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1.
Comput Struct Biotechnol J ; 20: 4015-4024, 2022.
Article in English | MEDLINE | ID: covidwho-1966470

ABSTRACT

Co-infection of RNA viruses may contribute to their recombination and cause severe clinical symptoms. However, the tracking and identification of SARS-CoV-2 co-infection persist as challenges. Due to the lack of methods for detecting co-infected samples in a large amount of deep sequencing data, the lineage composition, spatial-temporal distribution, and frequency of SARS-CoV-2 co-infection events in the population remains unclear. Here, we propose a hypergeometric distribution-based method named Cov2Coinfect with the ability to decode the lineage composition from 50,809 deep sequencing data. By resolving the mutational patterns in each sample, Cov2Coinfect can precisely determine the co-infected SARS-CoV-2 variants from deep sequencing data. Results from two independent and parallel projects in the United States achieved a similar co-infection rate of 0.3-0.5 % in SARS-CoV-2 positive samples. Notably, all co-infected variants were highly consistent with the co-circulating SARS-CoV-2 lineages in the regional epidemiology, demonstrating that the co-circulation of different variants is an essential prerequisite for co-infection. Overall, our study not only provides a robust method to identify the co-infected SARS-CoV-2 variants from sequencing samples, but also highlights the urgent need to pay more attention to co-infected patients for better disease prevention and control.

2.
BMC Infect Dis ; 22(1): 641, 2022 Jul 24.
Article in English | MEDLINE | ID: covidwho-1957049

ABSTRACT

BACKGROUND: The COVID-19 pandemic has driven public health intervention strategies, including keeping social distance, wearing masks in crowded places, and having good health habits, to prevent the transmission of the novel coronavirus (SARS-CoV-2). However, it is unknown whether the use of these intervention strategies influences morbidity in other human infectious diseases, such as tuberculosis. METHODS: In this study, three prediction models were constructed to compare variations in PTB incidences after January 2020 without or with intervention includes strict and regular interventions, when the COVID-19 outbreak began in China. The non-interventional model was developed with an autoregressive integrated moving average (ARIMA) model that was trained with the monthly incidence of PTB in China from January 2005 to December 2019. The interventional model was established using an ARIMA model with a continuing intervention function that was trained with the monthly PTB incidence in China from January 2020 to December 2020. RESULTS: Starting with the assumption that no COVID-19 outbreak had occurred in China, PTB incidence was predicted, and then the actual incidence was compared with the predicted incidence. A remarkable overall decline in PTB incidence from January 2020 to December 2020 was observed, which was likely due to the potential influence of intervention policies for COVID-19. If the same intervention strategy is applied for the next 2 years, the monthly PTB incidence would reduce on average by about 1.03 per 100,000 people each month compared with the incidence predicted by the non-interventional model. The annual incidence estimated 59.15 under regular intervention per 100,000 in 2021, and the value would decline to 50.65 with strict interventions. CONCLUSIONS: Our models quantified the potential knock-on effect on PTB incidence of the intervention strategy used to control the transmission of COVID-19 in China. Combined with the feasibility of the strategies, these results suggested that continuous regular interventions would play important roles in the future prevention and control of PTB.


Subject(s)
COVID-19 , Tuberculosis, Pulmonary , COVID-19/epidemiology , COVID-19/prevention & control , China/epidemiology , Humans , Incidence , Pandemics/prevention & control , SARS-CoV-2 , Tuberculosis, Pulmonary/epidemiology , Tuberculosis, Pulmonary/prevention & control
3.
Viruses ; 14(5)2022 05 18.
Article in English | MEDLINE | ID: covidwho-1903490

ABSTRACT

Early identification of adaptive mutations could provide timely help for the control and prevention of the COVID-19 pandemic. The fast accumulation of SARS-CoV-2 sequencing data provides important support, while also raising a great challenge for the recognition of adaptive mutations. Here, we proposed a computational strategy to detect potentially adaptive mutations from their fixed and parallel patterns in the phylogenetic trajectory. We found that the biological meanings of fixed substitution and parallel mutation are highly complementary, and can reasonably be integrated as a fixed and parallel (paraFix) mutation, to identify potentially adaptive mutations. Tracking the dynamic evolution of SARS-CoV-2, 37 sites in spike protein were identified as having experienced paraFix mutations. Interestingly, 70% (26/37) of them have already been experimentally confirmed as adaptive mutations. Moreover, most of the mutations could be inferred as paraFix mutations one month earlier than when they became regionally dominant. Overall, we believe that the concept of paraFix mutations will help researchers to identify potentially adaptive mutations quickly and accurately, which will provide invaluable clues for disease control and prevention.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Mutation , Pandemics , Phylogeny , SARS-CoV-2/genetics
4.
J Med Virol ; 2022 Jun 15.
Article in English | MEDLINE | ID: covidwho-1888759

