In vivo antiviral host transcriptional response to SARS-CoV-2 by viral load, sex, and age

Exploring COVID-19 Pandemic Disparities with Transcriptomic Meta-analysis from the Perspective of Personalized Medicine

Infection with SARS-CoV2, which is responsible for COVID-19, can lead to differences in disease development, severity and mortality rates depending on gender, age or the presence of certain diseases. Considering that existing studies ignore these differences, this study aims to uncover potential differences attributable to gender, age and source of sampling as well as viral load using bioinformatics and multi-omics approaches. Differential gene expression analyses were used to analyse the phenotypic differences between SARS-CoV-2 patients and controls at the mRNA level. Pathway enrichment analyses were performed at the gene set level to identify the activated pathways corresponding to the differences in the samples. Drug repurposing analysis was performed at the protein level, focusing on host-mediated drug candidates to uncover potential therapeutic differences. Significant differences (i.e. the number of differentially expressed genes and their characteristics) were observed for COVID-19 at the mRNA level depending on the sample source, gender and age of the samples. The results of the pathway enrichment show that SARS-CoV-2 can be combated more effectively in the respiratory tract than in the blood samples. Taking into account the different sample sources and their characteristics, different drug candidates were identified. Evaluating disease prediction, prevention and/or treatment strategies from a personalised perspective is crucial. In this study, we not only evaluated the differences in COVID-19 from a personalised perspective, but also provided valuable data for further experimental and clinical efforts. Our findings could shed light on potential pandemics.

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

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

COVID-19 knowledge and practices in Jigawa State, Nigeria: A cross-sectional survey conducted during the second wave

Population knowledge of COVID-19 and adherence to prevention measures may not be equitably distributed, limiting the success of public health measures. We aimed to understand whether COVID-19 knowledge differed by socio-economic status in a rural low-income setting of Jigawa State, Nigeria. We conducted a secondary analysis of the baseline cross-sectional survey of the INSPIRING cluster randomised controlled trial in Kiyawa Local Government Area, Jigawa State, from January-June 2021. Compounds were selected using simple random sampling proportional to trial cluster size. Within each compound, a representative head of compound and all women aged 16-49 years were eligible to complete a survey, which asked about socioeconomics, knowledge of COVID-19 symptoms, prevention strategies and risks for poor outcomes. We converted these into binary outcomes of "good knowledge" for symptoms, prevention and risks. Associations between woman and head of compound characteristics and good knowledge were assessed using adjusted logistic regression. We surveyed 3800 compound heads and 9564 women. Overall, <1% of respondents had been tested for COVID-19, but access to facemasks (HoC 60.0%; women 86.3%) and willingness to be vaccinated (HoC 73.9%; women 73.4%) were high. COVID-19 knowledge was low, with 33.2% of heads of compounds and 26.0% of women having good symptom knowledge, 39.5% and 30.4% having good prevention knowledge, and 17.7% and 15.4% having good risk knowledge, respectively. Those with more education, from higher wealth quintiles and access to a radio had better knowledge. Access to a mobile phone was associated with good symptom knowledge, but worse prevention and risk knowledge. We found significant differences in COVID-19 knowledge associated with socio-economic factors in rural Jigawa state, and access to communication devices was not consistently associated with better knowledge. Public health messaging in Nigeria needs to be adapted and delivered in way that ensures accessibility to all.

Vitamin D regulates COVID-19 associated severity by suppressing the NLRP3 inflammasome pathway

BACKGROUND

The role of vitamin D3 (VitD3) in modulating innate and adaptive immunity has been reported in different disease contexts. Since the start of the coronavirus disease-2019 (COVID-19) pandemic, the role of VitD3 has been highlighted in many correlational and observational studies. However, the exact mechanisms of action are not well identified. One of the mechanisms via which VitD3 modulates innate immunity is by regulating the NLRP3-inflammasome pathway, being a main underlying cause of SARS-CoV-2-induced hyperinflammation.

AIMS AND MAIN METHODS

Blood specimens of severe COVID-19 patients with or without VitD3 treatment were collected during their stay in the intensive care unit and patients were followed up for 29 days. qPCR, western blot, and ELISA were done to investigate the mechanism of action of VitD3 on the NLRP3 inflammasome activation.

KEY FINDINGS

We here report the ability of VitD3 to downregulate the NLRP3-inflammsome pathway in severe COVID-19 patients. Lower inflammasome pathway activation was observed with significantly lower gene and protein expression of NLRP3, cleaved caspase-1, ASC and IL-1β among severe COVID-19 patients treated with VitD3. The reduction of the inflammasome pathway was associated with a reduction in disease severity markers and enhancement of type I IFN pathway.

SIGNIFICANCE

Our data reveals an important anti-inflammatory effect of VitD3 during SARS-CoV-2 infection. Further investigations are warranted to better characterize the ability of VitD3 to control disease pathogenesis and prevent progression to severe states. This will allow for a more efficient use of a low cost and accessible treatment like VitD3.

Drugs targeting CMPK2 inhibit pyroptosis to alleviate severe pneumonia caused by multiple respiratory viruses

Severe pneumonia caused by respiratory viruses has become a major threat to humans, especially with the SARS-CoV-2 outbreak and epidemic. The aim of this study was to investigate the universal molecular mechanism of severe pneumonia induced by multiple respiratory viruses and to search for therapeutic strategies targeting this universal molecular mechanism. The common differential genes of four respiratory viruses, including respiratory syncytial virus (RSV), rhinovirus, influenza, and SARS-CoV-2, were screened by GEO database, and the hub gene was obtained by Sytohubba in Cytoscape. Then, the effect of hub genes on inflammasome and pyrodeath was investigated in the model of RSV infection in vitro and in vivo. Finally, through virtual screening, drugs targeting the hub gene were obtained, which could alleviate severe viral pneumonia in vitro and in vivo. The results showed that CMPK2 is one of the hub genes after infection by four respiratory viruses. CMPK2 activates the inflammasome by activating NLRP3, and promotes the releases of inflammatory factors interleukin (IL)-1β and IL-18 to induce severe viral pneumonia. Z25 and Z08 can reduce the expression level of CMPK2 mRNA and protein, thereby inhibiting NLRP3 and alleviating the development of severe viral pneumonia. In conclusion, the inflammatory response mediated by CMPK2 is the common molecular mechanism of severe pneumonia induced by viral infection, and Z25 and Z08 can effectively alleviate viral infection and severe pneumonia through this mechanism.

Identification of key gene expression associated with quality of life after recovery from COVID-19

Post-acute sequelae of COVID-19 (PASC) is a persistent complication of severe acute respiratory syndrome coronavirus 2 infection that includes symptoms, such as fatigue, cognitive impairment, and respiratory distress. These symptoms severely affect the quality of life of patients after their recovery from COVID-19. In this study, a group of machine learning algorithms analyzed the whole blood RNA-seq data from patients with different PASC levels. The purpose of this analysis was to identify the gene markers associated with PASC and the special expression patterns for different PASC levels. By comparing the quality of life of patients after the acute phase of COVID-19 and before the disease, samples in the dataset were divided into three groups, namely, "Better," "The Same," and "Worse." Each patient was represented by the expression levels of 58,929 genes. The machine learning-based workflow included six feature-ranking algorithms, incremental feature selection (IFS), and four classification algorithms. The feature ranking algorithms were in charge of assessing feature importance, whereas IFS with classification algorithms were used to extract essential genes and to construct efficient classifiers and classification rules. The expression of top genes in the results was associated with the immune response to viral infection, which is supported by the published literature. For example, patients with low CCDC18 expression and high CPED1 expression had good quality of life, whereas those with low CDC16 expression had poor quality of life.

NLRC5/MHC class I transactivator: A key target for immune escape by SARS-CoV-2

Antigen presentation to CD8+ T cells by MHC class I molecules is essential for host defense against viral infections. Various mechanisms have evolved in multiple viruses to escape immune surveillance and defense to support viral proliferation in host cells. Through in vitro SARS-CoV-2 infection studies and analysis of COVID-19 patient samples, we found that SARS-CoV-2 suppresses the induction of the MHC class I pathway by inhibiting the expression and function of NLRC5, a major transcriptional regulator of MHC class I genes. In this review, we discuss the molecular mechanisms for suppression of the MHC class I pathway and clinical implications for COVID-19.

