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| Funder | NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES |
|---|---|
| Recipient Organization | University of California Los Angeles |
| Country | United States |
| Start Date | Jul 11, 2023 |
| End Date | Jun 30, 2028 |
| Duration | 1,816 days |
| Number of Grantees | 2 |
| Roles | Co-Investigator; Principal Investigator |
| Data Source | NIH (US) |
| Grant ID | 10886137 |
This application aims to develop improved methods for detecting novel pathogens that can be deployed on a large scale and are flexible to multiple pathogens. The method uses the power of next generation sequencing technology to analyse hundreds of thousands of samples simultaneously. In contrast to standard clinical testing, where one person's sample is tested in a single tube, mass testing labels each person's sample with a unique piece of DNA that acts as a molecular barcode, then pools multiple samples together so that they can be jointly tested.
DNA sequencing is then used to detect those samples with virus in the pool of hundreds of thousands of individuals, and assign the virus to the samples it came from on the basis of the molecular barcodes. A bench top sequencer can process tens of thousands a day. A larger machine generates enough sequence to run up to hundreds of thousands of tests in one day.
Our aim is to make it possible for a moderately well-equipped molecular biology laboratory to be able to process tens of thousands of samples without much investment. We have successfully deployed SwabSeq testing at the high-complexity, CLIA-certified, UCLA SwabSeq COVID19 Testing laboratory. Our work has demonstrated the utility for high-throughput asymptomatic testing and with additional improvements can increase testing capacity by orders of magnitude, making it possible to deploy testing on a population scale.
Our sequencing-based approach can be extended to also detect viral variants at the same time and to other viral pathogens. Mass testing will f nd asymptomatic carriers and thus inform public health policies so that containment of infection will be effective.
University of California Los Angeles
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