ABSTRACT

Among numerous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concerns, Omicron is more infectious and immune-escaping, while Delta is more pathogenic. Here, we provide evidence for both intervariant and intravariant recombination of the rapidly evolving new SARS-CoV-2 genomes, including XD/XE/XF and BA.3, raising concerns of potential more infectious, immune-escaping, and disease-causing Omicron and Delta-Omicron variants.

5.
Int J Mol Sci ; 23(11)2022 Jun 02.
Article in English | MEDLINE | ID: covidwho-1884206

ABSTRACT

Being in the epicenter of the COVID-19 pandemic, our lab tested 193,054 specimens for SARS-CoV-2 RNA by diagnostic multiplex reverse transcription polymerase chain reaction (mRT-PCR) starting in March 2020, of which 17,196 specimens resulted positive. To investigate the dynamics of virus molecular evolution and epidemiology, whole genome amplification (WGA) and Next Generation Sequencing (NGS) were performed on 9516 isolates. 7586 isolates with a high quality were further analyzed for the mutation frequency and spectrum. Lastly, we evaluated the utility of the mRT-PCR detection pattern among 26 reinfected patients with repeat positive testing three months after testing negative from the initial infection. Our results show a continuation of the genetic divergence in viral genomes. Furthermore, our results indicate that independent mutations in the primer and probe regions of the nucleocapsid gene amplicon and envelope gene amplicon accumulate over time. Some of these mutations correlate with the changes of detection pattern of viral targets of mRT-PCR. Our data highlight the significance of a continuous genetic divergence on a gene amplification-based assay, the value of the mRT-PCR detection pattern for complementing the clinical diagnosis of reinfection, and the potential for WGA and NGS to identify mutation hotspots throughout the entire viral genome to optimize the design of the PCR-based gene amplification assay.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/diagnosis , COVID-19/genetics , COVID-19 Testing , Clinical Laboratory Techniques/methods , Humans , Multiplex Polymerase Chain Reaction , Pandemics , RNA, Viral/analysis , RNA, Viral/genetics , Reverse Transcriptase Polymerase Chain Reaction , SARS-CoV-2/genetics , Sensitivity and Specificity
6.
Viruses ; 14(5):1087, 2022.
Article in English | MDPI | ID: covidwho-1857303

ABSTRACT

Early identification of adaptive mutations could provide timely help for the control and prevention of the COVID-19 pandemic. The fast accumulation of SARS-CoV-2 sequencing data provides important support, while also raising a great challenge for the recognition of adaptive mutations. Here, we proposed a computational strategy to detect potentially adaptive mutations from their fixed and parallel patterns in the phylogenetic trajectory. We found that the biological meanings of fixed substitution and parallel mutation are highly complementary, and can reasonably be integrated as a fixed and parallel (paraFix) mutation, to identify potentially adaptive mutations. Tracking the dynamic evolution of SARS-CoV-2, 37 sites in spike protein were identified as having experienced paraFix mutations. Interestingly, 70% (26/37) of them have already been experimentally confirmed as adaptive mutations. Moreover, most of the mutations could be inferred as paraFix mutations one month earlier than when they became regionally dominant. Overall, we believe that the concept of paraFix mutations will help researchers to identify potentially adaptive mutations quickly and accurately, which will provide invaluable clues for disease control and prevention.

