A universal tool for marine metazoan species identification – Towards best practices in proteomic fingerprinting

Proteomic fingerprinting using MALDI-TOF mass spectrometry is a well-established tool for identifying microorganisms and has shown promising results for identification of animal species, particularly disease vectors and marine organisms. However, few studies have tested species identification across different orders and classes. In this study, we collected data from 1,246 specimens and 198 species to test species identification in a diverse dataset. We also evaluated different specimen preparation and data processing approaches for machine learning and developed a workflow to optimize classification using random forest. Our results showed high success rates of over 90%, but we also found that the size of the reference library affects classification error. Additionally, we demonstrated the ability of the method to differentiate marine cryptic-species complexes and to distinguish sexes within species., Tissue for measurements was taken mainly from the marine organisms tissue bank of the Senckenberg am Meer, German Centre for Marine Biodiversity Research, which was established using samples from numerous studies (Knebelsberger and Thiel, 2014; Knebelsberger et al., 2014; Markert et al., 2014; Gebhardt and Knebelsberger, 2015; Raupach et al., 2015; Barco et al., 2016; Laakmann et al., 2016; Rossel et al., 2020b) (supplementary table S1 for accession numbers) on North Sea metazoans. The material from this collection was taken from specimens processed for COI-barcoding to create reference libraries for a variety of marine animal groups. During this process, tissue samples of the respective specimens were stored in ethanol at -80°C. Tissue samples were available for Bivalvia (muscle, 18 species), Cephalopoda (muscle from arm, 12 species), Gastropoda (muscle from foot, 24 species), Polyplacophora (muscle from foot, 2 species), Ascidiacea (tissue, 1 species), Teleostei (muscle, 67 species), ..., Data can be analyzed using Bruker proprietary software such as Bruker Flex analysis or Bruker Biotyper.
Alternatively, data can be analyzed in R using R-packages MaldiQuant and MaldiQuantForeign following the vignette that can be found via:
https://cran.r-project.org/web/packages/MALDIquant/index.html, # Data from: Proteomic fingerprinting as universal tool for species identification in marine metazoans on the road to best practices

The data relates to the publication Proteomic fingerprinting as universal tool for species identification in marine metazoans on the road to best practices in Nature Scientific Reports.

DOI:*10.1038/s41598-024-51235-z*

This dataset contains an Excel file called ReferenceTable.csv and a .zip file containing raw Bruker mass spectrometry files for 1246 measurements from a variety of marine species. For each specimen, one folder is included in the .zip file. These files are named according to specimen names in the Excel file. Furthermore, the excel file contains information on
taxonomical classification of each specimen.

The .zip file contains a folder named Dryad in which folders for the 1246 specimens are deposited. These again containing folders for each specimen. The \"specimen folders\" are build up according to the default Bruker flex container system ...