Author ORCID Identifier:
Date of Graduation
8-2025
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Engineering (PhD)
Degree Level
Graduate
Department
Biomedical Engineering
Advisor/Mentor
Quinn, Kyle
Committee Member
Paré, Adam
Second Committee Member
Balachandran, Kartik
Third Committee Member
Rajaram, Narasimhan
Keywords
autofluorescence; metabolism; microscopy; mitochondria
Abstract
Optical imaging of metabolism using the autofluorescence of the metabolic cofactors NADH, NADPH, and FAD has a wide range of sensitivities and the capability to collect a great deal of metabolic information. Multiphoton microscopy (MPM) is a non-invasive, label-free optical imaging technique capable of performing fluorescence lifetime imaging (FLIM) using time correlated single photon counting (TCSPC). However, autofluorescence FLIM presents a challenge in collecting sufficient photons to provide adequate signal to noise ratios (SNR) for analysis. Additionally, the specificity of autofluorescence biomarkers of metabolism has not been well-defined. Contextualizing these autofluorescence measures using established functional biomarkers can improve interpretability of metabolic information collected using MPM-FLIM. The goal of this dissertation was to establish non-invasive, label-fee optical approaches to characterize mitochondrial membrane potential (MMP), an essential biomarker of mitochondrial and cellular function, to improve the quantitative analysis of autofluorescence measures of metabolism. A custom, iterative MATLAB fitting algorithm was developed to mitigate the effects of low SNR and proved to greatly increase the accuracy of bi-exponential fitting of autofluorescence FLIM decays compared to that of a commercial software package often used to analyze autofluorescence FLIM (SPCImage). Accuracy was tested using simulated NAD(P)H decay curves and verified using an NADH and lactate dehydrogenase solution of known concentration and binding proportion. This fitting algorithm allowed for a whole-cell binning approach that further improved accuracy for low SNR data and cut FLIM collection time in half. This fitting algorithm was applied to NAD(P)H and FAD autofluorescence collected from NIH3T3 cells treated with extracellular ATP, the mitochondrial uncoupler BAM15, and starved of glucose and L-glutamine to vary metabolic responses and MMP. Autofluorescence measurements were paired cell-by-cell with the FLIM intensity of TMRE, a fluorescent MMP probe. These measurements informed a random forest regression model for predicting TMRE intensity based on nine different autofluorescence biomarkers of metabolism identified using a multiple linear regression model. This work provides a toolset for increasing autofluorescence FLIM SNR for accurate analysis that can be applied as part of a methodological framework combining spectral, temporal, and spatial information derived from cellular autofluorescence measurements of metabolism to predict other additional functional biomarkers.
Citation
Kolenc, O. I. (2025). Improved Autofluorescence Lifetime Decay Analysis for Identification of Cellular Autofluorescence Biomarkers for Label-Free, Single-Cell Assessment of Mitochondrial Membrane Potential. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/5960
