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

Identification of biomarkers and pathways for the SARS-CoV-2 infections in obstructive sleep apnea patients based on machine learning and proteomic analysis

BACKGROUND

The prevalence of obstructive sleep apnea (OSA) was found to be higher in individuals following COVID-19 infection. However, the intricate mechanisms that underscore this concomitance remain partially elucidated. The aim of this study was to delve deeper into the molecular mechanisms that underpin this comorbidity.

METHODS

We acquired gene expression profiles for COVID-19 (GSE157103) and OSA (GSE75097) from the Gene Expression Omnibus (GEO) database. Upon identifying shared feature genes between OSA and COVID-19 utilizing LASSO, Random forest and Support vector machines algorithms, we advanced to functional annotation, analysis of protein-protein interaction networks, module construction, and identification of pivotal genes. Furthermore, we established regulatory networks encompassing transcription factor (TF)-gene and TF-miRNA interactions, and searched for promising drug targets. Subsequently, the expression levels of pivotal genes were validated through proteomics data from COVID-19 cases.

RESULTS

Fourteen feature genes shared between OSA and COVID-19 were selected for further investigation. Through functional annotation, it was indicated that metabolic pathways play a role in the pathogenesis of both disorders. Subsequently, employing the cytoHubba plugin, ten hub genes were recognized, namely TP53, CCND1, MDM2, RB1, HIF1A, EP300, STAT3, CDK2, HSP90AA1, and PPARG. The finding of proteomics unveiled a substantial augmentation in the expression level of HSP90AA1 in COVID-19 patient samples, especially in severe conditions.

CONCLUSIONS

Our investigation illuminate a mutual pathogenic mechanism that underlies both OSA and COVID-19, which may provide novel perspectives for future investigations into the underlying mechanisms.

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.

Analysis of blood and nasal epithelial transcriptomes to identify mechanisms associated with control of SARS-CoV-2 viral load in the upper respiratory tract

OBJECTIVES

The amount of SARS-CoV-2 detected in the upper respiratory tract (URT viral load) is a key driver of transmission of infection. Current evidence suggests that mechanisms constraining URT viral load are different from those controlling lower respiratory tract viral load and disease severity. Understanding such mechanisms may help to develop treatments and vaccine strategies to reduce transmission. Combining mathematical modelling of URT viral load dynamics with transcriptome analyses we aimed to identify mechanisms controlling URT viral load.

METHODS

COVID-19 patients were recruited in Spain during the first wave of the pandemic. RNA sequencing of peripheral blood and targeted NanoString nCounter transcriptome analysis of nasal epithelium were performed and gene expression analysed in relation to paired URT viral load samples collected within 15 days of symptom onset. Proportions of major immune cells in blood were estimated from transcriptional data using computational differential estimation. Weighted correlation network analysis (adjusted for cell proportions) and fixed transcriptional repertoire analysis were used to identify associations with URT viral load, quantified as standard deviations (z-scores) from an expected trajectory over time.

RESULTS

Eighty-two subjects (50% female, median age 54 years (range 3-73)) with COVID-19 were recruited. Paired URT viral load samples were available for 16 blood transcriptome samples, and 17 respiratory epithelial transcriptome samples. Natural Killer (NK) cells were the only blood cell type significantly correlated with URT viral load z-scores (r = -0.62, P = 0.010). Twenty-four blood gene expression modules were significantly correlated with URT viral load z-score, the most significant being a module of genes connected around IFNA14 (Interferon Alpha-14) expression (r = -0.60, P = 1e-10). In fixed repertoire analysis, prostanoid-related gene expression was significantly associated with higher viral load. In nasal epithelium, only GNLY (granulysin) gene expression showed significant negative correlation with viral load.

CONCLUSIONS

Correlations between the transcriptional host response and inter-individual variations in SARS-CoV-2 URT viral load, revealed many molecular mechanisms plausibly favouring or constraining viral replication. Existing evidence corroborates many of these mechanisms, including likely roles for NK cells, granulysin, prostanoids and interferon alpha-14. Inhibition of prostanoid production and administration of interferon alpha-14 may be attractive transmission-blocking interventions.