ACE2 and TMPRSS2 expression in patients before, during, and after SARS-CoV-2 infection

During the SARS-CoV-2 pandemic angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) were constantly under the scientific spotlight, but most studies evaluated ACE2 and TMPRSS2 expression levels in patients infected by SARS-CoV-2. Thus, this study aimed to evaluate the expression levels of both proteins before, during, and after-infection. For that, nasopharyngeal samples from 26 patients were used to measure ACE2/TMPRSS2 ex-pression via qPCR. Symptomatic patients presented lower ACE2 expression levels before and after the infection than those in asymptomatic patients; however, these levels increased during SARS-CoV-2 infection. In addition, symptomatic patients presented higher expression levels of TMPRSS2 pre-infection, which decreased in the following periods. In summary, ACE2 and TMPRSS2 expression levels are potential risk factors for the development of symptomatic COVID-19, and the presence of SARS-CoV-2 potentially modulates those levels.

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

Introduction

The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing.

Methods

Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors.

Results

Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19.

Discussion

The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.

Upper Airway Epithelial Tissue Transcriptome Analysis Reveals Immune Signatures Associated with COVID-19 Severity in Ghanaians

The immunological signatures driving the severity of coronavirus disease 19 (COVID-19) in Ghanaians remain poorly understood. We performed bulk transcriptome sequencing of nasopharyngeal samples from severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-infected Ghanaians with mild and severe COVID-19, as well as healthy controls to characterize immune signatures at the primary SARS-CoV-2 infection site and identify drivers of disease severity. Generally, a heightened antiviral response was observed in SARS-CoV-2-infected Ghanaians compared with uninfected controls. COVID-19 severity was associated with immune suppression, overexpression of proinflammatory cytokines, including CRNN, IL1A, S100A7, and IL23A, and activation of pathways involved in keratinocyte proliferation. SAMD9L was among the differentially regulated interferon-stimulated genes in our mild and severe disease cohorts, suggesting that it may play a critical role in SARS-CoV-2 pathogenesis. By comparing our data with a publicly available dataset from a non-African (Indians) (GSE166530), an elevated expression of antiviral response-related genes was noted in COVID-19-infected Ghanaians. Overall, the study describes immune signatures driving COVID-19 severity in Ghanaians and identifies immune drivers that could serve as potential prognostic markers for future outbreaks or pandemics. It further provides important preliminary evidence suggesting differences in antiviral response at the upper respiratory interface in sub-Saharan Africans (Ghanaians) and non-Africans, which could be contributing to the differences in disease outcomes. Further studies using larger datasets from different populations will expand on these findings.

Gene set correlation enrichment analysis for interpreting and annotating gene expression profiles

Pathway analysis, including nontopology-based (non-TB) and topology-based (TB) methods, is widely used to interpret the biological phenomena underlying differences in expression data between two phenotypes. By considering dependencies and interactions between genes, TB methods usually perform better than non-TB methods in identifying pathways that include closely relevant or directly causative genes for a given phenotype. However, most TB methods may be limited by incomplete pathway data used as the reference network or by difficulties in selecting appropriate reference networks for different research topics. Here, we propose a gene set correlation enrichment analysis method, Gscore, based on an expression dataset-derived coexpression network to examine whether a differentially expressed gene (DEG) list (or each of its DEGs) is associated with a known gene set. Gscore is better able to identify target pathways in 89 human disease expression datasets than eight other state-of-the-art methods and offers insight into how disease-wide and pathway-wide associations reflect clinical outcomes. When applied to RNA-seq data from COVID-19-related cells and patient samples, Gscore provided a means for studying how DEGs are implicated in COVID-19-related pathways. In summary, Gscore offers a powerful analytical approach for annotating individual DEGs, DEG lists, and genome-wide expression profiles based on existing biological knowledge.

Discovery of common molecular signatures and drug repurposing for COVID-19/Asthma comorbidity: ACE2 and multi-partite networks

Angiotensin-converting enzyme 2 (ACE2) is identified as the functional receptor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the ongoing global coronavirus disease-2019 (COVID-19) pandemic. This study aimed to elucidate potential therapeutic avenues by scrutinizing approved drugs through the identification of the genetic signature associated with SARS-CoV-2 infection in individuals with asthma. This exploration was conducted through an integrated analysis, encompassing interaction networks between the ACE2 receptor and common host (co-host) factors implicated in COVID-19/asthma comorbidity. The comprehensive analysis involved the identification of common differentially expressed genes (cDEGs) and hub-cDEGs, functional annotations, interaction networks, gene set variation analysis (GSVA), gene set enrichment analysis (GSEA), and module construction. Interaction networks were used to identify overlapping disease modules and potential drug targets. Computational biology and molecular docking analyzes were utilized to discern functional drug modules. Subsequently, the impact of the identified drugs on the expression of hub-cDEGs was experimentally validated using a mouse model. A total of 153 cDEGs or co-host factors associated with ACE2 were identified in the COVID-19 and asthma comorbidity. Among these, seven significant cDEGs and proteins - namely, HRAS, IFNG, JUN, CDH1, TLR4, ICAM1, and SCD-were recognized as pivotal host factors linked to ACE2. Regulatory network analysis of hub-cDEGs revealed eight top-ranked transcription factors (TFs) proteins and nine microRNAs as key regulatory factors operating at the transcriptional and post-transcriptional levels, respectively. Molecular docking simulations led to the proposal of 10 top-ranked repurposable drug molecules (Rapamycin, Ivermectin, Everolimus, Quercetin, Estradiol, Entrectinib, Nilotinib, Conivaptan, Radotinib, and Venetoclax) as potential treatment options for COVID-19 in individuals with comorbid asthma. Validation analysis demonstrated that Rapamycin effectively inhibited ICAM1 expression in the HDM-stimulated mice group (p < 0.01). This study unveils the common pathogenesis and genetic signature underlying asthma and SARS-CoV-2 infection, delineated by the interaction networks of ACE2-related host factors. These findings provide valuable insights for the design and discovery of drugs aimed at more effective therapeutics within the context of lung disease comorbidities.

Transcriptome and machine learning analysis of the impact of COVID-19 on mitochondria and multiorgan damage

The effects of coronavirus disease 2019 (COVID-19) primarily concern the respiratory tract and lungs; however, studies have shown that all organs are susceptible to infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 may involve multiorgan damage from direct viral invasion through angiotensin-converting enzyme 2 (ACE2), through inflammatory cytokine storms, or through other secondary pathways. This study involved the analysis of publicly accessible transcriptome data from the Gene Expression Omnibus (GEO) database for identifying significant differentially expressed genes related to COVID-19 and an investigation relating to the pathways associated with mitochondrial, cardiac, hepatic, and renal toxicity in COVID-19. Significant differentially expressed genes were identified and ranked by statistical approaches, and the genes derived by biological meaning were ranked by feature importance; both were utilized as machine learning features for verification. Sample set selection for machine learning was based on the performance, sample size, imbalanced data state, and overfitting assessment. Machine learning served as a verification tool by facilitating the testing of biological hypotheses by incorporating gene list adjustment. A subsequent in-depth study for gene and pathway network analysis was conducted to explore whether COVID-19 is associated with cardiac, hepatic, and renal impairments via mitochondrial infection. The analysis showed that potential cardiac, hepatic, and renal impairments in COVID-19 are associated with ACE2, inflammatory cytokine storms, and mitochondrial pathways, suggesting potential medical interventions for COVID-19-induced multiorgan damage.

Gene expression profiling of host lipid metabolism in SARS-CoV-2 infected patients: a systematic review and integrated bioinformatics analysis

BACKGROUND

The Coronavirus disease 2019 (COVID-19) pandemic occurred due to the dispersion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Severe symptoms can be observed in COVID-19 patients with lipid-related comorbidities such as obesity and diabetes. Yet, the extensive molecular mechanisms of how SARS-CoV-2 causes dysregulation of lipid metabolism remain unknown.

METHODS

Here, an advanced search of articles was conducted using PubMed, Scopus, EBSCOhost, and Web of Science databases using terms from Medical Subject Heading (MeSH) like SARS-CoV-2, lipid metabolism and transcriptomic as the keywords. From 428 retrieved studies, only clinical studies using next-generation sequencing as a gene expression method in COVID-19 patients were accepted. Study design, study population, sample type, the method for gene expression and differentially expressed genes (DEGs) were extracted from the five included studies. The DEGs obtained from the studies were pooled and analyzed using the bioinformatics software package, DAVID, to determine the enriched pathways. The DEGs involved in lipid metabolic pathways were selected and further analyzed using STRING and Cytoscape through visualization by protein-protein interaction (PPI) network complex.

RESULTS

The analysis identified nine remarkable clusters from the PPI complex, where cluster 1 showed the highest molecular interaction score. Three potential candidate genes (PPARG, IFITM3 and APOBEC3G) were pointed out from the integrated bioinformatics analysis in this systematic review and were chosen due to their significant role in regulating lipid metabolism. These candidate genes were significantly involved in enriched lipid metabolic pathways, mainly in regulating lipid homeostasis affecting the pathogenicity of SARS-CoV-2, specifically in mechanisms of viral entry and viral replication in COVID-19 patients.

