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Introduction

Library based MS approaches for microbial identification require labeled sets of microbial mass spectra. Starting with version 0.82, MicrobeMS can work with experimental MALDI-TOF or LC-MS¹ mass spectra and their corresponding MS databases.
The RKI databases of microbial MALDI-TOF mass spectra contain mass spectra of highly pathogenic (biosafety level 3, BSL-3) bacteria such as Bacillus anthracis, Yersinia pestis, Burkholderia mallei, Burkholderia pseudomallei, Brucella melitensis and Francisella tularensis as well as a selection of MALDI-TOF mass spectra of their close and distant relatives. The RKI mass spectral databases can be used as a reference for the diagnosis of BSL-3 bacteria using proprietary and free software packages for MALDI-TOF MS-based microbial identification. The databases are distributed as zip archives and contain the original mass spectra in their native data format (Bruker Daltonics). The MALDI-TOF MS databases are updated on a regular basis.
The LC-MS¹ database is an in silico database compiled from Uni-Prot Knowledgebase resources (Uni-Prot/KB Swissprot and TrEMBL), for details see below).

MALDI-TOF MS databases

The different versions of RKI biosafety level 3 (BSL-3) MALDI-TOF MS database can be downloaded from the following locations:

 1. Zenodo database version 4 (20230306):
    Lasch P, Stämmler M & Schneider A, (2023). Version 4 (20230306) of the 
    MALDI-TOF Mass Spectrometry Database for Identification and Classification of Highly
    Pathogenic Microorganisms from the Robert Koch-Institute (RKI). 
    Zenodo. https://doi.org/10.5281/zenodo.7702375
    Version Mar 06, 2023, creative commons CC BY-NC-SA 4.0 license

 2. Zenodo database version 3 (20181130):
    Lasch P, Stämmler M & Schneider A, (2018). Version 3 (20181130) of the 
    MALDI-TOF Mass Spectrometry Database for Identification and Classification of Highly
    Pathogenic Microorganisms from the Robert Koch-Institute (RKI). 
    Zenodo. https://doi.org/10.5281/zenodo.1880975
    Version Nov 30, 2018, creative commons CC BY-NC-SA 4.0 license

 3. Zenodo database version 2 (20170523):
    Lasch P, Stämmler M & Schneider , (2017). Version 2 (20170523) of the 
    MALDI-TOF Mass Spectrometry Database for Identification and Classification of Highly
    Pathogenic Microorganisms from the Robert Koch-Institute (RKI). 
    Zenodo. http://doi.org/10.5281/zenodo.582602
    Version May 23, 2017, creative commons CC BY-NC-SA 4.0 license

 4. Zenodo database version 1 (20161027):
    Lasch P, Stämmler M & Schneider A, (2016). A MALDI-TOF Mass Spectrometry
    Database for Identification and Classification of Highly Pathogenic Microorganisms from 
    the Robert Koch-Institute (RKI). Zenodo. http://doi.org/10.5281/zenodo.163517
    Version October 27, 2016, creative commons CC BY-NC-SA 4.0 license

LC-MS¹ databases

The original concept of microbial identification by means of MALDI-TOF MS of cultivated microbial cells and spectral distance-based comparison with entries of a microorganism spectra library has been adapted for LC-MS¹ microbial identification, see this preprint: Lasch P, Schneider A, Blumenscheit C and Doellinger J, Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MS¹) and in silico Peptide Mass Data, bioRxiv (Dec 10, 2018), doi:10.1101/870089.

 1. Lasch P, Schneider A, Blumenscheit C, Doellinger J. (2019). In silico Database for 
    Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MS¹). 
    Zenodo. https://doi.org/10.5281/zenodo.3573996
    Version December 13, 2019, creative commons CC BY-NC-SA 4.0 license

Details can be found here: Identification analysis by means of LC-MS¹ and in silico databases