Single-Cell RNA Sequencing Analysis of the Immunometabolic Rewiring and Immunopathogenesis of Coronavirus Disease 2019

An insight into COVID-19 host immunity at single-cell resolution

Host immunity helps the body to fight against COVID-19. Single-cell transcriptomics has provided the scope of investigating cellular and molecular underpinnings of host immune response against SARS-CoV-2 infection at high resolution. In this review, we have systematically described the virus-induced dysregulation of relative abundance as well as molecular behavior of each innate and adaptive immune cell type and cell state during COVID-19 infection and for different vaccinations, based on single-cell studies published in last three-four years. Identification and characterization of these disease-associated specific cell populations might help to design better, efficient, and targeted therapeutic avenues.

Distinct immunometabolic signatures in circulating immune cells define disease outcome in acute-on-chronic liver failure

BACKGROUND AND AIMS

Acute-on-chronic liver failure (ACLF) is a complication of cirrhosis characterized by multiple organ failure and high short-term mortality. The pathophysiology of ACLF involves elevated systemic inflammation leading to organ failure, along with immune dysfunction that heightens susceptibility to bacterial infections. However, it is unclear how these aspects are associated with recovery and nonrecovery in ACLF.

APPROACH AND RESULTS

Here, we mapped the single-cell transcriptome of circulating immune cells from patients with ACLF and acute decompensated (AD) cirrhosis and healthy individuals. We further interrogate how these findings, as well as immunometabolic and functional profiles, associate with ACLF-recovery (ACLF-R) or nonrecovery (ACLF-NR). Our analysis unveiled 2 distinct states of classical monocytes (cMons). Hereto, ACLF-R cMons were characterized by transcripts associated with immune and stress tolerance, including anti-inflammatory genes such as RETN and LGALS1 . Additional metabolomic and functional validation experiments implicated an elevated oxidative phosphorylation metabolic program as well as an impaired ACLF-R cMon functionality. Interestingly, we observed a common stress-induced tolerant state, oxidative phosphorylation program, and blunted activation among lymphoid populations in patients with ACLF-R. Conversely, ACLF-NR cMon featured elevated expression of inflammatory and stress response genes such as VIM , LGALS2 , and TREM1 , along with blunted metabolic activity and increased functionality.

CONCLUSIONS

This study identifies distinct immunometabolic cellular states that contribute to disease outcomes in patients with ACLF. Our findings provide valuable insights into the pathogenesis of ACLF, shedding light on factors driving either recovery or nonrecovery phenotypes, which may be harnessed as potential therapeutic targets in the future.

Differential detection workflows for multi-sample single-cell RNA-seq data

In single-cell transcriptomics, differential gene expression (DE) analyses typically focus on testing differences in the average expression of genes between cell types or conditions of interest. Single-cell transcriptomics, however, also has the promise to prioritise genes for which the expression differ in other aspects of the distribution. Here we develop a workflow for assessing differential detection (DD), which tests for differences in the average fraction of samples or cells in which a gene is detected. After benchmarking eight different DD data analysis strategies, we provide a unified workflow for jointly assessing DE and DD. Using simulations and two case studies, we show that DE and DD analysis provide complementary information, both in terms of the individual genes they report and in the functional interpretation of those genes.

Single cell dynamics of tumor specificity vs bystander activity in CD8+ T cells define the diverse immune landscapes in colorectal cancer

CD8+ T cell activation via immune checkpoint blockade (ICB) is successful in microsatellite instable (MSI) colorectal cancer (CRC) patients. By comparison, the success of immunotherapy against microsatellite stable (MSS) CRC is limited. Little is known about the most critical features of CRC CD8+ T cells that together determine the diverse immune landscapes and contrasting ICB responses. Hence, we pursued a deep single cell mapping of CRC CD8+ T cells on transcriptomic and T cell receptor (TCR) repertoire levels in a diverse patient cohort, with additional surface proteome validation. This revealed that CRC CD8+ T cell dynamics are underscored by complex interactions between interferon-γ signaling, tumor reactivity, TCR repertoire, (predicted) TCR antigen-specificities, and environmental cues like gut microbiome or colon tissue-specific 'self-like' features. MSI CRC CD8+ T cells showed tumor-specific activation reminiscent of canonical 'T cell hot' tumors, whereas the MSS CRC CD8+ T cells exhibited tumor unspecific or bystander-like features. This was accompanied by inflammation reminiscent of 'pseudo-T cell hot' tumors. Consequently, MSI and MSS CRC CD8+ T cells showed overlapping phenotypic features that differed dramatically in their TCR antigen-specificities. Given their high discriminating potential for CD8+ T cell features/specificities, we used the single cell tumor-reactive signaling modules in CD8+ T cells to build a bulk tumor transcriptome classification for CRC patients. This "Immune Subtype Classification" (ISC) successfully distinguished various tumoral immune landscapes that showed prognostic value and predicted immunotherapy responses in CRC patients. Thus, we deliver a unique map of CRC CD8+ T cells that drives a novel tumor immune landscape classification, with relevance for immunotherapy decision-making.

