Issue 16, 2023

Identification of bacteria in mixed infection from urinary tract of patient's samples using Raman analysis of dried droplets

Abstract

Urinary tract infections (UTI) are among the most frequent nosocomial infections. A fast identification of the pathogen and assignment of Gram type could help to prescribe most suitable treatments. Raman spectroscopy holds high potential for fast and reliable bacterial pathogens identification. While most studies so far have focused on individual pathogens or artificial mixtures, this contribution aims to translate the analysis to primary urine samples from patients with suspected UTIs. For this, we have included 59 primary urine samples out of which 29 were diagnosed as mixed infections. For Raman analysis, we first trained two classification models based on principal component analysis – linear discriminant analysis (PCA-LDA) with more than 3500 Raman spectra of 85 clinical isolates from 23 species in order to (1) identify the Gram type of the bacteria and (2) assign family membership to one of the six most abundant bacterial families in urinary tract infections (Enterobacteriaceae, Morganellaceae, Pseudomonadaceae, Enterococcaceae, Staphylococcaceae and Streptococcaceae). The classification models were applied to artificial mixtures of Gram positive and Gram negative bacteria to correctly predict mixed infections with an accuracy of 75%. Raman scans of dried droplets did not yet yield optimal classification results on family level. When translating the method to primary urine samples, we observed a strong bias towards Gram negative bacteria, on family level towards Morganellaceae, which reduced prediction accuracy. Spectral differences were observed between isolates grown on standard growth medium and bacteria of the same strain when characterized directly from the patient. Thus, improvement of the classification accuracy is expected with a larger data base containing also bacteria measured directly from the urine sample.

Graphical abstract: Identification of bacteria in mixed infection from urinary tract of patient's samples using Raman analysis of dried droplets

Supplementary files

Article information

Article type
Paper
Submitted
30 เม.ย. 2566
Accepted
10 ก.ค. 2566
First published
17 ก.ค. 2566

Analyst, 2023,148, 3806-3816

Identification of bacteria in mixed infection from urinary tract of patient's samples using Raman analysis of dried droplets

K. Aubrechtová Dragounová, O. Ryabchykov, D. Steinbach, V. Recla, N. Lindig, M. J. González Vázquez, S. Foller, M. Bauer, T. W. Bocklitz, J. Popp, J. Rödel and U. Neugebauer, Analyst, 2023, 148, 3806 DOI: 10.1039/D3AN00679D

To request permission to reproduce material from this article, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements