Expansion of Single Cell Transcriptomics Data of SARS-CoV Infection in Human Bronchial Epithelial Cells to COVID-19

Impact of IL-6 rs1800795 and IL-17A rs2275913 gene polymorphisms on the COVID-19 prognosis and susceptibility in a sample of Iranian patients

BACKGROUND

From asymptomatic to acute and life-threatening pulmonary infection, the clinical manifestations of COVID-19 are highly variable. Interleukin (IL)-6 and IL-17A are key drivers of hyper inflammation status in COVID-19, and their elevated levels are hallmarks of the infection progression. To explore whether prognosis and susceptibility to COVID-19 are linked to IL-6 rs1800795 and IL-17A rs2275913, these single-nucleotide polymorphisms (SNPs) were assessed in a sample of Iranian COVID-19 patients.

METHODS

This study enrolled two hundred and eighty COVID-19 patients (140 non-severe and 140 severe). Genotyping for IL-6 rs1800795 and IL-17A rs2275913 was performed using tetra primer-amplification refractory mutation system-polymerase chain reaction (tetra-ARMS-PCR). IL-6 and IL-17A circulating levels were measured using enzyme-linked immunosorbent assay (ELISA). Also, mortality predictors of COVID-19 were investigated.

RESULTS

The rs1800795 GG genotype (78/140 (55.7 %)) and G allele (205/280 (73.2 %)) were significantly associated with a positive risk of COVID-19 severe infection (OR = 2.19, 95 %CI: 1.35-3.54, P =.006 and OR = 1.79, 95 %CI: 1.25-2.56, P <.001, respectively). Also, rs1800795 GG genotype was significantly linked to disease mortality (OR = 1.95, 95 %CI: 1.06-3.61, P =.04). The rs2275913 GA genotype was protective against severe COVID-19 (OR = 0.5, 95 %CI: 0.31--0.80, P =.012). However, the present study did not reveal any significant link between rs2275913 genotypes with disease mortality. INR ≥ 1.2 (OR = 2.19, 95 %CI: 1.61-3.78, P =.007), D-dimer ≥ 565.5 ng/mL (OR = 3.12, 95 %CI: 1.27-5.68, P =.019), respiratory rate ≥ 29 (OR = 1.19, 95 %CI: 1.12-1.28, P =.001), IL-6 serum concentration ≥ 28.5 pg/mL (OR = 1.97, 95 %CI: 1.942-2.06, P =.013), and IL-6 rs1800795 GG genotype (OR = 1.95, 95 %CI: 1.06-3.61, P =.04) were predictive of COVID-19 mortality.

CONCLUSION

The rs1800795 GG genotype and G allele were associated with disease severity, and INR, D-dimer, respiratory rate, IL-6 serum concentration, and IL-6 rs1800795 GG genotype were predictive of COVID-19 mortality.

Single-Cell RNA Sequencing Reveals Alterations in Patient Immune Cells with Pulmonary Long COVID-19 Complications

Since the emergence of the COVID-19 pandemic, the effects of SARS-CoV-2 have been extensively researched. While much is already known about the acute phase of the infection, increasing attention has turned to the prolonged symptoms experienced by a subset of individuals, commonly referred to as long COVID-19 patients. This study aims to delve deeper into the immune landscape of patients with prolonged symptoms by implementing single-cell mRNA analysis. A 71-year-old COVID-19 patient presenting with persistent viral pneumonia was recruited, and peripheral blood samples were taken at 3 and 2 years post-acute infection onset. Patients and control peripheral blood mononuclear cells (PBMCs) were isolated and single-cell sequenced. Immune cell population identification was carried out using the ScType script. Three months post-COVID-19 patients' PBMCs contained a significantly larger immature neutrophil population compared to 2-year and control samples. However, the neutrophil balance shifted towards a more mature profile after 18 months. In addition, a notable increase in the CD8+ NKT-like cells could be observed in the 3-month patient sample as compared to the later one and control. The subsequent change in these cell populations over time may be an indicator of an ongoing failure to clear the SARS-CoV-2 infection and, thus, lead to chronic COVID-19 complications.