Neuroimmune Mechanisms Underlying Post-acute Sequelae of SARS-CoV-2 (PASC) Pain, Predictions from a Ligand-Receptor Interactome

PURPOSE OF REVIEW

Individuals with post-acute sequelae of SARS-CoV-2 (PASC) complain of persistent musculoskeletal pain. Determining how COVID-19 infection produces persistent pain would be valuable for the development of therapeutics aimed at alleviating these symptoms.

RECENT FINDINGS

To generate hypotheses regarding neuroimmune interactions in PASC, we used a ligand-receptor interactome to make predictions about how ligands from PBMCs in individuals with COVID-19 communicate with dorsal root ganglia (DRG) neurons to induce persistent pain. In a structured literature review of -omics COVID-19 studies, we identified ligands capable of binding to receptors on DRG neurons, which stimulate signaling pathways including immune cell activation and chemotaxis, the complement system, and type I interferon signaling. The most consistent finding across immune cell types was an upregulation of genes encoding the alarmins S100A8/9 and MHC-I. This ligand-receptor interactome, from our hypothesis-generating literature review, can be used to guide future research surrounding mechanisms of PASC-induced pain.

Shared miRNA landscapes of COVID-19 and neurodegeneration confirm neuroinflammation as an important overlapping feature

Introduction

Development and worsening of most common neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, and multiple sclerosis, have been associated with COVID-19 However, the mechanisms associated with neurological symptoms in COVID-19 patients and neurodegenerative sequelae are not clear. The interplay between gene expression and metabolite production in CNS is driven by miRNAs. These small non-coding molecules are dysregulated in most common neurodegenerative diseases and COVID-19.

Methods

We have performed a thorough literature screening and database mining to search for shared miRNA landscapes of SARS-CoV-2 infection and neurodegeneration. Differentially expressed miRNAs in COVID-19 patients were searched using PubMed, while differentially expressed miRNAs in patients with five most common neurodegenerative diseases (Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, and multiple sclerosis) were searched using the Human microRNA Disease Database. Target genes of the overlapping miRNAs, identified with the miRTarBase, were used for the pathway enrichment analysis performed with Kyoto Encyclopedia of Genes and Genomes and Reactome.

Results

In total, 98 common miRNAs were found. Additionally, two of them (hsa-miR-34a and hsa-miR-132) were highlighted as promising biomarkers of neurodegeneration, as they are dysregulated in all five most common neurodegenerative diseases and COVID-19. Additionally, hsa-miR-155 was upregulated in four COVID-19 studies and found to be dysregulated in neurodegeneration processes as well. Screening for miRNA targets identified 746 unique genes with strong evidence for interaction. Target enrichment analysis highlighted most significant KEGG and Reactome pathways being involved in signaling, cancer, transcription and infection. However, the more specific identified pathways confirmed neuroinflammation as being the most important shared feature.

Discussion

Our pathway based approach has identified overlapping miRNAs in COVID-19 and neurodegenerative diseases that may have a valuable potential for neurodegeneration prediction in COVID-19 patients. Additionally, identified miRNAs can be further explored as potential drug targets or agents to modify signaling in shared pathways. Graphical AbstractShared miRNA molecules among the five investigated neurodegenerative diseases and COVID-19 were identified. The two overlapping miRNAs, hsa-miR-34a and has-miR-132, present potential biomarkers of neurodegenerative sequelae after COVID-19. Furthermore, 98 common miRNAs between all five neurodegenerative diseases together and COVID-19 were identified. A KEGG and Reactome pathway enrichment analyses was performed on the list of shared miRNA target genes and finally top 20 pathways were evaluated for their potential for identification of new drug targets. A common feature of identified overlapping miRNAs and pathways is neuroinflammation. AD, Alzheimer's disease; ALS, amyotrophic lateral sclerosis; COVID-19, coronavirus disease 2019; HD, Huntington's disease; KEGG, Kyoto Encyclopedia of Genes and Genomes; MS, multiple sclerosis; PD, Parkinson's disease.

