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1.
Viruses ; 14(6):1127, 2022.
Article in English | MDPI | ID: covidwho-1857857

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has emerged as the prime challenge facing public health safety since 2019. Correspondingly, coronavirus disease 2019 (COVID-19) vaccines have been developed and administered worldwide, varying in design strategies, delivery routes, immunogenicity and protective efficacy. Here, a replication-competent vesicular stomatitis virus (VSV) vectored recombinant COVID-19 vaccine was constructed and evaluated in BALB/c mice and Syrian golden hamsters. In BALB/c mice, intramuscular (i.m.) inoculation of recombinant vaccine induced significantly higher humoral immune response than that of the intranasal (i.n.) inoculation group. Analyses of cellular immunity revealed that a Th1-biased cellular immune response was induced in i.n. inoculation group while both Th1 and Th2 T cells were activated in i.m. inoculation group. In golden hamsters, i.n. inoculation of the recombinant vaccine triggered robust humoral immune response and conferred prominent protective efficacy post-SARS-CoV-2 challenge, indicating a better protective immunity in the i.n. inoculation group than that of the i.m. inoculation group. This study provides an effective i.n.-delivered recombinant COVID-19 vaccine candidate and elucidates a route-dependent manner of this vaccine candidate in two most frequently applied small animal models. Moreover, the golden hamster is presented as an economical and convenient small animal model that precisely reflects the immune response and protective efficacy induced by replication-competent COVID-19 vaccine candidates in other SARS-CoV-2 susceptible animals and human beings, especially in the exploration of i.n. immunization.

2.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-336738

ABSTRACT

ABSTRACT Comprehensive analyses showed that SARS-CoV-2 infection caused COVID-19 and induced strong immune responses and sometimes severe illnesses. However, cellular features of recovered patients and long-term health consequences remain largely unexplored. In this study, we collected peripheral blood samples from recovered COVID-19 patients (average age of 35.7 years old) from Hubei province, China, 3 months after discharge;and carried out RNA-seq and whole-genome bisulfite sequencing (WGBS) to identify hallmarks of recovered COVID-19 patients. Our analyses showed significant changes both in expression and DNA methylation of genes and transposable elements (TEs) in recovered COVID-19 patients. We identified 639 misregulated genes and 18516 differentially methylated regions (DMRs) in total. Genes with aberrant expression and DMRs were found to be associated with immune responses and other related biological processes, implicating prolonged overreaction of the immune system in response to SARS-CoV-2 infection. Notably, a significant amount of TEs were aberrantly activated and TE activation was positively correlated with COVID-19 severity. Moreover, differentially methylated TEs may regulate adjacent gene expression as regulatory elements. Those identified transcriptomic and epigenomic signatures define and drive the features of recovered COVID-19 patients, helping determine the risks of long COVID-19, and providing guidance for clinical intervention.

3.
Preprint in English | medRxiv | ID: ppmedrxiv-22274029

ABSTRACT

Comprehensive analyses showed that SARS-CoV-2 infection caused COVID-19 and induced strong immune responses and sometimes severe illnesses. However, cellular features of recovered patients and long-term health consequences remain largely unexplored. In this study, we collected peripheral blood samples from recovered COVID-19 patients (average age of 35.7 years old) from Hubei province, China, 3 months after discharge; and carried out RNA-seq and whole-genome bisulfite sequencing (WGBS) to identify hallmarks of recovered COVID-19 patients. Our analyses showed significant changes both in expression and DNA methylation of genes and transposable elements (TEs) in recovered COVID-19 patients. We identified 639 misregulated genes and 18516 differentially methylated regions (DMRs) in total. Genes with aberrant expression and DMRs were found to be associated with immune responses and other related biological processes, implicating prolonged overreaction of the immune system in response to SARS-CoV-2 infection. Notably, a significant amount of TEs were aberrantly activated and TE activation was positively correlated with COVID-19 severity. Moreover, differentially methylated TEs may regulate adjacent gene expression as regulatory elements. Those identified transcriptomic and epigenomic signatures define and drive the features of recovered COVID-19 patients, helping determine the risks of long COVID-19, and providing guidance for clinical intervention.

