Details
| Original language | English |
|---|---|
| Pages (from-to) | 3198-3207 |
| Number of pages | 10 |
| Journal | ANALYST |
| Volume | 150 |
| Issue number | 14 |
| Publication status | Published - 17 Jun 2025 |
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.
ASJC Scopus subject areas
- Chemistry(all)
- Analytical Chemistry
- Biochemistry, Genetics and Molecular Biology(all)
- Biochemistry
- Environmental Science(all)
- Environmental Chemistry
- Chemistry(all)
- Spectroscopy
- Chemistry(all)
- Electrochemistry
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In: ANALYST, Vol. 150, No. 14, 17.06.2025, p. 3198-3207.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Differentiation and identification of commensal and pathogenic oral bacteria at strain level using ATR-FTIR spectroscopy
AU - Frings, Katharina Anna
AU - Mukherjee, Rumjhum
AU - Schulze, Vivien
AU - Heine, Nils
AU - Debener, Nicolas
AU - Bahnemann, Janina
AU - Szafrański, Szymon Piotr
AU - Stiesch, Meike
AU - Doll-Nikutta, Katharina
AU - Torres-Mapa, Maria Leilani
AU - Heisterkamp, Alexander
N1 - Publisher Copyright: © 2025 The Royal Society of Chemistry.
PY - 2025/6/17
Y1 - 2025/6/17
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=105008651630&partnerID=8YFLogxK
U2 - 10.1039/d5an00165j
DO - 10.1039/d5an00165j
M3 - Article
C2 - 40539919
AN - SCOPUS:105008651630
VL - 150
SP - 3198
EP - 3207
JO - ANALYST
JF - ANALYST
SN - 0003-2654
IS - 14
ER -