Summary To date, seven human coronaviruses (HCoVs) have been detected: HCoV‐NL63, HCoV‐229E, HCoV‐HKU1, HCoV‐OC43, severe acute respiratory syndrome coronavirus (SARS‐CoV), Middle East respiratory syndrome coronavirus (MERS‐CoV) and SARS‐CoV‐2. Four of these viruses, including HCoV‐NL63, ‐229E, ‐HKU1 and ‐OC43, usually cause mild‐to‐moderate respiratory diseases with a seasonal pattern. Since 2000, three new HCoVs have emerged with a significant mortality rate. Although SARS‐CoV and MERS‐CoV caused an epidemic in some countries, SARS‐CoV‐2 escalated into a pandemic. All HCoVs can cause severe complications in the elderly and immunocompromised individuals. The bat origin of HCoVs, the presence of intermediate hosts and the nature of their viral replication suggest that other new coronaviruses may emerge in the future. Despite the fact that all HCoVs share similarities in viral replication, they differ in their accessory proteins, incubation period and pathogenicity. This study aims to review these differences between the seven HCoVs.

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused COVID-19 disease in China. So far, no vaccine has licensed to protect against infection with COVID-19, therefore an effective COVID-19 vaccine needed. The aim of this study was to predict antigenic peptides of SARS-CoV-2 for designing the COVID-19 vaccine using immunoinformatic analysis. In this study, T and B-cell epitopes of S protein were predicted and screened based on the antigenicity, toxicity, allergenicity, and cross-reactivity with human proteomes. The epitopes were joined by the appropriate linker. LT-IIc as an adjuvant was attached to the end of the structure. The secondary and 3D structure of the vaccine was predicted. The refinement process was performed to improve the quality of the 3D model structure; the validation process is performed using the Ramachandran plot and ProSA z-score. The proposed vaccine's binding affinity to the HLA-A11:01 and HLA-DRB1_01:01 molecule was evaluated by molecular docking. Using molecular dynamics, the stability of vaccine-HLA complexes was also evaluated. Finally, in silico gene cloning was performed in the pET30a (+) vector. The findings suggest that the current vaccine may be a promising vaccine to prevent SARS-CoV-2 infection.

Recently, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiologic agent of coronavirus disease 2019 (COVID-19), has led to a worldwide pandemic with millions of infected patients. Alteration in humans’ microbiota was also reported in COVID-19 patients. The alteration in human microbiota may contribute to bacterial or viral infections and affect the immune system. Moreover, human’s microbiota can be altered due to SARS-CoV-2 infection, and these microbiota changes can indicate the progression of COVID-19. While current studies focus on the gut microbiota, it seems necessary to pay attention to the lung microbiota in COVID-19. This study is aimed at reviewing respiratory microbiota dysbiosis among COVID-19 patients to encourage further studies on the field for assessment of SARS-CoV-2 and respiratory microbiota interaction.

The ongoing pandemic of Coronavirus disease 2019 (COVID-19) has infected more than 27 million confirmed cases and 8,90,000 deaths all around the world. Verity of viral infections can infect the nervous system; these viral infections can present a wide range of manifestation. The aim of the current study was to systematically review the COVID-19 associated central nervous system manifestations, mental and neurological symptoms. For that we conducted a comprehensive systematic literature review of four online databases, including Web of Science, PubMed, Scopus and Embase. All relevant articles that reported psychiatric/psychological symptoms or disorders in COVID-19 without considering time and language restrictions were assessed. All the study procedures were performed based on the PRISMA criteria. Due to the screening, 14 studies were included. The current study result indicated that, the pooled prevalence of CNS or mental associated disorders with 95% CI was 50.68% (6.68–93.88). The most prevalence symptoms were hyposmia/anosmia/olfactory dysfunction (number of study: 10) with 36.20% (14.99–60.51). Only one study reported numbness/paresthesia and dysphonia. Pooled prevalence of numbness/paresthesia and dysphonia was 5.83% (2.17–12.25) and 2.39% (10.75–14.22). The pooled prevalence of depression and anxiety was 3.52% (2.62–4.54) and 13.92% (9.44–19.08). Our findings demonstrate that COVID-19 has a certain relation with neurological symptoms. The hypsomia, anosmia or olfactory dysfunction was most frequent symptom. Other symptoms were headache or dizziness, dysgeusia or ageusia, dysphonia and fatigue. Depression, anxiety, and confusion were less frequent symptoms.

According to the evidence, the coronavirus disease 19 (COVID-19) is caused by a zoonotic pathogen named respiratory syndrome coronavirus 2 (SARS-CoV-2). This virus can spread through personal contact, respiratory droplets, and also through airborne transmission. A rapid, low-cost, and effective biosensor platform is essential to diagnose patients with COVID-19 infection, predominantly the asymptomatic individuals, and prevent the spread of the SARS-CoV-2 via transmission routes. The objective of this review is to provide a comparative view among current diagnostic methods, focusing on recently suggested biosensors for the detection of SARS-CoV2 in clinical samples. A capable SARS-CoV-2 biosensor can be designed by the holistic insights of various biosensor studies.

Background. Coinfections have a potential role in increased morbidity and mortality rates during pandemics. Our investigation is aimed at evaluating the viral coinfection prevalence in COVID-19 patients. Methods. We systematically searched scientific databases, including Medline, Scopus, WOS, and Embase, from December 1, 2019, to December 30, 2020. Preprint servers such as medRxiv were also scanned to find other related preprint papers. All types of studies evaluating the viral coinfection prevalence in COVID-19 patients were considered. We applied the random effects model to pool all of the related studies. Results. Thirty-three studies including 10484 patients were identified. The viral coinfection estimated pooled prevalence was 12.58%; 95% CI: 7.31 to 18.96). Blood viruses (pooled prevalence: 12.48%; 95% CI: 8.57 to 16.93) had the most frequent viral coinfection, and respiratory viruses (pooled prevalence: 4.32%; 95% CI: 2.78 to 6.15) had less frequent viral coinfection. The herpesvirus pooled prevalence was 11.71% (95% CI: 3.02 to 24.80). Also, the maximum and minimum of viral coinfection pooled prevalence were in AMRO and EMRO with 15.63% (95% CI: 3.78 to 33.31) and 7.05% (95% CI: 3.84 to 11.07), respectively. Conclusion. The lowest rate of coinfection belonged to respiratory viruses. Blood-borne viruses had the highest coinfection rate. Our results provide important data about the prevalence of blood-borne viruses among COVID-19 patients which can be critical when it comes to their treatment procedure.

MicroRNAs (miRNAs) are non-coding RNAs with 19 to 24 nucleotides which are evolutionally conserved. MicroRNAs play a regulatory role in many cellular functions such as immune mechanisms, apoptosis, and tumorigenesis. The main function of miRNAs is the post-transcriptional regulation of gene expression via mRNA degradation or inhibition of translation. In fact, many of them act as an oncogene or tumor suppressor. These molecular structures participate in many physiological and pathological processes of the cell. The virus can also produce them for developing its pathogenic processes. It was initially thought that viruses without nuclear replication cycle such as Poxviridae and RNA viruses can not code miRNA, but recently, it has been proven that RNA viruses can also produce miRNA. The aim of this articles is to describe viral miRNAs biogenesis and their effects on cellular and viral genes.