4.
J Virol ; 96(9): e0003822, 2022 05 11.
Article in English | MEDLINE | ID: covidwho-1788914

ABSTRACT

Due to the limitation of human studies with respect to individual difference or the accessibility of fresh tissue samples, how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection results in pathological complications in lung, the main site of infection, is still incompletely understood. Therefore, physiologically relevant animal models under realistic SARS-CoV-2 infection conditions would be helpful to our understanding of dysregulated inflammation response in lung in the context of targeted therapeutics. Here, we characterized the single-cell landscape in lung and spleen upon SARS-CoV-2 infection in an acute severe disease mouse model that replicates human symptoms, including severe lung pathology and lymphopenia. We showed a reduction of lymphocyte populations and an increase of neutrophils in lung and then demonstrated the key role of neutrophil-mediated lung immunopathology in both mice and humans. Under severe conditions, neutrophils recruited by a chemokine-driven positive feedback produced elevated "fatal signature" proinflammatory genes and pathways related to neutrophil activation or releasing of granular content. In addition, we identified a new Cd177high cluster that is undergoing respiratory burst and Stfahigh cluster cells that may dampen antigen presentation upon infection. We also revealed the devastating effect of overactivated neutrophil by showing the highly enriched neutrophil extracellular traps in lung and a dampened B-cell function in either lung or spleen that may be attributed to arginine consumption by neutrophil. The current study helped our understanding of SARS-CoV-2-induced pneumonia and warranted the concept of neutrophil-targeting therapeutics in COVID-19 treatment. IMPORTANCE We demonstrated the single-cell landscape in lung and spleen upon SARS-CoV-2 infection in an acute severe disease mouse model that replicated human symptoms, including severe lung pathology and lymphopenia. Our comprehensive study revealed the key role of neutrophil-mediated lung immunopathology in SARS-CoV-2-induced severe pneumonia, which not only helped our understanding of COVID-19 but also warranted the concept of neutrophil targeting therapeutics in COVID-19 treatment.


Subject(s)
COVID-19 , Lung , Neutrophils , Animals , COVID-19/immunology , Disease Models, Animal , Humans , Lung/pathology , Lung/virology , Lymphopenia/virology , Mice , Neutrophils/immunology , SARS-CoV-2 , Spleen/pathology , Spleen/virology
5.
J Cheminform ; 14(1): 14, 2022 Mar 15.
Article in English | MEDLINE | ID: covidwho-1741955

ABSTRACT

MOTIVATION: Drug-target binding affinity (DTA) reflects the strength of the drug-target interaction; therefore, predicting the DTA can considerably benefit drug discovery by narrowing the search space and pruning drug-target (DT) pairs with low binding affinity scores. Representation learning using deep neural networks has achieved promising performance compared with traditional machine learning methods; hence, extensive research efforts have been made in learning the feature representation of proteins and compounds. However, such feature representation learning relies on a large-scale labelled dataset, which is not always available. RESULTS: We present an end-to-end deep learning framework, ELECTRA-DTA, to predict the binding affinity of drug-target pairs. This framework incorporates an unsupervised learning mechanism to train two ELECTRA-based contextual embedding models, one for protein amino acids and the other for compound SMILES string encoding. In addition, ELECTRA-DTA leverages a squeeze-and-excitation (SE) convolutional neural network block stacked over three fully connected layers to further capture the sequential and spatial features of the protein sequence and SMILES for the DTA regression task. Experimental evaluations show that ELECTRA-DTA outperforms various state-of-the-art DTA prediction models, especially with the challenging, interaction-sparse BindingDB dataset. In target selection and drug repurposing for COVID-19, ELECTRA-DTA also offers competitive performance, suggesting its potential in speeding drug discovery and generalizability for other compound- or protein-related computational tasks.

