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Comparative Transcriptome Analysis Reveals the Intensive Early Stage Responses of Host Cells to SARS-CoV-2 Infection.

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.

SUBMITTER: Sun J

PROVIDER: S-EPMC7723856 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Comparative Transcriptome Analysis Reveals the Intensive Early Stage Responses of Host Cells to SARS-CoV-2 Infection.

Sun Jiya J Ye Fei F Wu Aiping A Yang Ren R Pan Mei M Sheng Jie J Zhu Wenjie W Mao Longfei L Wang Ming M Xia Zanxian Z Huang Baoying B Tan Wenjie W Jiang Taijiao T

Frontiers in microbiology 20201125

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 ...[more]

PMID: 33324374

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Project description:Effective systems for the analysis of molecular data are fundamental for monitoring the spread of infectious diseases and studying pathogen evolution. The rapid identification of emerging viral strains, and/or genetic variants potentially associated with novel phenotypic features is one of the most important objectives of genomic surveillance of human pathogens and represents one of the first lines of defense for the control of their spread. During the COVID 19 pandemic, several taxonomic frameworks have been proposed for the classification of SARS-Cov-2 isolates. These systems, which are typically based on phylogenetic approaches, represent essential tools for epidemiological studies as well as contributing to the study of the origin of the outbreak. Here, we propose an alternative, reproducible, and transparent phenetic method to study changes in SARS-CoV-2 genomic diversity over time. We suggest that our approach can complement other systems and facilitate the identification of biologically relevant variants in the viral genome. To demonstrate the validity of our approach, we present comparative genomic analyses of more than 175,000 genomes. Our method delineates 22 distinct SARS-CoV-2 haplogroups, which, based on the distribution of high-frequency genetic variants, fall into four major macrohaplogroups. We highlight biased spatiotemporal distributions of SARS-CoV-2 genetic profiles and show that seven of the 22 haplogroups (and of all of the four haplogroup clusters) showed a broad geographic distribution within China by the time the outbreak was widely recognized-suggesting early emergence and widespread cryptic circulation of the virus well before its isolation in January 2020. General patterns of genomic variability are remarkably similar within all major SARS-CoV-2 haplogroups, with UTRs consistently exhibiting the greatest variability, with s2m, a conserved secondary structure element of unknown function in the 3'-UTR of the viral genome showing evidence of a functional shift. Although several polymorphic sites that are specific to one or more haplogroups were predicted to be under positive or negative selection, overall our analyses suggest that the emergence of novel types is unlikely to be driven by convergent evolution and independent fixation of advantageous substitutions, or by selection of recombined strains. In the absence of extensive clinical metadata for most available genome sequences, and in the context of extensive geographic and temporal biases in the sampling, many questions regarding the evolution and clinical characteristics of SARS-CoV-2 isolates remain open. However, our data indicate that the approach outlined here can be usefully employed in the identification of candidate SARS-CoV-2 genetic variants of clinical and epidemiological importance.

Project description:BackgroundAgarwood is a valuable Chinese medicinal herb and spice that is produced from wounded Aquilaria spp., is widely used in Southeast Asia and is highly traded on the market. The lack of highly responsive Aquilaria lines has seriously restricted agarwood yield and the development of its industry. In this article, a comparative transcriptome analysis was carried out between ordinary A. sinensis and Chi-Nan germplasm, which is a kind of A. sinensis tree with high agarwood-producing capacity in response to wounding stress, to elucidate the molecular mechanism underlying wounding stress in different A. sinensis germplasm resources and to help identify and breed high agarwood-producing strains.ResultsA total of 2427 and 1153 differentially expressed genes (DEGs) were detected in wounded ordinary A. sinensis and Chi-Nan germplasm compared with the control groups, respectively. KEGG enrichment analysis revealed that genes participating in starch metabolism, secondary metabolism and plant hormone signal transduction might play major roles in the early regulation of wound stress. 86 DEGs related to oxygen metabolism, JA pathway and sesquiterpene biosynthesis were identified. The majority of the expression of these genes was differentially induced between two germplasm resources under wounding stress. 13 candidate genes related to defence and sesquiterpene biosynthesis were obtained by WGCNA. Furthermore, the expression pattern of genes were verified by qRT-PCR. The candidate genes expression levels were higher in Chi-Nan germplasm than that in ordinary A. sinensis during early stage of wounding stress, which may play important roles in regulating high agarwood-producing capacity in Chi-Nan germplasm.ConclusionsCompared with A. sinensis, Chi-Nan germplasm invoked different biological processes in response to wounding stress. The genes related to defence signals and sesquiterepene biosynthesis pathway were induced to expression differentially between two germplasm resources. A total of 13 candidate genes were identified, which may correlate with high agarwood-producting capacity in Chi-Nan germplasm during the early stage of wounding stress. These genes will contribute to the development of functional molecular markers and the rapid breeding highly of responsive Aquilaria lines.

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Comparative Transcriptome Analysis Reveals the Intensive Early Stage Responses of Host Cells to SARS-CoV-2 Infection.

Publications

Comparative Transcriptome Analysis Reveals the Intensive Early Stage Responses of Host Cells to SARS-CoV-2 Infection.

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