Longitudinal transcriptome analyses show robust T cell immunity during recovery from COVID-19

Identification of gene and protein signatures associated with long-term effects of COVID-19 on the immune system after patient recovery by analyzing single-cell multi-omics data using a machine learning approach

Viral infections significantly impact the immune system, and impact will persist until recovery. However, the influence of severe acute respiratory syndrome coronavirus 2 infection on the homeostatic immune status and secondary immune response in recovered patients remains unclear. To investigate these persistent alterations, we employed five feature-ranking algorithms (LASSO, MCFS, RF, CATBoost, and XGBoost), incremental feature selection, synthetic minority oversampling technique and two classification algorithms (decision tree and k-nearest neighbors) to analyze multi-omics data (surface proteins and transcriptome) from coronavirus disease 2019 (COVID-19) recovered patients and healthy controls post-influenza vaccination. The single-cell multi-omics dataset was divided into five subsets corresponding to five immune cell subtypes: B cells, CD4+ T cells, CD8+ T cells, Monocytes, and Natural Killer cells. Each cell was represented by 28,402 scRNA-seq (RNA) features, 3 Hash Tag Oligo (HTO) features, 138 Cellular indexing of transcriptomes and epitopes by sequencing (CITE) features and 23,569 Single Cell Transform (SCT) features. Some multi-omics markers were identified and effective classifiers were constructed. Our findings indicate a distinct immune status in COVID-19 recovered patients, characterized by low expression of ribosomal protein (RPS26) and high expression of immune cell surface proteins (CD33, CD48). Notably, TMEM176B, a membrane protein, was highly expressed in monocytes of COVID-19 convalescent patients. These observations aid in discerning molecular differences among immune cell subtypes and contribute to understanding the prolonged effects of COVID-19 on the immune system, which is valuable for treating infectious diseases like COVID-19.

Bacterial sepsis causes more dramatic pathogenetic changes in the Th1 pathway than does viral (COVID-19) sepsis: a prospective observational study of whole blood transcriptomes

OBJECTIVES

This study aimed to comprehensively compare host responses of patients with bacterial sepsis and those with viral (COVID-19) sepsis by analyzing messenger RNA (mRNA) and microRNA (miRNA) profiles to shed light on their distinct pathophysiological mechanisms.

DESIGN

Prospective observational study.

SETTING

Whole blood RNA sequencing was used to analyze mRNA and miRNA profiles of patients diagnosed as having bacterial sepsis or viral (COVID-19) sepsis at the Department of Trauma and Emergency Medicine, Osaka University Graduate School of Medicine.

PATIENTS

Twenty-two bacterial sepsis patients, 35 viral (COVID-19) sepsis patients, and 15 healthy subjects admitted to the department were included. We diagnosed bacterial sepsis patients according to the sepsis-3 criterion that the Sequential Organ Failure Assessment score must increase to 2 points or more among patients with suspected infections. Viral (COVID-19) sepsis patients were diagnosed using SARS-CoV-2 RT-PCR testing, and presence of pneumonia was assessed through chest computed tomography scans.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

For RNA sequencing, 14,500 mRNAs, 1121 miRNAs, and 2556 miRNA-targeted mRNAs were available for analysis in the bacterial sepsis patients. Numbers of genes showing upregulated: downregulated gene expression (false discovery rate < 0.05, |log2 fold change| > 1.5) were 256:2887 for mRNA, 53:5 for miRNA, and 49:2507 for miRNA-targeted mRNA. Similarly, in viral (COVID-19) sepsis patients, 14,500 mRNAs, 1121 miRNAs, and 327 miRNA-targeted mRNAs were analyzed, with numbers of genes exhibiting upregulated: downregulated gene expression of 672:1147 for mRNA, 3:4 for miRNA, and 165:162 for miRNA-targeted mRNA. This analysis revealed significant differences in the numbers of upregulated and downregulated genes expressed and pathways between the bacterial sepsis and viral (COVID-19) sepsis patients. Bacterial sepsis patients showed activation of the PD-1 and PD-L1 cancer immunotherapy signaling pathway and concurrent suppression of Th1 signaling.

CONCLUSION

Our study illuminated distinct molecular variances between bacterial sepsis and viral (COVID-19) sepsis. Bacterial sepsis patients had a greater number of upregulated and downregulated genes and pathways compared to viral (COVID-19) sepsis patients. Especially, bacterial sepsis caused more dramatic pathogenetic changes in the Th1 pathway than did viral (COVID-19) sepsis.

Longitudinal transcriptomic analysis reveals persistent enrichment of iron homeostasis and erythrocyte function pathways in severe COVID-19 ARDS

Introduction

The acute respiratory distress syndrome (ARDS) is a common complication of severe COVID-19 and contributes to patient morbidity and mortality. ARDS is a heterogeneous syndrome caused by various insults, and results in acute hypoxemic respiratory failure. Patients with ARDS from COVID-19 may represent a subgroup of ARDS patients with distinct molecular profiles that drive disease outcomes. Here, we hypothesized that longitudinal transcriptomic analysis may identify distinct dynamic pathobiological pathways during COVID-19 ARDS.

Methods

We identified a patient cohort from an existing ICU biorepository and established three groups for comparison: 1) patients with COVID-19 ARDS that survived hospitalization (COVID survivors, n = 4), 2) patients with COVID-19 ARDS that did not survive hospitalization (COVID non-survivors, n = 5), and 3) patients with ARDS from other causes as a control group (ARDS controls, n = 4). RNA was isolated from peripheral blood mononuclear cells (PBMCs) at 4 time points (Days 1, 3, 7, and 10 following ICU admission) and analyzed by bulk RNA sequencing.

Results

We first compared transcriptomes between groups at individual timepoints and observed significant heterogeneity in differentially expressed genes (DEGs). Next, we utilized the likelihood ratio test to identify genes that exhibit different patterns of change over time between the 3 groups and identified 341 DEGs across time, including hemoglobin subunit alpha 2 (HBA1, HBA2), hemoglobin subunit beta (HBB), von Willebrand factor C and EGF domains (VWCE), and carbonic anhydrase 1 (CA1), which all demonstrated persistent upregulation in the COVID non-survivors compared to COVID survivors. Of the 341 DEGs, 314 demonstrated a similar pattern of persistent increased gene expression in COVID non-survivors compared to survivors, associated with canonical pathways of iron homeostasis signaling, erythrocyte interaction with oxygen and carbon dioxide, erythropoietin signaling, heme biosynthesis, metabolism of porphyrins, and iron uptake and transport.

Discussion

These findings describe significant differences in gene regulation during patient ICU course between survivors and non-survivors of COVID-19 ARDS. We identified multiple pathways that suggest heme and red blood cell metabolism contribute to disease outcomes. This approach is generalizable to larger cohorts and supports an approach of longitudinal sampling in ARDS molecular profiling studies, which may identify novel targetable pathways of injury and resolution.

The knowns and unknowns of long COVID-19: from mechanisms to therapeutical approaches

The coronavirus disease 2019 (COVID-19) pandemic caused by SARS-CoV-2 has been defined as the greatest global health and socioeconomic crisis of modern times. While most people recover after being infected with the virus, a significant proportion of them continue to experience health issues weeks, months and even years after acute infection with SARS-CoV-2. This persistence of clinical symptoms in infected individuals for at least three months after the onset of the disease or the emergence of new symptoms lasting more than two months, without any other explanation and alternative diagnosis have been named long COVID, long-haul COVID, post-COVID-19 conditions, chronic COVID, or post-acute sequelae of SARS-CoV-2 (PASC). Long COVID has been characterized as a constellation of symptoms and disorders that vary widely in their manifestations. Further, the mechanisms underlying long COVID are not fully understood, which hamper efficient treatment options. This review describes predictors and the most common symptoms related to long COVID's effects on the central and peripheral nervous system and other organs and tissues. Furthermore, the transcriptional markers, molecular signaling pathways and risk factors for long COVID, such as sex, age, pre-existing condition, hospitalization during acute phase of COVID-19, vaccination, and lifestyle are presented. Finally, recommendations for patient rehabilitation and disease management, as well as alternative therapeutical approaches to long COVID sequelae are discussed. Understanding the complexity of this disease, its symptoms across multiple organ systems and overlapping pathologies and its possible mechanisms are paramount in developing diagnostic tools and treatments.