High-sensitivity profiling of SARS-CoV-2 noncoding region-host protein interactome reveals the potential regulatory role of negative-sense viral RNA

A deep understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-host interactions is crucial to developing effective therapeutics and addressing the threat of emerging coronaviruses. The role of noncoding regions of viral RNA (ncrRNAs) has yet to be systematically scrutinized. We developed a method using MS2 affinity purification coupled with liquid chromatography-mass spectrometry and designed a diverse set of bait ncrRNAs to systematically map the interactome of SARS-CoV-2 ncrRNA in Calu-3, Huh7, and HEK293T cells. Integration of the results defined the core ncrRNA-host protein interactomes among cell lines. The 5' UTR interactome is enriched with proteins in the small nuclear ribonucleoproteins family and is a target for the regulation of viral replication and transcription. The 3' UTR interactome is enriched with proteins involved in the stress granules and heterogeneous nuclear ribonucleoproteins family. Intriguingly, compared with the positive-sense ncrRNAs, the negative-sense ncrRNAs, especially the negative-sense of 3' UTR, interacted with a large array of host proteins across all cell lines. These proteins are involved in the regulation of the viral production process, host cell apoptosis, and immune response. Taken together, our study depicts the comprehensive landscape of the SARS-CoV-2 ncrRNA-host protein interactome and unveils the potential regulatory role of the negative-sense ncrRNAs, providing a new perspective on virus-host interactions and the design of future therapeutics. Given the highly conserved nature of UTRs in positive-strand viruses, the regulatory role of negative-sense ncrRNAs should not be exclusive to SARS-CoV-2. IMPORTANCE Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19, a pandemic affecting millions of lives. During replication and transcription, noncoding regions of the viral RNA (ncrRNAs) may play an important role in the virus-host interactions. Understanding which and how these ncrRNAs interact with host proteins is crucial for understanding the mechanism of SARS-CoV-2 pathogenesis. We developed the MS2 affinity purification coupled with liquid chromatography-mass spectrometry method and designed a diverse set of ncrRNAs to identify the SARS-CoV-2 ncrRNA interactome comprehensively in different cell lines and found that the 5' UTR binds to proteins involved in U1 small nuclear ribonucleoprotein, while the 3' UTR interacts with proteins involved in stress granules and the heterogeneous nuclear ribonucleoprotein family. Interestingly, negative-sense ncrRNAs showed interactions with a large number of diverse host proteins, indicating a crucial role in infection. The results demonstrate that ncrRNAs could serve diverse regulatory functions.

Using Machine Learning Methods in Identifying Genes Associated with COVID-19 in Cardiomyocytes and Cardiac Vascular Endothelial Cells

Corona Virus Disease 2019 (COVID-19) not only causes respiratory system damage, but also imposes strain on the cardiovascular system. Vascular endothelial cells and cardiomyocytes play an important role in cardiac function. The aberrant expression of genes in vascular endothelial cells and cardiomyocytes can lead to cardiovascular diseases. In this study, we sought to explain the influence of respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on the gene expression levels of vascular endothelial cells and cardiomyocytes. We designed an advanced machine learning-based workflow to analyze the gene expression profile data of vascular endothelial cells and cardiomyocytes from patients with COVID-19 and healthy controls. An incremental feature selection method with a decision tree was used in building efficient classifiers and summarizing quantitative classification genes and rules. Some key genes, such as MALAT1, MT-CO1, and CD36, were extracted, which exert important effects on cardiac function, from the gene expression matrix of 104,182 cardiomyocytes, including 12,007 cells from patients with COVID-19 and 92,175 cells from healthy controls, and 22,438 vascular endothelial cells, including 10,812 cells from patients with COVID-19 and 11,626 cells from healthy controls. The findings reported in this study may provide insights into the effect of COVID-19 on cardiac cells and further explain the pathogenesis of COVID-19, and they may facilitate the identification of potential therapeutic targets.

Comparative susceptibility of SARS-CoV-2, SARS-CoV, and MERS-CoV across mammals

Exploring wild reservoirs of pathogenic viruses is critical for their long-term control and for predicting future pandemic scenarios. Here, a comparative in vitro infection analysis was first performed on 83 cell cultures derived from 55 mammalian species using pseudotyped viruses bearing S proteins from SARS-CoV-2, SARS-CoV, and MERS-CoV. Cell cultures from Thomas's horseshoe bats, king horseshoe bats, green monkeys, and ferrets were found to be highly susceptible to SARS-CoV-2, SARS-CoV, and MERS-CoV pseudotyped viruses. Moreover, five variants (del69-70, D80Y, S98F, T572I, and Q675H), that beside spike receptor-binding domain can significantly alter the host tropism of SARS-CoV-2. An examination of phylogenetic signals of transduction rates revealed that closely related taxa generally have similar susceptibility to MERS-CoV but not to SARS-CoV and SARS-CoV-2 pseudotyped viruses. Additionally, we discovered that the expression of 95 genes, e.g., PZDK1 and APOBEC3, were commonly associated with the transduction rates of SARS-CoV, MERS-CoV, and SARS-CoV-2 pseudotyped viruses. This study provides basic documentation of the susceptibility, variants, and molecules that underlie the cross-species transmission of these coronaviruses.

