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Validation of Fourier Transform Infrared Spectroscopy for Serotyping of Streptococcus pneumoniae.
Passaris, I; Mauder, N; Kostrzewa, M; Burckhardt, I; Zimmermann, S; van Sorge, N M; Slotved, H-C; Desmet, S; Ceyssens, P-J.
Afiliación
  • Passaris I; Bacterial Diseases Unit, Sciensano, Brussels, Belgium.
  • Mauder N; Bruker Daltonic GmbH, Bremen, Germany.
  • Kostrzewa M; Bruker Daltonic GmbH, Bremen, Germany.
  • Burckhardt I; Department of Infectious Diseases, Microbiology and Hygiene, University Hospital of Heidelberg, Heidelberg, Germany.
  • Zimmermann S; Department of Infectious Diseases, Microbiology and Hygiene, University Hospital of Heidelberg, Heidelberg, Germany.
  • van Sorge NM; Department of Medical Microbiology and Infection Prevention, UMC Amsterdam, University of Amsterdam, Amsterdam, The Netherlands.
  • Slotved HC; Netherlands Reference Laboratory for Bacterial Meningitis, UMC Amsterdam, University of Amsterdam, Amsterdam, The Netherlands.
  • Desmet S; Department of Bacteria, Parasites and Fungi, Statens Serum Institutgrid.6203.7, Copenhagen, Denmark.
  • Ceyssens PJ; National Reference Centre for (invasive) S. pneumoniae, UZ Leuven, Leuven, Belgium.
J Clin Microbiol ; 60(7): e0032522, 2022 07 20.
Article en En | MEDLINE | ID: mdl-35699436
ABSTRACT
Fourier transform infrared (FT-IR) spectroscopy (IR Biotyper; Bruker) allows highly discriminatory fingerprinting of closely related bacterial strains. In this study, FT-IR spectroscopy-based capsular typing of Streptococcus pneumoniae was validated as a rapid, cost-effective, and medium-throughput alternative to the classical phenotypic techniques. A training set of 233 strains was defined, comprising 34 different serotypes and including all 24 vaccine types (VTs) and 10 non-vaccine types (NVTs). The acquired spectra were used to (i) create a dendrogram where strains clustered together according to their serotypes and (ii) train an artificial neural network (ANN) model to predict unknown pneumococcal serotypes. During validation using 153 additional strains, we reached 98.0% accuracy for determining serotypes represented in the training set. Next, the performance of the IR Biotyper was assessed using 124 strains representing 59 non-training set serotypes. In this setting, 42 of 59 serotypes (71.1%) could be accurately categorized as being non-training set serotypes. Furthermore, it was observed that comparability of spectra was affected by the source of the Columbia medium used to grow the pneumococci and that this complicated the robustness and standardization potential of FT-IR spectroscopy. A rigorous laboratory workflow in combination with specific ANN models that account for environmental noise parameters can be applied to overcome this issue in the near future. The IR Biotyper has the potential to be used as a fast, cost-effective, and accurate phenotypic serotyping tool for S. pneumoniae.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Infecciones Neumocócicas / Streptococcus pneumoniae Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans Idioma: En Revista: J Clin Microbiol Año: 2022 Tipo del documento: Article País de afiliación: Bélgica

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Infecciones Neumocócicas / Streptococcus pneumoniae Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans Idioma: En Revista: J Clin Microbiol Año: 2022 Tipo del documento: Article País de afiliación: Bélgica