Academic Minute Podcast
Regina Ragan, University of California, Irvine – Using E. coli to Detect Water Contamination
On University of California, Irvine Week: We hear about the harm bacteria can do, but what about the good?
Regina Ragan, professor of materials science and engineering, examines this question.
Ragan is a recipient of the National Science Foundation Faculty Early CAREER Award and a Fulbright Fellow. She is co-Director of the Institute for Design and Manufacturing Innovation and Education Director for the Center for Complex Active Materials (CCAM – an NSF MRSEC). She received her B.S. summa cum laude in Material Science and Engineering from the University of California, Los Angeles and Ph.D. in Applied Physics from the California Institute of Technology where she was awarded as a NSF, Bell Laboratories, and Intel Fellow. As postdoctoral scholar in the Information & Quantum Systems Laboratory at Hewlett Packard, Ragan worked on emerging technologies including molecular electronics that provided fundamental understanding leading to memristors, a resistive RAM technology. Since joining the Faculty at UC Irvine, she began a research effort in self-assembly as she foresaw this would play a vital role in (nano) manufacturing of nanoscale devices and pioneered methods for assembling colloidal metal nanoparticles into photonic devices, a nascent research area a decade ago. Her activities include investigating and gaining fundamental understanding material platforms capable of assembling at scale, integration in device architectures, and connecting architecture design with device performance.
Using E. coli to Detect Water Contamination
E. coli has often had a negative association because of contaminated food. However, the bacterium is also a workhorse in biotechnology, serving as a cell factory for biofuels and pharamceuticals.
Now more than ever, we are seeing people all over the world struggle to find clean, safe water. Many people live their lives not knowing that their water contains unsafe levels of metal contaminants. That’s why my team and I set out to discover how E.coli could be used to detect metal contamination.
Through our study, we used a machine-learning analysis of the optical spectra of metabolites released from E. Coli in response to chromium and arsenic exposure. We were able to not only detect metals in lower concentrations but deduce the type and amount with higher than 96% accuracy.
This entire process is easy and effective and the sensors can be manufacturered at a low-cost. It also has the capacity to spot metal toxins such as lead and mercury below regulatory limits.
Our research shows how important it is to find innovative ways to safeguard our water. Thanks to the trained algorithm we used, we’re able to test unseen tap water and wastewater samples at a much faster speed, around 10 minutes. It allowed us to determine if the water was within the U.S. Environmental Protection Agency and World Health Organization’s recommend limits for each contaminant.
This is a great sign that with this type of technology, more people will be able to test their water sources and supplies anywhere in the world. We hope that with research like ours, we’ll be one step closer to finding the solution for water security.
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