Bioinformatics Approach to Identify the Influences of COVID-19 on Ischemic Stroke.

As severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) is becoming more infectious and less virulent, symptoms beyond the lungs of the Coronavirus Disease 2019 (COVID-19) patients are a growing concern. Studies have found that the severity of COVID-19 patients is associated with an increased risk of ischemic stroke (IS); however, the underlying pathogenic mechanisms remain unknown. In this study, bioinformatics approaches were utilized to explore potential pathogenic mechanisms and predict potential drugs that may be useful in the treatment of COVID-19 and IS. The GSE152418 and GSE122709 datasets were downloaded from the GEO website to obtain the common differentially expressed genes (DEGs) of the two datasets for further functional enrichment, pathway analysis, and drug candidate prediction. A total of 80 common DEGs were identified in COVID-19 and IS datasets for GO and KEGG analysis. Next, the protein-protein interaction (PPI) network was constructed and hub genes were identified. Further, transcription factor-gene interactions and DEGs-miRNAs coregulatory network were investigated to explore their regulatory roles in disease. Finally, protein-drug interactions with common DEGs were analyzed to predict potential drugs. We successfully identified the top 10 hub genes that could serve as novel targeted therapies for COVID-19 and screened out some potential drugs for the treatment of COVID-19 and IS.

Age-related rhesus macaque models of COVID-19.

BACKGROUND: Since December 2019, an outbreak of the Corona Virus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus (SARS-CoV-2) in Wuhan, China, has become a public health emergency of international concern. The high fatality of aged cases caused by SARS-CoV-2 was a need to explore the possible age-related phenomena with non-human primate models. METHODS: Three 3-5 years old and two 15 years old rhesus macaques were intratracheally infected with SARS-CoV-2, and then analyzed by clinical signs, viral replication, chest X-ray, histopathological changes and immune response. RESULTS: Viral replication of nasopharyngeal swabs, anal swabs and lung in old monkeys was more active than that in young monkeys for 14 days after SARS-CoV-2 challenge. Monkeys developed typical interstitial pneumonia characterized by thickened alveolar septum accompanied with inflammation and edema, notably, old monkeys exhibited diffuse severe interstitial pneumonia. Viral antigens were detected mainly in alveolar epithelial cells and macrophages. CONCLUSION: SARS-CoV-2 caused more severe interstitial pneumonia in old monkeys than that in young monkeys. Rhesus macaque models infected with SARS-CoV-2 provided insight into the pathogenic mechanism and facilitated the development of vaccines and therapeutics against SARS-CoV-2 infection.

Surveillance of SARS-CoV-2 at the Huanan Seafood Market.

SARS-CoV-2, the causative agent of COVID-19, emerged in December 2019. Its origins remain uncertain. It has been reported that a number of the early human cases had a history of contact with the Huanan Seafood Market. Here we present the results of surveillance for SARS-CoV-2 within the market. From January 1st 2020, after closure of the market, 923 samples were collected from the environment. From 18th January, 457 samples were collected from 18 species of animals, comprising of unsold contents of refrigerators and freezers, swabs from stray animals, and the contents of a fish tank. Using RT-qPCR, SARS-CoV-2 was detected in 73 environmental samples, but none of the animal samples. Three live viruses were successfully isolated. The viruses from the market shared nucleotide identity of 99.99% to 100% with the human isolate HCoV-19/Wuhan/IVDC-HB-01/2019. SARS-CoV-2 lineage A (8782T and 28144C) was found in an environmental sample. RNA-seq analysis of SARS-CoV-2 positive and negative environmental samples showed an abundance of different vertebrate genera at the market. In summary, this study provides information about the distribution and prevalence of SARS-CoV-2 in the Huanan Seafood Market during the early stages of the COVID-19 outbreak.

Classification of Coronavirus Spike Proteins by Deep-Learning-Based Raman Spectroscopy and its Interpretative Analysis.

