STREAMLINED IDENTIFICATION AND CHARACTERIZATION OF VIRAL STRAINS

Overcoming the top 9 bioinformatics challenges in the time of COVID-19

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Chapter 3: Case Study: Rapid Analysis of Viral Strains During the COVID-19 Pandemic

Case Study: Rapid analysis of viral strains during the COVID-19 pandemic

While many researchers can find commercial or open-source software solutions that are sufficient to perform their viral genome analysis, sometimes the sequencing protocols evolve more quickly than the software. This has been especially true during the COVID-19 pandemic, when innovative technologies were developed to support rapid sequencing of a high volume of patient samples. One example is the ARTIC Network, which employs MinION sequencing to support the creation of real- time epidemiological data.

DNASTAR recently partnered with Impetus Bioscience in Germany to develop software to analyze Oxford Nanopore reads generated through the ARTIC protocol. The group was using this protocol to sequence and identify SARS-coV-2 strains in the German population but needed a comprehensive software solution to get from sequencing data to useful results. The team at Impetus didn’t have the resources to develop or modify bioinformatics command line tools, and time was of the essence.

Working closely with their team, DNASTAR developed a software solution that enabled researchers to input sequencing data, perform assembly and visualize results without any special bioinformatics expertise. With the help of DNASTAR software, the team was able to quickly and easily analyze thousands of samples.

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“In our Lab we are analysing COVID 19 samples by PCR. Since Feb 2021 5% of COVID 19 positive samples must be sequenced in Germany. Therefore, we used the Oxford Nanopore technic. The sequencing technic runs very well, but for the data analysis you cannot get a commercial software package from Oxford Nanopore. In the community you can find some protocols, but these protocols are not plug and play, if you are not familiar with bioinformatics (I mean writing programs). So, we looked for an easy-to-handle analysis tool. With the DNASTAR we can analyse the data set for 1 Sample in 5-10 min.

I believe many people have a problem with handling the Oxford Nanopore data, because the sequencing itself is easy to handle in every lab, which is a big advantage (time and money). But many small labs like use have no bioinformatics for data analysis. With DNASTAR this problem can be solved.”