Issue 56, 2019

Identification of ceftazidime interaction with bacteria in wastewater treatment by Raman spectroscopic mapping

Abstract

Raman spectroscopy yields a fingerprint spectrum and is of great importance in medical and biological sciences as it is non-destructive, non-invasive, and available in the aqueous environment. In this study, Raman spectroscopy and Raman mapping were used to explore the dynamic biochemical processes in screened bacteria under ceftazidime stress. The Raman spectral difference between bacteria with and without antibiotic stress was analyzed by principal component analysis and characteristic peaks were obtained. The results showed that amino acids changed first and lipids were reduced when bacteria were exposed to ceftazidime stress. Furthermore, in Raman mapping, when bacteria were subjected to antibiotic stress, the peak at 1002 cm−1 (phenylalanine) increased, while the peak at 1172 cm−1 (lipids) weakened. This indicates that when bacteria were stimulated by antibiotics, the intracellular lipids decreased and the content of specific amino acids increased. The reduction of intracellular lipids may suggest a change of membrane permeability. The increase of specific amino acids suggests that bacteria resist external stimuli of antibiotics by regulating the activities of related enzymes. This study explored the processes of the action between bacteria and antibiotics by Raman spectroscopy, and provides a foundation for the further study of the dynamics of microbial biochemical processes in the future.

Graphical abstract: Identification of ceftazidime interaction with bacteria in wastewater treatment by Raman spectroscopic mapping

Supplementary files

Article information

Article type
Paper
Submitted
02 Aug 2019
Accepted
03 Oct 2019
First published
15 Oct 2019
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2019,9, 32744-32752

Identification of ceftazidime interaction with bacteria in wastewater treatment by Raman spectroscopic mapping

M. Peng, X. Wei, Q. Yu, P. Yan, Y. Chen and J. Guo, RSC Adv., 2019, 9, 32744 DOI: 10.1039/C9RA06006E

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