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1.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.01.19.21250079

ABSTRACT

Viral pandemics, such as Covid-19, pose serious threats to human societies. To control the spread of highly contagious viruses such as SARS-CoV-2, effective test-trace-isolate strategies require population-wide, systematic testing. Currently, RT-qPCR on extracted RNA is the only broadly accepted test for SARS-CoV-2 diagnostics, which bears the risk of supply chain bottlenecks, often exaggerated by dependencies on proprietary reagents. Here, we directly compare the performance of gold standard diagnostic RT-qPCR on extracted RNA to direct input RT-PCR, RT-LAMP and bead-LAMP on 384 primary patient samples collected from individuals with suspected Covid-19 infection. With a simple five minute crude sample inactivation step and one hour of total reaction time, we achieve assay sensitivities of 98% (direct RT-PCR), 93% (bead-LAMP) and 82% (RTLAMP) for clinically relevant samples (diagnostic RT-qPCR Ct <35) and a specificity of >98%. For direct RT-PCR, our data further demonstrate a perfect agreement between real-time and end-point measurements, which allow a simple binary classification similar to the powerful visual readout of colorimetric LAMP assays. Our study provides highly sensitive and specific, easy to implement, rapid and cost-effective alternatives to diagnostic RT-qPCR tests.


Subject(s)
COVID-19
2.
medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.10.28.20217778

ABSTRACT

During a pandemic, mitigation as well as protection of system-critical or vulnerable institutions requires massive 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 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.


Subject(s)
Respiratory Tract Diseases
3.
biorxiv; 2020.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2020.07.15.204339

ABSTRACT

Superspreading events shape the COVID-19 pandemic. Here we provide a national-scale analysis of SARS-CoV-2 outbreaks in Austria, a country that played a major role for virus transmission across Europe and beyond. Capitalizing on a national epidemiological surveillance system, we performed deep whole-genome sequencing of virus isolates from 576 samples to cover major Austrian SARS-CoV-2 clusters. Our data chart a map of early viral spreading in Europe, including the path from low-frequency mutations to fixation. Detailed epidemiological surveys enabled us to calculate the effective SARS-CoV-2 population bottlenecks during transmission and unveil time-resolved intra-patient viral quasispecies dynamics. This study demonstrates the power of integrating deep viral genome sequencing and epidemiological data to better understand how SARS-CoV-2 spreads through populations. Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY


Subject(s)
COVID-19
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