“Emerging nanophotonic platforms for infectious disease diagnostics: Re-imagining the conventional microbiology toolkit”
Jennifer Dionne, PhD
Senior Associate Vice Provost for Research Platforms/Shared Facilities
Associate Professor of Materials Science and Engineering, by courtesy, of Radiology (Molecular Imaging Program at Stanford)
Stanford University
Location: Zoom Webinar
Webinar URL: https://stanford.zoom.us/j/95883654314
Dial: +1 650 724 9799 or +1 833 302 1536
Webinar ID: 958 8365 4314
Passcode: 105586
ABSTRACT
We present our research controlling light at the nanoscale for infectious disease diagnostics, including detecting bacteria at low concentration, sensing COVID gene sequences, and visualizing in-vivo inter-cellular forces. First, we combine Raman spectroscopy and deep learning to accurately classify bacteria by both species and antibiotic resistance in a single step. We design a convolutional neural network (CNN) for spectral data and train it to identify 30 of the most common bacterial strains from single-cell Raman spectra, achieving antibiotic treatment identification accuracies exceeding 99% and species identification accuracies similar to leading mass spectrometry identification techniques. Our combined Raman-CNN system represents a proof-of-concept for rapid, culture-free identification of bacterial isolates and antibiotic resistance. Second, we describe resonant nanophotonic surfaces, known as “metasurfaces” that enable multiplexed detection of SARS-CoV-2 gene sequences. Our metasurfaces utilize guided mode resonances excited in high refractive index nanostructures. The high quality factor modes produce a large amplification of the electromagnetic field near the nanostructures that increase the response to targeted binding of nucleic acids; simultaneously, the optical signal is beam-steered for multiplexed detection. We describe how this platform can be manufactured at scale for portable, low-cost assays. Finally, we introduce a new class of in vivo optical probes to monitor biological forces with high spatial resolution. Our design is based on upconverting nanoparticles that, when excited in the near-infrared, emit light of a different color and intensity in response to nano-to-microNewton forces. The nanoparticles are sub-30nm in size, do not bleach or photoblink, and can enable deep tissue imaging with minimal tissue autofluorescence. We present the design, synthesis, and characterization of these nanoparticles both in vitro and in vivo, focusing on the forces generated by the roundworm C. elegans as it feeds and digests its bacterial food.
ABOUT DR. DIONNE
Jennifer Dionne is the Senior Associate Vice Provost of Research Platforms/Shared Facilities and an associate professor of Materials Science and Engineering and, by courtesy, of Radiology at Stanford. She is also an Associate Editor of Nano Letters, director of the DOE-funded Photonics at Thermodynamic Limits Energy Frontier Research Center, and an affiliate faculty of the Wu Tsai Neurosciences Institute, the Institute for Immunity, Transplantation, and Infection, and Bio-X. Jen received her B.S. degrees in Physics and Systems Science and Mathematics from Washington University in St. Louis, her Ph. D. in Applied Physics at the California Institute of Technology in 2009, and her postdoctoral training in Chemistry at Berkeley. Her research develops nanophotonic methods to observe and control chemical and biological processes as they unfold with nanometer scale resolution, emphasizing critical challenges in global health and sustainability. Her work has been recognized with the Alan T. Waterman Award, a NIH Director’s New Innovator Award, a Moore Inventor Fellowship, the Materials Research Society Young Investigator Award, and the Presidential Early Career Award for Scientists and Engineers, and was featured on Oprah’s list of “50 Things that will make you say ‘Wow’!”. Beyond the lab, Jen enjoys exploring the intersection of art and science, long-distance cycling, and reliving her childhood with her two young sons.
Hosted by: Katherine Ferrara, PhD
Sponsored by: Molecular Imaging Program at Stanford & the Department of Radiology