Bioinformatics-based investigation on the genetic influence between SARS-CoV-2 infections and idiopathic pulmonary fibrosis (IPF) diseases, and drug repurposing

Some recent studies showed that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and idiopathic pulmonary fibrosis (IPF) disease might stimulate each other through the shared genes. Therefore, in this study, an attempt was made to explore common genomic biomarkers for SARS-CoV-2 infections and IPF disease highlighting their functions, pathways, regulators and associated drug molecules. At first, we identified 32 statistically significant common differentially expressed genes (cDEGs) between disease (SARS-CoV-2 and IPF) and control samples of RNA-Seq profiles by using a statistical r-package (edgeR). Then we detected 10 cDEGs (CXCR4, TNFAIP3, VCAM1, NLRP3, TNFAIP6, SELE, MX2, IRF4, UBD and CH25H) out of 32 as the common hub genes (cHubGs) by the protein-protein interaction (PPI) network analysis. The cHubGs regulatory network analysis detected few key TFs-proteins and miRNAs as the transcriptional and post-transcriptional regulators of cHubGs. The cDEGs-set enrichment analysis identified some crucial SARS-CoV-2 and IPF causing common molecular mechanisms including biological processes, molecular functions, cellular components and signaling pathways. Then, we suggested the cHubGs-guided top-ranked 10 candidate drug molecules (Tegobuvir, Nilotinib, Digoxin, Proscillaridin, Simeprevir, Sorafenib, Torin 2, Rapamycin, Vancomycin and Hesperidin) for the treatment against SARS-CoV-2 infections with IFP diseases as comorbidity. Finally, we investigated the resistance performance of our proposed drug molecules compare to the already published molecules, against the state-of-the-art alternatives publicly available top-ranked independent receptors by molecular docking analysis. Molecular docking results suggested that our proposed drug molecules would be more effective compare to the already published drug molecules. Thus, the findings of this study might be played a vital role for diagnosis and therapies of SARS-CoV-2 infections with IPF disease as comorbidity risk.

Management, control, and decision making in unexpected recurrent venous thromboembolism in COVID-19: a case report

BACKGROUND

Coronavirus disease 2019 was spread worldwide, as a pandemic, from December 2019. Venous thromboembolism events can inflict patients with coronavirus disease 2019 during the hospitalization or convalescent period. Therefore, monitoring of these patients, in terms of venous thromboembolism events signs and symptoms, and timely management of antithrombotic agents are of great importance.

CASE REPORT

A 45-year-old Iranian man, who is the first author of this case report, was infected by severe acute respiratory syndrome coronavirus 2 and displayed the typical signs and symptoms of coronavirus disease 2019. Although reverse transcription polymerase chain reaction for coronavirus disease 2019, and specific immunoglobulin M and immunoglobulin G against severe acute respiratory syndrome coronavirus 2, were negative at first, chest computed tomography scan showed the characteristic pattern of lung involvement of a coronavirus disease 2019 infection including bilateral and multilobar ground-glass opacities. At that time, there were no signs or symptoms of deep-vein thrombosis or pulmonary thromboembolism, so these were not investigated. About 30 hours after hospital discharge, the patient presented back to the hospital with acute-onset chest pain. We instantly tested his blood for D-dimer, and sent him to take a Doppler sonography of his lower legs and a chest computed tomography angiography in search of pulmonary thromboembolism and deep-vein thrombosis. Although we could confirm pulmonary thromboembolism with computed tomography angiography in our patient, there were no signs or symptoms of venous thromboembolism in his lower legs, and color Doppler sonography of lower limbs was normal. So, the patient was treated with rivaroxaban as an antithrombotic agent. After some days, he was discharged in good condition. About 1 month later, he was referred to our hospital because of left lower limb edema. Although he was under antithrombotic therapy, color Doppler sonography of lower limbs revealed acute deep-vein thrombosis of the left leg. Hence, we decided to shift antithrombotic therapy from rivaroxaban to warfarin, as it is more potent than rivaroxaban in recurrent venous thromboembolism and when taking new oral anticoagulants. Unlike rivaroxaban, which needs no blood test to monitor its efficacy but has a warning for signs and symptoms of bleeding, warfarin therapy must be monitored carefully by regular blood tests for prothrombin time and international normalized ratio to maintain them in the therapeutic range. The patient was informed about the bleeding cautions, and required regular check of prothrombin time and international normalized ratio to maintain them in the proper and advised range of treatment (international normalized ratio therapeutic range 2-3).

CONCLUSION

In the case of unexpected recurrent venous thromboembolism in coronavirus disease 2019, especially when patients are taking rivaroxaban or other new oral anticoagulants, such drugs should be substituted by warfarin, with routine follow-up, to maintain the value of prothrombin time and international normalized ratio within the therapeutic range.