Differential haplotype expression in class I MHC genes during SARS-CoV-2 infection of human lung cell lines

Introduction

Cell entry of SARS-CoV-2 causes genome-wide disruption of the transcriptional profiles of genes and biological pathways involved in the pathogenesis of COVID-19. Expression allelic imbalance is characterized by a deviation from the Mendelian expected 1:1 expression ratio and is an important source of allele-specific heterogeneity. Expression allelic imbalance can be measured by allele-specific expression analysis (ASE) across heterozygous informative expressed single nucleotide variants (eSNVs). ASE reflects many regulatory biological phenomena that can be assessed by combining genome and transcriptome information. ASE contributes to the interindividual variability associated with the disease. We aim to estimate the transcriptome-wide impact of SARS-CoV-2 infection by analyzing eSNVs.

Methods

We compared ASE profiles in the human lung cell lines Calu-3, A459, and H522 before and after infection with SARS-CoV-2 using RNA-Seq experiments.

Results

We identified 34 differential ASE (DASE) sites in 13 genes (HLA-A, HLA-B, HLA-C, BRD2, EHD2, GFM2, GSPT1, HAVCR1, MAT2A, NQO2, SUPT6H, TNFRSF11A, UMPS), all of which are enriched in protein binding functions and play a role in COVID-19. Most DASE sites were assigned to the MHC class I locus and were predominantly upregulated upon infection. DASE sites in the MHC class I locus also occur in iPSC-derived airway epithelium basal cells infected with SARS-CoV-2. Using an RNA-Seq haplotype reconstruction approach, we found DASE sites and adjacent eSNVs in phase (i.e., predicted on the same DNA strand), demonstrating differential haplotype expression upon infection. We found a bias towards the expression of the HLA alleles with a higher binding affinity to SARS-CoV-2 epitopes.

Discussion

Independent of gene expression compensation, SARS-CoV-2 infection of human lung cell lines induces transcriptional allelic switching at the MHC loci. This suggests a response mechanism to SARS-CoV-2 infection that swaps HLA alleles with poor epitope binding affinity, an expectation supported by publicly available proteome data.

Extensive blood transcriptome analysis reveals cellular signaling networks activated by circulating glycocalyx components reflecting vascular injury in COVID-19

Background

Degradation of the endothelial protective glycocalyx layer during COVID-19 infection leads to shedding of major glycocalyx components. These circulating proteins and their degradation products may feedback on immune and endothelial cells and activate molecular signaling cascades in COVID-19 associated microvascular injury. To test this hypothesis, we measured plasma glycocalyx components in patients with SARS-CoV-2 infection of variable disease severity and identified molecular signaling networks activated by glycocalyx components in immune and endothelial cells.

Methods

We studied patients with RT-PCR confirmed COVID-19 pneumonia, patients with COVID-19 Acute Respiratory Distress Syndrome (ARDS) and healthy controls (wildtype, n=20 in each group) and measured syndecan-1, heparan sulfate and hyaluronic acid. The in-silico construction of signaling networks was based on RNA sequencing (RNAseq) of mRNA transcripts derived from blood cells and of miRNAs isolated from extracellular vesicles from the identical cohort. Differentially regulated RNAs between groups were identified by gene expression analysis. Both RNAseq data sets were used for network construction of circulating glycosaminoglycans focusing on immune and endothelial cells.

Results

Plasma concentrations of glycocalyx components were highest in COVID-19 ARDS. Hyaluronic acid plasma levels in patients admitted with COVID-19 pneumonia who later developed ARDS during hospital treatment (n=8) were significantly higher at hospital admission than in patients with an early recovery. RNAseq identified hyaluronic acid as an upregulator of TLR4 in pneumonia and ARDS. In COVID-19 ARDS, syndecan-1 increased IL-6, which was significantly higher than in pneumonia. In ARDS, hyaluronic acid activated NRP1, a co-receptor of activated VEGFA, which is associated with pulmonary vascular hyperpermeability and interacted with VCAN (upregulated), a proteoglycan important for chemokine communication.

