designed can discern SARS-CoV-2 samples, reaching an accuracy equal to 91.5%, a mean F1-Score equal to 88.5%, and a SARS-CoV-2 AUC equal to 94% by using only 15 genes as predictors. A biological interpretation of the gene signature extracted reveals relations with processes involved in viral responses.

Conclusion:

This work proposes a COVID-19 gene signature composed of 15 genes, selected after applying the feature selection ‘minimum Redundancy Maximum Relevance’ algorithm. The integration among several RNA-Seq datasets was a success, allowing for a considerable large number of samples and therefore providing greater statistical significance to the results than previous studies. Biological interpretation of the selected genes was also provided.