6.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-325382

ABSTRACT

There were 27 novel coronavirus pneumonia cases found in Wuhan, China in December 2019, named as 2019-nCoV temporarily and COVID-19 formally by WHO on 11 February, 2020. In December 2019 and January 2020, COVID-19 has spread in large scale among the population, which brought terrible disaster to the life and property of the Chinese people. In this paper, we will first analyze the feature and pattern of the virus transmission, and discuss the key impact factors and uncontrollable factors of epidemic transmission based on public data. Then the virus transmission can be modelled and used for the inflexion and extinction period of epidemic development so as to provide theoretical support for the Chinese government in the decision-making of epidemic prevention and recovery of economic production. Further, this paper demonstrates the effectiveness of the prevention methods taken by the Chinese government such as multi-level administrative region isolation. It is of great importance and practical significance for the world to deal with public health emergencies.

7.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-296268

ABSTRACT

Motivation : Drug-target binding affinity (DTA) reflects the strength of the drug-target interaction;therefore, predicting the DTA can considerably benefit drug discovery by narrowing the search space and pruning drug-target (DT) pairs with low binding affinity scores. Representation learning using deep neural networks has achieved promising performance compared with traditional machine learning methods;hence, extensive research efforts have been made in learning the feature representation of proteins and compounds. However, such feature representation learning relies on a large-scale labelled dataset, which is not always available. Results: We present an end-to-end deep learning framework, ELECTRA-DTA, to predict the binding affinity of drug-target pairs. This framework incorporates an unsupervised learning mechanism to train two ELECTRA-based contextual embedding models, one for protein amino acids and the other for compound SMILES string encoding. In addition, ELECTRA-DTA leverages a squeeze-and-excitation (SE) convolutional neural network block stacked over three fully connected layers to further capture the sequential and spatial features of the protein sequence and SMILES for the DTA regression task. Experimental evaluations show that ELECTRA-DTA outperforms various state-of-the-art DTA prediction models, especially with the challenging, interaction-sparse BindingDB dataset. In target selection and drug repurposing for COVID-19, ELECTRA-DTA also offers competitive performance, suggesting its potential in speeding drug discovery and generalizability for other compound- or protein-related computational tasks.

8.
Brief Bioinform ; 23(1)2022 01 17.
Article in English | MEDLINE | ID: covidwho-1493682

ABSTRACT

Since the first report of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019, over 100 million people have been infected by COVID-19, millions of whom have died. In the latest year, a large number of omics data have sprung up and helped researchers broadly study the sequence, chemical structure and function of SARS-CoV-2, as well as molecular abnormal mechanisms of COVID-19 patients. Though some successes have been achieved in these areas, it is necessary to analyze and mine omics data for comprehensively understanding SARS-CoV-2 and COVID-19. Hence, we reviewed the current advantages and limitations of the integration of omics data herein. Firstly, we sorted out the sequence resources and database resources of SARS-CoV-2, including protein chemical structure, potential drug information and research literature resources. Next, we collected omics data of the COVID-19 hosts, including genomics, transcriptomics, microbiology and potential drug information data. And subsequently, based on the integration of omics data, we summarized the existing data analysis methods and the related research results of COVID-19 multi-omics data in recent years. Finally, we put forward SARS-CoV-2 (COVID-19) multi-omics data integration research direction and gave a case study to mine deeper for the disease mechanisms of COVID-19.


Subject(s)
Antiviral Agents , COVID-19 , Genomics , SARS-CoV-2 , Antiviral Agents/chemistry , Antiviral Agents/therapeutic use , COVID-19/drug therapy , COVID-19/epidemiology , COVID-19/genetics , Humans , SARS-CoV-2/chemistry , SARS-CoV-2/genetics , SARS-CoV-2/metabolism
9.
Nucleic Acids Res ; 50(D1): D867-D874, 2022 01 07.
Article in English | MEDLINE | ID: covidwho-1462427