A multiscale mechanistic model of human dendritic cells for in-silico investigation of immune responses and novel therapeutics discovery

Dendritic cells (DCs) are professional antigen-presenting cells (APCs) with the unique ability to mediate inflammatory responses of the immune system. Given the critical role of DCs in shaping immunity, they present an attractive avenue as a therapeutic target to program the immune system and reverse immune disease disorders. To ensure appropriate immune response, DCs utilize intricate and complex molecular and cellular interactions that converge into a seamless phenotype. Computational models open novel frontiers in research by integrating large-scale interaction to interrogate the influence of complex biological behavior across scales. The ability to model large biological networks will likely pave the way to understanding any complex system in more approachable ways. We developed a logical and predictive model of DC function that integrates the heterogeneity of DCs population, APC function, and cell-cell interaction, spanning molecular to population levels. Our logical model consists of 281 components that connect environmental stimuli with various layers of the cell compartments, including the plasma membrane, cytoplasm, and nucleus to represent the dynamic processes within and outside the DC, such as signaling pathways and cell-cell interactions. We also provided three sample use cases to apply the model in the context of studying cell dynamics and disease environments. First, we characterized the DC response to Sars-CoV-2 and influenza co-infection by in-silico experiments and analyzed the activity level of 107 molecules that play a role in this co-infection. The second example presents simulations to predict the crosstalk between DCs and T cells in a cancer microenvironment. Finally, for the third example, we used the Kyoto Encyclopedia of Genes and Genomes enrichment analysis against the model's components to identify 45 diseases and 24 molecular pathways that the DC model can address. This study presents a resource to decode the complex dynamics underlying DC-derived APC communication and provides a platform for researchers to perform in-silico experiments on human DC for vaccine design, drug discovery, and immunotherapies.

An insight overview on COVID-19 mRNA vaccines: Advantageous, pharmacology, mechanism of action, and prospective considerations

The worldwide spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has urged scientists to present some novel vaccine platforms during this pandemic to provide a rather prolonged immunity against this respiratory viral infection. In spite of many campaigns formed against the administration of mRNA-based vaccines, those platforms were the most novel types, which helped us meet the global demand by developing protection against COVID-19 and reducing the development of severe forms of this respiratory viral infection. Some societies are worry about the COVID-19 mRNA vaccine administration and the potential risk of genetic integration of inoculated mRNA into the human genome. Although the efficacy and long-term safety of mRNA vaccines have not yet been fully clarified, obviously their application has switched the mortality and morbidity of the COVID-19 pandemic. This study describes the structural features and technologies used in producing of COVID-19 mRNA-based vaccines as the most influential factor in controlling this pandemic and a successful pattern for planning to produce other kind of genetic vaccines against infections or cancers.

Dose response relationship between D-dimer level and mortality in critically ill COVID-19 patients: a retrospective observational study

BACKGROUND

Coronavirus disease 2019 (COVID-19) is a global pandemic. Coagulopathy is one of the most common complications characterized by increased D-dimer level. We aimed to investigate the dose-response relationship between elevated D-dimer level and mortality in critically ill COVID-19 patients.

METHODS

This was a retrospective observational study in 259 critically ill COVID-19 patients requiring intensive care unit admission between March and December 2020. We compared the mortality rate between patients with and without elevated D-dimer. Receiver operating characteristic (ROC) curve analysis, Fagan's nomogram, and dose-response relationship were performed to determine the association between D-dimer level and mortality.

RESULTS

Overall mortality rate was 40.9% (106 patients). Median D-dimer level was higher in non-survivor group (10,170 ng/mL vs 4,050 ng/mL, p=0.028). The association remained significant after multivariate logistic regression analysis (p=0.046). The optimal cut-off for D-dimer level to predict mortality from ROC curve analysis was 9,020 ng/mL (OR (odds ratio) 3.73 [95% CI (confidence interval) 1.91 - 7.28], p<0.001). D-dimer level >9,020 ng/mL confers 67% posterior probability of mortality and D-dimer level <9,020 ng/mL had 35% probability of mortality.

CONCLUSIONS

There was a non-linear dose-response relationship between D-dimer level and mortality with P nonlinearity of 0.004. D-dimer level was associated with mortality in critically ill COVID-19 patients in the non-linear dose-response relationship.

The Impact of LEP rs7799039 Polymorphism and Obesity on the Severity of Coronavirus Disease-19

BACKGROUND AND AIMS

SARS-CoV-2 infection has been recorded in 230 countries to date. Obesity has a negative impact on one's quality of life and is one of the main causes of mortality globally. Obesity affects the immune system, making the host more susceptible to infectious infections. Also, obesity commonly provokes the severity of respiratory diseases so the correlation of LEP rs7799039 Polymorphism in corpulent patients with COVID-19 infection was clearly investigated in the current study.

