McQ - An open-source multiplexed SARS-CoV-2 quantification platform
Vonesch, S. C.; Bredikhin, D.; Dobrev, N.; Villacorta, L.; Kleinendorst, R.; Cacace, E.; Flock, J.; Frank, M.; Jung, F.; Kornienko, J.; Mitosch, K.; Osuna-Lopez, M.; Zimmermann, J.; Goettig, S.; Hamprecht, A.; Kraeusslich, H.-G.; Knop, M.; Typas, A.; Steinmetz, L. M.; Benes, V.; Remans, K.; Krebs, A. R.
Show 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 (McQ), an in-expensive scalable framework for SARS-CoV-2 quantification in saliva samples. McQ is based on the parallel sequencing of barcoded amplicons generated from SARS- CoV-2 genomic RNA. McQ uses indexed, target-specific reverse transcription (RT) to generate barcoded cDNA for amplifying viral- and human-specific regions. The barcoding system enables early sample pooling to reduce hands-on time and makes the ap-proach scalable to thousands of samples per sequencing run. Robust and accurate quantification of viral load is achieved by measuring the abundance of Unique Molecular Identifiers (UMIs) introduced during reverse transcription. The use of homemade reverse transcriptase and polymerase enzymes and non-proprietary buffers reduces RNA to library reagent costs to 92 cents/sample and circumvents potential supply chain short-ages. We demonstrate the ability of McQ to robustly quantify various levels of viral RNA in 838 clinical samples and accu-rately diagnose positive and negative control samples in a test-ing workflow entailing self-sampling and automated RNA ex-traction from saliva. The implementation of McQ is modular, scalable and could be extended to other pathogenic targets in future.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- SARSeq, a robust and highly multiplexed NGS assay for parallel detection of SARS-CoV2 and other respiratory infections 97%
- Development and Implementation of a scalable and versatile test for COVID-19 diagnostics in rural communities 96%
- Laboratory validation of a clinical metagenomic next-generation sequencing assay for respiratory virus detection and discovery 96%
Similar papers in this journal
- Sensitive detection and quantification of SARS-CoV-2 in saliva 95%
- Real-time SARS-CoV-2 diagnostic and variants tracking over multiple candidates using nanopore DNA sequencing 94%
- Validation of a rapid, saliva-based, and ultra-sensitive SARS-CoV-2 screening system for a pandemic-scale infection surveillance 94%
Similar papers in this journal
- Lightning Fast and Highly Sensitive Full-Length Single-cell sequencing using FLASH-Seq 94%
- Highly accurate barcode and UMI error correction using dual nucleotide dimer blocks allows direct single-cell nanopore transcriptome sequencing 93%
- Sequencing by avidity enables high accuracy with low reagent consumption 92%
Similar papers in this journal
- Sensitive extraction-free SARS-CoV-2 RNA virus detection using a novel RNA preparation method 95%
- Bacterial cell-free DNA profiling reveals co-elevation of multiple bacteria in newborn foals with suspected sepsis 92%
- Resolving cellular systems by ultra-sensitive and economical single-cell transcriptome filtering 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.