Blood-brain barrier disruption and sustained systemic inflammation in individuals with long COVID-associated cognitive impairment

Vascular disruption has been implicated in coronavirus disease 2019 (COVID-19) pathogenesis and may predispose to the neurological sequelae associated with long COVID, yet it is unclear how blood-brain barrier (BBB) function is affected in these conditions. Here we show that BBB disruption is evident during acute infection and in patients with long COVID with cognitive impairment, commonly referred to as brain fog. Using dynamic contrast-enhanced magnetic resonance imaging, we show BBB disruption in patients with long COVID-associated brain fog. Transcriptomic analysis of peripheral blood mononuclear cells revealed dysregulation of the coagulation system and a dampened adaptive immune response in individuals with brain fog. Accordingly, peripheral blood mononuclear cells showed increased adhesion to human brain endothelial cells in vitro, while exposure of brain endothelial cells to serum from patients with long COVID induced expression of inflammatory markers. Together, our data suggest that sustained systemic inflammation and persistent localized BBB dysfunction is a key feature of long COVID-associated brain fog.

Evaluation of long non-coding RNAs EGOT, NRAV, NRIR and mRNAs ISG15 and IFITM3 expressions in COVID-19 patients

Individuals with Coronavirus Disease 2019 (COVID-19) may show no symptoms to moderate or severe complications. This variation may be due to differences in the strength of the immune response, including a delayed interferon (IFN) response in asymptomatic patients and higher IFN levels in severe patients. Some long non-coding RNAs (lncRNAs), as regulators of the IFN pathway, may contribute to the emergence of different COVID-19 symptoms. This study aimed to comparatively investigate the relationship between lncRNAs (eosinophil granule ontogeny transcript (EGOT), negative regulator of antiviral response (NRAV), and negative regulator of interferon response (NRIR)), alongside interferon-stimulated genes (ISGs) like ISG-15 and interferon-induced transmembrane protein 3 (IFITM3) in COVID-19 patients with asymptomatic, moderate, and severe symptoms. Buffy coat samples were collected from 17 asymptomatic, 23 moderate, 22 severe patients, and 44 healthy controls. Quantitative real-time PCR was utilized to determine the expression levels. In a comparison between COVID-19 patients and healthy individuals, higher expression levels of EGOT and NRAV were observed in severe and moderate patients. NRIR expression was increased across all patient groups. Meanwhile, ISG15 expression decreased in all patient groups, and the moderate group showed a significant decrease in IFITM3 expression. Comparing COVID-19 patient groups, EGOT expression was significantly higher in moderate COVID-19 patients compared to asymptomatic patients. NRAV was higher in moderate and severe patients compared to asymptomatic. NRIR levels did not differ significantly between the COVID-19 patient groups. ISG15 was higher in moderate and severe patients compared to asymptomatic. IFITM3 expression was significantly higher in severe patients compared to the moderate group. In severe COVID-19 patients, EGOT expression was positively correlated with NRAV levels. EGOT and NRAV showed a significant positive correlation in asymptomatic patients, and both were positively correlated with IFITM3 expression. This study suggests that EGOT, NRAV, NRIR, ISG15, and IFITM3 may serve as diagnostic biomarkers for COVID-19. The lncRNA NRAV may be a good biomarker in a prognostic panel between asymptomatic and severe patients in combination with other high-sensitivity biomarkers. EGOT, NRAV, and ISG15 could also be considered as specific biomarkers in a prognostic panel comparing asymptomatic and moderate patients with other high-sensitivity biomarkers.

Evaluation of the Expression of Infection-Related Long Noncoding RNAs among COVID-19 Patients: A Case-Control Study

Background and Aims

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a worldwide pandemic, activates signaling cascades and leads to innate immune responses and secretion of multiple chemokines and cytokines. Long noncoding RNAs (lncRNAs) have a crucial role in inflammatory pathways. Through our search on the PubMed database, we discovered that existing research has primarily focused on examining the regulatory impacts of five lncRNAs in the context of viral infections. However, their role in regulating other conditions, including SARS-CoV-2, has not been explored. Therefore, this study aimed to investigate the expression pattern of lncRNAs in the peripheral blood mononuclear cells (PBMC) and their potential roles in SARS-CoV-2 infection. Potentially significant competing endogenous RNA (ceRNA) networks of these five lncRNAs were found using online in-silico techniques.

Methods

Ethylenediaminetetraacetic acid (EDTA) blood samples of the control group consisted of 45 healthy people, and a total of 53 COVID-19-infected patients in case group, with a written informed consent, was collected. PBMCs were extracted, and then, the RNA extraction and complementary DNA (cDNA) synthesis was performed. The expression of five lncRNAs (lnc ISR, lnc ATV, lnc PAAN, lnc SG20, and lnc HEAL) was assessed by real-time PCR. In order to evaluate the biomarker roles of genes, receiver operating characteristic (ROC) curve was drawn.

Results

Twenty-four (53.3%) and 29 (54.7%) of healthy and COVID-19-infected participants were male, respectively. The most prevalent symptoms were as follows: cough, general weakness, contusion, headache, and sore throat. The results showed that three lncRNAs, including lnc ISR, lnc ATV, and lnc HEAL, were expressed dramatically higher in the case group compared to healthy controls. According to ROC curve analysis, lnc ATV has a higher AUC and is a better biomarker to differentiate COVID-19 patients from the healthy controls. Then, using bioinformatics methods, the ceRNA network of these lncRNAs enabled the identification of mRNAs and miRNAs with crucial functions in COVID-19.

Conclusion

The considerable higher expression of ISR, ATV, and HEAL lncRNAs and the significant area under curve (AUC) in ROC curve demonstrate that these RNAs probably have a potential role in controlling the host innate immune responses and regulate the viral replication of SARS-CoV-2. However, these assumptions need further in vitro and in vivo investigations to be confirmed.

Non-coding RNAs expression in SARS-CoV-2 infection: pathogenesis, clinical significance, and therapeutic targets

The coronavirus disease 2019 (COVID-19) pandemic has been looming globally for three years, yet the diagnostic and treatment methods for COVID-19 are still undergoing extensive exploration, which holds paramount importance in mitigating future epidemics. Host non-coding RNAs (ncRNAs) display aberrations in the context of COVID-19. Specifically, microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) exhibit a close association with viral infection and disease progression. In this comprehensive review, an overview was presented of the expression profiles of host ncRNAs following SARS-CoV-2 invasion and of the potential functions in COVID-19 development, encompassing viral invasion, replication, immune response, and multiorgan deficits which include respiratory system, cardiac system, central nervous system, peripheral nervous system as well as long COVID. Furthermore, we provide an overview of several promising host ncRNA biomarkers for diverse clinical scenarios related to COVID-19, such as stratification biomarkers, prognostic biomarkers, and predictive biomarkers for treatment response. In addition, we also discuss the therapeutic potential of ncRNAs for COVID-19, presenting ncRNA-based strategies to facilitate the development of novel treatments. Through an in-depth analysis of the interplay between ncRNA and COVID-19 combined with our bioinformatic analysis, we hope to offer valuable insights into the stratification, prognosis, and treatment of COVID-19.

The regulation of lncRNAs and miRNAs in SARS-CoV-2 infection

The coronavirus disease 2019 (COVID-19) was a global endemic that continues to cause a large number of severe illnesses and fatalities. There is increasing evidence that non-coding RNAs (ncRNAs) are crucial regulators of viral infection and antiviral immune response and the role of non-coding RNAs in SARS-CoV-2 infection has now become the focus of scholarly inquiry. After SARS-CoV-2 infection, some ncRNAs' expression levels are regulated to indirectly control the expression of antiviral genes and viral gene replication. However, some other ncRNAs are hijacked by SARS-CoV-2 in order to help the virus evade the immune system by suppressing the expression of type I interferon (IFN-1) and controlling cytokine levels. In this review, we summarize the recent findings of long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) among non-coding RNAs in SARS-CoV-2 infection and antiviral response, discuss the potential mechanisms of actions, and prospects for the detection, treatment, prevention and future directions of SARS-CoV-2 infection research.