CONCLUSIONS

Taken together, our findings in this systematic review highlight the affected lipid-metabolic pathways along with the affected genes upon SARS-CoV-2 invasion, which could be a potential target for new therapeutic strategies study in the future.

Interferon response and profiling of interferon response genes in peripheral blood of vaccine-naive COVID-19 patients

Introduction

There is insufficient understanding on systemic interferon (IFN) responses during COVID-19 infection. Early reports indicated that interferon responses were suppressed by the coronavirus (SARS-CoV-2) and clinical trials of administration of various kinds of interferons had been disappointing. Expression of interferon-stimulated genes (ISGs) in peripheral blood (better known as interferon score) has been a well-established bioassay marker of systemic IFN responses in autoimmune diseases. Therefore, with archival samples of a cohort of COVID-19 patients collected before the availability of vaccination, we aimed to better understand this innate immune response by studying the IFN score and related ISGs expression in bulk and single cell RNAs sequencing expression datasets.

Methods

In this study, we recruited 105 patients with COVID-19 and 30 healthy controls in Hong Kong. Clinical risk factors, disease course, and blood sampling times were recovered. Based on a set of five commonly used ISGs (IFIT1, IFIT2, IFI27, SIGLEC1, IFI44L), the IFN score was determined in blood leukocytes collected within 10 days after onset. The analysis was confined to those blood samples collected within 10 days after disease onset. Additional public datasets of bulk gene and single cell RNA sequencing of blood samples were used for the validation of IFN score results.

Results

Compared to the healthy controls, we showed that ISGs expression and IFN score were significantly increased during the first 10 days after COVID infection in majority of patients (71%). Among those low IFN responders, they were more commonly asymptomatic patients (71% vs 25%). 22 patients did not mount an overall significant IFN response and were classified as low IFN responders (IFN score < 1). However, early IFN score or ISGs level was not a prognostic biomarker and could not predict subsequent disease severity. Both IFI27 and SIGLEC1 were monocyte-predominant expressing ISGs and IFI27 were activated even among those low IFN responders as defined by IFN score. In conclusion, a substantial IFN response was documented in this cohort of COVID-19 patients who experience a natural infection before the vaccination era. Like innate immunity towards other virus, the ISGs activation was observed largely during the early course of infection (before day 10). Single-cell RNA sequencing data suggested monocytes were the cell-type that primarily accounted for the activation of two highly responsive ISGs (IFI44L and IFI27).

Discussion

As sampling time and age were two major confounders of ISG expression, they may account for contradicting observations among previous studies. On the other hand, the IFN score was not associated with the severity of the disease.

Predicting host-based, synthetic lethal antiviral targets from omics data

Traditional antiviral therapies often have limited effectiveness due to toxicity and the emergence of drug resistance. Host-based antivirals are an alternative, but can cause nonspecific effects. Recent evidence shows that virus-infected cells can be selectively eliminated by targeting synthetic lethal (SL) partners of proteins disrupted by viral infection. Thus, we hypothesized that genes depleted in CRISPR knockout (KO) screens of virus-infected cells may be enriched in SL partners of proteins altered by infection. To investigate this, we established a computational pipeline predicting antiviral SL drug targets. First, we identified SARS-CoV-2-induced changes in gene products via a large compendium of omics data. Second, we identified SL partners for each altered gene product. Last, we screened CRISPR KO data for SL partners required for cell viability in infected cells. Despite differences in virus-induced alterations detected by various omics data, they share many predicted SL targets, with significant enrichment in CRISPR KO-depleted datasets. Our comparison of SARS-CoV-2 and influenza infection data revealed potential broad-spectrum, host-based antiviral SL targets. This suggests that CRISPR KO data are replete with common antiviral targets due to their SL relationship with virus-altered states and that such targets can be revealed from analysis of omics datasets and SL predictions.

Virome Data Explorer: A web resource to longitudinally explore respiratory viral infections, their interactions with other pathogens and host transcriptomic changes in over 100 people

Viral respiratory infections are an important public health concern due to their prevalence, transmissibility, and potential to cause serious disease. Disease severity is the product of several factors beyond the presence of the infectious agent, including specific host immune responses, host genetic makeup, and bacterial coinfections. To understand these interactions within natural infections, we designed a longitudinal cohort study actively surveilling respiratory viruses over the course of 19 months (2016 to 2018) in a diverse cohort in New York City. We integrated the molecular characterization of 800+ nasopharyngeal samples with clinical data from 104 participants. Transcriptomic data enabled the identification of respiratory pathogens in nasopharyngeal samples, the characterization of markers of immune response, the identification of signatures associated with symptom severity, individual viruses, and bacterial coinfections. Specific results include a rapid restoration of baseline conditions after infection, significant transcriptomic differences between symptomatic and asymptomatic infections, and qualitatively similar responses across different viruses. We created an interactive computational resource (Virome Data Explorer) to facilitate access to the data and visualization of analytical results.

A Retrospective Study on COVID-19 Infections Caused by Omicron Variant with Clinical, Epidemiological, and Viral Load Evaluations in Breakthrough Infections

Purpose: To explore the clinical, epidemiological, and viral load characteristics of COVID-19 caused by the omicron variant. Methods: Based on the COVID-19 epidemic caused by SARS-CoV-2 Omicron BA.2 broke out in Shanghai, China. To analyze whether there is any association between clinical symptoms and viral load of COVID-19 with age, sex, and combined disease and whether the clinical symptoms and viral load are associated with vaccine-breakthrough infections. Results: The most common symptoms were cough, expectoration, and fatigue, which were more common in women than males (p < 0.001). The average viral clearance time in the > 75 years group was the longest (6.64 days). The viral load in the 60-75 years group was significantly higher than that in the other groups (p < 0.001). The 18-45 years old group had the most clinical symptoms at admission (45.39%). The days of nucleic acid-negative conversion, average viral load, highest viral load, and clinical symptoms in comorbid chronic disease patients are longer (p < 0.001). The average and highest viral loads in the unvaccinated group were longer than those in the vaccine breakthrough infection groups (p < 0.001). However, the clinical symptoms in the vaccine breakthrough infection group were significantly more severe than those in the unvaccinated group (p < 0.001). Conclusions: We found that female patients, the elderly, and those with underlying comorbidities had longer clinical positive symptoms and viral loads. Although vaccination may not reduce clinical symptoms, it can shorten the viral load and the time required for virus clearance.

Transgenic mouse models support a protective role of type I IFN response in SARS-CoV-2 infection-related lung immunopathology and neuroinvasion

Type I interferon (IFN-I) response is the first line of host defense against invading viruses. In the absence of definite mouse models, the role of IFN-I in SARS-CoV-2 infection remains perplexing. Here, we develop two mouse models, one with constitutively high IFN-I response (hACE2; Irgm1-/-) and the other with dampened IFN-I response (hACE2; Ifnar1-/-), to comprehend the role of IFN-I response. We report that hACE2; Irgm1-/- mice are resistant to lethal SARS-CoV-2 infection. In contrast, a severe SARS-CoV-2 infection along with immune cell infiltration, cytokine storm, and enhanced pathology is observed in the lungs and brain of hACE2; Ifnar1-/- mice. The hACE2; Irgm1-/-Ifnar1-/- double-knockout mice display loss of the protective phenotype observed in hACE2; Irgm1-/- mice, suggesting that heightened IFN-I response accounts for the observed immunity. Taking the results together, we demonstrate that IFN-I protects from lethal SARS-CoV-2 infection, and Irgm1 (IRGM) could be an excellent therapeutic target against SARS-CoV-2.

The two-stage molecular scenery of SARS-CoV-2 infection with implications to disease severity: An in-silico quest

Introduction

The two-stage molecular profile of the progression of SARS-CoV-2 (SCOV2) infection is explored in terms of five key biological/clinical questions: (a) does SCOV2 exhibits a two-stage infection profile? (b) SARS-CoV-1 (SCOV1) vs. SCOV2: do they differ? (c) does and how SCOV2 differs from Influenza/INFL infection? (d) does low viral-load and (e) does COVID-19 early host response relate to the two-stage SCOV2 infection profile? We provide positive answers to the above questions by analyzing the time-series gene-expression profiles of preserved cell-lines infected with SCOV1/2 or, the gene-expression profiles of infected individuals with different viral-loads levels and different host-response phenotypes.

