Description: Morphological identification of cnidarian species can be difficult throughout all life stages due to the lack of distinct morphological characters. Moreover, in some cnidarian taxa genetic markers are not fully informative, and in these cases combinations of different markers or additional morphological verifications may be required. Proteomic fingerprinting based on MALDI-TOF mass spectra was previously shown to provide reliable species identification in different metazoans including some cnidarian taxa. For the first time, we tested the method across four cnidarian classes (Staurozoa, Scyphozoa, Anthozoa, Hydrozoa) and included different scyphozoan life-history stages (polyp, ephyra, medusa) in our dataset. Our results revealed reliable species identification based on MALDI-TOF mass spectra across all taxa with species-specific clusters for all 23 analysed species. In addition, proteomic fingerprinting was successful for distinguishing developmental stages, still by retaining a species specific signal. Furthermore, we identified the impact of different salinities in different regions (North Sea and Baltic Sea) on proteomic fingerprints to be negligible. In conclusion, the effects of environmental factors and developmental stages on proteomic fingerprints seem to be low in cnidarians. This would allow using reference libraries built up entirely of adult or cultured cnidarian specimens for the identification of their juvenile stages or specimens from different geographic regions in future biodiversity assessment studies.

Description: Species identification is pivotal in biodiversity assessments and proteomic fingerprinting by MALDI-TOF mass spectrometry has already been shown to reliably identify calanoid copepods to species level. However, MALDI-TOF data may contain more information beyond mere species identification. In this study, we investigated different ontogenetic stages (copepodids C1–C6 females) of three co-occurring Calanus species from the Arctic Fram Strait, which cannot be identified to species level based on morphological characters alone. Differentiation of the three species based on mass spectrometry data was without any error. In addition, a clear stage-specific signal was detected in all species, supported by clustering approaches as well as machine learning using Random Forest. More complex mass spectra in later ontogenetic stages as well as relative intensities of certain mass peaks were found as the main drivers of stage distinction in these species. Through a dilution series, we were able to show that this did not result from the higher amount of biomass that was used in tissue processing of the larger stages. Finally, the data were tested in a simulation for application in a real biodiversity assessment by using Random Forest for stage classification of specimens absent from the training data. This resulted in a successful stage-identification rate of almost 90%, making proteomic fingerprinting a promising tool to investigate polewards shifts of Atlantic Calanus species and, in general, to assess stage compositions in biodiversity assessments of Calanoida, which can be notoriously difficult using conventional identification methods.

Description: 〈jats:title〉Abstract〈/jats:title〉〈jats:p〉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. And thus can be a vital tool for biodiversity assessments in ecological studies. However, few studies have tested species identification across different orders and classes. In this study, we collected data from 1246 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.〈/jats:p〉

Description: We analysed the robustness of species identification based on proteomic composition to data processing and intraspecific variability, specificity and sensitivity of species-markers as well as discriminatory power of proteomic fingerprinting and its sensitivity to phylogenetic distance. Our analysis is based on MALDI-TOF MS (matrix-assisted laser desorption ionization time of flight mass spectrometry) data from 32 marine copepod species coming from 13 regions (North and Central Atlantic and adjacent seas). A random forest (RF) model correctly classified all specimens to the species level with only small sensitivity to data processing, demonstrating the strong robustness of the method. Compounds with high specificity showed low sensitivity, that is identification was based on complex pattern-differences rather than on presence of single markers. Proteomic distance was not consistently related to phylogenetic distance. A species-gap in proteome composition appeared at 0.7 Euclidean distance when using only specimens from the same sample. When other regions or seasons were included, intraspecific variability increased, resulting in overlaps of intra and inter-specific distance. Highest intraspecific distances (〉0.7) were observed between specimens from brackish and marine habitats (i.e., salinity probably affects proteomic patterns). When testing library sensitivity of the RF model to regionality, strong misidentification was only detected between two congener pairs. Still, the choice of reference library may have an impact on identification of closely related species and should be tested before routine application. We envisage high relevance of this time- and cost-efficient method for future zooplankton monitoring as it provides not only in-depth taxonomic resolution for counted specimens but also add-on information, such as on developmental stage or environmental conditions.