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_18
Snippet: A major advantage of the proposed method is that early pooling allows for scalable logistics (a hypothetical deployment protocol is provided in Suppl. Note 2). To that end, one or several barcode sequences need to be inserted in the forward inner primer (FIP) or backward inner primer (BIP) primer used during the RT-LAMP reaction, which we experimentally validated. We consider that one limitation of the presented approach is that skewing of sample.....
Document: A major advantage of the proposed method is that early pooling allows for scalable logistics (a hypothetical deployment protocol is provided in Suppl. Note 2). To that end, one or several barcode sequences need to be inserted in the forward inner primer (FIP) or backward inner primer (BIP) primer used during the RT-LAMP reaction, which we experimentally validated. We consider that one limitation of the presented approach is that skewing of sample representation at the pooling stage may affect testing sensitivity. Although in initial tests, the LAMP reaction saturated in positive samples largely independently of template concentrations, thus potentially equalizing the representation across positive samples in an advantageous manner (Fig. 1E) , the reaction might also add random skewing to pooled samples; however, preliminary modeling suggested that pooling 100,000 samples per NextSeq run offers robust detection even assuming linear amplification of anticipated spread of viral loads (Supplementary Note 1). Remaining critical parameters to establish are the sensitivity of the RT-LAMP reaction using unpurified swab samples, the stability of RT-LAMP reactions during shipment, and, most importantly, the timely regulatory and ethical assessment of this novel testing approach for clinical validation.
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