Rapid and cost-effective evaluation of bacterial viability using fluorescence spectroscopy

TL;DR

This study presents a rapid, cost-effective fluorescence spectroscopy method using an optrode and multi-spectra support vector regression to accurately determine bacterial viability in samples, facilitating quick assessments in microbiology.

Contribution

The paper introduces a novel combination of fluorescence spectroscopy with multi-spectra SVR and an optrode device for efficient bacterial viability analysis, improving accuracy over traditional methods.

Findings

Multi-spectra SVR reliably predicts bacterial viability percentages.

The optrode provides a cost-effective, convenient platform for fluorescence spectral analysis.

The method works effectively across different bacterial concentrations.

Abstract

The fluorescence spectra of bacterial samples stained with SYTO 9 and propidium iodide (PI) were used to monitor bacterial viability. Stained mixtures of live and dead Escherichia coli with proportions of live:dead cells varying from 0 to 100% were measured using the optrode, a cost effective and convenient fibre-based spectroscopic device. We demonstrated several approaches to obtaining the proportions of live:dead E. coli in a mixture of both live and dead, from analyses of the fluorescence spectra collected by the optrode. To find a suitable technique for predicting the percentage of live bacteria in a sample, four analysis methods were assessed and compared: SYTO 9:PI fluorescence intensity ratio, an adjusted fluorescence intensity ratio, single-spectrum support vector regression (SVR) and multi-spectra SVR. Of the four analysis methods, multi-spectra SVR obtained the most reliable results and was able to predict the percentage of live bacteria in 10^8 bacteria/mL samples between c. 7% and 100% live, and in 10^7 bacteria/mL samples between c. 7% and 73% live. By demonstrating the use of multi-spectra SVR and the optrode to monitor E. coli viability, we raise points of consideration for spectroscopic analysis of SYTO 9 and PI and aim to lay the foundation for future work that use similar methods for different bacterial species.