Ascites-Derived Organoids to Depict Platinum Resistance in Gynaecological Serous Carcinomas

Gynaecological serous carcinomas (GSCs) constitute a distinctive entity among female tumours characterised by a very poor prognosis. In addition to late-stage diagnosis and a high rate of recurrent disease associated with massive peritoneal carcinomatosis, the systematic acquisition of resistance to first-line chemotherapy based on platinum determines the unfavourable outcome of GSC patients. To explore the molecular mechanisms associated with platinum resistance, we generated patient-derived organoids (PDOs) from liquid biopsies of GSC patients. PDOs are emerging as a relevant preclinical model system to assist in clinical decision making, mainly from tumoural tissue and particularly for personalised therapeutic options. To approach platinum resistance in a GSC context, proficient PDOs were generated from the ascitic fluid of ovarian, primary peritoneal and uterine serous carcinoma patients in platinum-sensitive and platinum-resistant clinical settings from the uterine aspirate of a uterine serous carcinoma patient, and we also induced platinum resistance in vitro in a representative platinum-sensitive PDO. Histological and immunofluorescent characterisation of these ascites-derived organoids showed resemblance to the corresponding original tumours, and assessment of platinum sensitivity in these preclinical models replicated the clinical setting of the corresponding GSC patients. Differential gene expression profiling of a panel of 770 genes representing major canonical cancer pathways, comparing platinum-sensitive and platinum-resistant PDOs, revealed cellular response to DNA damage stimulus as the principal biological process associated with the acquisition of resistance to the first-line therapy for GSC. Additionally, candidate genes involved in regulation of cell adhesion, cell cycles, and transcription emerged from this proof-of-concept study. In conclusion, we describe the generation of PDOs from liquid biopsies in the context of gynaecological serous carcinomas to explore the molecular determinants of platinum resistance.

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

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

The immune mechanism of the nasal epithelium in COVID-19-related olfactory dysfunction

During the first waves of the coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, olfactory dysfunction (OD) was reported as a frequent clinical sign. The nasal epithelium is one of the front-line protections against viral infections, and the immune responses of the nasal mucosa may be associated with OD. Two mechanisms underlying OD occurrence in COVID-19 have been proposed: the infection of sustentacular cells and the inflammatory reaction of the nasal epithelium. The former triggers OD and the latter likely prolongs OD. These two alternative mechanisms may act in parallel; the infection of sustentacular cells is more important for OD occurrence because sustentacular cells are more likely to be the entry point of SARS-CoV-2 than olfactory neurons and more susceptible to early injury. Furthermore, sustentacular cells abundantly express transmembrane protease, serine 2 (TMPRSS2) and play a major role in the olfactory epithelium. OD occurrence in COVID-19 has revealed crucial roles of sustentacular cells. This review aims to elucidate how immune responses of the nasal epithelium contribute to COVID-19-related OD. Understanding the underlying immune mechanisms of the nasal epithelium in OD may aid in the development of improved medical treatments for COVID-19-related OD.

Saline nasal irrigation and gargling in COVID-19: a multidisciplinary review of effects on viral load, mucosal dynamics, and patient outcomes

With unrelenting SARS-CoV-2 variants, additional COVID-19 mitigation strategies are needed. Oral and nasal saline irrigation (SI) is a traditional approach for respiratory infections/diseases. As a multidisciplinary network with expertise/experience with saline, we conducted a narrative review to examine mechanisms of action and clinical outcomes associated with nasal SI, gargling, spray, or nebulization in COVID-19. SI was found to reduce SARS-CoV-2 nasopharyngeal loads and hasten viral clearance. Other mechanisms may involve inhibition of viral replication, bioaerosol reduction, improved mucociliary clearance, modulation of ENaC, and neutrophil responses. Prophylaxis was documented adjunctive to personal protective equipment. COVID-19 patients experienced significant symptom relief, while overall data suggest lower hospitalization risk. We found no harm and hence recommend SI use, as safe, inexpensive, and easy-to-use hygiene measure, complementary to hand washing or mask-wearing. In view of mainly small studies, large well-controlled or surveillance studies can help to further validate the outcomes and to implement its use.

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.