The outbreak of COVID-19 has spread worldwide, causing great damage to the global economy. Raman spectroscopy is expected to become a rapid and accurate method for the detection of coronavirus. A classification method of coronavirus spike proteins by Raman spectroscopy based on deep learning was implemented. A Raman spectra dataset of the spike proteins of five coronaviruses (including MERS-CoV, SARS-CoV, SARS-CoV-2, HCoVHKU1, and HCoV-OC43) was generated to establish the neural network model for classification. Even for rapidly acquired spectra with a low signal-to-noise ratio, the average accuracy exceeded 97%. An interpretive analysis of the classification results of the neural network was performed, which indicated that the differences in spectral characteristics captured by the neural network were consistent with the experimental analysis. The interpretative analysis method provided a valuable reference for identifying complex Raman spectra using deep-learning techniques. Our approach exhibited the potential to be applied in clinical practice to identify COVID-19 and other coronaviruses, and it can also be applied to other identification problems such as the identification of viruses or chemical agents, as well as in industrial areas such as oil and gas exploration.

Classification of Coronavirus Spike Proteins by Deep-Learning-Based Raman Spectroscopy and its Interpretative Analysis

The outbreak of COVID-19 has spread worldwide, causing great damage to the global economy. Raman spectroscopy is expected to become a rapid and accurate method for the detection of coronavirus. A classification method of coronavirus spike proteins by Raman spectroscopy based on deep learning was implemented. A Raman spectra dataset of the spike proteins of five coronaviruses (including MERS-CoV, SARS-CoV, SARS-CoV-2, HCoVHKU1, and HCoV-OC43) was generated to establish the neural network model for classification. Even for rapidly acquired spectra with a low signal-to-noise ratio, the average accuracy exceeded 97%. An interpretive analysis of the classification results of the neural network was performed, which indicated that the differences in spectral characteristics captured by the neural network were consistent with the experimental analysis. The interpretative analysis method provided a valuable reference for identifying complex Raman spectra using deep-learning techniques. Our approach exhibited the potential to be applied in clinical practice to identify COVID-19 and other coronaviruses, and it can also be applied to other identification problems such as the identification of viruses or chemical agents, as well as in industrial areas such as oil and gas exploration.

Vaccination with Omicron Inactivated Vaccine in Pre-vaccinated Mice Protects against SARS-CoV-2 Prototype and Omicron Variants.

In response to the fast-waning immune response and the great threat of the Omicron variant of concern (VOC) to the public, we report the pilot-scale production of an inactivated Omicron vaccine candidate that induces high levels of neutralizing antibody titers to protect against the Omicron virus. Here, we demonstrate that the inactivated Omicron vaccine is safe and effective in recalling immune responses to the HB02, Omicron, and Delta viruses after one or two doses of BBIBP-CorV. In addition, the efficient productivity and good genetic stability of the manufactured inactivated vaccine is proved. These results support the further evaluation of the Omicron vaccine in a clinical trial.

Immunogenicity Evaluating of the Multivalent COVID-19 Inactivated Vaccine against the SARS-CoV-2 Variants.

It has been reported that the novel coronavirus (COVID-19) has caused more than 286 million cases and 5.4 million deaths to date. Several strategies have been implemented globally, such as social distancing and the development of the vaccines. Several severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants have appeared, such as Alpha, Beta, Gamma, Delta, and Omicron. With the rapid spread of the novel coronavirus and the rapidly changing mutants, the development of a broad-spectrum multivalent vaccine is considered to be the most effective way to defend against the constantly mutating virus. Here, we evaluated the immunogenicity of the multivalent COVID-19 inactivated vaccine. Mice were immunized by multivalent COVID-19 inactivated vaccine, and the neutralizing antibodies in serum were analyzed. The results show that HB02 + Delta + Omicron trivalent vaccine could provide broad spectrum protection against HB02, Beta, Delta, and Omicron virus. Additionally, the different multivalent COVID-19 inactivated vaccines could enhance cellular immunity. Together, our findings suggest that the multivalent COVID-19 inactivated vaccine can provide broad spectrum protection against HB02 and other virus variants in humoral and cellular immunity, providing new ideas for the development of a broad-spectrum COVID-19 vaccine.