ABSTRACT

SCovid (http://bio-annotation.cn/scovid) aims at providing a comprehensive resource of single-cell data for exposing molecular characteristics of coronavirus disease 2019 (COVID-19) across 10 human tissues. COVID-19, an epidemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been found to be accompanied with multiple-organ failure since its first report in Dec 2019. To reveal tissue-specific molecular characteristics, researches regarding to COVID-19 have been carried out widely, especially at single-cell resolution. However, these researches are still relatively independent and scattered, limiting the comprehensive understanding of the impact of virus on diverse tissues. To this end, we developed a single-cell atlas of COVID-19. Firstly we collected 21 single-cell datasets of COVID-19 across 10 human tissues paired with control datasets. Then we constructed a pipeline for the analysis of these datasets to reveal molecular characteristics of COVID-19 based on manually annotated cell types. The current version of SCovid documents 1 042 227 single cells of 21 single-cell datasets across 10 human tissues, 11 713 stably expressed genes and 3778 significant differentially expressed genes (DEGs). SCovid provides a user-friendly interface for browsing, searching, visualizing and downloading all detailed information.


Subject(s)
COVID-19/pathology , Databases, Factual , Single-Cell Analysis , COVID-19/genetics , Humans , Transcriptome , User-Computer Interface
12.
Brief Bioinform ; 22(2): 1442-1450, 2021 03 22.
Article in English | MEDLINE | ID: covidwho-1343666

ABSTRACT

Since the first report of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019, the COVID-19 pandemic has spread rapidly worldwide. Due to the limited virus strains, few key mutations that would be very important with the evolutionary trends of virus genome were observed in early studies. Here, we downloaded 1809 sequence data of SARS-CoV-2 strains from GISAID before April 2020 to identify mutations and functional alterations caused by these mutations. Totally, we identified 1017 nonsynonymous and 512 synonymous mutations with alignment to reference genome NC_045512, none of which were observed in the receptor-binding domain (RBD) of the spike protein. On average, each of the strains could have about 1.75 new mutations each month. The current mutations may have few impacts on antibodies. Although it shows the purifying selection in whole-genome, ORF3a, ORF8 and ORF10 were under positive selection. Only 36 mutations occurred in 1% and more virus strains were further analyzed to reveal linkage disequilibrium (LD) variants and dominant mutations. As a result, we observed five dominant mutations involving three nonsynonymous mutations C28144T, C14408T and A23403G and two synonymous mutations T8782C, and C3037T. These five mutations occurred in almost all strains in April 2020. Besides, we also observed two potential dominant nonsynonymous mutations C1059T and G25563T, which occurred in most of the strains in April 2020. Further functional analysis shows that these mutations decreased protein stability largely, which could lead to a significant reduction of virus virulence. In addition, the A23403G mutation increases the spike-ACE2 interaction and finally leads to the enhancement of its infectivity. All of these proved that the evolution of SARS-CoV-2 is toward the enhancement of infectivity and reduction of virulence.


Subject(s)
Biological Evolution , Mutation , SARS-CoV-2/genetics , COVID-19/virology , Humans , Linkage Disequilibrium , Open Reading Frames , SARS-CoV-2/pathogenicity , Virulence/genetics
15.
Front Nutr ; 8: 638825, 2021.
Article in English | MEDLINE | ID: covidwho-1247884

ABSTRACT

Coronavirus disease 2019 (COVID-19) has infected over 124 million people worldwide. In addition to the development of therapeutics and vaccines, the evaluation of the sequelae in recovered patients is also important. Recent studies have indicated that COVID-19 has the ability to infect intestinal tissues and to trigger alterations of the gut microbiota. However, whether these changes in gut microbiota persist into the recovery stage remains largely unknown. Here, we recruited seven healthy Chinese men and seven recovered COVID-19 male patients with an average of 3-months after discharge and analyzed their fecal samples by 16S rRNA sequencing analysis to identify the differences in gut microbiota. Our results suggested that the gut microbiota differed in male recovered patients compared with healthy controls, in which a significant difference in Chao index, Simpson index, and ß-diversity was observed. And the relative abundance of several bacterial species differed clearly between two groups, characterized by enrichment of opportunistic pathogens and insufficiency of some anti-inflammatory bacteria in producing short chain fatty acids. The above findings provide preliminary clues supporting that the imbalanced gut microbiota may not be fully restored in recovered patients, highlighting the importance of continuous monitoring of gut health in people who have recovered from COVID-19.