Transcriptomic identification of genes expressed in invasive S. aureus diabetic foot ulcer infection

Introduction

Infection in diabetic foot ulcers (DFUs) is one of the major complications associated with patients with diabetes. Staphylococcus aureus is the most common offending pathogen in patients with infected DFU. Previous studies have suggested the application of species-specific antibodies against S. aureus for diagnosis and monitoring treatment response. Early and accurate identification of the main pathogen is critical for management of DFU infection. Understanding the host immune response against species-specific infection may facilitate diagnosis and may suggest potential intervention options to promote healing infected DFUs. We sought to investigate evolving host transcriptome associated with surgical treatment of S. aureus- infected DFU.

Methods

This study compared the transcriptome profile of 21 patients with S. aureus- infected DFU who underwent initial foot salvage therapy with irrigation and debridement followed by intravenous antibiotic therapy. Blood samples were collected at the recruitment (0 weeks) and 8 weeks after therapy to isolate peripheral blood mononuclear cells (PBMCs). We analyzed the PBMC expression of transcriptomes at two different time points (0 versus 8 weeks). Subjects were further divided into two groups at 8 weeks: healed (n = 17, 80.95%) versus non-healed (n = 4, 19.05%) based on the wound healing status. DESeq2 differential gene analysis was performed.

Results and discussion

An increased expression of IGHG1, IGHG2, IGHG3, IGLV3-21, and IGLV6-57 was noted during active infection at 0 weeks compared with that at 8 weeks. Lysine- and arginine-rich histones (HIST1H2AJ, HIST1H2AL, HIST1H2BM, HIST1H3B, and HIST1H3G) were upregulated at the initial phase of active infection at 0 weeks. CD177 and RRM2 were also upregulated at the initial phase of active infection (0 weeks) compared with that at 8 weeks of follow-up. Genes of heat shock protein members (HSPA1A, HSPE1, and HSP90B1) were high in not healed patients compared with that in healed patients 8 weeks after therapy. The outcome of our study suggests that the identification of genes evolution based on a transcriptomic profiling could be a useful tool for diagnosing infection and assessing severity and host immune response to therapies.

Dynamics of Gene Expression Profiling and Identification of High-Risk Patients for Severe COVID-19

The clinical manifestations of SARS-CoV-2 infection vary widely, from asymptomatic infection to the development of acute respiratory distress syndrome (ARDS) and death. The host response elicited by SARS-CoV-2 plays a key role in determining the clinical outcome. We hypothesized that determining the dynamic whole blood transcriptomic profile of hospitalized adult COVID-19 patients and characterizing the subgroup that develops severe disease and ARDS would broaden our understanding of the heterogeneity in clinical outcomes. We recruited 60 hospitalized patients with RT-PCR-confirmed SARS-CoV-2 infection, among whom 19 developed ARDS. Peripheral blood was collected using PAXGene RNA tubes within 24 h of admission and on day 7. There were 2572 differently expressed genes in patients with ARDS at baseline and 1149 at day 7. We found a dysregulated inflammatory response in COVID-19 ARDS patients, with an increased expression of genes related to pro-inflammatory molecules and neutrophil and macrophage activation at admission, in addition to an immune regulation loss. This led, in turn, to a higher expression of genes related to reactive oxygen species, protein polyubiquitination, and metalloproteinases in the latter stages. Some of the most significant differences in gene expression found between patients with and without ARDS corresponded to long non-coding RNA involved in epigenetic control.

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.

Multi-omics characterization of RNA binding proteins reveals disease comorbidities and potential drugs in COVID-19

The COVID-19 has led to a devastating global health crisis, which emphasizes the urgent need to deepen our understanding of the molecular mechanism and identifying potential antiviral drugs. Here, we comprehensively analyzed the transcriptomic and proteomic profiles of 178 COVID-19 patients, ranging from asymptomatic to critically ill. Our analyses found that the RNA binding proteins (RBPs) were likely to be perturbed in infection. Interactome analysis revealed that RBPs interact with virus proteins and the viral interacting RBPs were likely to locate in central regions of human protein-protein interaction network. Functional enrichment analysis revealed that the viral interacting RBPs were likely to be enriched in RNA transport, apoptosis and viral genome replication-related pathways. Based on network proximity analyses of 299 human complex-disease genes and COVID-19-related RBPs in the human interactome, we revealed the significant associations between complex diseases and COVID-19. Network analysis also implicated potential antiviral drugs for treatment of COVID-19. In summary, our integrative characterization of COVID-19 patients may thus help providing evidence regarding pathophysiology and potential therapeutic strategies for COVID-19.

Role of the MicroRNAs in the Pathogenic Mechanism of Painful Symptoms in Long COVID: Systematic Review

The ongoing pandemic of COVID-19 has caused more than 6.7 million tragic deaths, plus, a large percentage of people who survived it present a myriad of chronic symptoms that last for at least 6 months; this has been named as long COVID. Some of the most prevalent are painful symptoms like headache, joint pain, migraine, neuropathic-like pain, fatigue and myalgia. MicroRNAs are small non-coding RNAs that regulate genes, and their involvement in several pathologies has been extensively shown. A deregulation of miRNAs has been observed in patients with COVID-19. The objective of the present systematic review was to show the prevalence of chronic pain-like symptoms of patients with long COVID and based on the expression of miRNAs in patients with COVID-19, and to present a proposal on how they may be involved in the pathogenic mechanisms of chronic pain-like symptoms. A systematic review was carried out in online databases for original articles published between March 2020 to April 2022; the systematic review followed the PRISMA guidelines, and it was registered in PROSPERO with registration number CRD42022318992. A total of 22 articles were included for the evaluation of miRNAs and 20 regarding long COVID; the overall prevalence of pain-like symptoms was around 10 to 87%, plus, the miRNAs that were commonly up and downregulated were miR-21-5p, miR-29a,b,c-3p miR-92a,b-3p, miR-92b-5p, miR-126-3p, miR-150-5p, miR-155-5p, miR-200a, c-3p, miR-320a,b,c,d,e-3p, and miR-451a. The molecular pathways that we hypothesized to be modulated by these miRNAs are the IL-6/STAT3 proinflammatory axis and the compromise of the blood-nerve barrier; these two mechanisms could be associated with the prevalence of fatigue and chronic pain in the long COVID population, plus they could be novel pharmacological targets in order to reduce and prevent these symptoms.

Cardiovascular Implications of microRNAs in Coronavirus Disease 2019

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic continues to be a global challenge due to resulting morbidity and mortality. Cardiovascular (CV) involvement is a crucial complication in coronavirus disease 2019 (COVID-19), and no strategies are available to prevent or specifically address CV events in COVID-19 patients. The identification of molecular partners contributing to CV manifestations in COVID-19 patients is crucial for providing early biomarkers, prognostic predictors, and new therapeutic targets. The current report will focus on the role of microRNAs (miRNAs) in CV complications associated with COVID-19. Indeed, miRNAs have been proposed as valuable biomarkers and predictors of both cardiac and vascular damage occurring in SARS-CoV-2 infection. SIGNIFICANCE STATEMENT: It is essential to identify the molecular mediators of coronavirus disease 2019 (COVID-19) cardiovascular (CV) complications. This report focused on the role of microRNAs in CV complications associated with COVID-19, discussing their potential use as biomarkers, prognostic predictors, and therapeutic targets.

Deep autoencoder for interpretable tissue-adaptive deconvolution and cell-type-specific gene analysis

Single-cell RNA-sequencing has become a powerful tool to study biologically significant characteristics at explicitly high resolution. However, its application on emerging data is currently limited by its intrinsic techniques. Here, we introduce Tissue-AdaPtive autoEncoder (TAPE), a deep learning method connecting bulk RNA-seq and single-cell RNA-seq to achieve precise deconvolution in a short time. By constructing an interpretable decoder and training under a unique scheme, TAPE can predict cell-type fractions and cell-type-specific gene expression tissue-adaptively. Compared with popular methods on several datasets, TAPE has a better overall performance and comparable accuracy at cell type level. Additionally, it is more robust among different cell types, faster, and sensitive to provide biologically meaningful predictions. Moreover, through the analysis of clinical data, TAPE shows its ability to predict cell-type-specific gene expression profiles with biological significance. We believe that TAPE will enable and accelerate the precise analysis of high-throughput clinical data in a wide range.

Blood Transcriptomes of SARS-CoV-2-Infected Kidney Transplant Recipients Associated with Immune Insufficiency Proportionate to Severity

BACKGROUND

Among patients with COVID-19, kidney transplant recipients (KTRs) have poor outcomes compared with non-KTRs. To provide insight into management of immunosuppression during acute illness, we studied immune signatures from the peripheral blood during and after COVID-19 infection from a multicenter KTR cohort.