Methods

Our analytical methodology follows an in-silico quest organized around an elaborate multi-step analysis pipeline including: (a) utilization of fifteen gene-expression datasets from NCBI's gene expression omnibus/GEO repository; (b) thorough designation of SCOV1/2 and INFL progression stages and COVID-19 phenotypes; (c) identification of differentially expressed genes (DEGs) and enriched biological processes and pathways that contrast and differentiate between different infection stages and phenotypes; (d) employment of a graph-based clustering process for the induction of coherent groups of networked genes as the representative core molecular fingerprints that characterize the different SCOV2 progression stages and the different COVID-19 phenotypes. In addition, relying on a sensibly selected set of induced fingerprint genes and following a Machine Learning approach, we devised and assessed the performance of different classifier models for the differentiation of acute respiratory illness/ARI caused by SCOV2 or other infections (diagnostic classifiers), as well as for the prediction of COVID-19 disease severity (prognostic classifiers), with quite encouraging results.

Results

The central finding of our experiments demonstrates the down-regulation of type-I interferon genes (IFN-1), interferon induced genes (ISGs) and fundamental innate immune and defense biological processes and molecular pathways during the early SCOV2 infection stages, with the inverse to hold during the later ones. It is highlighted that upregulation of these genes and pathways early after infection may prove beneficial in preventing subsequent uncontrolled hyperinflammatory and potentially lethal events.

Discussion

The basic aim of our study was to utilize in an intuitive, efficient and productive way the most relevant and state-of-the-art bioinformatics methods to reveal the core molecular mechanisms which govern the progression of SCOV2 infection and the different COVID-19 phenotypes.

Genetic determinants of severe COVID-19 in young Asian and Middle Eastern patients: a case series

Studies of genetic factors associated with severe COVID-19 in young adults have been limited in non-Caucasian populations. Here, we clinically characterize a case series of patients with COVID-19, who were otherwise healthy, young adults (N = 55; mean age 34.1 ± SD 5.0 years) from 16 Asian, Middle Eastern, and North African countries. Using whole exome sequencing, we identify rare, likely deleterious variants affecting 16 immune-related genes in 17 out of 55 patients (31%), including 7 patients (41% of all carriers or 12.7% of all patients) who harbored multiple such variants mainly in interferon and toll-like receptor genes. Protein network analysis as well as transcriptomic analysis of nasopharyngeal swabs from an independent COVID-19 cohort (N = 50; 42% Asians and 22% Arabs) revealed that most of the altered genes, as identified by whole exome sequencing, and the associated molecular pathways were significantly altered in COVID-19 patients. Genetic variants tended to be associated with mortality, intensive care admission, and ventilation support. Our clinical cases series, genomic and transcriptomic findings suggest a possible role for interferon pathway genes in severe COVID-19 and highlight the importance of extending genetic studies to diverse populations to better understand the human genetics of disease.

Genomic and transcriptomic characterization of delta SARS-CoV-2 infection in free-ranging white-tailed deer (Odocoileus virginianus)

White-tailed deer (WTD) are susceptible to SARS-CoV-2 and represent an important species for surveillance. Samples from WTD (n = 258) collected in November 2021 from Québec, Canada were analyzed for SARS-CoV-2 RNA. We employed viral genomics and host transcriptomics to further characterize infection and investigate host response. We detected Delta SARS-CoV-2 (B.1.617.2) in WTD from the Estrie region; sequences clustered with human sequences from October 2021 from Vermont, USA, which borders this region. Mutations in the S-gene and a deletion in ORF8 were detected. Host expression patterns in SARS-CoV-2 infected WTD were associated with the innate immune response, including signaling pathways related to anti-viral, pro- and anti-inflammatory signaling, and host damage. We found limited correlation between genes associated with innate immune response from human and WTD nasal samples, suggesting differences in responses to SARS-CoV-2 infection. Our findings provide preliminary insights into host response to SARS-CoV-2 infection in naturally infected WTD.

Tracking antigen-specific TCR clonotypes in SARS-CoV-2 infection reveals distinct severity trajectories

Despite the importance of antigen-specific T cells in infectious disease, characterizing and tracking clonally amplified T cells during the progression of a patient's symptoms remain unclear. Here, we performed a longitudinal, in-depth single-cell multiomics analysis of samples from asymptomatic, mild, usual severe, and delayed severe patients of SARS-CoV-2 infection. Our in-depth analysis revealed that hyperactive or improper T-cell responses were more aggressive in delayed severe patients. Interestingly, tracking of antigen-specific T-cell receptor (TCR) clonotypes along the developmental trajectory indicated an attenuation in functional T cells upon severity. In addition, increased glycolysis and interleukin-6 signaling in the cytotoxic T cells were markedly distinct in delayed severe patients compared to usual severe patients, particularly in the middle and late stages of infection. Tracking B-cell receptor clonotypes also revealed distinct transitions and somatic hypermutations within B cells across different levels of disease severity. Our results suggest that single-cell TCR clonotype tracking can distinguish the severity of patients through immunological hallmarks, leading to a better understanding of the severity differences in and improving the management of infectious diseases by analyzing the dynamics of immune responses over time.

Understanding COVID-19 progression with longitudinal peripheral blood mononuclear cell proteomics: Changes in the cellular proteome over time

The clinical presentation of COVID-19 is highly variable, and understanding the underlying biological processes is crucial. This study utilized a proteomic analysis to investigate dysregulated processes in the peripheral blood mononuclear cells of patients with COVID-19 compared to healthy volunteers. Samples were collected at different stages of the disease, including hospital admission, after 7 days of hospitalization, and 30 days after discharge. Metabolic pathway alterations and increased abundance of neutrophil-related proteins were observed in patients. Patients progressing to critical illness had significantly low-abundance proteins in the pentose phosphate and glycolysis pathways compared with those presenting clinical recovery. Important biological processes, such as fatty acid concentration and glucose metabolism disorder, remained altered even after 30 days of hospital discharge. Temporal proteomic changes revealed distinct pathways in critically ill and non-critically ill patients. Our study emphasizes the significance of longitudinal cellular proteomic studies in identifying disease progression-related pathways and persistent protein changes post-hospitalization.

The Protective Effect of Pumpkin and Fermented Whey Mixture against AFB1 and OTA Immune Toxicity In Vitro. A Transcriptomic Approach

SCOPE

The aim of the study is to investigate in Jurkat cells the possible beneficial effect of pumpkin (P) and fermented milk whey (FW) mixture against aflatoxin B1 (AFB1) and ochratoxin A (OTA) induced alterations in gene expression profile.

METHODS AND RESULTS

Human T cells are exposed for 7 days to digested bread extracts containing P-FW mixture along with AFB1 and OTA, individually and in combination. The results of RNA sequencing show that AFB1 P-FW exposure resulted in 34 differentially expressed genes (DEGs) while 3450 DEGs are found in OTA P-FW exposure and 3264 DEGs in AFB1-OTA P-FW treatment. Gene ontology analysis reveals biological processes and molecular functions related to immune system and inflammatory response. Moreover, PathVisio analysis points to eicosanoid signaling via lipoxygenase as the main pathway altered by AFB1 P-FW exposure whereas interferon signaling is the most affected pathway after OTA P-FW and AFB1-OTA P-FW treatments.

CONCLUSIONS

The mitigation of genes and inherent pathways typically associated with the inflammatory response suggest not only the anti-inflammatory and protective role of P-FW mixture but also their possible application in food industry to counteract AFB1 and OTA toxic effects on human and animal health.

Type I/type III IFN and related factors regulate JEV infection and BBB endothelial integrity

BACKGROUND

Japanese encephalitis virus (JEV) remains a predominant cause of Japanese encephalitis (JE) globally. Its infection is usually accompanied by disrupted blood‒brain barrier (BBB) integrity and central nervous system (CNS) inflammation in a poorly understood pathogenesis. Productive JEV infection in brain microvascular endothelial cells (BMECs) is considered the initial event of the virus in penetrating the BBB. Type I/III IFN and related factors have been described as negative regulators in CNS inflammation, whereas their role in JE remains ambiguous.

METHODS

RNA-sequencing profiling (RNA-seq), real-time quantitative PCR, enzyme-linked immunosorbent assay, and Western blotting analysis were performed to analyze the gene and protein expression changes between mock- and JEV-infected hBMECs. Bioinformatic tools were used to cluster altered signaling pathway members during JEV infection. The shRNA-mediated immune factor-knockdown hBMECs and the in vitro transwell BBB model were utilized to explore the interrelation between immune factors, as well as between immune factors and BBB endothelial integrity.

RESULTS

RNA-Seq data of JEV-infected hBMECs identified 417, 1256, and 2748 differentially expressed genes (DEGs) at 12, 36, and 72 h post-infection (hpi), respectively. The altered genes clustered into distinct pathways in gene ontology (GO) terms and KEGG pathway enrichment analysis, including host antiviral immune defense and endothelial cell leakage. Further investigation revealed that pattern-recognition receptors (PRRs, including TLR3, RIG-I, and MDA5) sensed JEV and initiated IRF/IFN signaling. IFNs triggered the expression of interferon-induced proteins with tetratricopeptide repeats (IFITs) via the JAK/STAT pathway. Distinct PRRs exert different functions in barrier homeostasis, while treatment with IFN (IFN-β and IFN-λ1) in hBMECs stabilizes the endothelial barrier by alleviating exogenous destruction. Despite the complex interrelationship, IFITs are considered nonessential in the IFN-mediated maintenance of hBMEC barrier integrity.

