April 30, 2020, by Lexi Earl

Genomic sequencing and Covid-19

Deep Seq, the University of Nottingham’s state of the art high-throughput genomics facility, is currently part of the COVID-19 Genomics UK Consortium, mapping the spread of coronavirus. We spoke to Prof Matt Loose and Dr Christopher Moore, about the work, the equipment they use, and how they are adjusting to this new challenge.

Tell us about Deep Seq. What sort of work do you normally undertake?

Deep Seq is the University of Nottingham’s high-throughput genomics facility. The projects that we carry out are very diverse and come from researchers across the University as well as from other institutions. In a single week, projects we are working on could include analysing the microbial species associated with a particular plant’s roots, mapping genome rearrangements in human cancer cell lines, analysing gene expression changes in zebrafish blood stem cell development and sequencing the genome of an emerging crop. Researchers often come to us with a genomics research question, and as long as they can obtain the DNA or RNA from their model system of interest we can normally help them find an appropriate way to answer it with the technologies we have in Deep Seq.

What kinds of equipment do you use?

Deep Seq has a range of equipment, each of which has its own individual strengths. These include Illumina short read sequencers, Oxford Nanopore long read sequencers, a Bionano optical mapper, automation robots and various other sample preparation and QC platforms. By not focusing too much on any one technology we have tried to make a broad range of techniques and services available to UoN researchers to enable their research. The Future Food Beacon’s support has been crucial in allowing us to expand the diversity of technologies available within Deep Seq. An example of one of the Beacon’s investments is the Oxford Nanopore GridION X5, which has rapidly become one of the most used pieces of equipment in the lab because of its versatility and convenience. It allows us to perform medium-throughput Nanopore long read sequencing with a powerful dedicated computer on board to process the data.

 

How does this equipment work?

Oxford Nanopore sequencing technology is based on DNA passing through membrane-embedded “nanopores” while a voltage is applied to the membrane. As the DNA passes through the nanopore there is a disruption of the ionic current across the pore producing a signal that can be detected by an underlying sensor array. The level of disruption in the current is determined by the combination of bases that are passing through the nanopore at any one time. The change in signal detected can be analysed by algorithms, which convert this into readable DNA sequences. Once this conversion has taken place the sequence data is available immediately for analysis, so unlike many other sequencing platforms it allows real time analysis of the data being produced. Each flow cell has a membrane, which has a possible 512 nanopore channels that can be sequencing at the same time. By using the GridION we can run up to five flow cells at once, meaning that we can be collecting and analysing sequence data from up to 2560 pieces of DNA at the same time, which is pretty cool.

What kinds of projects have you done with it previously? How does the GridION help the research?

One of the major advantages of Oxford Nanopore technology is that you can sequence really long pieces of DNA as single sequences. This makes the data really useful for assembling genomes. To use an analogy, it’s like trying to do a 300 piece jigsaw compared to a 10,000 piece jigsaw: bigger pieces mean less pieces and make an easier jigsaw. We often use the GridION for sequencing relatively small genomes (<600 Mb) and metagenomics. Recent projects have included sequencing the genomes of bambara groundnut and mealworm as well as performing metagenomic sequencing on samples from cholera patients. The GridION has also been key to the Loose lab’s work in developing and optimising “Read Until”, a software based selective sequencing approach, which allows targeted re-sequencing of specific regions in a genome. Most recently the Deep Seq team has been using the GridION to help us with our work for the COVID-19 Genomics UK Consortium.

 What are you doing now as part of the Consortium?

We are currently sequencing SARS-CoV-2 genomes from COVID-19 patient derived samples. These viral genome sequences that we produce feed into the consortium, which comprises of the NHS, Public Health Agencies as well as academic institutions. These data will help increase understanding of the dynamics of transmission in the UK and globally, especially as we closely monitor the waves that may emerge over time.

What are the logistics of working on Covid-19 & what challenges have you faced?

We have had some logistical challenges to overcome in terms of sample processing, ordering reagents and maintaining social distancing. We have been working closely with one of the UoN virology groups led by Prof Jonathan Ball and NUH Clinical Microbiology to obtain processed samples for us to sequence. The increase in testing in recent weeks means more samples are arriving at the hospital, which is bringing benefits and challenges. Our initial sequencing strategy had a modest throughput, however we are now looking at ways to scale this up while maintaining a minimal lab presence.

What have you learnt from this experience?

I think we’ve learnt a lot, particularly about how well we work as a team even in difficult situations such as this. We have worked together to adapt protocols, perform the sequencing, create bioinformatics pipelines and solve the logistical difficulties of ordering and delivery, all while maintaining physical separation from each other. It has also been great to see how other UoN researchers and the wider research community have been able to come together and pool resources on this project and others at such short notice.

Links:

Artic Network COVID-19 sequencing protocol (that Deep Seq have based their sequencing approach on)

Global Initiative on Sharing All Influenza (to which some of the data is being contributed)

Nextstrain SARS-CoV-2 genome data visualisation

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