ALBERT

Description: Sequence-based specimen identification, known as DNA barcoding, is a common method complementing traditional morphology-based taxonomic assignments. The fundamental resource in DNA barcoding is the availability of a taxonomically reliable sequence database to use as a reference for sequence comparisons. Here, we provide a reference library including 579 sequences of the mitochondrial cytochrome c oxidase subunit I for 113 North Sea mollusc species. We tested the efficacy of this library by simulating a sequence-based specimen identification scenario using Best Match, Best Close Match (BCM) and All Species Barcode (ASB) criteria with three different threshold values. Each identification result was compared with our prior morphology-based taxonomic assignments. Our simulation resulted in 87.7% congruent identifications (93.8% when excluding singletons). The highest number of congruent identifications was obtained with BCM and ASB and a 0.05 threshold. We also compared identifications with genetic clustering (Barcode Index Numbers, BINs) computed by the Barcode of Life Datasystem (BOLD). About 68% of our morphological identifications were congruent with BINs created by BOLD. Forty-nine sequences were clustered in 16 discordant BINs, and these were divided in two classes: sequences from different species clustered in a single BIN and conspecific sequences divided in more BINs. Whereas former incongruences were probably caused by BOLD entries in need of a taxonomic update, the latter incongruences regarded taxa requiring further investigations. These include species with amphi-Atlantic distribution, whose genetic structure should be evaluated over their entire range to produce a reliable sequence-based identification system.

Description: Accurate and reliable biodiversity estimates of marine zooplankton are a prerequisite to understand how changes in diversity can affect whole ecosystems. Species identification in the deep sea is significantly impeded by high numbers of new species and decreasing numbers of taxonomic experts, hampering any assessment of biodiversity. We used in parallel morphological, genetic, and proteomic characteristics of specimens of calanoid copepods from the abyssal South Atlantic to test if proteomic fingerprinting can accelerate estimating biodiversity. We cross-validated the respective molecular discrimination methods with morphological identifications to establish COI and proteomic reference libraries, as they are a pre-requisite to assign taxonomic information to the identified molecular species clusters. Due to the high number of new species only 37% of the individuals could be assigned to species or genus level morphologically. COI sequencing was successful for 70% of the specimens analysed, while proteomic fingerprinting was successful for all specimens examined. Predicted species richness based on morphological and molecular methods was 42 morphospecies, 56 molecular operational taxonomic units (MOTUs) and 79 proteomic operational taxonomic units (POTUs), respectively. Species diversity was predicted based on proteomic profiles using hierarchical cluster analysis followed by application of the variance ratio criterion for identification of species clusters. It was comparable to species diversity calculated based on COI sequence distances. Less than 7% of specimens were misidentified by proteomic profiles when compared with COI derived MOTUs, indicating that unsupervised machine learning using solely proteomic data could be used for quickly assessing species diversity.

Description: Marine community diversity surveys require a reliable assessment to estimate ecosystem functions and their dynamics. For these, non-invasive environmental DNA (eDNA) metabarcoding is increasingly applied in zoological studies to complement or even replace traditional morphological identification methods. However, uncertainties remain about the accuracy of the diversity detected with eDNA to capture the actual diversity in the field. Here, we validate the reliability of eDNA metabarcoding in identifying metazoan biodiversity in highly dynamic marine waters of the North Sea. We analyzed biodiversity from water (eDNA) and zooplankton samples with cytochrome c oxidase subunit 1 (COI) and 18S rRNA (18S) metabarcoding at Helgoland Roads and validated the optimal molecular resolution by morphological and molecular zooplankton identification (metabarcoding) with the result of merely a few false-negative detections. eDNA and zooplankton metabarcoding resolved 354 species from all major and in total 16 metazoan phyla. This molecular genetic species inventory overlapped by 95.9% (COI) and 81.9% (18S) with published inventories of local, morphologically identified species, among them neozoa and rediscovered species. Even though half of all species were detected by both eDNA and zooplankton metabarcoding, the methods differed significantly in their detected diversity. eDNA metabarcoding performed very well in cnidarians and annelids, whereas zooplankton metabarcoding identified higher numbers of fish and malacostraca. Species assemblages significantly differed between the individual sampling events and the cumulative number of identified species increased steadily over the sampling period and did not reach saturation. About a third of the species were detected only once while a core community of 22 species was identified continuously. Our study confirms eDNA metabarcoding to be a powerful tool to identify and analyze North Sea fauna in highly dynamic waters and we recommend investing in high sampling efforts by repetitive sampling and replication using at least 0.45 μm filters to increase filtration volume.

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.

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: 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.

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: Interoceanic canals can facilitate biological invasions as they connect the world's oceans and remove dispersal barriers between bioregions. As a consequence, multiple opportunities for biotic exchange arise and the resulting establishment of migrant species often causes adverse ecological and economic impacts. The Panama Canal is a key region for biotic exchange as it connects the Pacific and Atlantic Oceans in Central America. In this study, we used two complementary methods (environmental DNA (eDNA) metabarcoding and gillnetting) to survey fish communities in this unique waterway. Using COI (cytochrome oxidase subunit I) metabarcoding, we detected a total of 142 fish species, including evidence for the presence of sixteen Atlantic and eight Pacific marine fish in different freshwater sections of the Canal. Of these, nine are potentially new records. Molecular data did not capture all species caught with gillnets, but generally provided a more complete image of the known fish fauna as more small-bodied fish species were detected. Diversity indices based on eDNA surveys revealed significant differences across different sections of the Canal reflecting in part the prevailing environmental conditions. The observed increase in the presence of marine fish species in the Canal indicates a growing potential for interoceanic fish invasions. The potential ecological and evolutionary consequences of this increase in marine fishes are not only restricted to the fish fauna in the Canal as they could also impact adjacent ecosystems in the Pacific and Atlantic Oceans.