CONCLUSIONS

This research provided the first comprehensive description of the molecular mechanisms of host‒pathogen interplay in hBMECs responding to JEV invasion, in which type I/III IFN and related factors strongly correlated with regulating the hBMEC barrier and restricting JEV infection. This might help with developing an attractive therapeutic strategy in JE.

A machine learning classifier using 33 host immune response mRNAs accurately distinguishes viral and non-viral acute respiratory illnesses in nasal swab samples

BACKGROUND

Viral acute respiratory illnesses (viral ARIs) contribute significantly to human morbidity and mortality worldwide, but their successful treatment requires timely diagnosis of viral etiology, which is complicated by overlap in clinical presentation with the non-viral ARIs. Multiple pandemics in the twenty-first century to date have further highlighted the unmet need for effective monitoring of clinically relevant emerging viruses. Recent studies have identified conserved host response to viral infections in the blood.

METHODS

We hypothesize that a similarly conserved host response in nasal samples can be utilized for diagnosis and to rule out viral infection in symptomatic patients when current diagnostic tests are negative. Using a multi-cohort analysis framework, we analyzed 1555 nasal samples across 10 independent cohorts dividing them into training and validation.

RESULTS

Using six of the datasets for training, we identified 119 genes that are consistently differentially expressed in viral ARI patients (N = 236) compared to healthy controls (N = 146) and further down-selected 33 genes for classifier development. The resulting locked logistic regression-based classifier using the 33-mRNAs had AUC of 0.94 and 0.89 in the six training and four validation datasets, respectively. Furthermore, we found that although trained on healthy controls only, in the four validation datasets, the 33-mRNA classifier distinguished viral ARI from both healthy or non-viral ARI samples with > 80% specificity and sensitivity, irrespective of age, viral type, and viral load. Single-cell RNA-sequencing data showed that the 33-mRNA signature is dominated by macrophages and neutrophils in nasal samples.

CONCLUSION

This proof-of-concept signature has potential to be adapted as a clinical point-of-care test ('RespVerity') to improve the diagnosis of viral ARIs.

Predicting host-based, synthetic lethal antiviral targets from omics data

Traditional antiviral therapies often have limited effectiveness due to toxicity and development of drug resistance. Host-based antivirals, while an alternative, may lead to non-specific effects. Recent evidence shows that virus-infected cells can be selectively eliminated by targeting synthetic lethal (SL) partners of proteins disrupted by viral infection. Thus, we hypothesized that genes depleted in CRISPR KO screens of virus-infected cells may be enriched in SL partners of proteins altered by infection. To investigate this, we established a computational pipeline predicting SL drug targets of viral infections. First, we identified SARS-CoV-2-induced changes in gene products via a large compendium of omics data. Second, we identified SL partners for each altered gene product. Last, we screened CRISPR KO data for SL partners required for cell viability in infected cells. Despite differences in virus-induced alterations detected by various omics data, they share many predicted SL targets, with significant enrichment in CRISPR KO-depleted datasets. Comparing data from SARS-CoV-2 and influenza infections, we found possible broad-spectrum, host-based antiviral SL targets. This suggests that CRISPR KO data are replete with common antiviral targets due to their SL relationship with virus-altered states and that such targets can be revealed from analysis of omics datasets and SL predictions.

Molecular mechanisms of COVID-19-induced pulmonary fibrosis and epithelial-mesenchymal transition

As the outbreak of COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) first broke out in Hubei Province, China, at the end of 2019. It has brought great challenges and harms to global public health. SARS-CoV-2 mainly affects the lungs and is mainly manifested as pulmonary disease. However, one of the biggest crises arises from the emergence of COVID-19-induced fibrosis. At present, there are still many questions about how COVID-19 induced pulmonary fibrosis (PF) occurs and how to treat and regulate its long-term effects. In addition, as an important process of fibrosis, the effect of COVID-19 on epithelial-mesenchymal transition (EMT) may be an important factor driving PF. This review summarizes the main pathogenesis and treatment mechanisms of COVID-19 related to PF. Starting with the basic mechanisms of PF, such as EMT, transforming growth factor-β (TGF-β), fibroblasts and myofibroblasts, inflammation, macrophages, innate lymphoid cells, matrix metalloproteinases and tissue inhibitors of metalloproteinases, hedgehog pathway as well as Notch signaling. Further, we highlight the importance of COVID-19-induced EMT in the process of PF and provide an overview of the related molecular mechanisms, which will facilitate future research to propose new clinical therapeutic solutions for the treatment of COVID-19-induced PF.

Differential expression of antiviral and immune-related genes in individuals with COVID-19 asymptomatic or with mild symptoms

COVID-19 is characterized by a wide range of symptoms where the genetic background plays a key role in SARS-CoV-2 infection. In this study, the relative expression of IRF9, CCL5, IFI6, TGFB1, IL1B, OAS1, and TFRC genes (related to immunity and antiviral activity) was analyzed in upper airway samples from 127 individuals (97 COVID-19 positive and 30 controls) by using a two-step RT-PCR. All genes excepting IL1B (p=0.878) showed a significantly higher expression (p<0.005) in COVID-19 cases than in the samples from the control group suggesting that in asymptomatic-mild cases antiviral and immune system cells recruitment gene expression is being promoted. Moreover, IFI6 (p=0.002) and OAS1 (p=0.044) were upregulated in cases with high viral loads, which could be related to protection against severe forms of this viral infection. In addition, a higher frequency (68.7%) of individuals infected with the Omicron variant presented higher viral load values of infection when compared to individuals infected with other variants (p<0.001). Furthermore, an increased expression of IRF9 (p<0.001), IFI6 (p<0.001), OAS1 (p=0.011), CCL5, (p=0.003) and TGFB1 (p<0.001) genes was observed in individuals infected with SARS-CoV-2 wildtype virus, which might be due to immune response evasion of the viral variants and/or vaccination. The obtained results indicate a protective role of IFI6, OAS1 and IRF9 in asymptomatic -mild cases of SARS-CoV-2 infection while the role of TGFB1 and CCL5 in the pathogenesis of the disease is still unclear. The importance of studying the dysregulation of immune genes in relation to the infective variant is stand out in this study.

Longitudinal host transcriptional responses to SARS-CoV-2 infection in adults with extremely high viral load

Current understanding of viral dynamics of SARS-CoV-2 and host responses driving the pathogenic mechanisms in COVID-19 is rapidly evolving. Here, we conducted a longitudinal study to investigate gene expression patterns during acute SARS-CoV-2 illness. Cases included SARS-CoV-2 infected individuals with extremely high viral loads early in their illness, individuals having low SARS-CoV-2 viral loads early in their infection, and individuals testing negative for SARS-CoV-2. We could identify widespread transcriptional host responses to SARS-CoV-2 infection that were initially most strongly manifested in patients with extremely high initial viral loads, then attenuating within the patient over time as viral loads decreased. Genes correlated with SARS-CoV-2 viral load over time were similarly differentially expressed across independent datasets of SARS-CoV-2 infected lung and upper airway cells, from both in vitro systems and patient samples. We also generated expression data on the human nose organoid model during SARS-CoV-2 infection. The human nose organoid-generated host transcriptional response captured many aspects of responses observed in the above patient samples, while suggesting the existence of distinct host responses to SARS-CoV-2 depending on the cellular context, involving both epithelial and cellular immune responses. Our findings provide a catalog of SARS-CoV-2 host response genes changing over time.

Impact of Changes in Human Airway Epithelial Cellular Composition and Differentiation on SARS-CoV-2 Infection Biology

The consequences of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can range from asymptomatic to fatal disease. Variations in epithelial susceptibility to SARS-CoV-2 infection depend on the anatomical location from the proximal to distal respiratory tract. However, the cellular biology underlying these variations is not completely understood. Thus, air-liquid interface cultures of well-differentiated primary human tracheal and bronchial epithelial cells were employed to study the impact of epithelial cellular composition and differentiation on SARS-CoV-2 infection by transcriptional (RNA sequencing) and immunofluorescent analyses. Changes of cellular composition were investigated by varying time of differentiation or by using specific compounds. We found that SARS-CoV-2 primarily infected not only ciliated cells but also goblet cells and transient secretory cells. Viral replication was impacted by differences in cellular composition, which depended on culturing time and anatomical origin. A higher percentage of ciliated cells correlated with a higher viral load. However, DAPT treatment, which increased the number of ciliated cells and reduced goblet cells, decreased viral load, indicating the contribution of goblet cells to infection. Cell entry factors, especially cathepsin L and transmembrane protease serine 2, were also affected by differentiation time. In conclusion, our study demonstrates that viral replication is affected by changes in cellular composition, especially in cells related to the mucociliary system. This could explain in part the variable susceptibility to SARS-CoV-2 infection between individuals and between anatomical locations in the respiratory tract.

