Presenter: Noah Pettinari – Physics
Faculty Mentor(s): Raghuveer Parthasarathy
Session: (In-Person) Oral Panel—Uniquely Their Own
The study of host-microbe interactions has been of growing interest in recent years, with new research highlighting their importance in ecology, human health, developmental biology, and immunology. Fluorescent imaging of larger multispecies bacterial communities within the host microbiome is generally limited to one species per fluorescent channel, greatly limiting the ability to image several species simultaneously. Additionally, the creation and integration of new fluorophores is a slow and labor intensive process, further limiting the use of fluorescent imaging. We assess an algorithm for classifying two bacterial species in vitro within one fluorescent channel using machine learning techniques on morphology data. We then applied this machine learning model to bacterial communities in the rotifer gut, testing new algorithms for removing unwanted autofluorescence along the way.