Association of programmed cell death 1 (PD-1) gene polymorphism (rs10204525) with COVID-19 severity and mortality: A case-control study in the Iranian population

BACKGROUND

Programmed cell death 1 (PD-1), as a negative immune regulator, regulates the activation of T cells and maintains the immune system's homeostasis. Previous studies suggest that the effective immune response against COVID-19 contributes to the outcome of the disease. The present study aims to evaluate whether the PD-1 rs10204525 polymorphism is associated with PDCD-1 expression and COVID-19 severity and mortality in the Iranian population.

METHODS

The PD-1 rs10204525 was genotyped in 810 COVID-19 patients and 164 healthy individuals as a control group using Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Moreover, we assessed the expression of PDCD-1 in peripheral blood nuclear cells by real-time PCR.

RESULTS

Regarding disease severity and mortality, no significant differences were detected between study groups in alleles and genotypes frequency distribution under different inheritance models. We found that the expression of PDCD-1 was significantly lower in COVID-19 patients with AG and GG genotypes than in the control group. Regarding disease severity, mRNA levels of PDCD-1 were significantly lower in moderate and critical patients carrying AG genotype than in control (P = 0.005 and P = 0.002, respectively) and mild (P = 0.014 and P = 0.005, respectively) individuals. Additionally, the severe and critical patients with GG genotype displayed a significantly lower level of PDCD-1 compared with the control (P = 0.002 and P < 0.001, respectively), mild (P = 0.004 and P < 0.001, respectively), and moderate (P = 0.014 and P < 0.001, respectively) ones. Regarding disease mortality, the expression of PDCD-1 was significantly lower in non-survivor COVID-19 patients with GG genotype than in survivors.

CONCLUSION

Considering the lack of significant differences in PDCD-1 expression in different genotypes in the control group, lower expression of PDCD-1 in COVID-19 patients carrying the G allele suggests the impact of this single-nucleotide polymorphism on the transcriptional activity of PD-1.

Using system biology and bioinformatics to identify the influences of COVID-19 co-infection with influenza virus on COPD

Coronavirus disease 2019 (COVID-19) has speedily increased mortality globally. Although they are risk factors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), less is known about the common molecular mechanisms behind COVID-19, influenza virus A (IAV), and chronic obstructive pulmonary disease (COPD). This research used bioinformatics and systems biology to find possible medications for treating COVID-19, IAV, and COPD via identifying differentially expressed genes (DEGs) from gene expression datasets (GSE171110, GSE76925, GSE106986, and GSE185576). A total of 78 DEGs were subjected to functional enrichment, pathway analysis, protein-protein interaction (PPI) network construct, hub gene extraction, and other potentially relevant disorders. Then, DEGs were discovered in networks including transcription factor (TF)-gene connections, protein-drug interactions, and DEG-microRNA (miRNA) coregulatory networks by using NetworkAnalyst. The top 12 hub genes were MPO, MMP9, CD8A, HP, ELANE, CD5, CR2, PLA2G7, PIK3R1, SLAMF1, PEX3, and TNFRSF17. We found that 44 TFs-genes, as well as 118 miRNAs, are directly linked to hub genes. Additionally, we searched the Drug Signatures Database (DSigDB) and identified 10 drugs that could potentially treat COVID-19, IAV, and COPD. Therefore, we evaluated the top 12 hub genes that could be promising DEGs for targeted therapy for SARS-CoV-2 and identified several prospective medications that may benefit COPD patients with COVID-19 and IAV co-infection.

Immunovirological and environmental screening reveals actionable risk factors for fatal COVID-19 during post-vaccination nursing home outbreaks

Coronavirus Disease 2019 (COVID-19) vaccination has resulted in excellent protection against fatal disease, including in older adults. However, risk factors for post-vaccination fatal COVID-19 are largely unknown. We comprehensively studied three large nursing home outbreaks (20-35% fatal cases among residents) by combining severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) aerosol monitoring, whole-genome phylogenetic analysis and immunovirological profiling of nasal mucosa by digital nCounter transcriptomics. Phylogenetic investigations indicated that each outbreak stemmed from a single introduction event, although with different variants (Delta, Gamma and Mu). SARS-CoV-2 was detected in aerosol samples up to 52 d after the initial infection. Combining demographic, immune and viral parameters, the best predictive models for mortality comprised IFNB1 or age, viral ORF7a and ACE2 receptor transcripts. Comparison with published pre-vaccine fatal COVID-19 transcriptomic and genomic signatures uncovered a unique IRF3 low/IRF7 high immune signature in post-vaccine fatal COVID-19 outbreaks. A multi-layered strategy, including environmental sampling, immunomonitoring and early antiviral therapy, should be considered to prevent post-vaccination COVID-19 mortality in nursing homes.

