Rapid, low-cost detection of Zika virus using paper-based synthetic gene networks
University of Toronto Assistant Professor of Pharmacy Keith Pardee and an international team of collaborators, including scientists from the Wyss Institute at Harvard University, have developed a low-cost, easy-to-use diagnostic platform for detecting the Zika virus. Using cutting-edge technologies, the team of collaborators from Wyss, Massachusetts Institute of Technology, Boston University, Arizona State University, Cornell University, University of Wisconsin-Madison, Broad Institute, and the University of Toronto have developed a cell-free, paper-based platform that can host synthetic gene networks for use outside of the lab.
Employing toehold sensors and isothermal RNA amplification, the team has created diagnostic sensors on a freeze-dried piece of paper the size of a stamp. Activated by the amplified sample, the diagnostic sensors programmed into this paper provide extremely sensitive, low-cost, programmable diagnostics that provide rapid results.
This revolutionary paper-based sensor system provides a much needed solution to the challenge of diagnosing the Zika virus. Currently, reliable diagnosis for patients suspected of the Zika virus involves nucleic acid-based testing, which is dependent on laboratory access, highly specific and expensive equipment, and trained technicians. As a result, this type of testing is unsuitable and unavailable in remote locations where surveillance and containment are critically needed.
This new technology, on the other hand, is easy to use and requires little to no training. Specifically tuned to the Zika virus, sensors are applied to small paper samples. Using a small saliva, urine, or blood sample, equivalent to the amount required by blood glucose monitors to test blood sugar levels, the sample is applied to the sensors, triggering a response that provides visually evident results in as little as an hour. If the sample contains the RNA of the Zika virus, the test area turns purple. In making such a simple to use test, the team has created a exciting tool that promises to bring portable, reliable, and inexpensive Zika diagnostics to the field at less than a dollar per test. Moreover, it does not require a lab, expensive equipment, or highly-trained technicians to administer.
"The diagnostic platform developed by our team has provided a high-performing, low-cost tool that can work in remote locations," notes Dr. Keith Pardee, the lead author of the study. "We have developed a workflow that combines molecular tools to provide diagnostics that can be read out on a piece of paper no larger than a postage stamp. We hope that through this work, we have created the template for a tool that can make a positive impact on public health across the globe."
"Our synthetic biology pipeline for rapid sensor design and prototyping has tremendous potential for application for the Zika virus and other public health threats, enabling us to rapidly develop new diagnostics when and where they are needed most."
While this study in Cell demonstrates proof-of-concept, the team is eager to secure the necessary partners and resources to proceed to the product development phase, followed up by scaled up manufacturing and distribution so that the diagnostic tool can be deployed for use in the field.
Ultimately, the development of quick, easy-to-use, in-the-field tests for Zika and similar pathogens could help governments stay ahead of pathogen outbreaks, curbing the spread of disease and lessening the burden on already overtaxed healthcare systems.
Source: University of Toronto
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- Rapid Zika Test Is Introduced by Researchersfrom NY Times HealthSat, 7 May 2016, 6:50:53 UTC
- Quick test for Zika effectively detects virus in monkeysfrom Science DailyFri, 6 May 2016, 18:01:12 UTC
- Rapid, low-cost detection of Zika virus using paper-based synthetic gene networksfrom Science DailyFri, 6 May 2016, 18:01:07 UTC
- A new paper-based test for the Zika virusfrom MIT ResearchFri, 6 May 2016, 16:30:48 UTC
- Finding Zika one paper disc at a timefrom PhysorgFri, 6 May 2016, 16:01:05 UTC