Alex Green honored for early career achievements

Alex Green honored for early career achievements

March 22, 2017

March 22, 2017

Honored for Zika virus work and New Investigator Award to develop valley fever test kit

ASU assistant professor of the School of Molecular Sciences and Biodesign Institute researcher Alex Green earned double accolades this year, for outstanding research in molecular science.

The most recent award, which comes from the Arizona Biomedical Research Commission (ABRC), will fund Green’s research on an easy to use test kit for Valley fever, which is a disease caused by fungal spores native to the Southwestern United States. He also received a Sloan Research Fellowship earlier this year in part for his work on an inexpensive Zika virus test kit, and for general early career achievements.

Green said that this test kit for Valley fever will work similarly to the Zika test kit that he and his research group have already tested. The Zika test kit can be used to diagnose the disease in its early stages and the test itself is relatively simple to perform, requiring only a pinprick to the finger and very little lab equipment.

His paper based Zika test kits detect small amounts of ribonucleic acid (RNA) unique to the Zika virus within a patient's blood stream. If Zika RNA is present in the blood sample it triggers a reaction on the paper test kit, causing it to change colors. He wants to use the same technology for the valley fever diagnostic system, checking blood samples for any RNA sequences unique to the disease to determine whether a person is infected.

In the current test, once the pinprick of blood is taken, the RNA inside the sample is amplified in a test tube and then placed on the piece of paper. A complex chemical reaction embedded in the paper is used to detect the RNA.

“What we’re trying to do now is make things much cheaper and accessible in general so that the process can be run without user input,” said Green, who is a researcher in the Biodesign Center for Molecular Design and Biomimetics.

By eliminating the need for a lab and lab technicians to perform diagnostic tests, the paper-based test kits can drastically reduce the cost of diagnosis and provide test results in much less time. Hopefully, this will make it easier for more people who are at risk of contracting a serious disease like Zika to get tested.

Green thinks that the RNA detection system he developed will one day be used to identify an array of different pathogens. Try to imagine a chemically treated paper the size of a business card that could be used in remote clinics to diagnose a variety of diseases, so that the proper medical treatment can be administered quickly.

Adapting this detection technology to look for different pathogens is not a simple task to complete, however. For example, Green and his team will have to tune the technology to each individual disease they want to detect.

“The concentrations of some pathogens in the bloodstream may be lower and harder to detect,” Green explained.

He hopes that in a few years his system for detecting Zika can secure the appropriate FDA approvals and be widely distributed, with the Valley fever system not far behind.

The ABRC grant Green received is called the New Investigator Award; it is given to new research professionals who have already made outstanding contributions to the respective biomedical fields. Similarly, the Sloan Fellowship seeks to support early-career scientists and researchers who show considerable promise by providing them with the flexibility to pursue high risk, high reward ideas.

“It's nice to have some recognition through these awards and to have the funding that will enable us to put our ideas into practice. The probability of getting these types of awards, in general, is often 10 percent or so. You encounter a lot of failures before you get these successes,” Green said.

Altogether, Green has raised $285,000 for research between the two awards.

His vision is to make diagnostic medicine cheaper and easier by creating versatile platforms for diagnosis that require minimal user intervention.

“As a scientist, you can work on something for a long time and never see the end game,” said Green. “This project is nice because it went from a fairly fundamental problem we were looking at to something that could have a real world impact in a few years.”




Written by: Gavin Maxwell