Author: Jonathan L Schmid-Burgk; David Li; David Feldman; Mikolaj Slabicki; Jacob Borrajo; Jonathan Strecker; Brian Cleary; Aviv Regev; Feng Zhang
Title: LAMP-Seq: Population-Scale COVID-19 Diagnostics Using a Compressed Barcode Space Document date: 2020_4_8
ID: 68ps3uit_4
Snippet: Here, we propose LAMP-Seq, a novel protocol that would allow for population-scale testing using massively parallel RT-LAMP (Nagamine et al., 2002; Notomi et al., 2000) by employing 4 sample-specific barcodes. This approach requires only a single heating step for each individual sample (i.e., nasal swab, oropharyngeal swab, nasal wash, fecal sample, or potentially sputum), followed by pooled processing, parallelizable deep sequencing, and standard.....
Document: Here, we propose LAMP-Seq, a novel protocol that would allow for population-scale testing using massively parallel RT-LAMP (Nagamine et al., 2002; Notomi et al., 2000) by employing 4 sample-specific barcodes. This approach requires only a single heating step for each individual sample (i.e., nasal swab, oropharyngeal swab, nasal wash, fecal sample, or potentially sputum), followed by pooled processing, parallelizable deep sequencing, and standard computational analysis. By using a simple thermal protocol for individual samples and pooling many samples prior to resource-intensive steps, the requirement for specialized reagents, equipment, and labor is greatly reduced as compared to established RT-qPCR protocols. Unique tracking of tens of millions of samples as well as asynchronous testing logistics can be obtained by additionally employing a compressed barcode space. Below, we describe the design and initial validation of the method and simulated barcoding strategies.
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