2020
DOI: 10.1101/2020.12.02.20242628
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

McQ – An open-source multiplexed SARS-CoV-2 quantification platform

Abstract: McQ is a SARS-CoV-2 quantification assay that couples early-stage barcoding with high-throughput sequencing to enable multiplexed processing of thousands of samples. McQ is based on homemade enzymes to enable low-cost testing of large sample pools, circumventing supply chain shortages.Implementation of cost-efficient high-throughput methods for detection of RNA viruses such as SARS-CoV-2 is a potent strategy to curb ongoing and future pandemics. Here we describe Multiplexed SARS-CoV-2 Quantification platform (… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
2

Citation Types

0
5
0

Year Published

2021
2021
2021
2021

Publication Types

Select...
2
2

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
(5 citation statements)
references
References 55 publications
(65 reference statements)
0
5
0
Order By: Relevance
“…We hope that continued development and dissemination of open‐source RT‐qPCR methods will help reduce the dependence of clinical testing centers and research labs on black‐box commercial products. Hopeful signs are recent publications describing other testing methods based on homemade enzymes (Bhadra et al., 2020; Mascuch et al., 2020; Vonesch et al., 2020) and growing online resources for open‐source molecular biology (OpenWetWare; Open Enzyme Collection; Pipette Jockey; see Internet Resources).…”
Section: Commentarymentioning
confidence: 99%
See 1 more Smart Citation
“…We hope that continued development and dissemination of open‐source RT‐qPCR methods will help reduce the dependence of clinical testing centers and research labs on black‐box commercial products. Hopeful signs are recent publications describing other testing methods based on homemade enzymes (Bhadra et al., 2020; Mascuch et al., 2020; Vonesch et al., 2020) and growing online resources for open‐source molecular biology (OpenWetWare; Open Enzyme Collection; Pipette Jockey; see Internet Resources).…”
Section: Commentarymentioning
confidence: 99%
“…The advantages of RT‐qPCR for clinical detection of viruses were realized early on (Beuret, 2004; Bustin & Mueller, 2005; Ishiguro et al., 1995; Monpoeho et al., 2002; Ozoemena, Minor, & Afzal, 2004), and the usefulness of this approach was demonstrated, in particular, during the first outbreak of SARS coronavirus (Hui et al., 2004; Jiang et al., 2004; Lau et al., 2003; Ng et al., 2003; Peiris et al., 2003; Poon et al., 2003; Poon et al., 2004). While other methods for rapid viral RNA detection have recently shown promise (Arizti‐Sanz et al., 2020; Bloom et al., 2020; Dao Thi et al., 2020; Vonesch et al., 2020; Zhang et al., 2020), RT‐qPCR has remained the state of the art for clinical diagnostics and has been the primary workhorse for SARS‐CoV‐2 testing.…”
Section: Commentarymentioning
confidence: 99%
“…In response to these limitations, many groups have described the successful implementation of homemade RT-PCR and RT-LAMP protocols based on homebrewed enzymes. 15,[20][21][22][23][24][25][26][27][28] Here, we describe the in-house production of RT-LAMP reactions for SARS-CoV-2 from homebrewed Moloney murine leukemia virus (M-MLV) reverse transcriptase and BstLF polymerase. We compare their performance to commercial reactions and tested their ability to detect SARS-CoV-2 from RNA extracted from clinical nasopharyngeal samples.…”
Section: Introductionmentioning
confidence: 99%
“…Other studies provide procedures to prepare reagents and a ‘blueprint’ that can be followed to replicate RT-qPCR kits in academic laboratories to overcome test shortages[ 19 , 20 ]. In addition, a barcoding system has also been proposed to reduce manipulation and scale the number of samples per sequencing run[ 21 ]. Using this open-source multiplexed platform together with homemade enzymes and non-protected buffers considerably reduces the cost per sample.…”
Section: Introductionmentioning
confidence: 99%