Co-infection and clinical characteristics of SARS-CoV-2 and influenza among COVID-19 cases: A-meta analysis (preprint)

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), that causes coronavirus disease 2019 (COVID-19) is a public health problem and may have co-infection with other pathogens such as influenza virus.This study aims to assess the co-infection of SARS-CoV-2 with influenza among COVID-19 cases.The all relevant studies were collected from international databases. For improving the quality of the present literature, the all studies were evaluated by two reviewers in order to confirm all of the studies have inclusion criteria. Finally, all articles with sufficient quality scores were included in meta-analysis. Assessment of heterogeneity among the studies of primary studies was performed using the statistic chi‐squared test (Cochran’s Q) and I2 index. In this results, random or fixed effect model were used for determination of heterogeneity test. All statistical analyses were performed using Comprehensive Meta-Analysis (CMA), V.2 software.This meta- analysis included 9 primary studies investigating the co-infection of SARS-CoV-2 with influenza among COVID-19 cases. Pooled prevalence (95% confidence interval) of co-infection is shown that the prevalence of influenza A is higher than influenza B. 2.3(0.5-9.3) vs 0.1 (0.4-3.3). Using the fixed effect model the frequency of fever was (80.6% [95% CI 76.1–84.40, p < 0.153]) and it is shown that fever is the most prevalent symptom in patients.Patients admitted to hospital with COVID-19 also infected with influenza virus. Thus, the current research provides a better understanding about the control and treatment of co-infection with SARS-CoV-2 and the influenza virus.

Relative Sensitivity of Common Target Genes For The Detection of SARS-Cov-2 In Real Time-PCR (preprint)

SARS-CoV-2(COVID-19) currently is the main cause of the severe acute respiratory disease and fatal outcomes in human beings worldwide. Several genes are used as targets for the detection of SARS-CoV-2, including the RDRP, N, and E genes. The present study aimed to determine the RDRP, N, and E genes expressions of SARS-CoV- 2 in clinical samples. For this purpose, 100 SARS-CoV-2 positive samples were collected from diagnostic laboratories of Mazandaran province, Iran. After RNA extraction, the real time RT-PCR assay was performed for differential gene expressions’ analysis of N, E, and RDRP. The CT values for N, RDRP, and E targets of 100 clinical samples for identifying SARS-CoV-2 were then evaluated using qRT-PCR. This result suggests N gene as a potential target for the detection of the SARS‐CoV‐2, since it was observed to be highly expressed in the nasopharyngeal or oropharynges of COVID-19 patients (P < 0.0001). Herein, we showed that SARS-CoV- 2 genes were differentially expressed in the host cells. Therefore, to reduce obtaining false negative results and to increase the sensitivity of the available diagnostic tests, the target genes should be carefully selected based on the most expressed genes in the cells.

IFI27 transcription is an early predictor for COVID-19 outcomes; a multi-cohort observational study (preprint)

Background. Robust biomarkers that predict disease outcomes amongst COVID19 patients are necessary for both patient triage and resource prioritisation. Numerous candidate biomarkers have been proposed for COVID19. However, at present, there is no consensus on the best diagnostic approach to predict outcomes in infected patients. Moreover, it is not clear whether such tools would apply to other potentially pandemic pathogens and therefore of use as stockpile for future pandemic preparedness. Methods. We conducted a multi cohort observational study to investigate the biology and the prognostic role of interferon alpha inducible protein 27 (IFI27) in COVID19 patients. Findings. We show that IFI27 is expressed in the respiratory tract of COVID19 patients and elevated IFI27 expression is associated with the presence of a high viral load. We further demonstrate that systemic host response, as measured by blood IFI27 expression, is associated with COVID19 severity. For clinical outcome prediction (e.g. respiratory failure), IFI27 expression displays a high positive (0.83) and negative (0.95) predictive value, outperforming all other known predictors of COVID19 severity. Furthermore, IFI27 is upregulated in the blood of infected patients in response to other respiratory viruses. For example, in the pandemic H1N1/09 swine influenza virus infection, IFI27 like genes were highly upregulated in the blood samples of severely infected patients. Interpretation. These data suggest that prognostic biomarkers targeting the family of IFI27 genes could potentially supplement conventional diagnostic tools in future virus pandemics, independent of whether such pandemics are caused by a coronavirus, an influenza virus or another as yet to be discovered respiratory virus.