METHODS

A total of 232 patients were recruited, 116 patients were obese with COVID-19 infection, and 116 patients were non obese COVID-19. Fasting blood glucose test (FBG), hemoglobin A1C (HbA1C), complete blood count (CBC), international normalized ratio (INR), urea, alanine transaminase (ALT), aspartate aminotransferase (AST), D dimer and C-reactive protein (CRP) were estimated. C.T. scan was performed for each patient, and C.T. severity score was calculated. Genotyping for the leptin rs7799039 SNPs was performed by TaqMan^® (Applied Biosystems Step One ^TM Real-time PCR).

RESULTS

Regarding LEP polymorphism, all individuals of non-obese groups significantly had the homozygous allele GG (100%), whereas only 56% of obese groups had GG alleles (P = 0.001). The severity scores significantly (P = 0.001) varied regarding LEP polymorphism regarding Rs7799039, where the largest proportion of those with Grade IV had the homozygous allele AA (57.1%).

CONCLUSION

There was a correlation between the leptin gene allelic discrimination and COVID-19 CT brutality in obese patients. The A allele was considered a risk factor for severity in COVID-19 patients while the G allele contributes to decreasing that risk.

Evaluating the ability of the NLHA2 and artificial neural network models to predict COVID-19 severity, and comparing them with the four existing scoring systems

To improve the identification and subsequent intervention of COVID-19 patients at risk for ICU admission, we constructed COVID-19 severity prediction models using logistic regression and artificial neural network (ANN) analysis and compared them with the four existing scoring systems (PSI, CURB-65, SMARTCOP, and MuLBSTA). In this prospective multi-center study, 296 patients with COVID-19 pneumonia were enrolled and split into the General-Ward-Care group (N = 238) and the ICU-Admission group (N = 58). The PSI model (AUC = 0.861) had the best results among the existing four scoring systems, followed by SMARTCOP (AUC = 0.770), motified-MuLBSTA (AUC = 0.761), and CURB-65 (AUC = 0.712). Data from 197 patients (training set) were analyzed for modeling. The beta coefficients from logistic regression were used to develop a severity prediction model and risk score calculator. The final model (NLHA2) included five covariates (consumes alcohol, neutrophil count, lymphocyte count, hemoglobin, and AKP). The NLHA2 model (training: AUC = 0.959; testing: AUC = 0.857) had similar results to the PSI model, but with fewer variable items. ANN analysis was used to build another complex model, which had higher accuracy (training: AUC = 1.000; testing: AUC = 0.907). Discrimination and calibration were further verified through bootstrapping (2000 replicates), Hosmer-Lemeshow goodness of fit testing, and Brier score calculation. In conclusion, the PSI model is the best existing system for predicting ICU admission among COVID-19 patients, while two newly-designed models (NLHA2 and ANN) performed better than PSI, and will provide a new approach for the development of prognostic evaluation system in a novel respiratory viral epidemic.

Clinical Characteristics, Outcomes and Prognostic Factors for Critical Illness in Hospitalized COVID-19 Patients in Saudi Arabia: A Retrospective Cohort Study

Background

A good understanding of the possible risk factors for coronavirus disease 19 (COVID‐19) severity could help clinicians in identifying patients who need prioritized treatment to prevent disease progression and adverse outcome. In the present study, we aimed to correlate clinical and laboratory characteristics of hospitalized COVID-19 patients to disease outcome in Saudi Arabia.

Materials and Methods

The present study included 199 COVID-19 patients admitted to King Fahd Specialist Hospital, Buraydah, Qassim, Saudi Arabia, from April to December 2020. Patients were followed-up until discharge either for recovery or death. Demographic data, clinical data and laboratory results were retrieved from electronic patient records.

Results

Critical COVID-19 cases showed higher mean of age and higher prevalence of co-morbid conditions. Fifty-five patients died during the observation period. Risk factors for in hospital death for COVID 19 patients were leukocytosis (OR 1.89, 95% CI 1.008–3.548, p = 0.081), lymphocytopenia (OR 2.152, 95% CI 1.079–4.295, p = 0.020), neutrophilia (OR 1.839, 95% CI 0.951–3.55, p = 0.047), thrombocytopenia (OR 2.152, 95% CI 0.852–5.430, p = 0.085), liver injury (OR 2.689, 95% CI 1.373–4.944, p = 0.003), acute kidney injury (OR 1.248, 95% CI 0.631–2.467 p = 0.319), pancreatic injury (OR 1.973, 95% CI 0.939–4.144, p = 0.056) and high D dimer (OR 2.635, 95% CI 0.747–9.287, p = 0.091).

Conclusion

Clinical and laboratory data of COVID-19 patients may help understanding the pathogenesis of the disease and subsequently improve of the outcome of patients by determination of the associated risk factors and recognition of high risk group who are more liable for complications and in hospital death. The present study put an eye on some parameters (laboratory and clinical) that should be alarming signs that the patient is at high risk bad prognosis.