Dynamic Changes in Coagulation Function in Patients With Pneumonia Under Admission and Non-admission Treatment.

Objective: We aimed to explore the dynamic changes in coagulation function and the effect of age on coagulation function in patients with pneumonia under admission and non-admission treatment. Methods: We included 178 confirmed adult inpatients with COVID-19 from Wuhan Union Hospital Affiliated to Huazhong University of Science and Technology (Wuhan, China). Patients were classified into common types, and all were cured and discharged after hospitalization. We recorded the time of the first clinical symptoms of the patients and performed blood coagulation tests at the time of admission and after admission. In total, eight factors (TT, FIB, INR, APTT, PT, DD, ATIII, and FDP) were analyzed. Patients were classified into four groups according to the time from the first symptom onset to hospital admission for comparative analysis. The patients who were admitted within 2 weeks of disease onset were analyzed for the dynamic changes in their blood coagulation tests. Further division into two groups, one group comprising patients admitted to the hospital within 2 weeks after the onset of disease and the other comprising patients admitted to the hospital 2 weeks after disease onset, was performed to form two groups based on whether the patient ages were over or under 55 years. Chi-square tests and T tests were used to explore the dynamic changes in coagulation function and the influence of age on the results of coagulation function tests. Results: A total of 178 inpatients, 34 of whom underwent dynamic detection, were included in this analysis. We divided these patients into four groups according to the interval between the onset of COVID-19 pneumonia and the time to admission in the hospital: the 1-7 days (group 1), 8-14 days (group 2), 15-21 days (group 3), and >21-days (group 4). Eight factors all increased within 2 weeks after onset and gradually decreased to normal 2 weeks before the patient was admitted. The changes in coagulation function of patients admitted to the hospital were similar. After being admitted to the hospital, the most significant decreases among the eight factors were between week 2 and 3. There were distinct differences among the eight factors between people older than 55 years and those younger than 55 years. In the first 2 weeks after being admitted, the levels of the eight factors in patients >55 years were significantly higher than those in patients <55 years, and after another 2 weeks of treatment, the factor levels in both age groups returned to normal. Conclusion: The eight factors all increased within 2 weeks after onset and gradually decreased to normal after 2 weeks regardless of treatment. Compared with patients younger than 55 years, patients older than 55 years have greater changes in their blood coagulation test values.

Morphogenesis and cytopathic effect of SARS-CoV-2 infection in human airway epithelial cells.

SARS-CoV-2, a ß-coronavirus, has rapidly spread across the world, highlighting its high transmissibility, but the underlying morphogenesis and pathogenesis remain poorly understood. Here, we characterize the replication dynamics, cell tropism and morphogenesis of SARS-CoV-2 in organotypic human airway epithelial (HAE) cultures. SARS-CoV-2 replicates efficiently and infects both ciliated and secretory cells in HAE cultures. In comparison, HCoV-NL63 replicates to lower titers and is only detected in ciliated cells. SARS-CoV-2 shows a similar morphogenetic process as other coronaviruses but causes plaque-like cytopathic effects in HAE cultures. Cell fusion, apoptosis, destruction of epithelium integrity, cilium shrinking and beaded changes are observed in the plaque regions. Taken together, our results provide important insights into SARS-CoV-2 cell tropism, replication and morphogenesis.

Development of an Inactivated Vaccine Candidate, BBIBP-CorV, with Potent Protection against SARS-CoV-2.

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) threatens global public health. The development of a vaccine is urgently needed for the prevention and control of COVID-19. Here, we report the pilot-scale production of an inactivated SARS-CoV-2 vaccine candidate (BBIBP-CorV) that induces high levels of neutralizing antibodies titers in mice, rats, guinea pigs, rabbits, and nonhuman primates (cynomolgus monkeys and rhesus macaques) to provide protection against SARS-CoV-2. Two-dose immunizations using 2 µg/dose of BBIBP-CorV provided highly efficient protection against SARS-CoV-2 intratracheal challenge in rhesus macaques, without detectable antibody-dependent enhancement of infection. In addition, BBIBP-CorV exhibits efficient productivity and good genetic stability for vaccine manufacture. These results support the further evaluation of BBIBP-CorV in a clinical trial.