7.
China CDC Weekly ; 4:1-2, 2022.
Article in English | China CDC Weekly | ID: covidwho-1848172

ABSTRACT

On April 29, 2022, a flight arrived at Baiyun International Airport, Guangzhou City, Guangdong Province, from Amsterdam Schiphol Airport, Netherlands. After the first test of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid at the airport, all passengers were admitted to a quarantine hotel for a routine 14-day medical observation. On April 30, one of the passengers (a 20-year-old Chinese female) was reported positive for coronavirus disease 2019 (COVID-19), and then a nasopharyngeal swab sample was immediately retested on May 1 and reported positive. The patient was fully vaccinated against COVID-19 and completed 14 days of quarantine before flying to China. She denied any history of exposure to COVID-19 cases. After diagnosis, the patient was sent to Foshan Fourth People’s Hospital for treatment. On May 4, 2022, the viral genomic sequence of the patient was obtained using the Illumina MiniSeq platform (Illumina, San Diego, CA, USA), and genotyping results showed that the genome belonged to the Omicron/variant of concern (VOC) sublineage BA.4, with a total of 30 amino acid mutations (V3G, T19I, A27S, G142D, V213G, G339D, S371F, S373P, S375F, T376A, D405N, R408S, K417N, N440K, L452R, S477N, T478K, E484A, F486V, Q498R, N501Y, Y505H, D614G, H655Y, N679K, P681H, N764K, D796Y, Q954H, N969K) and 5 deletions (L24del, P25del, P26del, H69del, V70del) in the Spike protein gene. The phylogenetic tree indicates that the sequenced BA.4 has high similarity to the genome detected in Denmark on May 4, 2022 (GISAID: EPI_ISL_12648960) (Figure 1). The sequence has been deposited in the National Genomics Data Center (under the accession number WGS025540). On May 4, 2022, the World Health Organization reminded to closely monitor Omicron BA.4 subvariants (1). BA.4 is driving the upsurge in South Africa and has rapidly replaced BA.2, with over 50% of sequenced cases since the first week of April 2022 (2). Compared to BA.2, the BA.4 subvariants also showed stronger immune escape to the plasma of 3-dose vaccinees, even vaccinated BA.1 convalescent plasma (3-4). Cases of BA.4 infection have been reported in at least 20 countries, mainly from South Africa (62.39%) (5-6). Researchers are focusing on this subvariant and trying to learn more.

8.
Biosaf Health ; 4(3): 171-178, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1803615

ABSTRACT

The recently emerged Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has quickly spread around the world. Although many consensus mutations of the Omicron variant have been recognized, little is known about its genetic variation during its transmission in the population. Here, we comprehensively analyzed the genetic differentiation and diversity of the Omicron variant during its early outbreak. We found that Omicron achieved more structural variations, especially deletions, on the SARS-CoV-2 genome than the other four variants of concern (Alpha, Beta, Gamma, and Delta) in the same timescale. In addition, the Omicron variant acquired, except for 50 consensus mutations, seven great new non-synonymous nucleotide substitutions during its spread. Three of them are on the S protein, including S_A701V, S_L1081V, and S_R346K, which belong to the receptor-binding domain (RBD). The Omicron BA.1 branch could be divided into five divergent groups spreading across different countries and regions based on these seven novel mutations. Furthermore, we found that the Omicron variant possesses more mutations related to a faster transmission rate than the other SARS-CoV-2 variants by assessing the relationship between the genetic diversity and transmission rate. The findings indicated that more attention should be paid to the significant genetic differentiation and diversity of the Omicron variant for better disease prevention and control.

10.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-332730

ABSTRACT

Background: The COVID-19 pandemic has driven public health intervention strategies, including keeping social distance, wearing masks in crowded places, and having good health habits, to prevent the transmission of the novel coronavirus (SARS-CoV-2). However, it is unknown whether the use of these intervention strategies influences morbidity in other human infectious diseases, such as tuberculosis. Methods: : In this study, three prediction models were constructed to compare variations in PTB incidences after January 2020 without or with intervention includes strict and normalized interventions, when the COVID-19 outbreak began in China. The non-interventional model was developed with an autoregressive integrated moving average (ARIMA) model that was trained with the monthly incidence of PTB in China from January 2005 to December 2019. The interventional model was established using an ARIMA model with a continuing intervention function that was trained with the monthly PTB incidence in China from January 2020 to December 2020. Results: : Starting with the assumption that no COVID-19 outbreak had occurred in China, PTB incidence was predicted, and then the actual incidence was compared with the predicted incidence. A remarkable overall decline in PTB incidence from January 2020 to December 2020 was observed likely due to the influence of intervention policies for COVID-19. If the same intervention strategy is applied for the next 2 years, the monthly PTB incidence would reduce on average by about 1.03 per 100,000 people each month compared with the incidence predicted by the non-interventional model. The annual incidence estimated 59.15 under normalized intervention per 100,000 in 2021, and the value would decline to 50.65 with strict interventions. Conclusions: : Our models quantified the knock-on effect on PTB incidence of the intervention strategy used to control the transmission of COVID-19 in China. Combined with the feasibility of the strategies, these results suggested that continuous normalized interventions would play important roles in the future prevention and control of PTB.