18.
Clin Infect Dis ; 71(16): 2158-2166, 2020 11 19.
Article in English | MEDLINE | ID: covidwho-1153176

ABSTRACT

BACKGROUND: In December 2019, the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) broke out in Wuhan. Epidemiological and clinical characteristics of patients with COVID-19 have been reported, but the relationships between laboratory features and viral load has not been comprehensively described. METHODS: Adult inpatients (≥18 years old) with COVID-19 who underwent multiple (≥5 times) nucleic acid tests with nasal and pharyngeal swabs were recruited from Renmin Hospital of Wuhan University, including general patients (n = 70), severe patients (n = 195), and critical patients (n = 43). Laboratory data, demographic data, and clinical data were extracted from electronic medical records. The fitted polynomial curve was used to explore the association between serial viral loads and illness severity. RESULTS: Viral load of SARS-CoV-2 peaked within the first few days (2-4 days) after admission, then decreased rapidly along with virus rebound under treatment. Critical patients had the highest viral loads, in contrast to the general patients showing the lowest viral loads. The viral loads were higher in sputum compared with nasal and pharyngeal swab (P = .026). The positive rate of respiratory tract samples was significantly higher than that of gastrointestinal tract samples (P < .001). The SARS-CoV-2 viral load was negatively correlated with portion parameters of blood routine and lymphocyte subsets and was positively associated with laboratory features of cardiovascular system. CONCLUSIONS: The serial viral loads of patients revealed whole viral shedding during hospitalization and the resurgence of virus during the treatment, which could be used for early warning of illness severity, thus improve antiviral interventions.


Subject(s)
COVID-19/epidemiology , Coronavirus/pathogenicity , China/epidemiology , Female , Humans , Male , Serologic Tests , Viral Load
19.
Brief Bioinform ; 22(2): 1442-1450, 2021 03 22.
Article in English | MEDLINE | ID: covidwho-1081049

ABSTRACT

Since the first report of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019, the COVID-19 pandemic has spread rapidly worldwide. Due to the limited virus strains, few key mutations that would be very important with the evolutionary trends of virus genome were observed in early studies. Here, we downloaded 1809 sequence data of SARS-CoV-2 strains from GISAID before April 2020 to identify mutations and functional alterations caused by these mutations. Totally, we identified 1017 nonsynonymous and 512 synonymous mutations with alignment to reference genome NC_045512, none of which were observed in the receptor-binding domain (RBD) of the spike protein. On average, each of the strains could have about 1.75 new mutations each month. The current mutations may have few impacts on antibodies. Although it shows the purifying selection in whole-genome, ORF3a, ORF8 and ORF10 were under positive selection. Only 36 mutations occurred in 1% and more virus strains were further analyzed to reveal linkage disequilibrium (LD) variants and dominant mutations. As a result, we observed five dominant mutations involving three nonsynonymous mutations C28144T, C14408T and A23403G and two synonymous mutations T8782C, and C3037T. These five mutations occurred in almost all strains in April 2020. Besides, we also observed two potential dominant nonsynonymous mutations C1059T and G25563T, which occurred in most of the strains in April 2020. Further functional analysis shows that these mutations decreased protein stability largely, which could lead to a significant reduction of virus virulence. In addition, the A23403G mutation increases the spike-ACE2 interaction and finally leads to the enhancement of its infectivity. All of these proved that the evolution of SARS-CoV-2 is toward the enhancement of infectivity and reduction of virulence.


Subject(s)
Biological Evolution , Mutation , SARS-CoV-2/genetics , COVID-19/virology , Humans , Linkage Disequilibrium , Open Reading Frames , SARS-CoV-2/pathogenicity , Virulence/genetics
20.
J Sports Med Phys Fitness ; 61(5): 760-761, 2021 05.
Article in English | MEDLINE | ID: covidwho-1055384
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