ArticleApplied and environmental microbiology2009
Identification of Bacillus anthracis by using matrix-assisted laser desorption ionization-time of flight mass spectrometry and artificial neural networks.
Article in Applied and environmental microbiology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
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Who cites it
53 citing papers in PubMed.
- TrackingACS omega · 2026Review
- Spectral Precision: Recent Advances in Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry for Pathogen Detection and Resistance Profiling.Microorganisms · 2025Review
- Isoelectric Focusing Fractionation Method for Signal Enhancement in Detection of Inactivated Biological Agents Using Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry.Electrophoresis · 2025Article
- A MALDI-ToF mass spectrometry database for identification and classification of highly pathogenic bacteria.Scientific data · 2025Article
- Resolution of MALDI-TOF compared to whole genome sequencing for identification ofFrontiers in microbiology · 2025Article
- Pseudo-outbreak of Bacillaceae species associated with poor compliance with blood culture collection recommendations.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2024Observational
- Article
- Machine Learning Algorithms for Classification of MALDI-TOF MS Spectra from Phylogenetically Closely Related SpeciesMicroorganisms · 2022Article
- Identification, characterization and antibiotic susceptibility testing forIranian journal of microbiology · 2022Article
- Current Scenario and Challenges in the Direct Identification of Microorganisms Using MALDI TOF MS.Microorganisms · 2021Review
- Discrimination ofMicroorganisms · 2021Article
- Assessing the ratio of Bacillus spores and vegetative cells by shotgun proteomics.Environmental science and pollution research international · 2021Article
- Proteomic Characterization of Bacteriophage Peptides from the Mastitis ProducerFoods (Basel, Switzerland) · 2021Article
- Bacterial species identification using MALDI-TOF mass spectrometry and machine learning techniques: A large-scale benchmarking study.Computational and structural biotechnology journal · 2021Article
- Article
- Elucidation of protein biomarkers for verification of selected biological warfare agents using tandem mass spectrometry.Scientific reports · 2020Article
- Detection and Identification ofMicroorganisms · 2020Review
- Helix Matrix Transformation Combined With Convolutional Neural Network Algorithm for Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry-Based Bacterial Identification.Frontiers in microbiology · 2020Article
- Detection of Bacillus anthracis and Bacillus anthracis-like spores in soil from state of Rio de Janeiro, Brazil.Memorias do Instituto Oswaldo Cruz · 2020Article
- Characterization of Bacteriophage Peptides of PathogenicFrontiers in microbiology · 2020Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This report demonstrates the applicability of a combination of matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry (MS) and chemometrics for rapid and reliable identification of vegetative cells of the causative agent of anthrax, Bacillus anthracis. Bacillus cultures were prepared under standardized conditions and inactivated according to a recently developed MS-compatible inactivation protocol for highly pathogenic microorganisms. MALDI-TOF MS was then employed to collect spectra from the microbial samples and to build up a database of bacterial reference spectra. This database comprised mass peak profiles of 374 strains from Bacillus and related genera, among them 102 strains of B. anthracis and 121 strains of B. cereus. The information contained in the database was investigated by means of visual inspection of gel view representations, univariate t tests for biomarker identification, unsupervised hierarchical clustering, and artificial neural networks (ANNs). Analysis of gel views and independent t tests suggested B. anthracis- and B. cereus group-specific signals. For example, mass spectra of B. anthracis exhibited discriminating biomarkers at 4,606, 5,413, and 6,679 Da. A systematic search in proteomic databases allowed tentative assignment of some of the biomarkers to ribosomal protein or small acid-soluble proteins. Multivariate pattern analysis by unsupervised hierarchical cluster analysis further revealed a subproteome-based taxonomy of the genus Bacillus. Superior classification accuracy was achieved when supervised ANNs were employed. For the identification of B. anthracis, independent validation of optimized ANN models yielded a diagnostic sensitivity of 100% and a specificity of 100%.
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