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 ...使用基质辅助激光解吸电离飞行时间质谱（MALDI-TOF mass spectrometry）开展蛋白质组指纹图谱分析，是目前成熟的微生物鉴定工具，在动物物种（尤其是病媒生物与海洋生物）鉴定领域已展现出良好应用前景。然而，当前鲜有研究在不同纲、目层面开展跨类群的物种鉴定测试。本研究收集了涵盖1246份标本、198个物种的数据集，用于评估物种鉴定模型的性能；同时针对机器学习任务，评估了不同标本制备与数据处理方案，并开发了基于随机森林（random forest）的分类优化流程。研究结果显示模型分类成功率超90%，同时发现参考数据库规模会对分类误差产生影响。此外，本研究证实该方法可有效区分海洋隐存物种复合群，还能实现物种内的性别分辨。 本研究的检测用组织主要取自德国海洋生物多样性研究中心森肯伯格海洋研究所（Senckenberg am Meer）的海洋生物组织库，该库依托北海后生动物的多项前期研究样本建立（Knebelsberger & Thiel, 2014; Knebelsberger等, 2014; Markert等, 2014; Gebhardt & Knebelsberger, 2015; Raupach等, 2015; Barco等, 2016; Laakmann等, 2016; Rossel等, 2020b）（样本登录号详见补充表S1）。该馆藏样本均为经COI条形码测序（COI-barcoding）处理的标本，用于构建各类海洋动物类群的参考数据库。在此流程中，对应标本的组织样本以乙醇保存于-80℃低温环境中。本次研究可用的组织样本类群包括：双壳纲（足肌，18个物种）、头足纲（腕部肌肉，12个物种）、腹足纲（足部肌肉，24个物种）、多板纲（足部肌肉，2个物种）、被囊动物亚门（组织样本，1个物种）、辐鳍鱼纲（肌肉组织，67个物种）…… 质谱数据可使用布鲁克（Bruker）专有软件进行分析，如Bruker Flex Analysis或Bruker Biotyper。此外，也可通过R语言环境下的MaldiQuant与MaldiQuantForeign软件包，按照官方教程进行数据分析，教程可通过以下链接获取：https://cran.r-project.org/web/packages/MALDIquant/index.html # 数据来源：《Proteomic fingerprinting as universal tool for species identification in marine metazoans on the road to best practices》 本数据集关联发表于《自然·科学报告》（Nature Scientific Reports）的同名研究论文，DOI：10.1038/s41598-024-51235-z。 本数据集包含一个名为ReferenceTable.csv的Excel文件，以及一个压缩包文件，内含1246份来自多种海洋物种的布鲁克质谱原始数据文件。压缩包中为每份标本单独设立一个文件夹，文件名与Excel文件中的标本名称一一对应。此外，该Excel文件包含所有标本的分类学分类信息。 该压缩包内包含一个名为Dryad的文件夹，其中存放1246份标本对应的子文件夹，每个标本子文件夹的构建遵循布鲁克Flex容器系统的默认格式……