11.
Microbiol Spectr ; 10(2): e0219121, 2022 04 27.
Article in English | MEDLINE | ID: covidwho-1731263

ABSTRACT

SARS-CoV-2 continues adapting to human hosts during the current worldwide pandemic since 2019. This virus evolves through multiple means, such as single nucleotide mutations and structural variations, which has brought great difficulty to disease prevention and control of COVID-19. Structural variation, including multiple nucleotide changes like insertions and deletions, has a greater impact relative to single nucleotide mutation on both genome structures and protein functions. In this study, we found that deletion occurred frequently in not only SARS-CoV-2 but also in other SARS-related coronaviruses. These deletions showed obvious location bias and formed 45 recurrent deletion regions in the viral genome. Some of these deletions showed proliferation advantages, including four high-frequency deletions (nsp6 Δ106-109, S Δ69-70, S Δ144, and Δ28271) that were detected in around 50% of SARS-CoV-2 genomes and other 19 median-frequency deletions. In addition, the association between deletions and the WHO reported variants of concern (VOC) and variants of interest (VOI) of SARS-CoV-2 indicated that these variants had a unique combination of deletion patterns. In the spike (S) protein, the deletions in SARS-CoV-2 were mainly in the N-terminal domain. Some deletions, such as S Δ144/145 and S Δ243-244, have been confirmed to block the binding sites of neutralizing antibodies. Overall, this study revealed a conservative regional pattern and the potential effect of some deletions in SARS-CoV-2 over the whole genome, providing important evidence for potential epidemic control and vaccine development. IMPORTANCE Mutations in SARS-CoV-2 were studied extensively, while only the structure variations on the spike protein were discussed well in previous studies. To study the role of structural variations in virus evolution, we described the distribution of structure variations on the whole genome. Conserved patterns were found of deletions among SARS-CoV-2, SARS-CoV-2-like, and SARS-CoV-like viruses. There were 45 recurrent deletion regions (RDRs) in SARS-CoV-2 generated through the integration of deleted positions. In these regions, four high-frequency deletions parallelly appeared in multiple strains. Furthermore, in the spike protein, the deletions in SARS-CoV-2 were mainly in the N-terminal domain, blocking the binding sites of some neutralizing antibodies, while the structural variations in SARS-related coronavirus were mainly in the N-terminal domain and receptor binding domain. The receptor binding domain is highly related to hosting recognition. The deletions in the receptor binding domain may play a role in host adaption.


Subject(s)
COVID-19 , SARS-CoV-2 , Antibodies, Neutralizing , COVID-19/epidemiology , Humans , Mutation , Nucleotides , SARS-CoV-2/genetics , Spike Glycoprotein, Coronavirus
13.
Brief Bioinform ; 22(2): 1297-1308, 2021 03 22.
Article in English | MEDLINE | ID: covidwho-1343641

ABSTRACT

The life-threatening coronaviruses MERS-CoV, SARS-CoV-1 and SARS-CoV-2 (SARS-CoV-1/2) have caused and will continue to cause enormous morbidity and mortality to humans. Virus-encoded noncoding RNAs are poorly understood in coronaviruses. Data mining of viral-infection-related RNA-sequencing data has resulted in the identification of 28 754, 720 and 3437 circRNAs encoded by MERS-CoV, SARS-CoV-1 and SARS-CoV-2, respectively. MERS-CoV exhibits much more prominent ability to encode circRNAs in all genomic regions than those of SARS-CoV-1/2. Viral circRNAs typically exhibit low expression levels. Moreover, majority of the viral circRNAs exhibit expressions only in the late stage of viral infection. Analysis of the competitive interactions of viral circRNAs, human miRNAs and mRNAs in MERS-CoV infections reveals that viral circRNAs up-regulated genes related to mRNA splicing and processing in the early stage of viral infection, and regulated genes involved in diverse functions including cancer, metabolism, autophagy, viral infection in the late stage of viral infection. Similar analysis in SARS-CoV-2 infections reveals that its viral circRNAs down-regulated genes associated with metabolic processes of cholesterol, alcohol, fatty acid and up-regulated genes associated with cellular responses to oxidative stress in the late stage of viral infection. A few genes regulated by viral circRNAs from both MERS-CoV and SARS-CoV-2 were enriched in several biological processes such as response to reactive oxygen and centrosome localization. This study provides the first glimpse into viral circRNAs in three deadly coronaviruses and would serve as a valuable resource for further studies of circRNAs in coronaviruses.