Molecular signature of postmortem lung tissue from COVID-19 patients suggests distinct trajectories driving mortality

To elucidate the molecular mechanisms that manifest lung abnormalities during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections, we performed whole-transcriptome sequencing of lung autopsies from 31 patients with severe COVID-19 and ten uninfected controls. Using metatranscriptomics, we identified the existence of two distinct molecular signatures of lethal COVID-19. The dominant 'classical' signature (n=23) showed upregulation of the unfolded protein response, steroid biosynthesis and complement activation, supported by massive metabolic reprogramming leading to characteristic lung damage. The rarer signature (n=8) that potentially represents 'cytokine release syndrome' (CRS) showed upregulation of cytokines such as IL1 and CCL19, but absence of complement activation. We found that a majority of patients cleared SARS-CoV-2 infection, but they suffered from acute dysbiosis with characteristic enrichment of opportunistic pathogens such as Staphylococcus cohnii in 'classical' patients and Pasteurella multocida in CRS patients. Our results suggest two distinct models of lung pathology in severe COVID-19 patients, which can be identified through complement activation, presence of specific cytokines and characteristic microbiome. These findings can be used to design personalized therapy using in silico identified drug molecules or in mitigating specific secondary infections.

Circular RNA Profiles in Viremia and ART Suppression Predict Competing circRNA–miRNA–mRNA Networks Exclusive to HIV-1 Viremic Patients

Since the onset of the HIV-1/AIDS epidemic in 1981, 75 million people have been infected with the virus, and the disease remains a public health crisis worldwide. Circular RNAs (circRNAs) are derived from excised exons and introns during backsplicing, a form of alternative splicing. The relevance of unconventional, non-capped, and non-poly(A) transcripts to transcriptomics studies remains to be routinely investigated. Knowledge gaps to be filled are the interface between host-encoded circRNAs and viral replication in chronically progressed patients and upon treatment with antiviral drugs. We implemented a bioinformatic pipeline and repurpose publicly archived RNA sequence reads from the blood of 19 HIV-1-positive patients that previously compared transcriptomes during viremia and viremia suppression by antiretroviral therapy (ART). The in silico analysis identified viremic patients’ circRNA that became undetectable after ART. The circRNAs originated from a subset of host genes enriched in the HDAC biological pathway. These circRNAs and parental mRNAs held in common a small collection of miRNA response elements (MREs), some of which were present in HIV-1 mRNAs. The function of the MRE-containing target mRNA enriched the RNA polymerase II GO pathway. To visualize the interplay between individual circRNA–miRNA–target mRNA, important for HIV-1 and potentially other diseases, an Interactive Circos tool was developed to efficiently parse the intricately competing endogenous network of circRNA–miRNA–mRNA interactions originating from seven circRNA singled out in viremic versus non-viremic patients. The combined downregulation of the identified circRNAs warrants investigation as a novel antiviral targeting strategy.

A contemporary review on the important role of in silico approaches for managing different aspects of COVID-19 crisis

In the last century, the emergence of in silico tools has improved the quality of healthcare studies by providing high quality predictions. In the case of COVID-19, these tools have been advantageous for bioinformatics analysis of SARS-CoV-2 structures, studying potential drugs and introducing drug targets, investigating the efficacy of potential natural product components at suppressing COVID-19 infection, designing peptide-mimetic and optimizing their structure to provide a better clinical outcome, and repurposing of the previously known therapeutics. These methods have also helped medical biotechnologists to design various vaccines; such as multi-epitope vaccines using reverse vaccinology and immunoinformatics methods, among which some of them have showed promising results through in vitro, in vivo and clinical trial studies. Moreover, emergence of artificial intelligence and machine learning algorithms have helped to classify the previously known data and use them to provide precise predictions and make plan for future of the pandemic condition. At this contemporary review, by collecting related information from the collected literature on valuable data sources; such as PubMed, Scopus, and Web of Science, we tried to provide a brief outlook regarding the importance of in silico tools in managing different aspects of COVID-19 pandemic infection and how these methods have been helpful to biomedical researchers.

Evaluation of potential sponge effects of SARS genomes in human

To date the coronavirus family is composed of seven different viruses which were commonly known as cold viruses until the appearance of the severe acute respiratory coronavirus (SARS-CoV) in 2002, the middle east respiratory syndrome coronavirus (MERS) in 2012 and the severe acute respiratory coronavirus 2 (SARS-CoV-2) which caused the COVID-19 global pandemic in 2019. Using bioinformatic approaches we tested the potential interactions of human miRNAs, expressed in pulmonary epithelial cells, with the available coronavirus genomes. Putative miRNA binding sites were then compared between pathogenic and non pathogenic virus groups. The pathogenic group shares 6 miRNA binding sites that can be potentially involved in the sequestration of miRNAs already known to be associated with deep vein thrombosis. We then analysed ∼100k SARS-CoV-2 variant genomes for their potential interaction with human miRNAs and this study highlighted a group of 97 miRNA binding sites which is present in all the analysed genomes. Among these, we identified 6 miRNA binding sites specific for SARS-CoV-2 and the other two pathogenic viruses whose down-regulation has been seen associated with deep vein thrombosis and cardiovascular diseases. Interestingly, one of these miRNAs, namely miR-20a-5p, whose expression decreases with advancing age, is involved in cytokine signaling, cell differentiation and/or proliferation. We hypothesize that depletion of poorly expressed miRNA could be related with disease severity.