DTSEA: A network-based drug target set enrichment analysis method for drug repurposing against COVID-19

The Coronavirus Disease 2019 (COVID-19) pandemic is still wreaking havoc worldwide. Therefore, the urgent need for efficient treatments pushes researchers and clinicians into screening effective drugs. Drug repurposing may be a promising and time-saving strategy to identify potential drugs against this disease. Here, we developed a novel computational approach, named Drug Target Set Enrichment Analysis (DTSEA), to identify potent drugs against COVID-19. DTSEA first mapped the disease-related genes into a gene functional interaction network, and then it used a network propagation algorithm to rank all genes in the network by calculating the network proximity of genes to disease-related genes. Finally, an enrichment analysis was performed on drug target sets to prioritize disease-candidate drugs. It was shown that the top three drugs predicted by DTSEA, including Ataluren, Carfilzomib, and Aripiprazole, were significantly enriched in the immune response pathways indicating the potential for use as promising COVID-19 inhibitors. In addition to these drugs, DTSEA also identified several drugs (such as Remdesivir and Olumiant), which have obtained emergency use authorization (EUA) for COVID-19. These results indicated that DTSEA could effectively identify the candidate drugs for COVID-19, which will help to accelerate the development of drugs for COVID-19. We then performed several validations to ensure the reliability and validity of DTSEA, including topological analysis, robustness analysis, and prediction consistency. Collectively, DTSEA successfully predicted candidate drugs against COVID-19 with high accuracy and reliability, thus making it a formidable tool to identify potential drugs for a specific disease and facilitate further investigation.

Infection of primary nasal epithelial cells differentiates among lethal and seasonal human coronaviruses

The nasal epithelium is the initial entry portal and primary barrier to infection by all human coronaviruses (HCoVs). We utilize primary human nasal epithelial cells grown at air-liquid interface, which recapitulate the heterogeneous cellular population as well as mucociliary clearance functions of the in vivo nasal epithelium, to compare lethal [Severe acute respiratory syndrome (SARS)-CoV-2 and Middle East respiratory syndrome-CoV (MERS-CoV)] and seasonal (HCoV-NL63 and HCoV-229E) HCoVs. All four HCoVs replicate productively in nasal cultures, though replication is differentially modulated by temperature. Infections conducted at 33 °C vs. 37 °C (reflective of temperatures in the upper and lower airway, respectively) revealed that replication of both seasonal HCoVs (HCoV-NL63 and -229E) is significantly attenuated at 37 °C. In contrast, SARS-CoV-2 and MERS-CoV replicate at both temperatures, though SARS-CoV-2 replication is enhanced at 33 °C late in infection. These HCoVs also diverge significantly in terms of cytotoxicity induced following infection, as the seasonal HCoVs as well as SARS-CoV-2 cause cellular cytotoxicity as well as epithelial barrier disruption, while MERS-CoV does not. Treatment of nasal cultures with type 2 cytokine IL-13 to mimic asthmatic airways differentially impacts HCoV receptor availability as well as replication. MERS-CoV receptor DPP4 expression increases with IL-13 treatment, whereas ACE2, the receptor used by SARS-CoV-2 and HCoV-NL63, is down-regulated. IL-13 treatment enhances MERS-CoV and HCoV-229E replication but reduces that of SARS-CoV-2 and HCoV-NL63, reflecting the impact of IL-13 on HCoV receptor availability. This study highlights diversity among HCoVs during infection of the nasal epithelium, which is likely to influence downstream infection outcomes such as disease severity and transmissibility.

