Lasch Peter, Beyer Wolfgang, Bosch Alejandra, Borriss Rainer, Drevinek Michal, Dupke Susann, Ehling-Schulz Monika, Gao Xuewen, Grunow Roland, Jacob Daniela, Klee Silke R, Paauw Armand, Rau Jörg, Schneider Andy, Scholz Holger C, Stämmler Maren, Thanh Tam Le Thi, Tomaso Herbert, Werner Guido, Doellinger Joerg
Robert Koch Institute, ZBS 6 - Proteomics and Spectroscopy, Seestraße 10, Berlin, D-13353, Germany.
Advisory Panel of the Medical Academy of the German Armed Forces, Bundeswehr Institute of Microbiology, Munich, Germany.
Sci Data. 2025 Jan 31;12(1):187. doi: 10.1038/s41597-025-04504-z.
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.
如今,基质辅助激光解吸电离飞行时间质谱(MALDI-ToF MS)是一种用于鉴定和识别病原菌的成熟技术。该技术在临床微生物实验室中应用越来越广泛,这些实验室使用市售的完整解决方案,包括涵盖临床相关细菌的光谱数据库。此类数据库已针对临床或研究应用进行了验证,但对于高致病性细菌(HPB)的覆盖往往不够全面。为了改进MALDI-ToF MS对HPB的诊断,我们多年前启动了一个项目,旨在开发可靠且与MALDI兼容的微生物灭活方案,并获取其质谱图。作为该项目的成果,涵盖HPB、密切相关细菌以及临床相关细菌的数据库已在诸如ZENODO等平台上公开提供。本出版物详细描述了该数据库的最新版本。该数据集总共包含来自1601个微生物菌株和264个物种的11055个光谱,主要用于改进HPB的诊断。我们希望我们的MALDI-ToF MS数据也可能成为开发基于机器学习的细菌鉴定和分类方法的宝贵资源。