Conclusions

Circulating glycocalyx components in COVID-19 have distinct biologic feedback effects on immune and endothelial cells and result in upregulation of key regulatory transcripts leading to further immune activation and more severe systemic inflammation. These consequences are most pronounced during the early hospital phase of COVID-19 before pulmonary failure develops. Elevated levels of circulating glycocalyx components may early identify patients at risk for microvascular injury and ARDS. The timely inhibition of glycocalyx degradation could provide a novel therapeutic approach to prevent the development of ARDS in COVID-19.

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.

Identification of Cardiovascular Disease-Related Genes Based on the Co-Expression Network Analysis of Genome-Wide Blood Transcriptome

Inference of co-expression network and identification of disease-related modules and gene sets can help us understand disease-related molecular pathophysiology. We aimed to identify a cardiovascular disease (CVD)-related transcriptomic signature, specifically, in peripheral blood tissue, based on differential expression (DE) and differential co-expression (DcoE) analyses. Publicly available blood sample datasets for coronary artery disease (CAD) and acute coronary syndrome (ACS) statuses were integrated to establish a co-expression network. A weighted gene co-expression network analysis was used to construct modules that include genes with highly correlated expression values. The DE criterion is a linear regression with module eigengenes for module-specific genes calculated from principal component analysis and disease status as the dependent and independent variables, respectively. The DcoE criterion is a paired t-test for intramodular connectivity between disease and matched control statuses. A total of 21 and 23 modules were established from CAD status- and ACS-related datasets, respectively, of which six modules per disease status (i.e., obstructive CAD and ACS) were selected based on the DE and DcoE criteria. For each module, gene-gene interactions with extremely high correlation coefficients were individually selected under the two conditions. Genes displaying a significant change in the number of edges (gene-gene interaction) were selected. A total of 6, 10, and 7 genes in each of the three modules were identified as potential CAD status-related genes, and 14 and 8 genes in each of the two modules were selected as ACS-related genes. Our study identified gene sets and genes that were dysregulated in CVD blood samples. These findings may contribute to the understanding of CVD pathophysiology.

Network Pharmacology and Bioinformatics Analysis Identifies Potential Therapeutic Targets of Paxlovid Against LUAD/COVID-19

Background

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a pandemic in many countries around the world. The virus is highly contagious and has a high fatality rate. Lung adenocarcinoma (LUAD) patients may have higher susceptibility and mortality to COVID-19. While Paxlovid is the first oral drug approved by the U.S. Food and Drug Administration (FDA) for COVID-19, its specific drug mechanism for lung cancer patients infected with COVID-19 remains to be further studied.

Methods

COVID-19 related genes were obtained from NCBI, GeneCards, and KEGG, and then the transcriptome data for LUAD was downloaded from TCGA. The drug targets of Paxlovid were revealed through BATMAN-TCM, DrugBank, SwissTargetPrediction, and TargetNet. The genes related to susceptibility to COVID-19 in LUAD patients were obtained through differential analysis. The interaction of LUAD/COVID-19 related genes was evaluated and displayed by STRING, and a COX risk regression model was established to screen and evaluate the correlation between genes and clinical characteristics. The Venn diagram was drawn to select the candidate targets of Paxlovid against LUAD/COVID-19, and the functional analysis of the target genes was performed using KEGG and GO enrichment analysis. Finally, Cytoscape was used to screen and visualize the Hub Gene, and Autodock was used for molecular docking between the drug and the target.

Result

Bioinformatics analysis was performed by combining COVID-19-related genes with the gene expression and clinical data of LUAD, including analysis of prognosis-related genes, survival rate, and hub genes screened out by the prognosis model. The key targets of Paxlovid against LUAD/COVID-19 were obtained through network pharmacology, the most important targets include IL6, IL12B, LBP. Furthermore, pathway analysis showed that Paxlovid modulates the IL-17 signaling pathway, the cytokine-cytokine receptor interaction, during LUAD/COVID-19 treatment.

Conclusions

Based on bioinformatics and network pharmacology, the prognostic signature of LUAD/COVID-19 patients was screened. And identified the potential therapeutic targets and molecular pathways of Paxlovid Paxlovid in the treatment of LUAD/COVID. As promising features, prognostic signatures and therapeutic targets shed light on improving the personalized management of patients with LUAD.

COVID-19 and plasma cells: Is there long-lived protection?