Subject(s)
Middle East Respiratory Syndrome Coronavirus/genetics , RNA, Circular/genetics , SARS Virus/genetics , SARS-CoV-2/genetics , Humans
14.
Brief Bioinform ; 22(2): 1267-1278, 2021 03 22.
Article in English | MEDLINE | ID: covidwho-1343631

ABSTRACT

Accessory proteins play important roles in the interaction between coronaviruses and their hosts. Accordingly, a comprehensive study of the compositional diversity and evolutionary patterns of accessory proteins is critical to understanding the host adaptation and epidemic variation of coronaviruses. Here, we developed a standardized genome annotation tool for coronavirus (CoroAnnoter) by combining open reading frame prediction, transcription regulatory sequence recognition and homologous alignment. Using CoroAnnoter, we annotated 39 representative coronavirus strains to form a compositional profile for all of the accessary proteins. Large variations were observed in the number of accessory proteins of 1-10 for different coronaviruses, with SARS-CoV-2 and SARS-CoV having the most (9 and 10, respectively). The variation between SARS-CoV and SARS-CoV-2 accessory proteins could be traced back to related coronaviruses in other hosts. The genomic distribution of accessory proteins had significant intra-genus conservation and inter-genus diversity and could be grouped into 1, 4, 2 and 1 types for alpha-, beta-, gamma-, and delta-coronaviruses, respectively. Evolutionary analysis suggested that accessory proteins are more conservative locating before the N-terminal of proteins E and M (E-M), while they are more diverse after these proteins. Furthermore, comparison of virus-host interaction networks of SARS-CoV-2 and SARS-CoV accessory proteins showed that they share multiple antiviral signaling pathways, those involved in the apoptotic process, viral life cycle and response to oxidative stress. In summary, our study provides a tool for coronavirus genome annotation and builds a comprehensive profile for coronavirus accessory proteins covering their composition, classification, evolutionary pattern and host interaction.


Subject(s)
Biological Evolution , COVID-19/virology , SARS-CoV-2/metabolism , Viral Proteins/genetics , Viral Proteins/metabolism , Genes, Viral , Humans , Molecular Sequence Annotation , Open Reading Frames , Protein Interaction Maps , SARS-CoV-2/genetics
15.
Cell Host Microbe ; 29(4): 503-507, 2021 04 14.
Article in English | MEDLINE | ID: covidwho-1309185

ABSTRACT

Since the outbreak of SARS-CoV-2, the etiologic agent of the COVID-19 pandemic, the viral genome has acquired numerous mutations with the potential to increase transmission. One year after its emergence, we now further analyze emergent SARS-CoV-2 genome sequences in an effort to understand the evolution of this virus.


Subject(s)
COVID-19/virology , Evolution, Molecular , Genome, Viral , Mutation , SARS-CoV-2/genetics , COVID-19/immunology , Humans
16.
Cell Res ; 31(4): 404-414, 2021 04.
Article in English | MEDLINE | ID: covidwho-1054016

ABSTRACT

The newly identified Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has resulted in a global health emergency because of its rapid spread and high mortality. The molecular mechanism of interaction between host and viral genomic RNA is yet unclear. We demonstrate herein that SARS-CoV-2 genomic RNA, as well as the negative-sense RNA, is dynamically N6-methyladenosine (m6A)-modified in human and monkey cells. Combined RIP-seq and miCLIP analyses identified a total of 8 m6A sites at single-base resolution in the genome. Especially, epidemic strains with mutations at these identified m6A sites have emerged worldwide, and formed a unique cluster in the US as indicated by phylogenetic analysis. Further functional experiments showed that m6A methylation negatively regulates SARS-CoV-2 infection. SARS-CoV-2 infection also triggered a global increase in host m6A methylome, exhibiting altered localization and motifs of m6A methylation in mRNAs. Altogether, our results identify m6A as a dynamic epitranscriptomic mark mediating the virus-host interaction.


