J Biophotonics. 2021 Sep 12:e202100175. doi: 10.1002/jbio.202100175. Online ahead of print.
ABSTRACT
We aim to develop a quantitative viability method that distinguishes individual quiescent from dead cells and is measured in time (ns) as a referenceable, comparable quantity. We demonstrate that fluorescence lifetime imaging of an anionic, fluorescent membrane voltage probe fulfills these requirements for Streptococcus mutans. A random forest machine learning model assesses whether individual S. mutans can be correctly classified into their original populations: stationary phase (quiescent) (SP), heat killed (HK), and inactivated via chemical fixation. We compare the results to intensity using three models: lifetime variables (τ1 , τ2 , p1 ), phasor variables (G, S) or all five variables, with the 5 variable model having the most accurate classification. This initial work affirms the potential for using fluorescence lifetime of a membrane voltage probe as a viability marker for quiescent bacteria, and future efforts on other bacterial species and fluorophores will help refine this approach. This article is protected by copyright. All rights reserved.
PMID:34510771 | DOI:10.1002/jbio.202100175
