SARSeq, a robust and highly multiplexed NGS assay for parallel detection of SARS-CoV2 and other respiratory infections

التفاصيل البيبلوغرافية
العنوان: SARSeq, a robust and highly multiplexed NGS assay for parallel detection of SARS-CoV2 and other respiratory infections
المؤلفون: Bence Hajdusits, Justine Schaeffer, Alexander Stark, Robert Heinen, Marcus Martin Strobl, Aleksandr Bykov, Ramesh Yelagandula, Ulrich Elling, Alexander Zoufaly, Sebija Izetbegovic, Franz Allerberger, Amina Kurtovic-Kozaric, Manuela Foedinger, Tamara Seitz, Alexander Vogt, Peter Hufnagl, Erna Suljic, Darja Kordic, Luisa Cochella, Kristina Uzunova, Juliane Christina Baar, Vienna Covid Detection Initiative, Ezgi Oezkan
بيانات النشر: Cold Spring Harbor Laboratory, 2020.
سنة النشر: 2020
مصطلحات موضوعية: Saliva analysis, Computer science, Sample (material), Computational biology, Parallel detection, False positive rate, Amplicon, Multiplexing, Massively parallel, DNA sequencing
الوصف: During a pandemic, mitigation as well as protection of system-critical or vulnerable institutions requires massively parallel, yet cost-effective testing to monitor the spread of agents such as the current SARS-CoV2 virus. Here we present SARSeq, saliva analysis by RNA sequencing, as an approach to monitor presence of SARS-CoV2 and other respiratory viruses performed on tens of thousands of samples in parallel. SARSeq is based on next generation sequencing of multiple amplicons generated in parallel in a multiplexed RT-PCR reaction. It relies on a two-dimensional unique dual indexing strategy using four indices in total, for unambiguous and scalable assignment of reads to individual samples. We calibrated this method using dilutions of synthetic RNA and virions to show sensitivity down to a few molecules, and applied it to hundreds of patient samples validating robust performance across various sample types. Double blinded benchmarking to gold-standard quantitative RT-PCR performed in a clinical setting and a human diagnostics laboratory showed robust performance up to a Ct of 36. The false positive rate, likely due to cross contamination during sample pipetting, was estimated at 0.04-0.1%. In addition to SARS-CoV2, SARSeq detects Influenza A and B viruses as well as human rhinovirus and can be easily expanded to include detection of other pathogens. In sum, SARSeq is an ideal platform for differential diagnostic of respiratory diseases at a scale, as is required during a pandemic.
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::636d34605a3e1f32e0089b4f4d058ae5Test
https://doi.org/10.1101/2020.10.28.20217778Test
حقوق: OPEN
رقم الانضمام: edsair.doi...........636d34605a3e1f32e0089b4f4d058ae5
قاعدة البيانات: OpenAIRE