METHODS

We ascertained clinical data by chart review. A single sample of blood was collected for transcriptome analysis. Total RNA was poly-A selected and RNA was sequenced to evaluate transcriptome changes. We also measured cytokines and chemokines of serum samples collected during acute infection.

RESULTS

A total of 64 patients with COVID-19 in KTRs were enrolled, including 31 with acute COVID-19 (<4 weeks from diagnosis) and 33 with post-acute COVID-19 (>4 weeks postdiagnosis). In the blood transcriptome of acute cases, we identified genes in positive or negative association with COVID-19 severity scores. Functional enrichment analyses showed upregulation of neutrophil and innate immune pathways but downregulation of T cell and adaptive immune activation pathways. This finding was independent of lymphocyte count, despite reduced immunosuppressant use in most KTRs. Compared with acute cases, post-acute cases showed "normalization" of these enriched pathways after 4 weeks, suggesting recovery of adaptive immune system activation despite reinstitution of immunosuppression. Analysis of the non-KTR cohort with COVID-19 showed significant overlap with KTRs in these functions. Serum inflammatory cytokines followed an opposite trend (i.e., increased with disease severity), indicating that blood lymphocytes are not the primary source.

CONCLUSIONS

The blood transcriptome of KTRs affected by COVID-19 shows decreases in T cell and adaptive immune activation pathways during acute disease that, despite reduced immunosuppressant use, associate with severity. These pathways show recovery after acute illness.

Non-coding RNAs: Key players in T cell exhaustion

T cell exhaustion caused by continuous antigen stimulation in chronic viral infections and the tumor microenvironment is a major barrier to successful elimination of viruses and tumor cells. Although immune checkpoint inhibitors should reverse T cell exhaustion, shortcomings, such as off-target effects and single targets, limit their application. Therefore, it is important to identify molecular targets in effector T cells that simultaneously regulate the expression of multiple immune checkpoints. Over the past few years, non-coding RNAs, including microRNAs and long non-coding RNAs, have been shown to participate in the immune response against viral infections and tumors. In this review, we focus on the roles and underlying mechanisms of microRNAs and long non-coding RNAs in the regulation of T cell exhaustion during chronic viral infections and tumorigenesis. We hope that this review will stimulate research to provide more precise and effective immunotherapies against viral infections and tumors.

Potential therapeutic strategies for quercetin targeting critical pathological mechanisms associated with colon adenocarcinoma and COVID-19

Patients with colon adenocarcinoma (COAD) are at a higher probability of infection with COVID-19 than healthy individuals. However, there is no globally accepted treatment protocol for patients with COAD/COVID-19. Quercetin has been found to have significant antitumor, antiviral and anti-inflammatory effects in several studies. Therefore, this study sought to evaluate the potential of quercetin as the agent for COAD/COVID-19 and to explore its mechanisms. We used bioinformatics algorithms to obtain COAD/COVID-19-related genes (CCRG) from COAD-related transcriptome data and COVID-related transcriptome sequencing data, and used these genes to construct a COAD prognostic model. We intersected the CCRG with the therapeutic target genes of quercetin and obtained a total of 105 genes (potential target genes of quercetin for the treatment of COAD/COVID-19). By constructing a protein-protein interaction (PPI) network, we ascertained FOS, NFKB1, NFKB1A, JUNB, and JUN as possible core target genes of quercetin for the treatment of COAD/COVID-19. Bioinformatic analysis of these 105 genes revealed that the mechanisms for quercetin the treatment of COAD/COVID-19 may be associated with oxidative stress, apoptosis, anti-inflammatory, immune, anti-viral and multiple pathways containing IL-17, TNF, HIF-1. In this study, we constructed a prognostic model of COAD/COVID19 patients by using CCRG and elucidated for the first time the potential target genes and molecular mechanisms of quercetin for the treatment of COAD/COVID-19, which may benefit the clinical treatment of COAD/COVID-19 patients. However, no clinical trials have yet been conducted to further validate the findings, but this will be the future direction of our research.

Non-coding RNA in SARS-CoV-2: Progress toward therapeutic significance

The recently developed pathogenic virus, SARS-CoV-2, was found in the Hubei Province, China. Giving rise to a broad spectrum of symptoms, SARS-CoV-2 rapidly spread across the globe, causing multi-systemic and dangerous complications, with death in extreme cases. Thereby, the number of research cases increases every day on preventing infection and treating its resulting damage. Accumulating evidence suggests noncoding RNAs (ncRNAs) are necessary for modifying virus infection and antiviral immune reaction, along with biological processes regulating SARS-CoV-2 and subsequent disease states. Therefore, understanding these mechanisms might provide a further understanding of the pathogenesis and feasible therapy alternatives against SARS-CoV2. Consequently, the molecular biology of SARS-CoV-2, ncRNA's role in its infection, and various RNA therapy tactics against the virus have been presented in this review section.

(Epi)transcriptomics in cardiovascular and neurological complications of COVID-19

Although systemic inflammation and pulmonary complications increase the mortality rate in COVID-19, a broad spectrum of cardiovascular and neurological complications can also contribute to significant morbidity and mortality. The molecular mechanisms underlying cardiovascular and neurological complications during and after SARS-CoV-2 infection are incompletely understood. Recently reported perturbations of the epitranscriptome of COVID-19 patients indicate that mechanisms including those derived from RNA modifications and non-coding RNAs may play a contributing role in the pathogenesis of COVID-19. In this review paper, we gathered recently published studies investigating (epi)transcriptomic fluctuations upon SARS-CoV-2 infection, focusing on the brain-heart axis since neurological and cardiovascular events and their sequelae are of utmost prevalence and importance in this disease.

Significance of interferon signaling based on mRNA-microRNA integration and plasma protein analyses in critically ill COVID-19 patients

We evaluated mRNA and miRNA in COVID-19 patients and elucidated the pathogenesis of COVID-19, including protein profiles, following mRNA and miRNA integration analysis. mRNA and miRNA sequencing was done on admission with whole blood of 5 and 16 healthy controls (HCs) and 10 and 31 critically ill COVID-19 patients (derivation and validation cohorts, respectively). Interferon (IFN)-α2, IFN-β, IFN-γ, interleukin-27, and IFN-λ1 were measured in COVID-19 patients on admission (day 1, 181 critical/22 non-critical patients) and days 6–8 (168 critical patients) and in 19 HCs. In the derivation cohort, 3,488 mRNA and 31 miRNA expressions were identified among differentially expressed RNA expressions in the patients versus those in HCs, and 2,945 mRNA and 32 miRNA expressions in the validation cohort. Canonical pathway analysis showed the IFN signaling pathway to be most activated. The IFN-β plasma level was elevated in line with increased severity compared with HCs, as were IFN-β downstream proteins, such as interleukin-27. IFN-λ1 was higher in non-critically ill patients versus HCs but lower in critical than non-critical patients. Integration of mRNA and miRNA analysis showed activated IFN signaling. Plasma IFN protein profile revealed that IFN-β (type I) and IFN-λ1 (type III) played important roles in COVID-19 disease progression.

Assessing the suitability of long non-coding RNAs as therapeutic targets and biomarkers in SARS-CoV-2 infection

Long non-coding RNAs (lncRNAs) are RNA transcripts that are over 200 nucleotides and rarely encode proteins or peptides. They regulate gene expression and protein activities and are heavily involved in many cellular processes such as cytokine secretion in respond to viral infection. In severe COVID-19 cases, hyperactivation of the immune system may cause an abnormally sharp increase in pro-inflammatory cytokines, known as cytokine release syndrome (CRS), which leads to severe tissue damage or even organ failure, raising COVID-19 mortality rate. In this review, we assessed the correlation between lncRNAs expression and cytokine release syndrome by comparing lncRNA profiles between COVID-19 patients and health controls, as well as between severe and non-severe cases. We also discussed the role of lncRNAs in CRS contributors and showed that the lncRNA profiles display consistency with patients’ clinic symptoms, thus suggesting the potential of lncRNAs as drug targets or biomarkers in COVID-19 treatment.

