含羞草传媒

With an eye on COVID-19 variants, U of T, Sinai Health researchers design next-gen sequencing platform

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An automated robotics platform designed by U of T and Sinai Health researchers is capable of analyzing thousands of COVID-19 patient samples in a single run with a high accuracy rate (photo courtesy of Sinai Health)

A robotics platform designed by Sinai Health and 含羞草传媒 researchers to screen COVID-19 samples could revolutionize how labs track the spread of viruses and other pathogens.

The next-generation, ultra-high-throughput sequencing system, called C19-SPAR-Seq, has a sensitivity rate greater than 95 per cent during peak virus onset and transmissibility, and over 90 per cent in samples with a low viral load.

The researchers鈥 approach .

鈥淚dentifying positive samples quickly and accurately is critical in beating this pandemic,鈥 said Jeff Wrana, a professor of molecular genetics in U of T鈥檚 Temerty Faculty of Medicine and senior investigator at Sinai Health鈥檚 Lunenfeld-Tanenbaum Research Institute (LTRI).

鈥淲ith new and potentially dangerous variants now circulating, this platform is scalable, automated and capable of analyzing thousands of COVID-19 patient samples in a single instrument run.鈥

Wrana and colleagues are now using the system to screen all positive samples identified in the shared clinical diagnostics lab at Sinai Health and University Health Network. The goal is to identify known and novel variants that emerge in the population.

鈥淏y systematically screening all positives using C19-SPAR-Seq, we can provide rapid feedback on the frequency of known variants in the population and quantitate their expansion 鈥 and most importantly, enable early discovery of emergent variants,鈥 Wrana said, adding that, as SARS-CoV-2 continues to evolve, it will be critical to catalogue variants that might evade immune responses in previously infected or vaccinated people.

A team of trainees shifted from other areas of research to help develop and validate the platform, allowing the group to go from concept to published paper in under 12 months.

鈥淭he system is extremely reliable and readily adaptable,鈥 said Javier Hernandez, a doctoral student in molecular genetics at U of T who was a co-lead author on the study with Marie-Ming Aynaud and Seda Barutcu.

鈥淭he turnaround is approximately 24 hours. It鈥檚 very simple as we鈥檝e automated practically every step in the process,鈥 Hernandez said. 鈥淚t鈥檚 been very exciting to see my work make a difference.鈥

Laurence Pelletier is a professor of molecular genetics at U of T and a senior investigator at the Lunenfeld-Tanenbaum Research Institute who was co-corresponding author on the paper with Wrana. He said the shared clinical diagnostic lab provided access to thousands of samples and was key to the study鈥檚 success.

The diagnostic lab is led by Tony Mazzulli, a professor of both medicine and laboratory medicine and pathobiology at U of T, who is microbiologist-in-chief for Sinai Health and University Health Network.

鈥淚t has been an absolute pleasure to work with Jeff and his team at the LTRI,鈥 said Mazzulli. 鈥淗is novel SPAR-Seq system is cutting-edge technology and his team鈥檚 ability to sequence COVID-19 samples in real time has tremendous potential for impacting our understanding of the epidemiology and spread of novel mutants in the province.鈥

The platform is also cost-effective. The study notes it only costs about US$8 per test when running thousands of samples at once, as the cost per sample decreases due to economies of scale.

This study was supported by the university鈥檚 Toronto COVID-19 Action Fund and a donation from the Krembil Foundation.

Medicine