ArticleJournal of clinical microbiology2022
Validation of Fourier Transform Infrared Spectroscopy for Serotyping of Streptococcus pneumoniae.
Article in Journal of clinical microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 25 citations in OpenAlex.
- A standardized workflow for typing S. marcescens outbreaks using FT-IR spectroscopy.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026Article
- Evaluation of AI-enhanced FTIR spectroscopy for species and biovar typing of intracellular pathogenic Brucella spp.BMC microbiology · 2026Article
- Evaluating the performance of Fourier transform infrared spectroscopy for typing and outbreak investigation of methicillin-resistant and -susceptibleMicrobiology spectrum · 2026Article
- Laboratory strategies for the identification of Burkholderia species: From classical phenotyping to advanced genomic and proteomic approaches.Antonie van Leeuwenhoek · 2026Review
- Fourier transform infrared spectroscopy enables rapid strain typing and cluster analysis ofFrontiers in microbiology · 2026Article
- Machine Learning Model with Fourier-Transform Infrared Spectroscopy (FTIR) as a Proof-of-Concept Tool for Predicting Group ADiagnostics (Basel, Switzerland) · 2025Article
- Use of IR Biotyper as a feasible methodology to typeMicrobiology spectrum · 2025Article
- AI-Enhanced FT-IR Spectroscopy: Evaluation of a Novel Tool for High-Throughput Serovar Typing ofPathogens (Basel, Switzerland) · 2025Article
- Development of a robust FT-IR typing system forMicrobiology spectrum · 2025Article
- Fourier-transform infrared spectroscopy for rapidFrontiers in microbiology · 2025Article
- Non-invasiveEuro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2024Article
- Standardized Electric-Field-Resolved Molecular Fingerprinting.Analytical chemistry · 2024Article
- A Comprehensive Methodology for Microbial Strain Typing Using Fourier-Transform Infrared Spectroscopy.Methods and protocols · 2024Article
- Perspectives of FTIR as Promising Tool for Pathogen Diagnosis, Sanitary and Welfare Monitoring in Animal Experimentation Models: A Review Based on Pertinent Literature.Microorganisms · 2024Review
- Development and validation of a quick, automated, and reproducible ATR FT-IR spectroscopy machine-learning model forJournal of clinical microbiology · 2024Article
- Fourier transform infrared spectroscopy forFrontiers in microbiology · 2024Article
- What are the most relevant publications in Clinical Microbiology in the last two years?Revista espanola de quimioterapia : publicacion oficial de la Sociedad Espanola de Quimioterapia · 2023Review
- A multi-center validation study on the discrimination ofFrontiers in microbiology · 2023Article
- Effect of β - hydroxy - γ -aminophosphonate (β - HPC) on the hydrolytic activity ofFrontiers in microbiology · 2023Article
- Investigating the Origin of Mycobacterium chimaera Contamination in Heater-Cooler Units: Integrated Analysis with Fourier Transform Infrared Spectroscopy and Whole-Genome Sequencing.Microbiology spectrum · 2022Article
Corrections and comments
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Authors and funding
9 authors at 6 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
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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