A MALDI-ToF mass spectrometry database for identification and classification of highly pathogenic bacteria

Today, MALDI-ToF MS is an established technique to characterize and identify pathogenic bacteria. The technique is increasingly applied by clinical microbiological laboratories that use commercially available complete solutions, including spectra databases covering clinically relevant bacteria. Such databases are validated for clinical, or research applications, but are often less comprehensive concerning highly pathogenic bacteria (HPB). To improve MALDI-ToF MS diagnostics of HPB we initiated a program to develop protocols for reliable and MALDI-compatible microbial inactivation and to acquire mass spectra thereof many years ago. As a result of this project, databases covering HPB, closely related bacteria, and bacteria of clinical relevance have been made publicly available on platforms such as ZENODO. This publication in detail describes the most recent version of this database. The dataset contains a total of 11,055 spectra from altogether 1,601 microbial strains and 264 species and is primarily intended to improve the diagnosis of HPB. We hope that our MALDI-ToF MS data may also be a valuable resource for developing machine learning-based bacterial identification and classification methods. Today, MALDI-ToF MS is an established technique to characterize and identify pathogenic bacteria. The technique is increasingly applied by clinical microbiological laboratories that use commercially available complete solutions, including spectra databases covering clinically relevant bacteria. Such databases are validated for clinical, or research applications, but are often less comprehensive concerning highly pathogenic bacteria (HPB). To improve MALDI-ToF MS diagnostics of HPB we initiated a program to develop protocols for reliable and MALDI-compatible microbial inactivation and to acquire mass spectra thereof many years ago. As a result of this project, databases covering HPB, closely related bacteria, and bacteria of clinical relevance have been made publicly available on platforms such as ZENODO. This publication in detail describes the most recent version of this database. The dataset contains a total of 11,055 spectra from altogether 1,601 microbial strains and 264 species and is primarily intended to improve the diagnosis of HPB. We hope that our MALDI-ToF MS data may also be a valuable resource for developing machine learning-based bacterial identification and classification methods.© 2025. The Author(s).

Natl Inst Nucl Chem & Biol Protect
Chem & Veterinaruntersuchungsamt Stuttgart CVUAS
Plant Protect Res Inst
Inst Marine Biotechnol E V IMaB
Nanjing Agr Univ
Robert Koch Institut
Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek
Veterinärmedizinische Universität Wien
Institut für Mikrobiologie der Bundeswehr
National Institute for Nuclear, Chemical & Biological Protection
Natl Reference Ctr Staphylococci & Enterococci
Nanjing Agricultural University
Universidad Nacional de La Plata
Freunde der Veterinäranästhesie, Intensivmedizin und Analgesie
Netherlands Organization Applied Science Research
Friedrich Loeffler Institute
Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET)
Robert Koch Institute
Bundeswehr Institute of Microbiology (IMB)