Magnetic hydrogel particles improve nanopore sequencing of SARS-CoV-2 and other respiratory viruses.

Presented here is a magnetic hydrogel particle enabled workflow for capturing and concentrating SARS-CoV-2 from diagnostic remnant swab samples that significantly improves sequencing results using the Oxford Nanopore Technologies MinION sequencing platform. Our approach utilizes a novel affinity-based magnetic hydrogel particle, circumventing low input sample volumes and allowing for both rapid manual and automated high throughput workflows that are compatible with Nanopore sequencing. This approach enhances standard RNA extraction protocols, providing up to 40 × improvements in viral mapped reads, and improves sequencing coverage by 20-80% from lower titer diagnostic remnant samples. Furthermore, we demonstrate that this approach works for contrived influenza virus and respiratory syncytial virus samples, suggesting that it can be used to identify and improve sequencing results of multiple viruses in VTM samples. These methods can be performed manually or on a KingFisher automation platform.

Hydrogel particles improve detection of SARS-CoV-2 RNA from multiple sample types.

Here we present a rapid and versatile method for capturing and concentrating SARS-CoV-2 from contrived transport medium and saliva samples using affinity-capture magnetic hydrogel particles. We demonstrate that the method concentrates virus from 1 mL samples prior to RNA extraction, substantially improving detection of virus using real-time RT-PCR across a range of viral titers (100-1,000,000 viral copies/mL) and enabling detection of virus using the 2019 nCoV CDC EUA Kit down to 100 viral copies/mL. This method is compatible with commercially available nucleic acid extraction kits (i.e., from Qiagen) and a simple heat and detergent method that extracts viral RNA directly off the particle, allowing a sample processing time of 10 min. We furthermore tested our method in transport medium diagnostic remnant samples that previously had been tested for SARS-CoV-2, showing that our method not only correctly identified all positive samples but also substantially improved detection of the virus in low viral load samples. The average improvement in cycle threshold value across all viral titers tested was 3.1. Finally, we illustrate that our method could potentially be used to enable pooled testing, as we observed considerable improvement in the detection of SARS-CoV-2 RNA from sample volumes of up to 10 mL.