SARS-CoV-2 leverages airway epithelial protective mechanism for viral infection

Despite much concerted effort to better understand severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral infection, relatively little is known about the dynamics of early viral entry and infection in the airway. Here we analyzed a single-cell RNA sequencing dataset of early SARS-CoV-2 infection in a humanized in vitro model, to elucidate key mechanisms by which the virus triggers a cell-systems-level response in the bronchial epithelium. We find that SARS-CoV-2 virus preferentially enters the tissue via ciliated cell precursors, giving rise to a population of infected mature ciliated cells, which signal to basal cells, inducing further rapid differentiation. This feedforward loop of infection is mitigated by further cell-cell communication, before interferon signaling begins at three days post-infection. These findings suggest hijacking by the virus of potentially beneficial tissue repair mechanisms, possibly exacerbating the outcome. This work both elucidates the interplay between barrier tissues and viral infections and may suggest alternative therapeutic approaches targeting non-immune response mechanisms.

Identification of host genomic biomarkers from multiple transcriptomics datasets for diagnosis and therapies of SARS-CoV-2 infections

The pandemic of COVID-19 is a severe threat to human life and the global economy. Despite the success of vaccination efforts in reducing the spread of the virus, the situation remains largely uncontrolled due to the random mutation in the RNA sequence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which demands different variants of effective drugs. Disease-causing gene-mediated proteins are usually used as receptors to explore effective drug molecules. In this study, we analyzed two different RNA-Seq and one microarray gene expression profile datasets by integrating EdgeR, LIMMA, weighted gene co-expression network and robust rank aggregation approaches, which revealed SARS-CoV-2 infection causing eight hub-genes (HubGs) including HubGs; REL, AURKA, AURKB, FBXL3, OAS1, STAT4, MMP2 and IL6 as the host genomic biomarkers. Gene Ontology and pathway enrichment analyses of HubGs significantly enriched some crucial biological processes, molecular functions, cellular components and signaling pathways that are associated with the mechanisms of SARS-CoV-2 infections. Regulatory network analysis identified top-ranked 5 TFs (SRF, PBX1, MEIS1, ESR1 and MYC) and 5 miRNAs (hsa-miR-106b-5p, hsa-miR-20b-5p, hsa-miR-93-5p, hsa-miR-106a-5p and hsa-miR-20a-5p) as the key transcriptional and post-transcriptional regulators of HubGs. Then, we conducted a molecular docking analysis to determine potential drug candidates that could interact with HubGs-mediated receptors. This analysis resulted in the identification of top-ranked ten drug agents, including Nilotinib, Tegobuvir, Digoxin, Proscillaridin, Olysio, Simeprevir, Hesperidin, Oleanolic Acid, Naltrindole and Danoprevir. Finally, we investigated the binding stability of the top-ranked three drug molecules Nilotinib, Tegobuvir and Proscillaridin with the three top-ranked proposed receptors (AURKA, AURKB, OAS1) by using 100 ns MD-based MM-PBSA simulations and observed their stable performance. Therefore, the findings of this study might be useful resources for diagnosis and therapies of SARS-CoV-2 infections.

A comparative study of COVID-19 transcriptional signatures between clinical samples and preclinical cell models in the search for disease master regulators and drug repositioning candidates

Coronavirus disease 2019 (COVID-19) is an acute viral disease with millions of cases worldwide. Although the number of daily new cases and deaths has been dropping, there is still a need for therapeutic alternatives to deal with severe cases. A promising strategy to prospect new therapeutic candidates is to investigate the regulatory mechanisms involved in COVID-19 progression using integrated transcriptomics approaches. In this work, we aimed to identify COVID-19 Master Regulators (MRs) using a series of publicly available gene expression datasets of lung tissue from patients which developed the severe form of the disease. We were able to identify a set of six potential COVID-19 MRs related to its severe form, namely TAL1, TEAD4, EPAS1, ATOH8, ERG, and ARNTL2. In addition, using the Connectivity Map drug repositioning approach, we identified 52 different drugs which could be used to revert the disease signature, thus being candidates for the design of novel clinical treatments. Furthermore, we compared the identified signature and drugs with the ones obtained from the analysis of nasopharyngeal swab samples from infected patients and preclinical cell models. This comparison showed significant similarities between them, although also revealing some limitations on the overlap between clinical and preclinical data in COVID-19, highlighting the need for careful selection of the best model for each disease stage.

Biological sex and age-related differences shape the antiviral response to SARS-CoV-2 infection

For the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, clinical manifestations are broad and highly heterogeneous for both sexes. We aimed to determine how biological sex and age impact immune gene expression, particularly influencing the humoral neutralizing antibody (NAb) response and the cytokine production in coronavirus disease 2019 (COVID-19) subjects. The immune gene expression, according to biological sex and age, was assessed using the genome wide expression profile of blood proteins from healthy individuals using the Genotype Tissue Expression (GTEx) database. Moreover, anti-SARS-CoV-2 neutralizing antibody titers and cytokine levels were determined in blood samples from 141 COVID-19 individuals from Medellín, Colombia. Among subjects with COVID-19, males had statistically significantly higher median NAb titers and serum concentrations of interleukin-6 and CC chemokine ligand 3 than females. Overall, our findings point out a more robust innate immune response in women that could help recognize and restrain the virus faster than in men.

Multi-OMICs landscape of SARS-CoV-2-induced host responses in human lung epithelial cells

COVID-19 pandemic continues to remain a global health concern owing to the emergence of newer variants. Several multi-Omics studies have produced extensive evidence on host-pathogen interactions and potential therapeutic targets. Nonetheless, an increased understanding of host signaling networks regulated by post-translational modifications and their ensuing effect on the cellular dynamics is critical to expanding the current knowledge on SARS-CoV-2 infections. Through an unbiased transcriptomics, proteomics, acetylomics, phosphoproteomics, and exometabolome analysis of a lung-derived human cell line, we show that SARS-CoV-2 Norway/Trondheim-S15 strain induces time-dependent alterations in the induction of type I IFN response, activation of DNA damage response, dysregulated Hippo signaling, among others. We identified interplay of phosphorylation and acetylation dynamics on host proteins and its effect on the altered release of metabolites, especially organic acids and ketone bodies. Together, our findings serve as a resource of potential targets that can aid in designing novel host-directed therapeutic strategies.

Identification of phytochemicals in Qingfei Paidu decoction for the treatment of coronavirus disease 2019 by targeting the virus-host interactome

Qingfei Paidu decoction (QFPDD) has been clinically proven to be effective in the treatment of coronavirus disease 2019 (COVID-19). However, the bioactive components and therapeutic mechanisms remain unclear. This study aimed to explore the effective components and underlying mechanisms of QFPDD in the treatment of COVID-19 by targeting the virus-host interactome and verifying the antiviral activities of its active components in vitro. Key active components and targets were identified by analysing the topological features of a compound-target-pathway-disease regulatory network of QFPDD for the treatment of COVID-19. The antiviral activity of the active components was determined by a live virus infection assay, and possible mechanisms were analysed by pseudotyped virus infection and molecular docking assays. The inhibitory effects of the components tested on the virus-induced release of IL-6, IL-1β and CXCL-10 were detected by ELISA. Three components of QFPDD, oroxylin A, hesperetin and scutellarin, exhibited potent antiviral activities against live SARS-CoV-2 virus and HCoV-OC43 virus with IC₅₀ values ranging from 18.68 to 63.27 μM. Oroxylin A inhibited the entry of SARS-CoV-2 pseudovirus into target cells and inhibited SARS-CoV-2 S protein-mediated cell-cell fusion by binding with the ACE2 receptor. The active components of QFPDD obviously inhibited the IL-6, IL-1β and CXCL-10 release induced by the SARS-CoV-2 S protein. This study supports the clinical application of QFPDD and provides an effective analysis method for the in-depth study of the mechanisms of traditional Chinese medicine (TCM) in the prevention and treatment of COVID-19.

Potential core genes associated with COVID-19 identified via weighted gene co-expression network analysis

AIMS

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel virus belonging to the Coronaviridae family that causes coronavirus disease (COVID-19). This disease rapidly reached pandemic status, presenting a serious threat to global health. However, the detailed molecular mechanism contributing to COVID-19 has not yet been elucidated.

