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

  • Anal Bioanal Chem. 2019 Jun;411(16):3653-3663. doi: 10.1007/s00216-019-01848-5.
Fang Ou  1  2 Cushla McGoverin  3  4 Simon Swift  5 Frédérique Vanholsbeeck  3  4
Affiliations
  • 1. Department of Physics, The University of Auckland, Auckland, 1010, New Zealand. [email protected].
  • 2. The Dodd-Walls Centre for Photonic and Quantum Technologies, Auckland, 1010, New Zealand. [email protected].
  • 3. Department of Physics, The University of Auckland, Auckland, 1010, New Zealand.
  • 4. The Dodd-Walls Centre for Photonic and Quantum Technologies, Auckland, 1010, New Zealand.
  • 5. School of Medical Sciences, The University of Auckland, Auckland, 1023, New Zealand.
Abstract

A rapid and easy method that takes advantage of an inexpensive and portable fibre-based spectroscopic system (optrode) to determine the ratio of live to dead bacteria is proposed. Mixtures of live and dead Escherichia coli with proportions of live:dead cells varying from 0 to 100% were stained using SYTO 9 and propidium iodide (PI) and measured using the optrode. 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 108 bacteria/mL samples between c. 7 and 100% live, and in 107 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 uses similar methods for different Bacterial species.

Keywords
Bacteria; Bacterial viability; Fluorescence; Spectroscopy; Support vector regression.
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