Scientia Marina 87 (2)
June 2023, e061
ISSN: 0214-8358, eISSN: 1886-8134
https://doi.org/10.3989/scimar.05275.061

Barcoding coffee grounds-Exploring pteropod gastropod biodiversity with dregs in collection jars

Barcoding a partir de posos de café - Explorando la biodiversidad de gasterópodos pterópodos a partir de posos de frascos de colección

Christina Franziska Laibl

SNSB-Bavarian State Collection of Zoology, Münchhausenstraße 21, 81247 München, Germany.
Ludwig-Maximilians-Universität München, Faculty of Biology, Großhadernerstraße 2, 82152 Planegg-Martinsried, Germany.

https://orcid.org/0000-0002-0306-3467

Juan Lucas Cervera Currado

Departamento de Biología, Facultad de Ciencias del Mar y Ambientales, Campus de Excelencia Internacional del Mar (CEIMAR), Universidad de Cádiz, Av. República Saharaui, s/n, P.O. Box 40, 11510 Puerto Real, Cádiz, Spain.
Instituto Universitario de Investigación Marina (INMAR), Campus de Excelencia Internacional del Mar (CEIMAR), Universidad de Cádiz, Av. República Saharaui, s/n, P.O. Box 40, 11510 Puerto Real, Cádiz, Spain.

https://orcid.org/0000-0002-8337-2867

Jérôme Morinière

AIM - Advanced Identification Methods GmbH. Niemeyerstr. 1, 04179 Leipzig, Germany.

https://orcid.org/0000-0001-9167-6409

Michael Schrödl

SNSB-Bavarian State Collection of Zoology, Münchhausenstraße 21, 81247 München, Germany.
Ludwig-Maximilians-Universität München, Faculty of Biology, Großhadernerstraße 2, 82152 Planegg-Martinsried, Germany.
GeoBioCentrer LMU, Centre of Geobiology and Biodiversity Research at the Ludwig-Maximilians-University Munich, Germany.

https://orcid.org/0000-0002-7629-1911

Summary

Despite their cosmopolitan occurrence and massive plankton sampling during expeditions, the genetic diversity within Pteropoda Cuvier, 1804 is still largely unexplored. In this study we present a next-generation environmental barcoding approach to zooplankton bulk samples, which were collected during the circumglobal 2010 Malaspina expedition to evaluate pteropod diversity. We introduce a technique that avoids destructive procedures and leaves material intact for further morphological investigations. We extracted DNA out of the dregs (organic material such as mucus or body parts) of 27 sample containers for molecular barcoding (average 100-260 bp of COI). We were able to identify 7128 operational taxonomic units corresponding to the species composition contained in the examined samples. Among them were three species of thecosome pteropods, Creseis acicula, Creseis virgula and Cavolinia inflexa, which are discussed with respect to their taxonomy and their geographic distribution. Unidentified gymnosomes were also present in our samples from warmer regions in oceanic waters of the southern Indian Ocean. To facilitate identification of species, it is beneficial to create a better database of pteropod COI barcodes. Furthermore, gathering environmental barcoding data on a broad global scale will help to better understand species abundance and distribution of pteropods in the world’s oceans, and potentially those of other planktonic organisms.

Keywords: 
Mollusca; Gastropoda; plankton; environmental DNA; circumglobally; pteropod diversity; Malaspina expedition
Resumen

A pesar de su presencia cosmopolita y las actividades de muestreo masivo de plancton durante las expediciones, la diversidad genética dentro de los Pteropoda Cuvier, 1804 está todavía inexplorada en gran medida. En este estudio se presenta una aproximación desde el barcoding ambiental aplicada a muestras generales de zooplancton recogidas durante la expedición circumglobal “Malaspina 2010”, con el fin de evaluar la diversidad de pterópodos. Se introduce una técnica que evita procedimientos destructivos de tal modo que el material permanece intacto para futuras investigaciones morfológicas. Extrajimos ADN de los posos (material orgánico como moco o partes del cuerpo) de 27 recipientes de muestras para el barcoding (promedio de 100- 260 bp de COI). Se pudieron identificar 7128 “OTUs” correspondientes a la composición de las especies contenidas en las muestras examinadas. Entre ellas se encontraron tres especies de pterópodos tecosomados, Creseis acicula, Creseis virgula y Cavolinia inflexa, cuya taxonomía y distribución geográfica son discutidas. Gimnosomados no identificados procedentes de regiones más templadas de aguas oceánicas del sur del Océnao Indico también estaban presentes. Para facilitar la identificación de especies, es beneficioso crear una base de datos ampliada de códigos de barras COI de pterópodos. Además, la recopilación de datos de barcoding ambiental a una escala mundial amplia ayudará a comprender mejor la abundancia y distribución de especies de pterópodos en los océanos del mundo y de otros posibles organismos planctónicos.

