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Pillay S, San JE, Tshiabuila D, Naidoo Y, Pillay Y, Maharaj A, Anyaneji UJ, Wilkinson E, Tegally H, Lessells RJ, Baxter C, de Oliveira T, Giandhari J. Evaluation of miniaturized Illumina DNA preparation protocols for SARS-CoV-2 whole genome sequencing. PLoS One 2023; 18:e0283219. [PMID: 37099540 PMCID: PMC10132692 DOI: 10.1371/journal.pone.0283219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 03/03/2023] [Indexed: 04/27/2023] Open
Abstract
The global pandemic caused by SARS-CoV-2 has increased the demand for scalable sequencing and diagnostic methods, especially for genomic surveillance. Although next-generation sequencing has enabled large-scale genomic surveillance, the ability to sequence SARS-CoV-2 in some settings has been limited by the cost of sequencing kits and the time-consuming preparations of sequencing libraries. We compared the sequencing outcomes, cost and turn-around times obtained using the standard Illumina DNA Prep kit protocol to three modified protocols with fewer clean-up steps and different reagent volumes (full volume, half volume, one-tenth volume). We processed a single run of 47 samples under each protocol and compared the yield and mean sequence coverage. The sequencing success rate and quality for the four different reactions were as follows: the full reaction was 98.2%, the one-tenth reaction was 98.0%, the full rapid reaction was 97.5% and the half-reaction, was 97.1%. As a result, uniformity of sequence quality indicated that libraries were not affected by the change in protocol. The cost of sequencing was reduced approximately seven-fold and the time taken to prepare the library was reduced from 6.5 hours to 3 hours. The sequencing results obtained using the miniaturised volumes showed comparability to the results obtained using full volumes as described by the manufacturer. The adaptation of the protocol represents a lower-cost, streamlined approach for SARS-CoV-2 sequencing, which can be used to produce genomic data quickly and more affordably, especially in resource-constrained settings.
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Affiliation(s)
- Sureshnee Pillay
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - James Emmanuel San
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Derek Tshiabuila
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Yeshnee Naidoo
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Yusasha Pillay
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Akhil Maharaj
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Ugochukwu J. Anyaneji
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Eduan Wilkinson
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Houriiyah Tegally
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Richard J. Lessells
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
- Center for AIDS Programme of Research in South Africa (CAPRISA), Durban, South Africa
| | - Cheryl Baxter
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
- Center for AIDS Programme of Research in South Africa (CAPRISA), Durban, South Africa
| | - Tulio de Oliveira
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
- Center for AIDS Programme of Research in South Africa (CAPRISA), Durban, South Africa
- Department of Global Health, University of Washington, Seattle, WA, United States of America
| | - Jennifer Giandhari
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
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