Subject(s)
Adenosine/analogs & derivatives , Genome, Viral , SARS-CoV-2/genetics , Adenosine/metabolism , Animals , COVID-19/pathology , COVID-19/virology , Cell Line , Chlorocebus aethiops , DNA Methylation , Gene Expression Regulation , Host-Pathogen Interactions , Humans , Mutagenesis, Site-Directed , Phylogeny , RNA, Messenger/genetics , SARS-CoV-2/classification , SARS-CoV-2/isolation & purification , SARS-CoV-2/physiology , Vero Cells , Virus Replication
17.
Front Microbiol ; 11: 593857, 2020.
Article in English | MEDLINE | ID: covidwho-979022

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a widespread outbreak of highly pathogenic coronavirus disease 2019 (COVID-19). It is therefore important and timely to characterize interactions between the virus and host cell at the molecular level to understand its disease pathogenesis. To gain insights, we performed high-throughput sequencing that generated time-series data simultaneously for bioinformatics analysis of virus genomes and host transcriptomes implicated in SARS-CoV-2 infection. Our analysis results showed that the rapid growth of the virus was accompanied by an early intensive response of host genes. We also systematically compared the molecular footprints of the host cells in response to SARS-CoV-2, SARS-CoV, and Middle East respiratory syndrome coronavirus (MERS-CoV). Upon infection, SARS-CoV-2 induced hundreds of up-regulated host genes hallmarked by a significant cytokine production, followed by virus-specific host antiviral responses. While the cytokine and antiviral responses triggered by SARS-CoV and MERS-CoV were only observed during the late stage of infection, the host antiviral responses during the SARS-CoV-2 infection were gradually enhanced lagging behind the production of cytokine. The early rapid host responses were potentially attributed to the high efficiency of SARS-CoV-2 entry into host cells, underscored by evidence of a remarkably up-regulated gene expression of TPRMSS2 soon after infection. Taken together, our findings provide novel molecular insights into the mechanisms underlying the infectivity and pathogenicity of SARS-CoV-2.

18.
Virol Sin ; 36(1): 133-140, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-680840

ABSTRACT

The virus receptors are key for the viral infection of host cells. Identification of the virus receptors is still challenging at present. Our previous study has shown that human virus receptor proteins have some unique features including high N-glycosylation level, high number of interaction partners and high expression level. Here, a random-forest model was built to identify human virus receptorome from human cell membrane proteins with an accepted accuracy based on the combination of the unique features of human virus receptors and protein sequences. A total of 1424 human cell membrane proteins were predicted to constitute the receptorome of the human-infecting virome. In addition, the combination of the random-forest model with protein-protein interactions between human and viruses predicted in previous studies enabled further prediction of the receptors for 693 human-infecting viruses, such as the enterovirus, norovirus and West Nile virus. Finally, the candidate alternative receptors of the SARS-CoV-2 were also predicted in this study. As far as we know, this study is the first attempt to predict the receptorome for the human-infecting virome and would greatly facilitate the identification of the receptors for viruses.


Subject(s)
Receptors, Virus/metabolism , Virome/physiology , Computational Biology , Host-Pathogen Interactions , Humans , Membrane Proteins/chemistry , Membrane Proteins/genetics , Membrane Proteins/metabolism , Models, Theoretical , Receptors, Virus/chemistry , Receptors, Virus/genetics , SARS-CoV-2/metabolism , Viral Proteins/metabolism
19.
Cell Host Microbe ; 27(3): 325-328, 2020 03 11.
Article in English | MEDLINE | ID: covidwho-709361

ABSTRACT

An in-depth annotation of the newly discovered coronavirus (2019-nCoV) genome has revealed differences between 2019-nCoV and severe acute respiratory syndrome (SARS) or SARS-like coronaviruses. A systematic comparison identified 380 amino acid substitutions between these coronaviruses, which may have caused functional and pathogenic divergence of 2019-nCoV.


Subject(s)
Betacoronavirus/classification , Coronavirus Infections/virology , Genome, Viral , Phylogeny , Pneumonia, Viral/virology , Amino Acid Substitution , COVID-19 , China , Middle East Respiratory Syndrome Coronavirus , Pandemics , SARS Virus , SARS-CoV-2
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