Genome analysis and prevalence of SARS-CoV-2 Indonesian variants and the correlation with the outbreak timeline
Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has undergone multiple mutations, leading to the development of various variants. Objective: To identify the genetic mutations associated with the transmission and virulence of SARS-CoV-2 variants in Indonesia and to examin...
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| Format: | Article |
| Language: | English |
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Indonesian Society for Biochemistry and Molecular Biology
2024-08-01
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| Series: | Acta Biochimica Indonesiana |
| Subjects: | |
| Online Access: | https://pbbmi.org/newjurnal/index.php/actabioina/article/view/163 |
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| _version_ | 1825199581771595776 |
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| author | Maria Prevyolita Indra Muliawan Timotius Christopher Tantokusumo Amalda Siti Anisa Kholis Abdurachim Audah |
| author_facet | Maria Prevyolita Indra Muliawan Timotius Christopher Tantokusumo Amalda Siti Anisa Kholis Abdurachim Audah |
| author_sort | Maria Prevyolita Indra Muliawan |
| collection | DOAJ |
| description |
Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has undergone multiple mutations, leading to the development of various variants.
Objective: To identify the genetic mutations associated with the transmission and virulence of SARS-CoV-2 variants in Indonesia and to examine their correlation with the outbreak timeline.
Methods: We analyzed whole genome sequences of SARS-CoV-2 wild type and variants isolated from Indonesian samples, sourced from GenBank and the GISAID EpiCoV database. The spike glycoprotein gene sequences were examined using the BLAST to identify nucleotide and amino acid changes. Additionally, we investigated the prevalence of these variants and their submission timelines on the GISAID database, correlating them with the outbreak timeline.
Results: Our analysis identified nine amino acid changes in the alpha, beta, and delta variants, and three in the gamma variant, compared to the wild type. A correlation between the submission timelines of SARS-CoV-2 variants and the outbreak timeline indicated that the delta variant (B.1.617.2) likely contributed to the surge in COVID-19 cases from July to September 2021.
Conclusion: Mutations were detected in each variant, emerging at distinct times, and are likely to influence transmission rates and virulence.
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| format | Article |
| id | doaj-art-7ea1b6305e804ca4b0b10c22864e8647 |
| institution | Kabale University |
| issn | 2654-6108 2654-3222 |
| language | English |
| publishDate | 2024-08-01 |
| publisher | Indonesian Society for Biochemistry and Molecular Biology |
| record_format | Article |
| series | Acta Biochimica Indonesiana |
| spelling | doaj-art-7ea1b6305e804ca4b0b10c22864e86472025-02-08T03:04:45ZengIndonesian Society for Biochemistry and Molecular BiologyActa Biochimica Indonesiana2654-61082654-32222024-08-017110.32889/actabioina.163Genome analysis and prevalence of SARS-CoV-2 Indonesian variants and the correlation with the outbreak timelineMaria Prevyolita Indra Muliawan0Timotius Christopher Tantokusumo1Amalda Siti Anisa2Kholis Abdurachim Audah3Department of Biomedical Engineering Swiss German University Tangerang 15143, IndonesiaDepartment of Biomedical Engineering Swiss German University Tangerang 15143, IndonesiaDepartment of Biomedical Engineering Swiss German University Tangerang 15143, IndonesiaDepartment of Biomedical Engineering, Faculty of Life Sciences and Technology, Swiss German University Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has undergone multiple mutations, leading to the development of various variants. Objective: To identify the genetic mutations associated with the transmission and virulence of SARS-CoV-2 variants in Indonesia and to examine their correlation with the outbreak timeline. Methods: We analyzed whole genome sequences of SARS-CoV-2 wild type and variants isolated from Indonesian samples, sourced from GenBank and the GISAID EpiCoV database. The spike glycoprotein gene sequences were examined using the BLAST to identify nucleotide and amino acid changes. Additionally, we investigated the prevalence of these variants and their submission timelines on the GISAID database, correlating them with the outbreak timeline. Results: Our analysis identified nine amino acid changes in the alpha, beta, and delta variants, and three in the gamma variant, compared to the wild type. A correlation between the submission timelines of SARS-CoV-2 variants and the outbreak timeline indicated that the delta variant (B.1.617.2) likely contributed to the surge in COVID-19 cases from July to September 2021. Conclusion: Mutations were detected in each variant, emerging at distinct times, and are likely to influence transmission rates and virulence. https://pbbmi.org/newjurnal/index.php/actabioina/article/view/163CoronavirusCOVID-19Genome analysisIndonesian isolatesMutation |
| spellingShingle | Maria Prevyolita Indra Muliawan Timotius Christopher Tantokusumo Amalda Siti Anisa Kholis Abdurachim Audah Genome analysis and prevalence of SARS-CoV-2 Indonesian variants and the correlation with the outbreak timeline Acta Biochimica Indonesiana Coronavirus COVID-19 Genome analysis Indonesian isolates Mutation |
| title | Genome analysis and prevalence of SARS-CoV-2 Indonesian variants and the correlation with the outbreak timeline |
| title_full | Genome analysis and prevalence of SARS-CoV-2 Indonesian variants and the correlation with the outbreak timeline |
| title_fullStr | Genome analysis and prevalence of SARS-CoV-2 Indonesian variants and the correlation with the outbreak timeline |
| title_full_unstemmed | Genome analysis and prevalence of SARS-CoV-2 Indonesian variants and the correlation with the outbreak timeline |
| title_short | Genome analysis and prevalence of SARS-CoV-2 Indonesian variants and the correlation with the outbreak timeline |
| title_sort | genome analysis and prevalence of sars cov 2 indonesian variants and the correlation with the outbreak timeline |
| topic | Coronavirus COVID-19 Genome analysis Indonesian isolates Mutation |
| url | https://pbbmi.org/newjurnal/index.php/actabioina/article/view/163 |
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