Issue 14, 2025

Differentiation and identification of commensal and pathogenic oral bacteria at strain level using ATR-FTIR spectroscopy

Abstract

The correct identification of different bacteria is a critical task in clinical applications and basic research especially in the oral cavity which has a complex bacterial community. Complementary to a variety of phenotyping and genotyping methods, we propose FTIR spectroscopy as a fast and non-destructive technique for accurate bacterial identification. This technique can be used to investigate the chemical makeup of a given sample and also allows for bacterial classification at strain level. In this work, we investigate the ability of ATR-FTIR spectroscopy to identify different oral bacteria from known laboratory stains as well as strains from patient-derived samples. Using this technique, six measured species could be classified with high accuracy (>97%) using chemometric models. Furthermore, the model which was only trained with laboratory strains could still correctly identify the patient-derived strains at the genus level. These results open the possibility of constructing a simplified tailored classification model based only on a target species and few other representative species, while still being able to distinguish the target species from a much larger number of other bacterial species for application to oral microbial communities.

Graphical abstract: Differentiation and identification of commensal and pathogenic oral bacteria at strain level using ATR-FTIR spectroscopy

Supplementary files

Article information

Article type
Paper
Submitted
13 Feb 2025
Accepted
14 Jun 2025
First published
17 Jun 2025
This article is Open Access
Creative Commons BY license

Analyst, 2025,150, 3198-3207

Differentiation and identification of commensal and pathogenic oral bacteria at strain level using ATR-FTIR spectroscopy

K. A. Frings, R. Mukherjee, V. Schulze, N. Heine, N. Debener, J. Bahnemann, S. P. Szafrański, M. Stiesch, K. Doll-Nikutta, M. L. Torres-Mapa and A. Heisterkamp, Analyst, 2025, 150, 3198 DOI: 10.1039/D5AN00165J

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