Co-infection of SARS-CoV-2 with influenza among COVID-19 cases: A-meta analysis (preprint)

Background The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), that causes coronavirus disease 2019 (COVID-19) is a public health problem and may have co-infection with other pathogens such as influenza virus.Objective This study aims to assess the co-infection of SARS-CoV-2 with influenza among COVID-19 cases.Material and methods The all relevant studies were collected from international databases. For improving the quality of the present literature, the all studies were evaluated by two reviewers in order to confirm all of the studies have inclusion criteria. Finally, all articles with sufficient quality scores were included in meta-analysis. Assessment of heterogeneity among the studies of primary studies was performed using the statistic chi‐squared test (Cochran's Q) and I2 index. In this results, random or fixed effect model were used for determination of heterogeneity test. All statistical analyses were performed using Comprehensive Meta-Analysis (CMA), V.2 software.Results This meta- analysis included 9 primary studies investigating the co-infection of SARS-CoV-2 with influenza among COVID-19 cases. Pooled prevalence (95% confidence interval) of co-infection is shown that the prevalence of influenza A is higher than influenza B. 2.3(0.5-9.3) vs 0.1 (0.4-3.3). Using the fixed effect model the frequency of fever was (80.6% [95% CI 76.1–84.40, p < 0.153]) and it is shown that fever is the most prevalent symptom in patients.Conclusion Patients admitted to hospital with COVID-19 also infected with influenza virus. Thus, the current research provides a better understanding about the control and treatment of co-infection with SARS-CoV-2 and the influenza virus.

Emerging SARS-CoV-2 Genetic Variations and Mutations in the COVID-19 genomic sequence: A Systematic and Meta-analysis review (preprint)

Objectives Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). The high mutation rate of RNA viruses causes genetic variation, virus evolution and it is a strategy to escape the immune system. In the present study, all researches and evidence were extracted from the available online national databases. Two researchers randomly evaluated the assessment of the research sensitivity. Finally, after quality assessment and specific inclusion and exclusion criteria, the eligible articles were entered for meta-analysis. The heterogeneity between the results of studies was measured using test statistic (Cochran's Q) and I2 index. The forest plots illustrated the point and pooled estimates with 95% confidence intervals (crossed lines). All statistical analyses were performed using Comprehensive meta-Analysis V.2 software.This meta-analysis included 13 primary studies investigating the SARS-CoV-2 genetic variations and mutations in the COVID-19 genomic sequence. According to the pooled prevalence (95% confidence interval) of mutations, the spike gene variations showed the highest non-synonymous mutation frequency (16.4%, CI: 13.6, 16.6) and the Non-structural protein (NSP) genes possess the highest mutation frequency among total mutations (31.6%, CI: 21, 44.6). Genomic mutation analysis of SARS-CoV-2 strains may provide knowledge about different biological infrequent mutations and their relationships of viral transmission, pathogenicity, infectivity, and fatality rates between SARS-CoV-2 and human cells.

Design an efficient multi-epitope peptide vaccine candidate against SARS-CoV-2: An in silico analysis (preprint)

BackgroundTo date, no specific vaccine or drug has been proven to be effective for SARS-CoV-2 infection. Therefore, we implemented immunoinformatics approach to design an efficient multi-epitopes vaccine against SARS-CoV-2. ResultsThe designed vaccine construct has several immunodominant epitopes from structural proteins of Spike, Nucleocapsid, Membrane and Envelope. These peptides promote cellular and humoral immunity and Interferon gamma responses. In addition, these epitopes have antigenicity ability and no allergenicity probability. To enhance the vaccine immunogenicity, we used three potent adjuvants; Flagellin, a driven peptide from high mobility group box 1 as HP-91 and human beta defensin 3 protein. The physicochemical and immunological properties of the vaccine structure were evaluated. Tertiary structure of the vaccine protein was predicted and refined by I-Tasser and galaxi refine and validated using Rampage and ERRAT. Results of Ellipro showed 242 residues from vaccine might be conformational B cell epitopes. Docking of vaccine with Toll-Like Receptors 3, 5 and 8 proved an appropriate interaction between the vaccine and receptor proteins. In silico cloning demonstrated that the vaccine can be efficiently expressed in Escherichia coli. ConclusionsThe designed multi epitope vaccine is potentially antigenic in nature and has the ability to induce humoral and cellular immune responses against SARS-CoV-2. This vaccine can interact appropriately with the TLR3, 5, and 8. Also, this vaccine has high quality structure and suitable characteristics such as high stability and potential for expression in Escherichia coli.

Repurposing naproxen as a potential antiviral agent against SARS-CoV-2 (preprint)

The Outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in late 2019 in China and many other countries around the world necessitate immediate action to develop new drugs against the virus. Repurposing of existing drugs for new targets is a fast, safe and unexpansive approach for this goal. Studies have shown that naproxen could specifically interact with the RNA binding domain of nueclporteins of RNA viruses such as the influenza virus. Therefore, this study aimed to evaluate the binding properties of naproxen to the nucleocapsid protein of SARS-CoV-2. 3D structure of N and C terminal domains of SARS-CoV- 2 nucleocapsid were constructed and each were docked with naproxen and analyzed during 100 ns of molecular dynamics. The results showed that naproxen interacts with the N terminal domain of the nucleocapsid via two salt bridges with Arg 88 and 92 and a network of h-bonds. Molecular dynamics analysis was also revealed that all the coordinations of naproxen with N terminal domain were kept during 100 ns of simulation time. The results of this study provide insights how naproxen can specifically interact with the conserved RNA binding module of the nucleocapsid of SARS-CoV-2 that would inhibit the packaging of viral genome into capsid and virus assembly. Therefore we recommend evaluating the antiviral effects of naproxen against SARS-CoV-2 in in vitro studies and clinical trials.