Humoral and cellular response in convalescent COVID-19 lupus patients

In SLE, underlying immune dysregulation and immunosuppression may increase the susceptibility to COVID-19 and impair the humoral and adaptive response. We aimed to characterize COVID-19 infection, identifying susceptibility and severity risk factors, assessing the presence of SARS-CoV-2 IgG antibodies and analyzing the cellular response. We established a prospective cohort of lupus patients to estimate the COVID-19 incidence compared to the reference general population. Data were collected via telephone interviews and medical record review. SARS-CoV-2 IgG antibodies were measured cross-sectionally as part of routine surveillance. Longitudinal changes in antibody titers and immunological profile from convalescent COVID-19 patients were evaluated at 6, 12 and 24 week after symptom onset. From immunological studies, PBMCs from convalescent patients were extracted and analyzed by flow cytometry and gene expression analysis. We included 725 patients, identifying 29 with PCR-confirmed COVID-19 infection and 16 with COVID-19-like symptoms without PCR-testing. Of the 29 confirmed cases, 7 had severe disease, 8 required hospital admission (27.6%), 4 intensive care, and 1 died. COVID-19 accumulated incidence was higher in lupus patients. Health care workers and anti-SSA/Ro52 antibody positivity were risk factors for COVID-19 susceptibility, and hypocomplementemia for severity. SARS-CoV-2 IgG antibodies were detected in 8.33% of patients. Three fourths of confirmed COVID-19 cases developed antibodies. High prednisone doses were associated with lack of antibody response. Antibody titers declined over time (39%). Convalescent patients at week 12 after symptom onset displayed a CD8⁺T cell reduction and predominant Th17 with a mild Th2 response, more pronounced in severe COVID-19 disease. Longitudinal immune response analysis showed a progressive sustained increase in CD8⁺ T and B memory cells with a decrease of Th17 signaling. Lupus patients are at higher risk of COVID-19 infection and new susceptibility and severity risk factors were identified. Lupus patients were able to mount humoral and cellular responses despite immunosuppressive therapy.

High Circulating Levels of the Homeostatic Chemokines CCL19 and CCL21 Predict Mortality and Disease Severity in COVID-19

BACKGROUND

Immune dysregulation is a major factor in the development of severe coronavirus disease 2019 (COVID-19). The homeostatic chemokines CCL19 and CCL21 have been implicated as mediators of tissue inflammation, but data on their regulation in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is limited. We thus investigated the levels of these chemokines in COVID-19 patients.

METHODS

Serial blood samples were obtained from patients hospitalized with COVID-19 (n = 414). Circulating CCL19 and CCL21 levels during hospitalization and 3-month follow-up were analyzed. In vitro assays and analysis of RNAseq data from public repositories were performed to further explore possible regulatory mechanisms.

RESULTS

A consistent increase in circulating levels of CCL19 and CCL21 was observed, with high levels correlating with disease severity measures, including respiratory failure, need for intensive care, and 60-day all-cause mortality. High levels of CCL21 at admission were associated with persisting impairment of pulmonary function at the 3-month follow-up.

CONCLUSIONS

Our findings highlight CCL19 and CCL21 as markers of immune dysregulation in COVID-19. This may reflect aberrant regulation triggered by tissue inflammation, as observed in other chronic inflammatory and autoimmune conditions. Determination of the source and regulation of these chemokines and their effects on lung tissue is warranted to further clarify their role in COVID-19.

CLINICAL TRIALS REGISTRATION

NCT04321616 and NCT04381819.

Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19

The biological determinants underlying the range of coronavirus 2019 (COVID-19) clinical manifestations are not fully understood. Here, over 1,400 plasma proteins and 2,600 single-cell immune features comprising cell phenotype, endogenous signaling activity, and signaling responses to inflammatory ligands are cross-sectionally assessed in peripheral blood from 97 patients with mild, moderate, and severe COVID-19 and 40 uninfected patients. Using an integrated computational approach to analyze the combined plasma and single-cell proteomic data, we identify and independently validate a multi-variate model classifying COVID-19 severity (multi-class area under the curve [AUC]training = 0.799, p = 4.2e-6; multi-class AUCvalidation = 0.773, p = 7.7e-6). Examination of informative model features reveals biological signatures of COVID-19 severity, including the dysregulation of JAK/STAT, MAPK/mTOR, and nuclear factor κB (NF-κB) immune signaling networks in addition to recapitulating known hallmarks of COVID-19. These results provide a set of early determinants of COVID-19 severity that may point to therapeutic targets for prevention and/or treatment of COVID-19 progression.

A multi-tissue study of immune gene expression profiling highlights the key role of the nasal epithelium in COVID-19 severity

Coronavirus Disease-19 (COVID-19) symptoms range from mild to severe illness; the cause for this differential response to infection remains unknown. Unravelling the immune mechanisms acting at different levels of the colonization process might be key to understand these differences. We carried out a multi-tissue (nasal, buccal and blood; n = 156) gene expression analysis of immune-related genes from patients affected by different COVID-19 severities, and healthy controls through the nCounter technology. Mild and asymptomatic cases showed a powerful innate antiviral response in nasal epithelium, characterized by activation of interferon (IFN) pathway and downstream cascades, successfully controlling the infection at local level. In contrast, weak macrophage/monocyte driven innate antiviral response and lack of IFN signalling activity were present in severe cases. Consequently, oral mucosa from severe patients showed signals of viral activity, cell arresting and viral dissemination to the lower respiratory tract, which ultimately could explain the exacerbated innate immune response and impaired adaptative immune responses observed at systemic level. Results from saliva transcriptome suggest that the buccal cavity might play a key role in SARS-CoV-2 infection and dissemination in patients with worse prognosis. Co-expression network analysis adds further support to these findings, by detecting modules specifically correlated with severity involved in the abovementioned biological routes; this analysis also provides new candidate genes that might be tested as biomarkers in future studies. We also found tissue specific severity-related signatures mainly represented by genes involved in the innate immune system and cytokine/chemokine signalling. Local immune response could be key to determine the course of the systemic response and thus COVID-19 severity. Our findings provide a framework to investigate severity host gene biomarkers and pathways that might be relevant to diagnosis, prognosis, and therapy.

Mature neutrophils and a NF-κB-to-IFN transition determine the unifying disease recovery dynamics in COVID-19

Disease recovery dynamics are often difficult to assess, as patients display heterogeneous recovery courses. To model recovery dynamics, exemplified by severe COVID-19, we apply a computational scheme on longitudinally sampled blood transcriptomes, generating recovery states, which we then link to cellular and molecular mechanisms, presenting a framework for studying the kinetics of recovery compared with non-recovery over time and long-term effects of the disease. Specifically, a decrease in mature neutrophils is the strongest cellular effect during recovery, with direct implications on disease outcome. Furthermore, we present strong indications for global regulatory changes in gene programs, decoupled from cell compositional changes, including an early rise in T cell activation and differentiation, resulting in immune rebalancing between interferon and NF-κB activity and restoration of cell homeostasis. Overall, we present a clinically relevant computational framework for modeling disease recovery, paving the way for future studies of the recovery dynamics in other diseases and tissues.

An Update on Protective Effectiveness of Immune Responses After Recovery From COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exhibits variable immunity responses among hosts based on symptom severity. Whether immunity in recovered individuals is effective for avoiding reinfection is poorly understood. Determination of immune memory status against SARS-CoV-2 helps identify reinfection risk and vaccine efficacy. Hence, after recovery from COVID-19, evaluation of protective effectiveness and durable immunity of prior disease could be significant. Recent reports described the dynamics of SARS-CoV-2 -specific humoral and cellular responses for more than six months in convalescent SARS-CoV-2 individuals. Given the current evidence, NK cell subpopulations, especially the memory-like NK cell subset, indicate a significant role in determining COVID-19 severity. Still, the information on the long-term NK cell immunity conferred by SARS-CoV-2 infection is scant. The evidence from vaccine clinical trials and observational studies indicates that hybrid natural/vaccine immunity to SARS-CoV-2 seems to be notably potent protection. We suggested the combination of plasma therapy from recovered donors and vaccination could be effective. This focused review aims to update the current information regarding immune correlates of COVID-19 recovery to understand better the probability of reinfection in COVID-19 infected cases that may serve as guides for ongoing vaccine strategy improvement.

scINSIGHT for interpreting single-cell gene expression from biologically heterogeneous data

The increasing number of scRNA-seq data emphasizes the need for integrative analysis to interpret similarities and differences between single-cell samples. Although different batch effect removal methods have been developed, none are suitable for heterogeneous single-cell samples coming from multiple biological conditions. We propose a method, scINSIGHT, to learn coordinated gene expression patterns that are common among, or specific to, different biological conditions, and identify cellular identities and processes across single-cell samples. We compare scINSIGHT with state-of-the-art methods using simulated and real data, which demonstrate its improved performance. Our results show the applicability of scINSIGHT in diverse biomedical and clinical problems.