Palabras clave: 
Mollusca; Gastropoda; plancton; ADN ambiental; circumglobal; diversidad de pterópodos; expedición Malaspina

Received: February  17,  2022. Accepted: January  10,  2023. Published: June  11,  2023

Editor: J. Viñas.

Citation/Cómo citar este artículo: Laibl C.F., Cervera Currado J.L., Morinière J., Schrödl M. 2023. Barcoding coffee grounds-Exploring pteropod gastropod biodiversity with dregs in collection jars. Sci. Mar. 87(2): e061. https://doi.org/10.3989/scimar.05275.061

CONTENT

INTRODUCTION

 

There are more than 230000 known metazoan species populating the world’s oceans. However, as a result of climate change, ocean acidification and marine pollution, the increasing loss of biodiversity presents a daunting challenge to taxonomists, requiring the discovery and analysis of biodiversity at a greatly accelerated pace. In the face of growing extinction rates that are without much doubt outpacing the number of discoveries of new taxa, fast and accurate biodiversity analysis methods are urgently needed (Bucklin et al. 2011Bucklin A., Steinke D., Blanco-Bercial L. 2011. DNA barcoding of marine metazoa. Annu. Rev. Mar. Science 3: 471-508. https://doi.org/10.1146/annurev-marine-120308-080950 ). Especially problematic is the taxonomic treatment of large-scale environmental bulk samples such as phyto- and zooplankton. Sorting and identifying the various organisms requires a lot of time before reliable diversity assessments are possible. Furthermore, traditional morphological approaches are limited and less efficient for analysing bulk samples or samples lacking distinguishing phenotypic features (for example immature or damaged specimens). It is well established that genetic markers, and especially COI barcoding, are a complementary tool to traditional morphology-based taxonomic research for the identification and delimitation of different lineages (Hajibabaei et al. 2007Hajibabaei M., Singer G.A., Hebert P.D., et al. 2007. DNA barcoding: how it complements taxonomy, molecular phylogenetics and population genetics. Trends Genet. 23: 167-172. https://doi.org/10.1016/j.tig.2007.02.001 ).

Applying barcoding methods to (environmental) organismic DNA material improves traditional biomonitoring activity: excluding uncertainties such as morphological identification, low detection probabilities and sampling methods (challenges of gear deployment) increases confidence in the monitoring results (e.g. Bucklin et al. 2021Bucklin A., Peijnenburg K.T., Kosobokova K.N., et al. 2021. Toward a global reference database of COI barcodes for marine zooplankton. Mar. Biol. 168: 1-26. https://doi.org/10.1007/s00227-021-03887-y , Wang et al. 2021Wang S., Yan Z., Hänfling B., et al. 2021. Methodology of fish eDNA and its applications in ecology and environment. Sci. Total Environ. 755: 142622. https://doi.org/10.1016/j.scitotenv.2020.142622 , Di Capua et al. 2022Di Capua I., D’Angiolo R., Piredda R., et al. 2022. From Phenotypes to Genotypes and Back: Toward an Integrated Evaluation of Biodiversity in Calanoid Copepods. Front. Mar. Sci. 75. https://doi.org/10.3389/fmars.2022.833089 ). DNA barcoding could thus accelerate the inventory analysis of biological diversity, especially of bulk samples such as those of sediments or plankton, and of older museum samples. A good example of such bulk sample collection is the worldwide multidisciplinary Malaspina expedition, in which over 70000 samples of water, air and plankton were gathered in different ocean regions from the surface down to 5000 m depth. This immense collection was sorted and divided into several sub-collections that were accessible for scientific research. Our focus is on the holopelagic group Pteropoda (thecosomes and gymnosomes), a group of gastropods with an important ecological role in the marine environment as microplankton grazers and as prey for fish and other zooplankton. Despite their cosmopolitan distribution, the genetic diversity within this group is still largely uncertain (Burridge et al. 2017aBurridge A.K., Hörnlein C., Janssen A.W., et al. 2017a. Time-calibrated molecular phylogeny of pteropods. PloS ONE 12: e0177325. https://doi.org/10.1371/journal.pone.0177325 ,bBurridge A.K., Goetze E., Wall-Palmer D., et al. 2017b. Diversity and abundance of pteropods and heteropods along a latitudinal gradient across the Atlantic Ocean. Prog. Oceanogr. 158: 213-223. https://doi.org/10.1016/j.pocean.2016.10.001 ).

