Algorithm for flow cytometry detects hundreds of proteins in one sample

Aug. 15, 2018
The new flow cytometry algorithm enables different colors of micro-beads to be generated with high accuracy.

Knowing that the vast majority of blood tests that exist target only a single protein at a time, a team of scientists at McGill University (Montreal, QC, Canada) has developed a technique to streamline the analysis of proteins, offering a quick, high-volume, and cost-effective tool to hospitals and research labs alike.

PhD candidate Milad Dagher, Professor David Juncker, and colleagues in McGill's Department of Biomedical Engineering have devised a technique that can detect hundreds of proteins with a single blood sample. Part of their published work describes a new and improved way to barcode microbeads using multicolor fluorescent dyes. By generating upwards of 500 differently colored microbeads, their new barcoding platform enables detection of markers in parallel from the same solution—for example, a blue barcode can be used to detect marker 1, while a red barcode can detect marker 2, and so on. Flow cytometry then counts the proteins that stick to the different colored beads.

Though this kind of analysis method has been available for some time, interference among multicolor dyes has limited the ability to generate the right colors. Now, a new algorithm developed by the research team enables different colors of microbeads to be generated with high accuracy.

"Current technologies hold a major tradeoff between the number of proteins that can be measured at once, and the cost and accuracy of a test," Dagher explains. "This means that large-scale studies, such as clinical trials, are underpowered because they tend to fall back on tried-and-true platforms with limited capabilities."

Dagher and Jeffrey Munzar, a postdoctoral fellow in the Juncker lab, have teamed up with Professor Juncker and spun-off a company, nplex biosciences, to commercialize their new approach. The research group was also recently awarded an NSERC Idea to Innovation grant to support the development of the next version of their technology platform.

Full details of the work appear in the journal Nature Nanotechnology.

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