Dysfunctional State of T Cells or Exhaustion During Chronic Viral Infections and COVID-19: A Review

Coronavirus disease 2019 (COVID-19) continuously affecting the lives of millions of people. The virus is spread through the respiratory route to an uninfected person, causing mild-to-moderate respiratory disease-like symptoms that sometimes progress to severe form and can be fatal. When the host is infected with the virus, both innate and adaptive immunity comes into play. The effector T cells act as the master player of adaptive immune response in eradicating the virus from the system. But during cancer and chronic viral infections, the fate of an effector T cell is altered, and the T cell may enters a state of exhaustion, which is marked by loss of effector function, depleted proliferative capacity and cytotoxic effect accomplished by an increased expression of numerous inhibitory receptors such as programmed cell death protein 1 (PD-1), lymphocyte-activation protein 3 (LAG-3), and cytotoxic T lymphocyte-associated antigen 4 (CTLA-4) on their surface. Various other transcriptional and epigenetic changes take place inside the T cell when it enters into an exhausted state. Latest studies point toward the induction of an abnormal immune response such as lymphopenia, cytokine storm, and T cell exhaustion during SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) infection. This review sheds light on the dysfunctional state of T cells during chronic viral infection and COVID-19. Understanding the cause and the effect of T cell exhaustion observed during COVID-19 may help resolve new therapeutic potentials for treating chronic infections and other diseases.

Differentially expressed plasmatic microRNAs in Brazilian patients with Coronavirus disease 2019 (COVID-19): preliminary results

Background

Coronavirus disease 2019 (COVID-19) is caused by a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It is known that host microRNAs (miRNAs) can be modulated to favor viral infection or to protect the host. Herein, we report preliminary results of a study aiming at identifying differentially expressed plasmatic miRNAs in Brazilian patients with COVID-19.

Methods and results

miRNAs were extracted from the plasma of eight patients with COVID-19 (four patients with mild COVID-19 and four patients with severe/critical COVID-19) and four healthy controls. Patients and controls were matched for sex and age. miRNA expression levels were detected using high-throughput sequencing. Differential miRNA expression and enrichment analyses were further evaluated. A total of 18 miRNAs were differentially expressed between patients with COVID-19 and controls. miR-4433b-5p, miR-6780b-3p, miR-6883-3p, miR-320b, miR-7111-3p, miR-4755-3p, miR-320c, and miR-6511a-3p were the most important miRNAs significantly involved in the PI3K/AKT, Wnt/β-catenin, and STAT3 signaling pathways. Moreover, 42 miRNAs were differentially expressed between severe/critical and mild patients with COVID-19. miR-451a, miR-101-3p, miR-185-5p, miR-30d-5p, miR-25-3p, miR-342-3p, miR-30e-5p, miR-150-5p, miR-15b-5p, and miR-29c-3p were the most important miRNAs significantly involved in the Wnt/β-catenin, NF-κβ, and STAT3 signaling pathways.

Conclusions

If validated by quantitative real-time reverse transcriptase-polymerase chain reaction (RT-PCR) in a larger number of participants, the miRNAs identified in this study might be used as possible biomarkers for the diagnosis and severity of COVID-19.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11033-022-07338-9.

SARS-CoV-2 causes a significant stress response mediated by small RNAs in the blood of COVID-19 patients

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had a serious impact on the world. In this study, small RNAs from the blood of COVID-19 patients with moderate or severe symptoms were extracted for high-throughput sequencing and analysis. Interestingly, the levels of a special group of tRNA-derived small RNAs (tsRNAs) were found to be dramatically upregulated after SARS-CoV-2 infection, particularly in coronavirus disease 2019 (COVID-19) patients with severe symptoms. In particular, the 3′CCA tsRNAs from tRNA-Gly were highly consistent with the inflammation indicator C-reactive protein (CRP). In addition, we found that the majority of significantly changed microRNAs (miRNAs) were associated with endoplasmic reticulum (ER)/unfolded protein response (UPR) sensors, which may lead to the induction of proinflammatory cytokine and immune responses. This study found that SARS-CoV-2 infection caused significant changes in the levels of stress-associated small RNAs in patient blood and their potential functions. Our research revealed that the cells of COVID-19 patients undergo tremendous stress and respond, which can be reflected or regulated by small non-coding RNA (sncRNAs), thus providing potential thought for therapeutic intervention in COVID-19 by modulating small RNA levels or activities.

COVID-19 and Mitochondrial Non-Coding RNAs: New Insights From Published Data

Scientists all around the world are working to investigate new ways to prevent and treat COVID-19, and recent research has been focusing on the effects of a syndrome commonly called “long COVID.” People affected by this syndrome usually suffer from symptoms like the ones observed in several types of fatigue syndrome. As these syndromes are often linked to mitochondrial dysfunction, researchers hypothesized that a dysfunction in the mitochondrial metabolism might be part of the causes of long COVID. However, while there are a few studies investigating the effect of SARS-CoV-2 infection on mitochondrial metabolism, the effect on the transcription of mitochondrial non-coding RNAs has not been investigated yet. Thus, using publicly available data, I explored the effect of SARS-CoV-2 on the expression of several mitochondrial non-coding RNAs in patients recovering from COVID-19. No change in the expression of long non-coding RNAs was detected at any stage of the infection, but up to 43 small mitochondrial RNAs have their expression altered during the recovery from COVID-19. This result suggests that the SARS-CoV-2 infection somehow affected the metabolism of small mitochondrial RNAs specifically without altering the overall mitochondrial transcription. Despite these being only preliminary results on a small cohort, the analyses clearly showed that individuals infected by SARS-CoV-2 retain an altered expression of these small RNAs. This persistent alteration in the expression of small mitochondrial RNAs might be involved in the long COVID syndrome and further studies are needed to confirm the possibility.

Blood transcriptomes of SARS-CoV-2 infected kidney transplant recipients demonstrate immune insufficiency

BACKGROUND

Kidney transplant recipients (KTRs) with COVID-19 have poor outcomes compared to non-KTRs. To provide insight into management of immunosuppression during acute illness, we studied immune signatures from the peripheral blood during and after COVID-19 infection from a multicenter KTR cohort.□.

METHODS

Clinical data were collected by chart review. PAXgene blood RNA was poly-A selected and RNA sequencing was performed to evaluate transcriptome changes.

RESULTS

A total of 64 cases of COVID-19 in KTRs were enrolled, including 31 acute cases (< 4 weeks from diagnosis) and 33 post-acute cases (>4 weeks). In the blood transcriptome of acute cases, we identified differentially expressed genes (DEGs) in positive or negative association COVID-19 severity scores. Functional enrichment analyses showed upregulation of neutrophil and innate immune pathways, but downregulation of T-cell and adaptive immune-activation pathways proportional to severity score. This finding was independent of lymphocyte count and despite reduction in immunosuppression (IS) in most KTRs. Comparison with post-acute cases showed "normalization" of these enriched pathways after >4 weeks, suggesting recovery of adaptive immune system activation despite reinstitution of IS. The latter analysis was adjusted for COVID-19 severity score and lymphocyte count. DEGs associated with worsening disease severity in a non-KTR cohort with COVID-19 (GSE152418) showed significant overlap with KTRs in these identified enriched pathways.

CONCLUSION

Blood transcriptome of KTRs affected by COVID-19 shows decrease in T-cell and adaptive immune activation pathways during acute disease that associate with severity despite IS reduction and show recovery after acute illness.

SIGNIFICANCE STATEMENT

Kidney transplant recipients (KTRs) are reported to have worse outcomes with COVID-19, and empiric reduction of maintenance immunosuppression is pursued. Surprisingly, reported rates of acute rejection have been low despite reduced immunosuppression. We evaluated the peripheral blood transcriptome of 64 KTRs either during or after acute COVID-19. We identified transcriptomic signatures consistent with suppression of adaptive T-cell responses which significantly associated with disease severity and showed evidence of recovery after acute disease, even after adjustment for lymphocyte number. Our transcriptomic findings of immune-insufficiency during acute COVID-19 provide an explanation for the low rates of acute rejection in KTRs despite reduced immunosuppression. Our data support the approach of temporarily reducing T -cell-directed immunosuppression in KTRs with acute COVID-19.