Infection with SARS-CoV-2, the etiology of the ongoing COVID-19 pandemic, has resulted in over 450 million cases with more than 6 million deaths worldwide, causing global disruptions since early 2020. Memory B cells and durable antibody protection from long-lived plasma cells (LLPC) are the mainstay of most effective vaccines. However, ending the pandemic has been hampered by the lack of long-lived immunity after infection or vaccination. Although immunizations offer protection from severe disease and hospitalization, breakthrough infections still occur, most likely due to new mutant viruses and the overall decline of neutralizing antibodies after 6 months. Here, we review the current knowledge of B cells, from extrafollicular to memory populations, with a focus on distinct plasma cell subsets, such as early-minted blood antibody-secreting cells and the bone marrow LLPC, and how these humoral compartments contribute to protection after SARS-CoV-2 infection and immunization.

Clinical and Gene Features of SARS-CoV-2-Positive Recurrence in Patients Recovered From COVID-19

There are still frequent reports that a number of recovered coronavirus disease 2019 (COVID-19) patients following discharge have re-detectable positive (RP) results by RT-PCR. Understanding the clinical and molecular characteristics of RP patients may have implications for curbing the COVID-19 pandemic. In this study, 318 COVID-19 convalescent patients, including 59 RP patients and 259 non-RP (NRP) patients, were enrolled. Among RP patients, women accounted for a significantly high proportion (67.8%), and the titers of IgG and IgM antibodies in this group were also significantly high. Differentially expressed genes (DEGs), including 692 upregulated and 383 downregulated genes, overlapped in two public GEO datasets containing RP and NRP blood cell samples. Enrichment analysis indicated that these DEGs were related to several key signaling pathways, such as viral infection, immune activation, and inflammatory responses. Importantly, 59 indicator genes constituting the core network exhibited high diagnostic values and were correlated with markers of different immune cells. Among these, 12 drug-related genes were associated with the RP results. Our work suggests that, in addition to clinically available features, blood cell transcriptome sequencing can be performed to obtain gene signatures for diagnosis of RP patients.

A systems biology approach identifies candidate drugs to reduce mortality in severely ill patients with COVID-19

Despite the availability of highly efficacious vaccines, coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lacks effective drug treatment, which results in a high rate of mortality. To address this therapeutic shortcoming, we applied a systems biology approach to the study of patients hospitalized with severe COVID. We show that, at the time of hospital admission, patients who were equivalent on the clinical ordinal scale displayed significant differential monocyte epigenetic and transcriptomic attributes between those who would survive and those who would succumb to COVID-19. We identified messenger RNA metabolism, RNA splicing, and interferon signaling pathways as key host responses overactivated by patients who would not survive. Those pathways are prime drug targets to reduce mortality of critically ill patients with COVID-19, leading us to identify tacrolimus, zotatifin, and nintedanib as three strong candidates for treatment of severely ill patients at the time of hospital admission.

Metabolic Landscape of Bronchoalveolar Lavage Fluid in Coronavirus Disease 2019 at Single Cell Resolution

Abnormal function of immune cells is one of the key mechanisms leading to severe clinical symptoms in coronavirus disease 2019 patients, and metabolic pathways can destroy the function of the immune system by affecting innate and adaptive immune responses. However, the metabolic characteristics of the immune cells of the SARS-CoV-2 infected organs in situ remaining elusive. We reanalyzed the metabolic-related gene profiles in single-cell RNA sequencing data, drew the metabolic landscape in bronchoalveolar lavage fluid immune cells, and elucidated the metabolic remodeling mechanism that might lead to the progression of COVID-19 and the cytokine storm. Enhanced glycolysis is the most important common metabolic feature of all immune cells in COVID-19 patients. CCL2⁺ T cells, Group 2 macrophages with high SPP1 expression and myeloid dendritic cells are among the main contributors to the cytokine storm produced by infected lung tissue. Two metabolic analysis methods, including Compass, showed that glycolysis, fatty acid metabolism, bile acid synthesis and purine and pyrimidine metabolism levels of CCL2⁺ T cells, Group 2 macrophages and myeloid dendritic cells were upregulated and correlated with cytokine storms of COVID-19 patients. This might be the key metabolic regulatory factor for immune cells to produce large quantities of cytokines.