Toll-Like Receptor 4 Polymorphisms (896A/G and 1196C/T) as an Indicator of COVID-19 Severity in a Convenience Sample of Egyptian Patients

Background

The clinical spectrum of COVID-19 is extremely variable. Thus, it is likely that the heterogeneity in the genetic make-up of the host may contribute to disease severity. Toll‐like receptor (TLR)-4 plays a vital role in the innate immune response to SARS-CoV-2 infection. The susceptibility of humans to severe COVID-19 concerning TLR-4 single nucleotide polymorphisms (SNPs) has not been well examined.

Objective

The goal of this research was to investigate the association between TLR-4 (Asp299Gly and Thr399Ile) SNPs and COVID-19 severity and progression as well as the cytokine storm in Egyptian patients.

Methods

We genotyped 300 adult COVID-19 Egyptian patients for TLR-4 (Asp299Gly and Thr399Ile) SNPs using PCR-restriction fragment length polymorphism (PCR-RFLP). We also measured interleukin (IL)-6 levels by enzyme-linked immunosorbent assay (ELISA) as an indicator of the cytokine storm.

Results

The minor 299Gly (G) and 399Ile (T) alleles were associated with a significant (P < 0.001) positive risk of severe COVID-19 (OR = 3.14; 95% CI = 2.02–4.88 and OR = 2.75; 95% CI = 1.66–4.57), their frequency in the severe group were 71.8% (84/150) and 70.7% (58/150), respectively. We detected significant differences between TLR-4 (Asp299Gly, Thr399Ile) genotypes with regard to serum levels of IL-6. Levels of IL-6 increased significantly with the presence of the mutant 299Gly (G) and 399Ile (T) alleles to reach the highest levels in the Gly299Gly (GG) and the Ile399Ile (TT) genotypes (170 pg/mL (145–208.25) and 112 pg/mL (24–284.75), respectively).

Conclusion

The TLR-4 (Asp299Gly and Thr399Ile) minor alleles 299Gly (G) and 399Ile (T) are associated with COVID-19 severity, mortality, and the cytokine storm.

Harnessing immunological targets for COVID-19 immunotherapy

COVID-19 is an infectious and highly contagious disease caused by SARS-CoV-2. The immunotherapy strategy has a great potential to develop a permanent cure against COVID-19. Innate immune cells are in constant motion to scan molecular alteration to cells led by microbial infections throughout the body and helps in clearing invading viruses. Harnessing immunological targets for removing viral infection, generally based on the principle of enhancing the T-cell and protective immune responses. Currently-approved COVID-19 vaccines are mRNA encapsulated in liposomes that stimulate the host immune system to produce antibodies. Given the vital role of innate immunity, harnessing these immune responses opens up new hope for the generation of long-lasting and protective immunity against COVID-19.

Identifying Loci Associated With Bovine Corona Virus Infection and Bovine Respiratory Disease in Dairy and Feedlot Cattle

Bovine coronavirus (BCoV) is associated with respiratory and enteric infections in both dairy and beef cattle worldwide. It is also one of a complex of pathogens associated with bovine respiratory disease (BRD), which affects millions of cattle annually. The objectives of this study were to identify loci and heritability estimates associated with BCoV infection and BRD in dairy calves and feedlot cattle. Dairy calves from California (n = 1,938) and New Mexico (n = 647) and feedlot cattle from Colorado (n = 915) and Washington (n = 934) were tested for the presence of BCoV when classified as BRD cases or controls following the McGuirk scoring system. Two comparisons associated with BCoV were investigated: (1) cattle positive for BCoV (BCoV⁺) were compared to cattle negative for BCoV (BCoV^-) and (2) cattle positive for BCoV and affected with BRD (BCoV⁺BRD⁺) were compared to cattle negative for BCoV and BRD (BCoV^-BRD^-). The Illumina BovineHD BeadChip was used for genotyping, and genome-wide association analyses (GWAA) were performed using EMMAX (efficient mixed-model association eXpedited). The GWAA for BCoV⁺ identified 51 loci (p < 1 × 10^-5; 24 feedlot, 16 dairy, 11 combined) associated with infection with BCoV. Three loci were associated with BCoV⁺ across populations. Heritability estimates for BCoV⁺ were 0.01 for dairy, 0.11 for feedlot cattle, and 0.03 for the combined population. For BCoV⁺BRD⁺, 80 loci (p < 1 × 10^-5; 26 feedlot, 25 dairy, 29 combined) were associated including 14 loci across populations. Heritability estimates for BCoV⁺BRD⁺ were 0.003 for dairy, 0.44 for feedlot cattle, and 0.07 for the combined population. Several positional candidate genes associated with BCoV and BRD in this study have been associated with other coronaviruses and respiratory infections in humans and mice. These results suggest that selection may reduce susceptibility to BCoV infection and BRD in cattle.

