Caltech Young Investigators Lecture
Abstract: In the past decade, breath has become an increasingly explored bioanalyte for clinical biomarker discovery. Breath contains hundreds of volatile metabolic products from the body and can be sampled non-invasively for analysis at the point of care. However, since the first report of quantitative breath analysis by Linus Pauling in 1971, few robust breath biomarkers have been discovered and used in the clinic. In this talk, I will discuss an alternative approach to breath-based diagnostics using inhalable nanoparticles that we have engineered to release synthetic volatiles in response to aberrant protease activity in the lungs. The advantages of this approach are four-fold: (1) high sensitivity due to protease-driven readouts (2) high specificity through multiplexing (3) minimal background through use of biorthogonal volatile reporters and (4) a priori knowledge of the biological pathways driving breath signal. My interests lie in respiratory infections in which we can leverage both host and bacterial proteases. I will discuss my progress on this front and how this platform can be paired with machine learning to address clinical needs such as rapid pathogen identification.
Bio: Leslie Chan received her B.S. in Biomedical Engineering from the Georgia Institute of Technology in 2009 and her Ph.D. in Bioengineering from the University of Washington in 2015. She completed her graduate work under the mentorship of Suzie Pun, where she developed peptide-functionalized polymers to promote blood clotting for trauma applications. Following completion of her graduate work, Leslie joined Sangeeta Bhatia’s lab at MIT, where she is currently engineering nanoscale materials to interface with microbial pathogens and the infected tissue microenvironment to diagnose, treat, and monitor bacterial infections. Her research interests broadly encompass drug delivery and the human microbiome.
This lecture is part of the Young Investigators Lecture Series sponsored by the Caltech Division of Engineering & Applied Science.