Influence of Carbon Sources on Quantification of Deuterium Incorporation in Heterotrophic Bacteria : A Raman-Stable Isotope Labeling Approach

Title data

Azemtsop Matanfack, Georgette ; Taubert, Martin ; Guo, Shuxia ; Houhou, Rola ; Bocklitz, Thomas ; Küsel, Kirsten ; Rösch, Petra ; Popp, Jürgen:
Influence of Carbon Sources on Quantification of Deuterium Incorporation in Heterotrophic Bacteria : A Raman-Stable Isotope Labeling Approach.
In: Analytical Chemistry. Vol. 92 (2020) Issue 16 . - pp. 11429-11437.
ISSN 1520-6882
DOI: https://doi.org/10.1021/acs.analchem.0c02443

Official URL:

Abstract in another language

A rapid and reliable method for the differentiation between active and inactive bacteria at single cell level is urgently needed in many fields including clinical diagnosis and environmental microbiology, to understand the contribution of metabolically active bacteria in fundamental processes triggering environmental and public health risks. Here, using heavy water (D2O) with Raman-stable isotope labeling (Raman-D2O), we evaluated the reliability of the quantification of deuterium uptake, a well-known indicator for the general metabolic activity of bacteria. For this purpose, we based our study on the quantification of deuterium assimilation from heavy water into single bacterial cells to check the influence of carbon source and bacterial identity on the deuterium uptake. We show that compared to complex carbon substrates, the deuterium assimilation is higher in the presence of simpler substrates such as sugars but differs significantly among bacterial isolates. Despite this variability, the developed classification models could differentiate deuterium labeled and nonlabeled single cells with high sensitivity and specificity. Highlighting the variability between single bacterial cells, the study emphasizes the challenges in establishing a threshold in terms of deuterium uptake to distinguish deuterium labeled and nonlabeled cells. Overall, we show that the Raman-D2O approach, when coupled with chemometrics, constitutes a powerful approach for monitoring single bacterial cells.

Further data

Item Type:	Article in a journal
Refereed:	Yes
Institutions of the University:	Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Lehrstuhl Künstliche Intelligenz in der Mikroskopie und Spektroskopie > Lehrstuhl Künstliche Intelligenz in der Mikroskopie und Spektroskopie - Univ.-Prof. Dr. Thomas Wilhelm Bocklitz
Result of work at the UBT:	No
DDC Subjects:	500 Science > 530 Physics
Date Deposited:	22 May 2023 13:04
Last Modified:	22 May 2023 13:04
URI:	https://eref.uni-bayreuth.de/id/eprint/76270