Nuclear Tkt promotes ischemic heart failure via the cleaved Parp1/Aif axis

Transketolase (Tkt), an enzyme in pentose phosphate pathway, has been reported to regulate genome instability and cell survival in cancers. Yet, the role of Tkt after myocardial ischemic injury remains to be elucidated. Label-free proteomics revealed dramatic elevation of Tkt in murine hearts after myocardial infarction (MI). Lentivirus-mediated Tkt knockdown ameliorated cardiomyocyte apoptosis and preserved the systolic function after myocardial ischemic injury. In contrast, Tkt overexpression led to the opposite effects. Inducible conditional cardiomyocyte Tkt-knockout mice were generated, and cardiomyocyte-expressed Tkt was found to play an intrinsic role in the ischemic heart failure of these model mice. Furthermore, through luciferase assay and chromatin immunoprecipitation, Tkt was shown to be a direct target of transcription factor Krüppel-like factor 5 (Klf5). In cardiomyocytes under ischemic stress, Tkt redistributed into the nucleus. By binding with the full-length poly(ADP-ribose) polymerase 1 (Parp1), facilitating its cleavage, and activating apoptosis inducible factor (Aif) subsequently, nuclear Tkt demonstrated its non-metabolic functions. Overall, our study confirmed that elevated nuclear Tkt plays a noncanonical role in promoting cardiomyocyte apoptosis via the cleaved Parp1/Aif pathway, leading to the deterioration of cardiac dysfunction.

Mechanistic Insights Into the Immune Pathophysiology of COVID-19; An In-Depth Review

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), which causes coronavirus-19 (COVID-19), has caused significant morbidity and mortality globally. In addition to the respiratory manifestations seen in severe cases, multi-organ pathologies also occur, making management a much-debated issue. In addition, the emergence of new variants can potentially render vaccines with a relatively limited utility. Many investigators have attempted to elucidate the precise pathophysiological mechanisms causing COVID-19 respiratory and systemic disease. Spillover of lung-derived cytokines causing a cytokine storm is considered the cause of systemic disease. However, recent studies have provided contradictory evidence, whereby the extent of cytokine storm is insufficient to cause severe illness. These issues are highly relevant, as management approaches considering COVID-19 a classic form of acute respiratory distress syndrome with a cytokine storm could translate to unfounded clinical decisions, detrimental to patient trajectory. Additionally, the precise immune cell signatures that characterize disease of varying severity remain contentious. We provide an up-to-date review on the immune dysregulation caused by COVID-19 and highlight pertinent discussions in the scientific community. The response from the scientific community has been unprecedented regarding the development of highly effective vaccines and cutting-edge research on novel therapies. We hope that this review furthers the conversations held by scientists and informs the aims of future research projects, which will potentially further our understanding of COVID-19 and its immune pathogenesis.

Cardiovascular Dysfunction in COVID-19: Association Between Endothelial Cell Injury and Lactate

Coronavirus disease 2019 (COVID-19), an infectious respiratory disease propagated by a new virus known as Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), has resulted in global healthcare crises. Emerging evidence from patients with COVID-19 suggests that endothelial cell damage plays a central role in COVID-19 pathogenesis and could be a major contributor to the severity and mortality of COVID-19. Like other infectious diseases, the pathogenesis of COVID-19 is closely associated with metabolic processes. Lactate, a potential biomarker in COVID-19, has recently been shown to mediate endothelial barrier dysfunction. In this review, we provide an overview of cardiovascular injuries and metabolic alterations caused by SARS-CoV-2 infection. We also propose that lactate plays a potential role in COVID-19-driven endothelial cell injury.

Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic

Background

The recent emergence of COVID-19, rapid worldwide spread, and incomplete knowledge of molecular mechanisms underlying SARS-CoV-2 infection have limited development of therapeutic strategies. Our objective was to systematically investigate molecular regulatory mechanisms of COVID-19, using a combination of high throughput RNA-sequencing-based transcriptomics and systems biology approaches.

Methods

RNA-Seq data from peripheral blood mononuclear cells (PBMCs) of healthy persons, mild and severe 17 COVID-19 patients were analyzed to generate a gene expression matrix. Weighted gene co-expression network analysis (WGCNA) was used to identify co-expression modules in healthy samples as a reference set. For differential co-expression network analysis, module preservation and module-trait relationships approaches were used to identify key modules. Then, protein-protein interaction (PPI) networks, based on co-expressed hub genes, were constructed to identify hub genes/TFs with the highest information transfer (hub-high traffic genes) within candidate modules.

