ArticlePloS one2016
The Technical and Biological Reproducibility of Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) Based Typing: Employment of Bioinformatics in a Multicenter Study.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Machine Learning-Based Prediction of Antimicrobial Resistance inDiagnostics (Basel, Switzerland) · 2026Article
- MALDI-TOF MS Classification of Formosan Thraustochytrids and Their Use in Shrimp Farming.Journal of agricultural and food chemistry · 2026Article
- A MALDI-ToF mass spectrometry database for identification and classification of highly pathogenic bacteria.Scientific data · 2025Article
- Using matrix assisted laser desorption ionisation mass spectrometry combined with machine learning for vaccine authenticity screening.NPJ vaccines · 2024Article
- Evaluation of Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry for Molecular Typing of Acinetobacter baumannii in Comparison with Orthogonal Methods.Microbiology spectrum · 2023Article
- Rapid Discrimination ofTransboundary and emerging diseases · 2023Article
- Development and Evaluation of a Core Genome Multilocus Sequencing Typing (cgMLST) Scheme for Serratia marcescens Molecular Surveillance and Outbreak Investigations.Journal of clinical microbiology · 2022Article
- Rapid and Reproducible MALDI-TOF-Based Method for the Detection of Vancomycin-ResistantDiagnostics (Basel, Switzerland) · 2022Article
- Direct antimicrobial resistance prediction from clinical MALDI-TOF mass spectra using machine learning.Nature medicine · 2022Article
- Toward improvement of screening through mass spectrometry-based proteomics: ovarian cancer as a case study.International journal of mass spectrometry · 2021Article
- Investigation of MALDI-TOF Mass Spectrometry for Assessing the Molecular Diversity ofDiagnostics (Basel, Switzerland) · 2021Article
- An Improved Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry Data Analysis Pipeline for the Identification of Carbapenemase-Producing Klebsiella pneumoniae.Journal of clinical microbiology · 2021Article
- Network Analysis Based on Unique Spectral Features Enables an Efficient Selection of Genomically Diverse Operational Isolation Units.Microorganisms · 2021Article
- Bacterial species identification using MALDI-TOF mass spectrometry and machine learning techniques: A large-scale benchmarking study.Computational and structural biotechnology journal · 2021Article
- Factors Associated With MALDI-TOF Mass Spectral Quality of Species Identification in Clinical Routine Diagnostics.Frontiers in cellular and infection microbiology · 2021Article
- Cumulative learning enables convolutional neural network representations for small mass spectrometry data classification.Nature communications · 2020Article
- Pathogen proteotyping: A rapidly developing application of mass spectrometry to address clinical concerns.Clinical mass spectrometry (Del Mar, Calif.) · 2019Review
- Use of MALDI-TOF mass spectrometry to detect nosocomial outbreaks of Serratia marcescens and Citrobacter freundii.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2019Article
- Article
- Review of the impact of MALDI-TOF MS in public health and hospital hygiene, 2018.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2019Article
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Authors and funding
8 authors.
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Abstract
backgroundThe technical, biological, and inter-center reproducibility of matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI TOF MS) typing data has not yet been explored. The aim of this study is to compare typing data from multiple centers employing bioinformatics using bacterial strains from two past outbreaks and non-related strains. MATERIAL/
methodsParticipants received twelve extended spectrum betalactamase-producing E. coli isolates and followed the same standard operating procedure (SOP) including a full-protein extraction protocol. All laboratories provided visually read spectra via flexAnalysis (Bruker, Germany). Raw data from each laboratory allowed calculating the technical and biological reproducibility between centers using BioNumerics (Applied Maths NV, Belgium).
resultsTechnical and biological reproducibility ranged between 96.8-99.4% and 47.6-94.4%, respectively. The inter-center reproducibility showed a comparable clustering among identical isolates. Principal component analysis indicated a higher tendency to cluster within the same center. Therefore, we used a discriminant analysis, which completely separated the clusters. Next, we defined a reference center and performed a statistical analysis to identify specific peaks to identify the outbreak clusters. Finally, we used a classifier algorithm and a linear support vector machine on the determined peaks as classifier. A validation showed that within the set of the reference center, the identification of the cluster was 100% correct with a large contrast between the score with the correct cluster and the next best scoring cluster.
conclusionsBased on the sufficient technical and biological reproducibility of MALDI-TOF MS based spectra, detection of specific clusters is possible from spectra obtained from different centers. However, we believe that a shared SOP and a bioinformatics approach are required to make the analysis robust and reliable.
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