Project 467233

All living cells produce unique vibrations due to internal metabolic processes which have previously been recorded using Atomic Force Microscopy (AFM). These studies have established proof of concept for the potential of cell vibrational profiling in biomedicine. However, few, if any, cell-specific frequencies were witnessed due to the lack of sensitivity of AFM for this application, precluding detailed phenotyping. In this proposal, we use the Optical Tweezers (OT), a more sensitive tool, to provide improved resolution of vibratory signals in a novel approach to cell vibrational profiling. We hypothesize that due to metabolic processes, every cell releases a unique vibrational frequency pattern (VFP) which contains sufficient information to phenotype the cell using OT. Testing this theory, we discovered distinct spectral sequences leading to the differentiation of VFPs of glioblastoma cells (i.e., BT48, BT53, and U251). We propose to expand on these discoveries and progress our novel methodology by incorporating real-time analysis of signals using a spectrum analyzer and utilizing multivariate statistical analysis (MVSA) techniques to statistically establish differentiation of VFPs of cell lines. Our improved methodology provides a real-time assessment of cells as they vibrate, providing an immediate diagnosis of cell condition and type, as well as an objective offline MVSA to reliably differentiate between healthy and cancerous cells. This proposal aims to establish the potential of VFP detection as a novel real-time diagnostic method for cancer types and stages, or metabolic diseases, among other applications. This proof-of-concept project is significant, building upon previous work, and bringing the OT and VFP detection closer to medical application.