Results

Based on differential co-expression network analysis, connectivity patterns and network density, 72% (15 of 21) of modules identified in healthy samples were altered by SARS-CoV-2 infection. Therefore, SARS-CoV-2 caused systemic perturbations in host biological gene networks. In functional enrichment analysis, among 15 non-preserved modules and two significant highly-correlated modules (identified by MTRs), 9 modules were directly related to the host immune response and COVID-19 immunopathogenesis. Intriguingly, systemic investigation of SARS-CoV-2 infection identified signaling pathways and key genes/proteins associated with COVID-19's main hallmarks, e.g., cytokine storm, respiratory distress syndrome (ARDS), acute lung injury (ALI), lymphopenia, coagulation disorders, thrombosis, and pregnancy complications, as well as comorbidities associated with COVID-19, e.g., asthma, diabetic complications, cardiovascular diseases (CVDs), liver disorders and acute kidney injury (AKI). Topological analysis with betweenness centrality (BC) identified 290 hub-high traffic genes, central in both co-expression and PPI networks. We also identified several transcriptional regulatory factors, including NFKB1, HIF1A, AHR, and TP53, with important immunoregulatory roles in SARS-CoV-2 infection. Moreover, several hub-high traffic genes, including IL6, IL1B, IL10, TNF, SOCS1, SOCS3, ICAM1, PTEN, RHOA, GDI2, SUMO1, CASP1, IRAK3, HSPA5, ADRB2, PRF1, GZMB, OASL, CCL5, HSP90AA1, HSPD1, IFNG, MAPK1, RAB5A, and TNFRSF1A had the highest rates of information transfer in 9 candidate modules and central roles in COVID-19 immunopathogenesis.

Conclusion

This study provides comprehensive information on molecular mechanisms of SARS-CoV-2-host interactions and identifies several hub-high traffic genes as promising therapeutic targets for the COVID-19 pandemic.

Metabolic Reprogramming in COVID-19

Plenty of research has revealed virus induced alternations in metabolic pathways, which is known as metabolic reprogramming. Studies focusing on COVID-19 have uncovered significant changes in metabolism, resulting in the perspective that COVID-19 is a metabolic disease. Reprogramming of amino acid, glucose, cholesterol and fatty acid is distinctive characteristic of COVID-19 infection. These metabolic changes in COVID-19 have a critical role not only in producing energy and virus constituent elements, but also in regulating immune response, offering new insights into COVID-19 pathophysiology. Remarkably, metabolic reprogramming provides great opportunities for developing novel biomarkers and therapeutic agents for COVID-19 infection. Such novel agents are expected to be effective adjuvant therapies. In this review, we integrate present studies about major metabolic reprogramming in COVID-19, as well as the possibility of targeting reprogrammed metabolism to combat virus infection.

Suppressive Monocytes Impair MAIT Cells Response via IL-10 in Patients with Severe COVID-19

Immune cell responses are strikingly altered in patients with severe coronavirus disease 2019 (COVID-19), but the immunoregulatory process in these individuals is not fully understood. In this study, 23 patients with mild and 22 patients with severe COVID-19 and 6 asymptomatic carriers of COVID-19 were enrolled, along with 44 healthy controls (HC). Peripheral immune cells in HC and patients with COVID-19 were comprehensively profiled using mass cytometry. We found that in patients with severe COVID-19, the number of HLA-DR^low/- monocytes was significantly increased, but that of mucosal-associated invariant T (MAIT) cells was greatly reduced. MAIT cells were highly activated but functionally impaired in response to Escherichia coli and IL-12/IL-18 stimulation in patients with severe COVID-19, especially those with microbial coinfection. Single-cell transcriptome analysis revealed that IFN-stimulated genes were significantly upregulated in peripheral MAIT cells and monocytes from patients with severe COVID-19. IFN-α pretreatment suppressed MAIT cells' response to E. coli by triggering high levels of IL-10 production by HLA-DR^low/--suppressive monocytes. Blocking IFN-α or IL-10 receptors rescued MAIT cell function in patients with severe COVID-19. Moreover, plasma from patients with severe COVID-19 inhibited HLA-DR expression by monocytes through IL-10. These data indicate a unique pattern of immune dysregulation in severe COVID-19, which is characterized by enrichment of suppressive HLA-DR^low/- monocytes associated with functional impairment of MAIT cells through the IFN/IL-10 pathway.