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New Disease Surveillance Tool Helps Detect Any Human Virus

Computational method helps scientists examine microbes at a larger, more comprehensive scale than previously possible

Brought to you byBroad Institute of MIT and Harvard
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During the Zika virus outbreak of 2015-16, public health officials scrambled to contain the epidemic and curb the pathogen's devastating effects on pregnant women. At the same time, scientists around the globe tried to understand the genetics of this mysterious virus.

The problem was, there just aren't many Zika virus particles in the blood of a sick patient. Looking for it in clinical samples can be like fishing for a minnow in an ocean.

A new computational method developed by Broad Institute scientists helps overcome this hurdle. Built in the lab of Broad Institute researcher Pardis Sabeti, the "CATCH" method can be used to design molecular "baits" for any virus known to infect humans and all their known strains, including those that are present in low abundance in clinical samples, such as Zika. The approach can help small sequencing centers around the globe conduct disease surveillance more efficiently and cost-effectively, which can provide crucial information for controlling outbreaks.

The new study was led by MIT graduate student Hayden Metsky and postdoctoral researcher Katie Siddle, and it appears online in Nature Biotechnology.

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