Biphasic effect of mechanical stress on lymphocyte activation

Mechanical forces can modulate the immune response, mostly described as promoting the activation of immune cells, but the role and mechanism of pathological levels of mechanical stress in lymphocyte activation have not been focused on before. By an ex vivo experimental approach, we observed that mechanical stressing of murine spleen lymphocytes with 50 mmHg for 3 h induced the nuclear localization of NFAT1, increased C-Jun, and increased the expression of early activation marker CD69 in resting CD8+ cells. Interestingly, 50 mmHg mechanical stressing induced the nuclear localization of NFAT1; but conversely decreased C-Jun and inhibited the expression of CD69 in lymphocytes under lipopolysaccharide or phorbol 12-myristate 13-acetate/ionomycin stimulation. Additionally, we observed similar changes trends when comparing RNA-seq data of hypertensive and normotensive COVID-19 patients. Our results indicate a biphasic effect of mechanical stress on lymphocyte activation, which provides insight into the variety of immune responses in pathologies involving elevated mechanical stress.

Sequence complementarity between human noncoding RNAs and SARS-CoV-2 genes: What are the implications for human health?

Objectives

To investigate in silico the presence of nucleotide sequence complementarity between the RNA genome of Severe Acute Respiratory Syndrome CoronaVirus-2 (SARS-CoV-2) and human non-coding (nc)RNA genes.

Methods

The FASTA sequence (NC_045512.2) of each of the 11 SARS-CoV-2 isolate Wuhan-Hu-1 genes was retrieved from NCBI.nlm.nih.gov/gene and the Ensembl.org library interrogated for any base-pair match with human ncRNA genes. SARS-CoV-2 gene-matched human ncRNAs were screened for functional activity using bioinformatic analysis. Finally, associations between identified ncRNAs and human diseases were searched in GWAS databases.

Results

A total of 252 matches were found between the nucleotide sequence of SARS-CoV-2 genes and human ncRNAs. With the exception of two small nuclear RNAs, all of them were long non-coding (lnc)RNAs expressed mainly in testis and central nervous system under physiological conditions. The percentage of alignment ranged from 91.30% to 100% with a mean nucleotide alignment length of 17.5 ± 2.4. Thirty-three (13.09%) of them contained predicted R-loop forming sequences, but none of these intersected the complementary sequences of SARS-CoV-2. However, in 31 cases matches fell on ncRNA regulatory sites, whose adjacent coding genes are mostly involved in cancer, immunological and neurological pathways. Similarly, several polymorphic variants of detected non-coding genes have been associated with neuropsychiatric and proliferative disorders.

Conclusion

This pivotal in silico study shows that SARS-CoV-2 genes have Watson-Crick nucleotide complementarity to human ncRNA sequences, potentially disrupting ncRNA epigenetic control of target genes. It remains to be elucidated whether this could result in the development of human disease in the long term.

Identification of potential therapeutic targets and mechanisms of COVID-19 through network analysis and screening of chemicals and herbal ingredients

After experiencing the COVID-19 pandemic, it is widely acknowledged that a rapid drug repurposing method is highly needed. A series of useful drug repurposing tools have been developed based on data-driven modeling and network pharmacology. Based on the disease module, we identified several hub proteins that play important roles in the onset and development of the COVID-19, which are potential targets for repositioning approved drugs. Moreover, different network distance metrics were applied to quantify the relationship between drug targets and COVID-19 disease targets in the protein-protein-interaction (PPI) network and predict COVID-19 therapeutic effects of bioactive herbal ingredients and chemicals. Furthermore, the tentative mechanisms of candidates were illustrated through molecular docking and gene enrichment analysis. We obtained 15 chemical and 15 herbal ingredient candidates and found that different drugs may play different roles in the process of virus invasion and the onset and development of the COVID-19 disease. Given pandemic outbreaks, our method has an undeniable immense advantage in the feasibility analysis of drug repurposing or drug screening, especially in the analysis of herbal ingredients.

Long-term perturbation of the peripheral immune system months after SARS-CoV-2 infection

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly infectious respiratory virus which is responsible for the coronavirus disease 2019 (COVID-19) pandemic. It is increasingly clear that recovered individuals, even those who had mild COVID-19, can suffer from persistent symptoms for many months after infection, a condition referred to as "long COVID", post-acute sequelae of COVID-19 (PASC), post-acute COVID-19 syndrome, or post COVID-19 condition. However, despite the plethora of research on COVID-19, relatively little is known about the molecular underpinnings of these long-term effects.

METHODS

We have undertaken an integrated analysis of immune responses in blood at a transcriptional, cellular, and serological level at 12, 16, and 24 weeks post-infection (wpi) in 69 patients recovering from mild, moderate, severe, or critical COVID-19 in comparison to healthy uninfected controls. Twenty-one of these patients were referred to a long COVID clinic and > 50% reported ongoing symptoms more than 6 months post-infection.

RESULTS

Anti-Spike and anti-RBD IgG responses were largely stable up to 24 wpi and correlated with disease severity. Deep immunophenotyping revealed significant differences in multiple innate (NK cells, LD neutrophils, CXCR3+ monocytes) and adaptive immune populations (T helper, T follicular helper, and regulatory T cells) in convalescent individuals compared to healthy controls, which were most strongly evident at 12 and 16 wpi. RNA sequencing revealed significant perturbations to gene expression in COVID-19 convalescents until at least 6 months post-infection. We also uncovered significant differences in the transcriptome at 24 wpi of convalescents who were referred to a long COVID clinic compared to those who were not.

CONCLUSIONS

Variation in the rate of recovery from infection at a cellular and transcriptional level may explain the persistence of symptoms associated with long COVID in some individuals.

Specific inhibition of the NLRP3 inflammasome suppresses immune overactivation and alleviates COVID-19 like pathology in mice

Background

The Coronavirus Disease 2019 (COVID-19) pandemic has been a great threat to global public health since 2020. Although the advance on vaccine development has been largely achieved, a strategy to alleviate immune overactivation in severe COVID-19 patients is still needed. The NLRP3 inflammasome is activated upon SARS-CoV-2 infection and associated with COVID-19 severity. However, the processes by which the NLRP3 inflammasome is involved in COVID-19 disease remain unclear.

Methods

We infected THP-1 derived macrophages, NLRP3 knockout mice, and human ACE2 transgenic mice with live SARS-CoV-2 in Biosafety Level 3 (BSL-3) laboratory. We performed quantitative real-time PCR for targeted viral or host genes from SARS-CoV-2 infected mouse tissues, conducted histological or immunofluorescence analysis in SARS-CoV-2 infected mouse tissues. We also injected intranasally AAV-hACE2 or intraperitoneally NLRP3 inflammasome inhibitor MCC950 before SARS-CoV-2 infection in mice as indicated.

Findings

We have provided multiple lines of evidence that the NLRP3 inflammasome plays an important role in the host immune response to SARS-CoV-2 invasion of the lungs. Inhibition of the NLRP3 inflammasome attenuated the release of COVID-19 related pro-inflammatory cytokines in cell cultures and mice. The severe pathology induced by SARS-CoV-2 in lung tissues was reduced in Nlrp3^−/− mice compared to wild-type C57BL/6 mice. Finally, specific inhibition of the NLRP3 inflammasome by MCC950 alleviated excessive lung inflammation and thus COVID-19 like pathology in human ACE2 transgenic mice.

Interpretation

Inflammatory activation induced by SARS-CoV-2 is an important stimulator of COVID-19 related immunopathology. Targeting the NLRP3 inflammasome is a promising immune intervention against severe COVID-19 disease.

