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Updated: Dec 13, 2025

Live Imaging and Quantification of Viral Infection in K18 hACE2 Transgenic Mice Using Reporter-Expressing Recombinant SARS-CoV-2
Published on: November 5, 2021
Deciphering the co-adaptation of codon usage between respiratory coronaviruses and their human host uncovers
1Shenzhen Nambou1 Biotech, 506, Block B, West Silicon Valley, 5010 Baoan Avenue, Baoan District, Shenzhen, China.
Abstract:
Coronavirus disease 2019 (COVID-19) has caused thousands of deaths worldwide and has become an urgent public health concern. The extraordinary interhuman transmission of this disease has urged scientists to examine the various facets of its pathogenic agent, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Herein, based on publicly available genomic data, we analyzed the codon usage co-adaptation profiles of SARS-CoV-2 and other respiratory coronaviruses (CoVs) with their human host, identified CoV-responsive human genes and their functional roles on the basis of both the relative synonymous codon usage (RSCU)-based correlation of viral genes with human genes and differential gene expression analysis, and predicted potential drugs for COVID-19 treatment based on these genes. The relatively high codon adaptation index (CAI) values (>0.70) signposted the gene expressivity efficiency of CoVs in human. The ENc-GC3 plot indicated that SARS-CoV-2 genome was under strict selection pressure while SARS-CoV and MERS-CoV were under selection and mutational pressures. The RSCU-based correlation analysis indicated that the viral genomes shared similar codons with a panoply of human genes. The merging of RSCU-based correlation data and SARS-CoV-2-responsive differentially expressed genes allowed the identification of human genes potentially affected by SARS-CoV-2 infection. Functional enrichment analysis indicated that these genes were enriched in biological processes and pathways related to host response to viral infection and immune response. Using the drug-gene interaction database, we screened a list of drugs that could target these genes as potential COVID-19 therapeutics. Our findings not only will contribute in vaccine development but also provide a useful set of drugs that could guide practitioners in strategical monitoring of COVID-19. We recommend practitioners to scrupulously screen this list of predicted drugs in order to authenticate those qualified for treating COVID-19 symptoms.
Insights
Researchers analyzed SARS-CoV-2 codon usage and identified human genes affected by the virus. This study predicts potential drugs for COVID-19 treatment and aids vaccine development.
Area of Science:
- Genomics
- Virology
- Computational Biology
Background:
- Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, is a global health crisis.
- Understanding SARS-CoV-2's interaction with the human host is crucial for developing effective treatments.
Purpose of the Study:
- To analyze codon usage co-adaptation profiles of SARS-CoV-2 and other respiratory coronaviruses (CoVs) with their human host.
- To identify CoV-responsive human genes and their functional roles.
- To predict potential drugs for COVID-19 treatment based on identified genes.
Main Methods:
- Analysis of publicly available genomic data.
- Relative Synonymous Codon Usage (RSCU)-based correlation between viral and human genes.
- Differential gene expression analysis.
- Functional enrichment analysis.
- Drug-gene interaction database screening.
Main Results:
- High Codon Adaptation Index (CAI) values (>0.70) indicate efficient CoV gene expression in humans.
- SARS-CoV-2 genome shows strict selection pressure; SARS-CoV and MERS-CoV exhibit selection and mutational pressures.
- Identified human genes potentially affected by SARS-CoV-2 infection through RSCU correlation and differential expression.
- Affected human genes are enriched in host response to viral infection and immune response pathways.
Conclusions:
- The study contributes to vaccine development strategies.
- Identified genes and predicted drugs offer guidance for COVID-19 monitoring and treatment.
- Further screening of predicted drugs is recommended for COVID-19 therapeutic validation.
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