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

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2025-01-31 DOI:10.1038/s41597-025-04504-z
Peter Lasch, Wolfgang Beyer, Alejandra Bosch, Rainer Borriss, Michal Drevinek, Susann Dupke, Monika Ehling-Schulz, Xuewen Gao, Roland Grunow, Daniela Jacob, Silke R Klee, Armand Paauw, Jörg Rau, Andy Schneider, Holger C Scholz, Maren Stämmler, Le Thi Thanh Tam, Herbert Tomaso, Guido Werner, Joerg Doellinger
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Abstract

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.

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用于高致病性细菌鉴定和分类的MALDI-ToF质谱数据库。
今天,MALDI-ToF质谱是一种成熟的表征和鉴定致病菌的技术。该技术越来越多地被临床微生物实验室应用,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。这些数据库在临床或研究应用中得到了验证,但在高致病性细菌(HPB)方面往往不太全面。为了提高MALDI-ToF质谱对HPB的诊断,我们多年前就启动了一个项目,开发可靠的、与maldi兼容的微生物失活方案,并获得其质谱。该项目的结果是,覆盖HPB、密切相关细菌和临床相关细菌的数据库已在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,主要用于提高HPB的诊断。我们希望我们的MALDI-ToF质谱数据也可以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。
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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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