JAK-STAT Pathway Inhibition and their Implications in COVID-19 Therapy

As the incidence of COVID-19 increases with time, more and more efforts are made to pave a way out for the therapeutic strategies to deal with the disease progression. Inflammation being a significant influencer in COVID-19 patients, it drives our focus onto the signaling cascades of the JAK/STAT pathway. JAK phosphorylation mediated by cytokine receptor activation leads to phosphorylation of STATs that translocate into the nucleus to translate for inflammatory mediators. The SARS-CoV-2 structural proteins like spike, nucleocapsid, membrane and envelope proteins along with the non- structural proteins 1-16 including proteases like 3CL pro and PLpro promote its entry and survival in hosts. The SARS-CoV-2 infection triggers inflammation via the JAK/STAT pathway leading to recruitment of pneumocytes, endothelial cells, macrophages, monocytes, lymphocytes, natural killer cells and dendritic cells progressing towards cytokine storm. This produces various inflammatory markers in the host that determine the disease severity. The JAK/STAT signaling also mediates immune responses via B cell and T cell differentiation.With an attempt to reduce excessive inflammation, JAK/STAT inhibitors like Ruxolitinib, Baricitinib, Tofacitinib have been employed that mediate its actions via suppressors of cytokine signaling, cytokine inducible SH2 containing protein, Protein inhibitor of activated STAT and protein tyrosine phosphatases. Even though they are implicated with multiple adverse effects, the regulatory authorities have supported its use, and numerous clinical trials are in progress to prove their safety and efficacy. On the contrary, the exact mechanism of JAK/STAT inhibition at molecular levels remains speculative for which further investigations are required.

Angiotensin System Polymorphisms' in SARS-CoV-2 Positive Patients: Assessment Between Symptomatic and Asymptomatic Patients: A Pilot Study

Introduction

The renin-angiotensin-aldosterone system (RAAS), a metabolic cascade regulating pressure and circulating blood volume, has been considered the main system involved in the pathogenesis of severe lung injury and organs decline in COVID-19 patients. The angiotensin I-converting enzyme (ACE1), angiotensin-converting enzyme 2 (ACE2), angiotensinogen (AGT) and receptors angiotensin II receptor type 1 (AGTR1) are key factors for SARS-CoV-2 entering in the cells, sodium and water retention with an increase blood pressure, promotion of fibrotic and inflammatory phenomena resulting in a cytokine storm.

Methods

In this pilot study, the frequencies of six polymorphisms in the ACE1, ACE2, AGT and AGTR1 genes were analysed in symptomatic patients affected by COVID-19 and compared with the results obtained from asymptomatic subjects.

Results

Thus, we have identified that rs2074192 (ACE2), rs1799752 (ACE1) and rs699 (AGT) SNPs could potentially be a valuable tool for predicting the clinical outcome of SARS-CoV-2 infected patients. A genetic predisposition may be prospected for severe internal organ damages and poor prognosis in patients with COVID-19 disease, as observed in symptomatic vs asymptomatic.

Conclusion

This study provides evidence that analysis of RAAS polymorphisms could be considered the key point in understanding and predicting the SARS-CoV-2 course infection.

Potential therapeutic agents to COVID-19: An update review on antiviral therapy, immunotherapy, and cell therapy

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, China, in December 2020 and coronavirus disease 19 (COVID-19) was later announced as pandemic by the World Health Organization (WHO). Since then, several studies have been conducted on the prevention and treatment of COVID-19 by potential vaccines and drugs. Although, the governments and global population have been attracted by some vaccine production projects, the presence of SARS-CoV-2-specific antiviral drugs would be an urge necessity in parallel with the efficient preventive vaccines. Various nonspecific drugs produced previously against other bacterial, viral, and parasite infections were recently evaluated for treating patients with COVID-19. In addition to therapeutic properties of these anti-COVID-19 compounds, some adverse effects were observed in different human organs as well. Not only several attentions were paid to antiviral therapy and treatment of COVID-19, but also nanomedicine, immunotherapy, and cell therapy were conducted against this viral infection. In this review study, we planned to introduce the present and potential future treatment strategies against COVID-19 and define the advantages and disadvantages of each treatment strategy.