A comprehensive insight into the present diversity and distribution of these planktonic molluscs is an important prerequisite for stating possible future changes in species composition and also in species-specific responses to changing conditions in the marine environment. So far, studies focusing on pteropod species distribution patterns were geographically limited to certain marine regions (e.g. Jennings et al. 2010, Burridge et al. 2017bBurridge A.K., Goetze E., Wall-Palmer D., et al. 2017b. Diversity and abundance of pteropods and heteropods along a latitudinal gradient across the Atlantic Ocean. Prog. Oceanogr. 158: 213-223. https://doi.org/10.1016/j.pocean.2016.10.001 ), and there are still areas where pteropod diversity remains unknown (Burridge et al. 2017bBurridge A.K., Goetze E., Wall-Palmer D., et al. 2017b. Diversity and abundance of pteropods and heteropods along a latitudinal gradient across the Atlantic Ocean. Prog. Oceanogr. 158: 213-223. https://doi.org/10.1016/j.pocean.2016.10.001 ). Here, with the help of the 2010 Malaspina zooplankton samples, we generated new data using an environmental barcoding approach on the debris taken from 27 selected bulk samples from different oceans in order to gain a better understanding of species abundance and distribution of pteropods and to explore the potential of the method for broad-scale application.

MATERIALS AND METHODS

 

Sampling

 

Plankton samples were gathered globally at 154 locations. The hauls were conducted in the morning and in the evening. Out of 154 we selected 27 locations of interest in the Caribbean Sea, the Atlantic Ocean and the Indian Ocean (Table 1). The locations were chosen to coincide with those where frequent occurrence of certain pteropod species had been previously described (e.g. Burridge et al. 2017bBurridge A.K., Goetze E., Wall-Palmer D., et al. 2017b. Diversity and abundance of pteropods and heteropods along a latitudinal gradient across the Atlantic Ocean. Prog. Oceanogr. 158: 213-223. https://doi.org/10.1016/j.pocean.2016.10.001 ), (Fig. 1).

Table 1.  - Sampling location, pteropod species detection. I , present; D, day catch; N, night catch; * bin sharing, () sampling location [the first number refers to the collector, the second, separated by an underscore, to the collection point along the route. See Table 2 for more details].
Locality data: North Atlantic 12 29.90 N, 25 59.17 W North Atlantic 16 09.84 N, 26 01.53 W North Atlantic 14 31.18 N, 26 00.02 W Indian Ocean 28 07.65 S, 66 29.59 E Indian Ocean 29 49.65 S, 79 36.66 E Caribbean Sea 15 31.50 N, 67 00.86 W
Species            
Gymnosomata sp.       I/ D (3_54)    
Cavolinia inflexa I/D (1_11)   I/D (1_10)     I/N (7_130)
Creseis acicula       I/D (3_54)    
Creseis virgula   I/D * (1_9)   I/D (3_54) I/N (3_58) I/N (7_130) *
*
Creseis_conica | Creseis_virgula
Atlantic_Ocean | Belize | Bermuda | Mexico
*
Creseis_chierchiae | Creseis_virgula
Atlantic_Ocean | Belize | Mexico
medium/medium-SCIMAR-87-02-e061-gf1.png
Fig. 1.  – Course of the research vessel Hesperides during the 2010 Malaspina Expedition. Locations: Caribbean Sea (1), Atlantic Ocean (2) and Indian Ocean (3); red dot marks Cadiz; scale bar, 1000 km. Google (2021). Available at: https://www.google.de/maps/ (Accessed: 06.02.2021).

