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Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates

Streptococcus pneumoniae, commonly referred to as pneumococci, can cause severe and invasive infections, which are major causes of communicable disease morbidity and mortality in Europe and globally. The differentiation of S. pneumoniae from other Streptococcus species, especially from other oral st...

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Autores principales: Dahms, Marcel, Eiserloh, Simone, Rödel, Jürgen, Makarewicz, Oliwia, Bocklitz, Thomas, Popp, Jürgen, Neugebauer, Ute
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9353136/
https://www.ncbi.nlm.nih.gov/pubmed/35937698
http://dx.doi.org/10.3389/fcimb.2022.930011
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author Dahms, Marcel
Eiserloh, Simone
Rödel, Jürgen
Makarewicz, Oliwia
Bocklitz, Thomas
Popp, Jürgen
Neugebauer, Ute
author_facet Dahms, Marcel
Eiserloh, Simone
Rödel, Jürgen
Makarewicz, Oliwia
Bocklitz, Thomas
Popp, Jürgen
Neugebauer, Ute
author_sort Dahms, Marcel
collection PubMed
description Streptococcus pneumoniae, commonly referred to as pneumococci, can cause severe and invasive infections, which are major causes of communicable disease morbidity and mortality in Europe and globally. The differentiation of S. pneumoniae from other Streptococcus species, especially from other oral streptococci, has proved to be particularly difficult and tedious. In this work, we evaluate if Raman spectroscopy holds potential for a reliable differentiation of S. pneumoniae from other streptococci. Raman spectra of eight different S. pneumoniae strains and four other Streptococcus species (S. sanguinis, S. thermophilus, S. dysgalactiae, S. pyogenes) were recorded and their spectral features analyzed. Together with Raman spectra of 59 Streptococcus patient isolates, they were used to train and optimize binary classification models (PLS-DA). The effect of normalization on the model accuracy was compared, as one example for optimization potential for future modelling. Optimized models were used to identify S. pneumoniae from other streptococci in an independent, previously unknown data set of 28 patient isolates. For this small data set balanced accuracy of around 70% could be achieved. Improvement of the classification rate is expected with optimized model parameters and algorithms as well as with a larger spectral data base for training.
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spelling pubmed-93531362022-08-06 Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates Dahms, Marcel Eiserloh, Simone Rödel, Jürgen Makarewicz, Oliwia Bocklitz, Thomas Popp, Jürgen Neugebauer, Ute Front Cell Infect Microbiol Cellular and Infection Microbiology Streptococcus pneumoniae, commonly referred to as pneumococci, can cause severe and invasive infections, which are major causes of communicable disease morbidity and mortality in Europe and globally. The differentiation of S. pneumoniae from other Streptococcus species, especially from other oral streptococci, has proved to be particularly difficult and tedious. In this work, we evaluate if Raman spectroscopy holds potential for a reliable differentiation of S. pneumoniae from other streptococci. Raman spectra of eight different S. pneumoniae strains and four other Streptococcus species (S. sanguinis, S. thermophilus, S. dysgalactiae, S. pyogenes) were recorded and their spectral features analyzed. Together with Raman spectra of 59 Streptococcus patient isolates, they were used to train and optimize binary classification models (PLS-DA). The effect of normalization on the model accuracy was compared, as one example for optimization potential for future modelling. Optimized models were used to identify S. pneumoniae from other streptococci in an independent, previously unknown data set of 28 patient isolates. For this small data set balanced accuracy of around 70% could be achieved. Improvement of the classification rate is expected with optimized model parameters and algorithms as well as with a larger spectral data base for training. Frontiers Media S.A. 2022-07-22 /pmc/articles/PMC9353136/ /pubmed/35937698 http://dx.doi.org/10.3389/fcimb.2022.930011 Text en Copyright © 2022 Dahms, Eiserloh, Rödel, Makarewicz, Bocklitz, Popp and Neugebauer https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cellular and Infection Microbiology
Dahms, Marcel
Eiserloh, Simone
Rödel, Jürgen
Makarewicz, Oliwia
Bocklitz, Thomas
Popp, Jürgen
Neugebauer, Ute
Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates
title Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates
title_full Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates
title_fullStr Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates
title_full_unstemmed Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates
title_short Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates
title_sort raman spectroscopic differentiation of streptococcus pneumoniae from other streptococci using laboratory strains and clinical isolates
topic Cellular and Infection Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9353136/
https://www.ncbi.nlm.nih.gov/pubmed/35937698
http://dx.doi.org/10.3389/fcimb.2022.930011
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