METHODS

The expression profiles, including the mRNA levels, of samples from patients infected with SARS-CoV-2 along with clinical data were obtained from the GSE152075 dataset in the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was used to identify co-expression modules, which were then implemented to evaluate the relationships between fundamental modules and clinical traits. The differentially expressed genes (DEGs), gene ontology (GO) functional enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were evaluated using R software packages.

RESULTS

A total of 377 SARS-CoV-2-infected samples and 54 normal samples with available clinical and genetic data were obtained from the GEO database. There were 1444 DEGs identified between the sample types, which were used to screen out 11 co-expression modules in the WGCNA. Six co-expression modules were significantly associated with three clinical traits (SARS-CoV-2 positivity, age, and sex). Among the DEGs in two modules significantly correlated with SARS-CoV-2 positivity, enrichment was observed in the biological process of viral infection strategies (viral translation) in the GO analysis. The KEGG signalling pathway analysis demonstrated that the DEGs in the two modules were commonly enriched in oxidative phosphorylation, ribosome, and thermogenesis pathways. Moreover, a five-core gene set (RPL35A, RPL7A, RPS15, RPS20, and RPL17) with top connectivity with other genes was identified in the SARS-CoV-2 infection modules, suggesting that these genes may be indispensable in viral transcription after infection.

CONCLUSION

The identified core genes and signalling pathways associated with SARS-CoV-2 infection can significantly supplement the current understanding of COVID-19. The five core genes encoding ribosomal proteins may be indispensable in viral protein biosynthesis after SARS-CoV-2 infection and serve as therapeutic targets for COVID-19 treatment. These findings can be used as a basis for creating a hypothetical model for future experimental studies regarding associations of SARS-CoV-2 infection with ribosomal protein function.

Circular RNAs as emerging regulators in COVID-19 pathogenesis and progression

Coronavirus disease 2019 (COVID-19), an infectious acute respiratory disease caused by a newly emerging RNA virus, is a still-growing pandemic that has caused more than 6 million deaths globally and has seriously threatened the lives and health of people across the world. Currently, several drugs have been used in the clinical treatment of COVID-19, such as small molecules, neutralizing antibodies, and monoclonal antibodies. In addition, several vaccines have been used to prevent the spread of the pandemic, such as adenovirus vector vaccines, inactivated vaccines, recombinant subunit vaccines, and nucleic acid vaccines. However, the efficacy of vaccines and the onset of adverse reactions vary among individuals. Accumulating evidence has demonstrated that circular RNAs (circRNAs) are crucial regulators of viral infections and antiviral immune responses and are heavily involved in COVID-19 pathologies. During novel coronavirus infection, circRNAs not only directly affect the transcription process and interfere with viral replication but also indirectly regulate biological processes, including virus-host receptor binding and the immune response. Consequently, understanding the expression and function of circRNAs during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection will provide novel insights into the development of circRNA-based methods. In this review, we summarize recent progress on the roles and underlying mechanisms of circRNAs that regulate the inflammatory response, viral replication, immune evasion, and cytokines induced by SARS-CoV-2 infection, and thus highlighting the diagnostic and therapeutic challenges in the treatment of COVID-19 and future research directions.

Genomic Transcriptome Benefits and Potential Harms of COVID-19 Vaccines Indicated from Optimized Genomic Biomarkers

COVID-19 vaccines can be the tugboats for preventing SARS-CoV-2 infections when they are practical and, more importantly, without adverse effects. However, the reality is that they may result in short-term or long-term impacts on COVID-19-related diseases and even trigger the formation of new variants of SARS-CoV-2. Using published data, we use a set of optimized-performance COVID-19 genomic biomarkers (MND1, CDC6, ZNF282) to study the benefits and adverse effects of the BNT162b2 vaccine. We found that the vaccine lowered the expression values of genes MND1 and CDC6 while heightening the expression values of ZNF282 in individuals who are SARS-CoV-2 naïve, which is expected and satisfies the biological equivalence between the COVID-19 disease and the genomic signature patterns established in the literature. However, we also found that COVID-19-convalescent octogenarians responded reversely. The vaccine heightened the expression values of MND1 and CDC6. In addition, it lowered the expression values of ZNF282. Such adverse effects raise outstanding concerns about whether or not COVID-19-convalescent individuals should take the current vaccine or when they can take it. These findings are new at the genomic level and can provide insights into developing next-generation vaccines, antiviral drugs, and pandemic management guidance.

Genomic Biomarker Heterogeneities between SARS-CoV-2 and COVID-19

Genes functionally associated with SARS-CoV-2 infection and genes functionally related to the COVID-19 disease can be different, whose distinction will become the first essential step for successfully fighting against the COVID-19 pandemic. Unfortunately, this first step has not been completed in all biological and medical research. Using a newly developed max-competing logistic classifier, two genes, ATP6V1B2 and IFI27, stand out to be critical in the transcriptional response to SARS-CoV-2 infection with differential expressions derived from NP/OP swab PCR. This finding is evidenced by combining these two genes with another gene in predicting disease status to achieve better-indicating accuracy than existing classifiers with the same number of genes. In addition, combining these two genes with three other genes to form a five-gene classifier outperforms existing classifiers with ten or more genes. These two genes can be critical in fighting against the COVID-19 pandemic as a new focus and direction with their exceptional predicting accuracy. Comparing the functional effects of these genes with a five-gene classifier with 100% accuracy identified and tested from blood samples in our earlier work, the genes and their transcriptional response and functional effects on SARS-CoV-2 infection, and the genes and their functional signature patterns on COVID-19 antibodies, are significantly different. We will use a total of fourteen cohort studies (including breakthrough infections and omicron variants) with 1481 samples to justify our results. Such significant findings can help explore the causal and pathological links between SARS-CoV-2 infection and the COVID-19 disease, and fight against the disease with more targeted genes, vaccines, antiviral drugs, and therapies.

Nucleocapsid and spike antibody responses following virologically confirmed SARS-CoV-2 infection: an observational analysis in the Virus Watch community cohort

OBJECTIVES

Seroprevalence studies can provide a measure of SARS-CoV-2 cumulative incidence, but a better understanding of spike and nucleocapsid (anti-N) antibody dynamics following infection is needed to assess the longevity of detectability.

METHODS

Adults aged ≥18 years, from households enrolled in the Virus Watch prospective community cohort study in England and Wales, provided monthly capillary blood samples, which were tested for spike antibody and anti-N. Participants self-reported vaccination dates and past medical history. Previous polymerase chain reaction (PCR) swabs were obtained through Second Generation Surveillance System linkage data. The primary outcome variables were seropositivity and total anti-N and spike antibody levels after PCR-confirmed infection.

RESULTS

A total of 13,802 eligible individuals provided 58,770 capillary blood samples. A total of 537 of these had a previous positive PCR-confirmed SARS-CoV-2 infection within 0-269 days of antibody sample date, among them 432 (80.45%) having a positive anti-N result. Median anti-N levels peaked between days 90 and 119 after PCR results and then began to decline. There is evidence of anti-N waning from 120 days onwards, with earlier waning for females and younger age categories.

CONCLUSION

Our findings suggest that anti-N has around 80% sensitivity for identifying previous COVID-19 infection, and the duration of detectability is affected by sex and age.

Shedding of infectious SARS-CoV-2 despite vaccination

The SARS-CoV-2 Delta Variant of Concern is highly transmissible and contains mutations that confer partial immune escape. The emergence of Delta in North America caused the first surge in COVID-19 cases after SARS-CoV-2 vaccines became widely available. To determine whether individuals infected despite vaccination might be capable of transmitting SARS-CoV-2, we compared RT-PCR cycle threshold (Ct) data from 20,431 test-positive anterior nasal swab specimens from fully vaccinated (n = 9,347) or unvaccinated (n = 11,084) individuals tested at a single commercial laboratory during the interval 28 June– 1 December 2021 when Delta variants were predominant. We observed no significant effect of vaccine status alone on Ct value, nor when controlling for vaccine product or sex. Testing a subset of low-Ct (<25) samples, we detected infectious virus at similar rates, and at similar titers, in specimens from vaccinated and unvaccinated individuals. These data indicate that vaccinated individuals infected with Delta variants are capable of shedding infectious SARS-CoV-2 and could play a role in spreading COVID-19.

A pivotal moment in the COVID-19 pandemic in the U.S. occurred during the summer of 2021—after the majority of people were vaccinated against the virus that causes COVID. The paradigm at the time was that infection and transmission after vaccination were rare. After contact tracers noticed an increase in infections after vaccination, we rapidly assembled a team of virologists, epidemiologists, and public health officials to investigate. Our study was conducted in Wisconsin at a time when the Delta variant accounted for almost all new infections. While data related to individual outbreaks and large gatherings were emerging, we examined data from community test sites spread over a wide geographic area in Wisconsin. We found that a large proportion of people with infection despite full vaccination had high levels of virus in their bodies, regardless of sex or the type of vaccine they received. Our study was one of the first to demonstrate the possibility that vaccinated people could play a role in spreading COVID, and helped inform public health policies (such as mask mandates) to cope with new surges in COVID-19 cases.

Pin-Pointing the Key Hubs in the IFN-γ Pathway Responding to SARS-CoV-2 Infection

Interferon gamma (IFN-γ) may be potential adjuvant immunotherapy for COVID-19 patients. In this work, we assessed gene expression profiles associated with the IFN-γ pathway in response to SARS-CoV-2 infection. Employing a case-control study from SARS-CoV-2-positive and -negative patients, we identified IFN-γ-associated pathways to be enriched in positive patients. Bioinformatics analyses showed upregulation of MAP2K6, CBL, RUNX3, STAT1, and JAK2 in COVID-19-positive vs. -negative patients. A positive correlation was observed between STAT1/JAK2, which varied alongside the patient’s viral load. Expression of MX1, MX2, ISG15, and OAS1 (four well-known IFN-stimulated genes (ISGs)) displayed upregulation in COVID-19-positive vs. -negative patients. Integrative analyses showcased higher levels of ISGs, which were associated with increased viral load and STAT1/JAK2 expression. Confirmation of ISGs up-regulation was performed in vitro using the A549 lung cell line treated with Poly (I:C), a synthetic analog of viral double-stranded RNA; and in different pulmonary human cell lines and ferret tracheal biopsies infected with SARS-CoV-2. A pre-clinical murine model of Coronavirus infection confirmed findings displaying increased ISGs in the liver and lungs from infected mice. Altogether, these results demonstrate the role of IFN-γ and ISGs in response to SARS-CoV-2 infection, highlighting alternative druggable targets that can boost the host response.

Upregulation of interleukin-19 in saliva of patients with COVID-19

Cytokines are major players in orchestrating inflammation, disease pathogenesis and severity during COVID-19 disease. However, the role of IL-19 in COVID-19 pathogenesis remains elusive. Herein, through the analysis of transcriptomic datasets of SARS-CoV-2 infected lung cells, nasopharyngeal swabs, and lung autopsies of COVID-19 patients, we report that expression levels of IL-19 and its receptor, IL-20R2, were upregulated following SARS-CoV-2 infection. Of 202 adult COVID-19 patients, IL-19 protein level was significantly higher in blood and saliva of asymptomatic patients compared to healthy controls when adjusted for patients’ demographics (P < 0.001). Interestingly, high saliva IL-19 level was also associated with COVID-19 severity (P < 0.0001), need for mechanical ventilation (P = 0.002), and/or death (P = 0.010) within 29 days of admission, after adjusting for patients’ demographics, diabetes mellitus comorbidity, and COVID-19 serum markers of severity such as D-dimer, C-reactive protein, and ferritin. Moreover, patients who received interferon beta during their hospital stay had lower plasma IL-19 concentrations (24 pg mL⁻¹) than those who received tocilizumab (39.2 pg mL⁻¹) or corticosteroids (42.5 pg mL⁻¹). Our findings indicate that high saliva IL-19 level was associated with COVID-19 infectivity and disease severity.

The Variation of Transcriptomic Perturbations is Associated with the Development and Progression of Various Diseases

Background

Although transcriptomic data have been widely applied to explore various diseases, few studies have investigated the association between transcriptomic perturbations and disease development in a wide variety of diseases.

Methods

Based on a previously developed algorithm for quantifying intratumor heterogeneity at the transcriptomic level, we defined the variation of transcriptomic perturbations (VTP) of a disease relative to the health status. Based on publicly available transcriptome datasets, we compared VTP values between the disease and health status and analyzed correlations between VTP values and disease progression or severity in various diseases, including neurological disorders, infectious diseases, cardiovascular diseases, respiratory diseases, liver diseases, kidney diseases, digestive diseases, and endocrine diseases. We also identified the genes and pathways whose expression perturbations correlated positively with VTP across diverse diseases.

Results

VTP values were upregulated in various diseases relative to their normal controls. VTP values were significantly greater in define than in possible or probable Alzheimer's disease. VTP values were significantly larger in intensive care unit (ICU) COVID-19 patients than in non-ICU patients, and in COVID-19 patients requiring mechanical ventilatory support (MVS) than in those not requiring MVS. VTP correlated positively with viral loads in acquired immune deficiency syndrome (AIDS) patients. Moreover, the AIDS patients treated with abacavir or zidovudine had lower VTP values than those without such therapies. In pulmonary tuberculosis (TB) patients, VTP values followed the pattern: active TB > latent TB > normal controls. VTP values were greater in clinically apparent than in presymptomatic malaria. VTP correlated negatively with the cardiac index of left ventricular ejection fraction (LVEF). In chronic obstructive pulmonary disease (COPD), VTP showed a negative correlation with forced expiratory volume in the first second (FEV1). VTP values increased with H. pylori infection and were upregulated in atrophic gastritis caused by H. pylori infection. The genes and pathways whose expression perturbations correlated positively with VTP scores across diseases were mainly involved in the regulation of immune, metabolic, and cellular activities.

Conclusions

VTP is upregulated in the disease versus health status, and its upregulation is associated with disease progression and severity in various diseases. Thus, VTP has potential clinical implications for disease diagnosis and prognosis.

Interleukin-17, a salivary biomarker for COVID-19 severity

Objectives

T-helper 17 cell-mediated response and their effector IL-17 cytokine induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a major cause of COVID-19 disease severity and death. Therefore, the study aimed to determine if IL-17 level in saliva mirrors its circulatory level and hence can be used as a non-invasive biomarker for disease severity.

Methods

Interleukin-17 (IL-17) level was evaluated by ELISA in saliva and blood of 201 adult COVID-19 patients with different levels of severity. The IL-17 saliva level was also associated with COVID-19 disease severity, and need for mechanical ventilation and/or death within 29 days after admission of severe COVID-19 patients.

Results

We found that IL-17 level in saliva of COVID-19 patients reflected its circulatory level. High IL-17 level in saliva was associated with COVID-19 severity (P<0.001), need for mechanical ventilation (P = 0.002), and/or death by 29 days (P = 0.002), after adjusting for patients’ demographics, comorbidity, and COVID-19 serum severity markers such as D-Dimer, C-reactive protein, and ferritin.

Conclusion

We propose that saliva IL-17 level could be used as a biomarker to identify patients at risk of developing severe COVID-19.

Quantitative proteomic analysis of SARS-CoV-2 infection of primary human airway ciliated cells and lung epithelial cells demonstrates the effectiveness of SARS-CoV-2 innate immune evasion

Background: Quantitative proteomics is able to provide a comprehensive, unbiased description of changes to cells caused by viral infection, but interpretation may be complicated by differential changes in infected and uninfected 'bystander' cells, or the use of non-physiological cellular models. Methods: In this paper, we use fluorescence-activated cell sorting (FACS) and quantitative proteomics to analyse cell-autonomous changes caused by authentic SARS-CoV-2 infection of respiratory epithelial cells, the main target of viral infection in vivo. First, we determine the relative abundance of proteins in primary human airway epithelial cells differentiated at the air-liquid interface (basal, secretory and ciliated cells). Next, we specifically characterise changes caused by SARS-CoV-2 infection of ciliated cells. Finally, we compare temporal proteomic changes in infected and uninfected 'bystander' Calu-3 lung epithelial cells and compare infection with B.29 and B.1.1.7 (Alpha) variants. Results: Amongst 5,709 quantified proteins in primary human airway ciliated cells, the abundance of 226 changed significantly in the presence of SARS-CoV-2 infection (q <0.05 and >1.5-fold). Notably, viral replication proceeded without inducing a type-I interferon response. Amongst 6,996 quantified proteins in Calu-3 cells, the abundance of 645 proteins changed significantly in the presence of SARS-CoV-2 infection (q < 0.05 and > 1.5-fold). In contrast to the primary cell model, a clear type I interferon (IFN) response was observed. Nonetheless, induction of IFN-inducible proteins was markedly attenuated in infected cells, compared with uninfected 'bystander' cells. Infection with B.29 and B.1.1.7 (Alpha) variants gave similar results. Conclusions: Taken together, our data provide a detailed proteomic map of changes in SARS-CoV-2-infected respiratory epithelial cells in two widely used, physiologically relevant models of infection. As well as identifying dysregulated cellular proteins and processes, the effectiveness of strategies employed by SARS-CoV-2 to avoid the type I IFN response is illustrated in both models.