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...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-07-01
|
| Series: | Frontiers in Cellular and Infection Microbiology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fcimb.2022.930011/full |
| _version_ | 1818190695262846976 |
|---|---|
| author | Marcel Dahms Marcel Dahms Simone Eiserloh Simone Eiserloh Jürgen Rödel Oliwia Makarewicz Oliwia Makarewicz Thomas Bocklitz Thomas Bocklitz Jürgen Popp Jürgen Popp Ute Neugebauer Ute Neugebauer Ute Neugebauer |
| author_facet | Marcel Dahms Marcel Dahms Simone Eiserloh Simone Eiserloh Jürgen Rödel Oliwia Makarewicz Oliwia Makarewicz Thomas Bocklitz Thomas Bocklitz Jürgen Popp Jürgen Popp Ute Neugebauer Ute Neugebauer Ute Neugebauer |
| author_sort | Marcel Dahms |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-12T00:02:48Z |
| format | Article |
| id | doaj.art-55a234666b4e496d9016dcb93ba99157 |
| institution | Directory Open Access Journal |
| issn | 2235-2988 |
| language | English |
| last_indexed | 2024-12-12T00:02:48Z |
| publishDate | 2022-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Cellular and Infection Microbiology |
| spelling | doaj.art-55a234666b4e496d9016dcb93ba991572022-12-22T00:45:11ZengFrontiers Media S.A.Frontiers in Cellular and Infection Microbiology2235-29882022-07-011210.3389/fcimb.2022.930011930011Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical IsolatesMarcel Dahms0Marcel Dahms1Simone Eiserloh2Simone Eiserloh3Jürgen Rödel4Oliwia Makarewicz5Oliwia Makarewicz6Thomas Bocklitz7Thomas Bocklitz8Jürgen Popp9Jürgen Popp10Ute Neugebauer11Ute Neugebauer12Ute Neugebauer13Leibniz Institute of Photonic Technology Jena (a member of Leibniz Health Technologies), Jena, GermanyInstitute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Jena, GermanyLeibniz Institute of Photonic Technology Jena (a member of Leibniz Health Technologies), Jena, GermanyCenter for Sepsis Control and Care, Jena University Hospital, Jena, GermanyInstitute for Medical Microbiology, Jena University Hospital, Jena, GermanyCenter for Sepsis Control and Care, Jena University Hospital, Jena, GermanyInstitute of Infectious Diseases and Infection Control, Jena University Hospital, Jena, GermanyLeibniz Institute of Photonic Technology Jena (a member of Leibniz Health Technologies), Jena, GermanyInstitute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Jena, GermanyLeibniz Institute of Photonic Technology Jena (a member of Leibniz Health Technologies), Jena, GermanyInstitute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Jena, GermanyLeibniz Institute of Photonic Technology Jena (a member of Leibniz Health Technologies), Jena, GermanyInstitute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Jena, GermanyCenter for Sepsis Control and Care, Jena University Hospital, Jena, GermanyStreptococcus 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.https://www.frontiersin.org/articles/10.3389/fcimb.2022.930011/fullpneumococcusbacteriaraman spectroscopybinary PLS-DA classification modelsstreptococcusclinical isolates |
| spellingShingle | Marcel Dahms Marcel Dahms Simone Eiserloh Simone Eiserloh Jürgen Rödel Oliwia Makarewicz Oliwia Makarewicz Thomas Bocklitz Thomas Bocklitz Jürgen Popp Jürgen Popp Ute Neugebauer Ute Neugebauer Ute Neugebauer Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates Frontiers in Cellular and Infection Microbiology pneumococcus bacteria raman spectroscopy binary PLS-DA classification models streptococcus 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 | pneumococcus bacteria raman spectroscopy binary PLS-DA classification models streptococcus clinical isolates |
| url | https://www.frontiersin.org/articles/10.3389/fcimb.2022.930011/full |
| work_keys_str_mv | AT marceldahms ramanspectroscopicdifferentiationofstreptococcuspneumoniaefromotherstreptococciusinglaboratorystrainsandclinicalisolates AT marceldahms ramanspectroscopicdifferentiationofstreptococcuspneumoniaefromotherstreptococciusinglaboratorystrainsandclinicalisolates AT simoneeiserloh ramanspectroscopicdifferentiationofstreptococcuspneumoniaefromotherstreptococciusinglaboratorystrainsandclinicalisolates AT simoneeiserloh ramanspectroscopicdifferentiationofstreptococcuspneumoniaefromotherstreptococciusinglaboratorystrainsandclinicalisolates AT jurgenrodel ramanspectroscopicdifferentiationofstreptococcuspneumoniaefromotherstreptococciusinglaboratorystrainsandclinicalisolates AT oliwiamakarewicz ramanspectroscopicdifferentiationofstreptococcuspneumoniaefromotherstreptococciusinglaboratorystrainsandclinicalisolates AT oliwiamakarewicz ramanspectroscopicdifferentiationofstreptococcuspneumoniaefromotherstreptococciusinglaboratorystrainsandclinicalisolates AT thomasbocklitz ramanspectroscopicdifferentiationofstreptococcuspneumoniaefromotherstreptococciusinglaboratorystrainsandclinicalisolates AT thomasbocklitz ramanspectroscopicdifferentiationofstreptococcuspneumoniaefromotherstreptococciusinglaboratorystrainsandclinicalisolates AT jurgenpopp ramanspectroscopicdifferentiationofstreptococcuspneumoniaefromotherstreptococciusinglaboratorystrainsandclinicalisolates AT jurgenpopp ramanspectroscopicdifferentiationofstreptococcuspneumoniaefromotherstreptococciusinglaboratorystrainsandclinicalisolates AT uteneugebauer ramanspectroscopicdifferentiationofstreptococcuspneumoniaefromotherstreptococciusinglaboratorystrainsandclinicalisolates AT uteneugebauer ramanspectroscopicdifferentiationofstreptococcuspneumoniaefromotherstreptococciusinglaboratorystrainsandclinicalisolates AT uteneugebauer ramanspectroscopicdifferentiationofstreptococcuspneumoniaefromotherstreptococciusinglaboratorystrainsandclinicalisolates |