Molecular modeling of C1-inhibitor as SARS-CoV-2 target identified from the immune signatures of multiple tissues: An integrated bioinformatics study

The expeditious transmission of the severe acute respiratory coronavirus 2 (SARS-CoV-2), a strain of COVID-19, crumbled the global economic strength and caused a veritable collapse in health infrastructure. The molecular modeling of the novel coronavirus research sounds promising and equips more evidence about the pragmatic therapeutic options. This article proposes a machine-learning framework for identifying potential COVID-19 transcriptomic signatures. The transcriptomics data contains immune-related genes collected from multiple tissues (blood, nasal, and buccal) with accession number: GSE183071. Extensive bioinformatics work was carried out to identify the potential candidate markers, including differential expression analysis, protein interactions, gene ontology, and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment studies. The overlapping investigation found SERPING1, the gene that encodes a glycosylated plasma protein C1-INH, in all three datasets. Furthermore, the immuno-informatics study was conducted on the C1-INH protein. 5DU3, the protein identifier of C1-INH, was fetched to identify the antigenicity, major histocompatibility (MHC) Class I and II binding epitopes, allergenicity, toxicity, and immunogenicity. The screening of peptides satisfying the vaccine-design criteria based on the metrics mentioned above is performed. The drug-gene interaction study reported that Rhucin is strongly associated with SERPING1. HSIC-Lasso (Hilbert-Schmidt independence criterion-least absolute shrinkage and selection operator), a model-free biomarker selection technique, was employed to identify the genes having a nonlinear relationship with the target class. The gene subset is trained with supervised machine learning models by a leave-one-out cross-validation method. Explainable artificial intelligence techniques perform the model interpretation analysis.

Sex-biased expression of the TLR7 gene in severe COVID-19 patients: Insights from transcriptomics and epigenomics

There is abundant epidemiological data indicating that the incidence of severe cases of coronavirus disease (COVID-19) is significantly higher in males than females worldwide. Moreover, genetic variation at the X-chromosome linked TLR7 gene has been associated with COVID-19 severity. It has been suggested that the sex-biased incidence of COVID-19 might be related to the fact that TLR7 escapes X-chromosome inactivation during early embryogenesis in females, thus encoding a doble dose of its gene product compared to males. We analyzed TLR7 expression in two acute phase cohorts of COVID-19 patients that used two different technological platforms, one of them in a multi-tissue context including saliva, nasal, and blood samples, and a third cohort that included different post-infection timepoints of long-COVID-19 patients. We additionally explored methylation patterns of TLR7 using epigenomic data from an independent cohort of COVID-19 patients stratified by severity and sex. In line with genome-wide association studies, we provide supportive evidence indicating that TLR7 has altered CpG methylation patterns and it is consistently downregulated in males compared to females in the most severe cases of COVID-19.

The environment, epidemics, and human health

In this editorial piece, the Editors of the Virtual Special Issue (VSI) "The environment, epidemics, and human health" comment on the papers accepted for publication, which were selected after peer-reviewing among all those manuscripts submitted to the Special Issue. In view of the title of the VSI, it is clear that its aim goes beyond the COVID-19 pandemic, trying to explore relations among environmental aspects, any kind of epidemics, and human health. However, COVID-19 is still hitting as a global and current main issue, causing that manuscripts dealing with this disease and the SARS-CoV-2 virus are of high relevance in the whole set of research papers published.

A Timeframe for SARS-CoV-2 Genomes: A Proof of Concept for Postmortem Interval Estimations

Establishing the timeframe when a particular virus was circulating in a population could be useful in several areas of biomedical research, including microbiology and legal medicine. Using simulations, we demonstrate that the circulation timeframe of an unknown SARS-CoV-2 genome in a population (hereafter, estimated time of a queried genome [QG]; tE-QG) can be easily predicted using a phylogenetic model based on a robust reference genome database of the virus, and information on their sampling dates. We evaluate several phylogeny-based approaches, including modeling evolutionary (substitution) rates of the SARS-CoV-2 genome (~10-3 substitutions/nucleotide/year) and the mutational (substitutions) differences separating the QGs from the reference genomes (RGs) in the database. Owing to the mutational characteristics of the virus, the present Viral Molecular Clock Dating (VMCD) method covers timeframes going backwards from about a month in the past. The method has very low errors associated to the tE-QG estimates and narrow intervals of tE-QG, both ranging from a few days to a few weeks regardless of the mathematical model used. The SARS-CoV-2 model represents a proof of concept that can be extrapolated to any other microorganism, provided that a robust genome sequence database is available. Besides obvious applications in epidemiology and microbiology investigations, there are several contexts in forensic casework where estimating tE-QG could be useful, including estimation of the postmortem intervals (PMI) and the dating of samples stored in hospital settings.

Infection of primary nasal epithelial cells differentiates among lethal and seasonal human coronaviruses

The nasal epithelium is the initial entry portal and primary barrier to infection by all human coronaviruses (HCoVs). We utilize primary nasal epithelial cells grown at air-liquid interface, which recapitulate the heterogeneous cellular population as well as mucociliary clearance functions of the in vivo nasal epithelium, to compare lethal (SARS-CoV-2 and MERS-CoV) and seasonal (HCoV-NL63 and HCoV-229E) HCoVs. All four HCoVs replicate productively in nasal cultures but diverge significantly in terms of cytotoxicity induced following infection, as the seasonal HCoVs as well as SARS-CoV-2 cause cellular cytotoxicity as well as epithelial barrier disruption, while MERS-CoV does not. Treatment of nasal cultures with type 2 cytokine IL-13 to mimic asthmatic airways differentially impacts HCoV replication, enhancing MERS-CoV replication but reducing that of SARS-CoV-2 and HCoV-NL63. This study highlights diversity among HCoVs during infection of the nasal epithelium, which is likely to influence downstream infection outcomes such as disease severity and transmissibility.

Pathogenic Mechanism and Multi-omics Analysis of Oral Manifestations in COVID-19

Coronavirus disease 2019 (COVID-19) is a respiratory infectious disease that seriously threatens human life. The clinical manifestations of severe COVID-19 include acute respiratory distress syndrome and multiple organ failure. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of COVID-19, spreads through contaminated droplets. SARS-CoV-2 particles have been detected in the saliva of COVID-19 patients, implying that the virus can infect and damage the oral cavity. The oral manifestations of COVID-19 include xerostomia and gustatory dysfunction. Numerous studies showed that the four structural proteins of SARS-CoV-2 are its potential pathogenic factors, especially the S protein, which binds to human ACE2 receptors facilitating the entry of the virus into the host cells. Usually, upon entry into the host cell, a pathogen triggers the host’s immune response. However, a mount of multi-omics and immunological analyses revealed that COVID-19 is caused by immune dysregulation. A decrease in the number and phenotypes of immune cells, IFN-1 production and excessive release of certain cytokines have also been reported. In conclusion, this review summarizes the oral manifestations of COVID-19 and multi-omics analysis of SARS-CoV-2 infection.

Classification and severity progression measure of COVID-19 patients using pairs of multi-omic factors

Early detection and effective treatment of severe COVID-19 patients remain two major challenges during the current pandemic. Analysis of molecular changes in blood samples of severe patients is one of the promising approaches to this problem. From thousands of proteomic, metabolomic, lipidomic, and transcriptomic biomarkers selected in other research, we identify several pairs of biomarkers that after additional nonlinear spline transformation are highly effective in classifying and predicting severe COVID-19 cases. The performance of these pairs is evaluated in-sample, in a cross-validation exercise, and in an out-of-sample analysis on two independent datasets. We further improve our classifier by identifying complementary pairs using hierarchical clustering. In a result, we achieve 96-98% AUC on the validation data. Our findings can help medical experts to identify small groups of biomarkers that after nonlinear transformation can be used to construct a cost-effective test for patient screening and prediction of severity progression.

Innate and Adaptive Immune Responses in the Upper Respiratory Tract and the Infectivity of SARS-CoV-2

Increasing evidence shows the nasal epithelium to be the initial site of SARS-CoV-2 infection, and that early and effective immune responses in the upper respiratory tract (URT) limit and eliminate the infection in the URT, thereby preventing infection of the lower respiratory tract and the development of severe COVID-19. SARS-CoV-2 interferes with innate immunity signaling and evolves mutants that can reduce antibody-mediated immunity in the URT. Recent genetic and immunological advances in understanding innate immunity to SARS-CoV-2 in the URT, and the ability of prior infections as well as currently available injectable and potential intranasal COVID-19 vaccines to generate anamnestic adaptive immunity in the URT, are reviewed. It is suggested that the more detailed investigation of URT immune responses to all types of COVID-19 vaccines, and the development of safe and effective COVID-19 vaccines for intranasal administration, are important needs.