Scientists have developed a novel technology for a CRISPR-based COVID-19 diagnostic test that uses a smartphone camera to provide accurate results in under 30 minutes. According to the research published in the journal Cell, the new diagnostic test can not only generate a positive or negative result, but it also measures the viral load – the concentration of virus – in a given sample. All CRISPR diagnostics to date have required that the viral RNA be converted to DNA and amplified before it can be detected, adding time and complexity, the researchers said.
In contrast, the new approach skips all the conversion and amplification steps, using CRISPR to detect the viral RNA directly, they said.
“One reason we are excited about CRISPR-based diagnostics is the potential for quick, accurate results at the point of need,” said Jennifer Doudna, a senior investigator at Gladstone Institutes in the US. “This is especially helpful in places with limited access to testing, or when frequent, rapid testing is needed. It could eliminate a lot of the bottlenecks we’ve seen with COVID-19,” she added.
Jennifer Doudna won the 2020 Nobel Prize in Chemistry for co-discovering CRISPR-Cas genome editing, the technology that underlies this work.
In the new test, the Cas13 protein is combined with a reporter molecule that becomes fluorescent when cut and then mixed with a patient sample from a nasal swab, the researchers said.
The sample is placed in a device that attaches to a smartphone. If the sample contains RNA from SARS-CoV-2, Cas13 will be activated and will cut the reporter molecule, causing the emission of a fluorescent signal, they said.
According to the researchers, the smartphone camera, essentially converted into a microscope, can detect the fluorescence and report that a swab tested positive for the virus.
They say that the assay could be adapted to various mobile phones, making the technology easily accessible.
When the scientists tested their device using patient samples, they confirmed that it could provide a speedy turnaround time for samples with clinically relevant viral loads.