The pathogenicity of SARS-CoV-2 in hACE2 transgenic mice.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of coronavirus disease 2019 (COVID-19), which has become a public health emergency of international concern1. Angiotensin-converting enzyme 2 (ACE2) is the cell-entry receptor for severe acute respiratory syndrome coronavirus (SARS-CoV)2. Here we infected transgenic mice that express human ACE2 (hereafter, hACE2 mice) with SARS-CoV-2 and studied the pathogenicity of the virus. We observed weight loss as well as virus replication in the lungs of hACE2 mice infected with SARS-CoV-2. The typical histopathology was interstitial pneumonia with infiltration of considerable numbers of macrophages and lymphocytes into the alveolar interstitium, and the accumulation of macrophages in alveolar cavities. We observed viral antigens in bronchial epithelial cells, macrophages and alveolar epithelia. These phenomena were not found in wild-type mice infected with SARS-CoV-2. Notably, we have confirmed the pathogenicity of SARS-CoV-2 in hACE2 mice. This mouse model of SARS-CoV-2 infection will be valuable for evaluating antiviral therapeutic agents and vaccines, as well as understanding the pathogenesis of COVID-19.

Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding.

BACKGROUND: In late December, 2019, patients presenting with viral pneumonia due to an unidentified microbial agent were reported in Wuhan, China. A novel coronavirus was subsequently identified as the causative pathogen, provisionally named 2019 novel coronavirus (2019-nCoV). As of Jan 26, 2020, more than 2000 cases of 2019-nCoV infection have been confirmed, most of which involved people living in or visiting Wuhan, and human-to-human transmission has been confirmed. METHODS: We did next-generation sequencing of samples from bronchoalveolar lavage fluid and cultured isolates from nine inpatients, eight of whom had visited the Huanan seafood market in Wuhan. Complete and partial 2019-nCoV genome sequences were obtained from these individuals. Viral contigs were connected using Sanger sequencing to obtain the full-length genomes, with the terminal regions determined by rapid amplification of cDNA ends. Phylogenetic analysis of these 2019-nCoV genomes and those of other coronaviruses was used to determine the evolutionary history of the virus and help infer its likely origin. Homology modelling was done to explore the likely receptor-binding properties of the virus. FINDINGS: The ten genome sequences of 2019-nCoV obtained from the nine patients were extremely similar, exhibiting more than 99·98% sequence identity. Notably, 2019-nCoV was closely related (with 88% identity) to two bat-derived severe acute respiratory syndrome (SARS)-like coronaviruses, bat-SL-CoVZC45 and bat-SL-CoVZXC21, collected in 2018 in Zhoushan, eastern China, but were more distant from SARS-CoV (about 79%) and MERS-CoV (about 50%). Phylogenetic analysis revealed that 2019-nCoV fell within the subgenus Sarbecovirus of the genus Betacoronavirus, with a relatively long branch length to its closest relatives bat-SL-CoVZC45 and bat-SL-CoVZXC21, and was genetically distinct from SARS-CoV. Notably, homology modelling revealed that 2019-nCoV had a similar receptor-binding domain structure to that of SARS-CoV, despite amino acid variation at some key residues. INTERPRETATION: 2019-nCoV is sufficiently divergent from SARS-CoV to be considered a new human-infecting betacoronavirus. Although our phylogenetic analysis suggests that bats might be the original host of this virus, an animal sold at the seafood market in Wuhan might represent an intermediate host facilitating the emergence of the virus in humans. Importantly, structural analysis suggests that 2019-nCoV might be able to bind to the angiotensin-converting enzyme 2 receptor in humans. The future evolution, adaptation, and spread of this virus warrant urgent investigation. FUNDING: National Key Research and Development Program of China, National Major Project for Control and Prevention of Infectious Disease in China, Chinese Academy of Sciences, Shandong First Medical University.