Funding

This work was supported by grants from the Bureau of Frontier Sciences and Education, CAS (grant no. QYZDJ-SSW-SMC005 to Y.G.Y.), the key project of the CAS “Light of West China” Program (to D.Y.) and Yunnan Province (202001AS070023 to D.Y.).

miRNAs, from Evolutionary Junk to Possible Prognostic Markers and Therapeutic Targets in COVID-19

The COVID-19 pandemic has been a public health issue around the world in the last few years. Currently, there is no specific antiviral treatment to fight the disease. Thus, it is essential to highlight possible prognostic predictors that could identify patients with a high risk of developing complications. Within this framework, miRNA biomolecules play a vital role in the genetic regulation of various genes, principally, those related to the pathophysiology of the disease. Here, we review the interaction of host and viral microRNAs with molecular and cellular elements that could potentiate the main pulmonary, cardiac, renal, circulatory, and neuronal complications in COVID-19 patients. miR-26a, miR-29b, miR-21, miR-372, and miR-2392, among others, have been associated with exacerbation of the inflammatory process, increasing the risk of a cytokine storm. In addition, increased expression of miR-15b, -199a, and -491 are related to the prognosis of the disease, and miR-192 and miR-323a were identified as clinical predictors of mortality in patients admitted to the intensive care unit. Finally, we address miR-29, miR-122, miR-155, and miR-200, among others, as possible therapeutic targets. However, more studies are required to confirm these findings.

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.

Expression of plasma IFN signaling-related miRNAs during acute SARS-CoV-2 infection and its association with RBD-IgG antibody response

Background

Coronavirus disease 2019 (COVID-19) is a huge challenge worldwide. Although previous studies have suggested that type I interferon (IFN-I) could inhibit the virus replication, the expression characteristics of IFN-I signaling-related miRNAs (ISR-miRNAs) during acute severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection and its relationship with receptor-binding domain (RBD) IgG antibody response at the recovery phase remain unclear.

Methods

Expression profiles of 12 plasma ISR-miRNAs in COVID-19 patients and healthy controls were analyzed using RT-qPCR. The level of RBD-IgG antibody was determined using the competitive ELISA. Spearman correlation was done to measure the associations of plasma ISR-miRNAs with clinical characteristics during acute SARS-CoV-2 infection and RBD-IgG antibody response at the recovery phase.

Results

Compared with the healthy controls, COVID-19 patients exhibited higher levels of miR-29b-3p (Z = 3.15, P = 0.002) and miR-1246 (Z = 4.98, P < 0.001). However, the expression of miR-186-5p and miR-15a-5p were significantly decreased. As the results shown, miR-30b-5p was negatively correlated with CD4 + T cell counts (r = − 0.41, P = 0.027) and marginally positively correlated with fasting plasma glucose in COVID-19 patients (r = 0.37, P = 0.052). The competitive ELISA analysis showed the plasma level of miR-497-5p at the acute phase was positively correlated with RBD-IgG antibody response (r = 0.48, P = 0.038).

Conclusions

Our present results suggested that the expression level of ISR-miRNAs was not only associated with acute SARS-CoV-2 infection but also with RBD-IgG antibody response at the recovery phase of COVID-19. Future studies should be performed to explore the biological significance of ISR-miRNAs in SARS-CoV-2 infection.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12985-021-01717-7.

Role of miRNAs as biomarkers of COVID-19: a scoping review of the status and future directions for research in this field

Aim: miRNAs are potential biomarkers of several diseases. This review aimed to identify the miRNAs that could serve as biomarkers of COVID-19. Materials & methods: A literature search of nine databases was carried out for studies published before 13 June 2021 that described dysregulated miRNAs in cells or animals infected by SARS-CoV-2 or in patients with COVID-19. Two independent reviewers selected the studies and extracted data; disagreements were resolved by a third reviewer. Results: Twenty studies were included in this scoping review; results suggested that miR-21-5p, miR-146a, miR-126-3p, miR-144 and miR-155 are the most important dysregulated miRNAs that could serve as biomarkers for diagnosing and indicating the severity of COVID-19. miRNAs appear to play key roles in viral replication, proliferation of infected cells, immune response, inflammation and cardiovascular dysfunction. Conclusion: This review provides insights into the role of miRNAs as biomarkers in COVID-19 and the current status and future directions for research in this field.

The Triangle Relationship Between Long Noncoding RNA, RIG-I-like Receptor Signaling Pathway, and Glycolysis

Long noncoding RNA (LncRNA), a noncoding RNA over 200nt in length, can regulate glycolysis through metabolic pathways, glucose metabolizing enzymes, and epigenetic reprogramming. Upon viral infection, increased aerobic glycolysis providzes material and energy for viral replication. Mitochondrial antiviral signaling protein (MAVS) is the only protein-specified downstream of retinoic acid-inducible gene I (RIG-I) that bridges the gap between antiviral immunity and glycolysis. MAVS binding to RIG-I inhibits MAVS binding to Hexokinase (HK2), thereby impairing glycolysis, while excess lactate production inhibits MAVS and the downstream antiviral immune response, facilitating viral replication. LncRNAs can also regulate antiviral innate immunity by interacting with RIG-I and downstream signaling pathways and by regulating the expression of interferons and interferon-stimulated genes (ISGs). Altogether, we summarize the relationship between glycolysis, antiviral immunity, and lncRNAs and propose that lncRNAs interact with glycolysis and antiviral pathways, providing a new perspective for the future treatment against virus infection, including SARS-CoV-2.

Genome-scale metabolic modeling reveals SARS-CoV-2-induced metabolic changes and antiviral targets

Tremendous progress has been made to control the COVID-19 pandemic caused by the SARS-CoV-2 virus. However, effective therapeutic options are still rare. Drug repurposing and combination represent practical strategies to address this urgent unmet medical need. Viruses, including coronaviruses, are known to hijack host metabolism to facilitate viral proliferation, making targeting host metabolism a promising antiviral approach. Here, we describe an integrated analysis of 12 published in vitro and human patient gene expression datasets on SARS-CoV-2 infection using genome-scale metabolic modeling (GEM), revealing complicated host metabolism reprogramming during SARS-CoV-2 infection. We next applied the GEM-based metabolic transformation algorithm to predict anti-SARS-CoV-2 targets that counteract the virus-induced metabolic changes. We successfully validated these targets using published drug and genetic screen data and by performing an siRNA assay in Caco-2 cells. Further generating and analyzing RNA-sequencing data of remdesivir-treated Vero E6 cell samples, we predicted metabolic targets acting in combination with remdesivir, an approved anti-SARS-CoV-2 drug. Our study provides clinical data-supported candidate anti-SARS-CoV-2 targets for future evaluation, demonstrating host metabolism targeting as a promising antiviral strategy.

Novel Systemic Inflammation Markers to Predict COVID-19 Prognosis

Coronavirus disease 2019 (COVID-19) has resulted in a global pandemic, challenging both the medical and scientific community for the development of novel vaccines and a greater understanding of the effects of the SARS-CoV-2 virus. COVID-19 has been associated with a pronounced and out-of-control inflammatory response. Studies have sought to understand the effects of inflammatory response markers to prognosticate the disease. Herein, we aimed to review the evidence of 11 groups of systemic inflammatory markers for risk-stratifying patients and prognosticating outcomes related to COVID-19. Numerous studies have demonstrated the effectiveness of neutrophil to lymphocyte ratio (NLR) in prognosticating patient outcomes, including but not limited to severe disease, hospitalization, intensive care unit (ICU) admission, intubation, and death. A few markers outperformed NLR in predicting outcomes, including 1) systemic immune-inflammation index (SII), 2) prognostic nutritional index (PNI), 3) C-reactive protein (CRP) to albumin ratio (CAR) and high-sensitivity CAR (hsCAR), and 4) CRP to prealbumin ratio (CPAR) and high-sensitivity CPAR (hsCPAR). However, there are a limited number of studies comparing NLR with these markers, and such conclusions require larger validation studies. Overall, the evidence suggests that most of the studied markers are able to predict COVID-19 prognosis, however NLR seems to be the most robust marker.

Multiomics: unraveling the panoramic landscapes of SARS-CoV-2 infection

In response to emerging infectious diseases, such as the recent pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), it is critical to quickly identify and understand responsible pathogens, risk factors, host immune responses, and pathogenic mechanisms at both the molecular and cellular levels. The recent development of multiomic technologies, including genomics, proteomics, metabolomics, and single-cell transcriptomics, has enabled a fast and panoramic grasp of the pathogen and the disease. Here, we systematically reviewed the major advances in the virology, immunology, and pathogenic mechanisms of SARS-CoV-2 infection that have been achieved via multiomic technologies. Based on well-established cohorts, omics-based methods can greatly enhance the mechanistic understanding of diseases, contributing to the development of new diagnostics, drugs, and vaccines for emerging infectious diseases, such as COVID-19.