Sample preparation

 

Out of 27 bulk samples the preservation medium and the bottom content in the collection jars were extracted and filtered for organic material. Species identification of organic material was performed using DNA metabarcoding following the protocol published in Hausmann et al. (2020)Hausmann A., Segerer A.H., Greifenstein T., et al. 2020. Toward a standardized quantitative and qualitative insect monitoring scheme. Ecol. Evol. 10: 4009-4020. https://doi.org/10.1002/ece3.6166 . Each single sample was dried in a 60°C oven for at least eight hours and subsequently homogenized in a FastPrep96 machine (MP Biomedicals) using sterile steel beads in order to generate a homogeneous mixture of faeces material before it was submitted for metabarcoding (conducted by AIM GmbH). Prior to DNA extraction, 1 mg of each homogenizate was weighed into sample vials and processed using adapted volumes of lysis buffer with the DNeasy 96 Blood and Tissue Kit (Qiagen) following the manufacturer’s instructions. For amplification of the CO1-5P target region and preparation of the MiSeq libraries, a two-step PCR was performed. First, a 313-bp-long mini-barcode region was amplified by PCR (Leray et al. 2013Leray M., Yang J.Y., Meyer C.P., et al. 2013. A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: application for characterizing coral reef fish gut contents. Front. Zool. 10: 1-14. https://doi.org/10.1186/1742-9994-10-34 , Morinière et al. 2016Morinière J., Cancian de Araujo B., Lam A. W., et al. 2016. Species identification in malaise trap samples by DNA barcoding based on NGS technologies and a scoring matrix. PloS ONE 11: e0155497. https://doi.org/10.1371/journal.pone.0155497 ) using forward and reverse high-throughput sequencing (HTS) primers equipped with complementary sites for the Illumina sequencing tails. In a subsequent PCR reaction, index primers with unique i5 and i7 inline tags and sequencing tails were used for amplification of indexed amplicons. Equimolar amplicon pools were then created and size-selected using preparative gel electrophoresis. Cleanup and concentration of amplicons were performed using the GeneJet Extraction Kit (Life Technologies). A bioanalyser (High Sensitivity DNA Kit, Agilent Technologies) was used for a final check of the bp distribution and concentration of the amplicons before the creation of the final library. All samples were pooled into one library, equimolar adjusted to 100 ng µL-1. Samples had DNA concentrations between 10.4 and 12.4 ng µL-1. HTS was performed on an Illumina MiSeq using v2 chemistry (2*250 bp, 500 cycles, maximum of 20mio reads) (Illumina). All samples were analysed on a single MiSeq run. The bioinformatics processing of raw FASTQ files from Illumina was carried out using the VSEARCH suite v2.9.1 (Rognes et al. 2016Rognes T., Flouri T., Nichols B., et al. 2016. VSEARCH: a versatile open source tool for metagenomics. PeerJ 4: e2584. https://doi.org/10.7717/peerj.2584 ) and Cutadapt v1.18 (Martin 2011Martin M. 2011. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17:10-12. https://doi.org/10.14806/ej.17.1.200 ). Forward and reverse reads in each sample were merged using the VSEARCH program “fastq_mergepairs” with a minimum overlap of 10 bp, yielding approximately 313 bp sequences. Forward and reverse primers which were not reliably detected at >90% identity, were removed with Cutadapt using the “discard_untrimmed” option. Quality filtering was done with the “fastq_filter” in VSEARCH, and sequences with zero expected errors were kept (“fastq_maxee” 1).

Sequences were dereplicated with “derep_fulllength,” first at the sample level and then concatenated into one FASTA file, which was subsequently dereplicated. Chimeric sequences were filtered out from the FASTA file using the “uchime_denovo” VSEARCH program. The remaining sequences were then clustered into operational taxonomic units (OTUs) at 97% identity with “cluster_size”, a greedy centroid-based clustering program. OTUs were blasted against a custom Animalia database downloaded from BOLD on 28 November 2018, including taxonomy and barcode index number (BIN) information, by means of Geneious (v.10.2.5, Biomatters, Auckland, New Zealand) and following methods described in Morinière et al. (2016)Morinière J., Cancian de Araujo B., Lam A. W., et al. 2016. Species identification in malaise trap samples by DNA barcoding based on NGS technologies and a scoring matrix. PloS ONE 11: e0155497. https://doi.org/10.1371/journal.pone.0155497 .

The resulting csv file, which included the OTU ID, BOLD Process ID, BIN, Hit-%-ID value (percentage of overlap similarity (identical basepairs) of an OTU query sequence with its closest counterpart in the database), length of the top BLAST hit sequence, phylum, class, order, family, genus, and species information for each detected out, was exported from Geneious and combined with the OTU table generated by the bioinformatic pipeline. The combined results table was then filtered by Hit-%-ID value and total read numbers per OTU. All entries with identifications below 97% and total read numbers below 0.01% of the summed reads per sample were removed from the analysis. OTUs were then assigned to the respective BIN. Additionally, the API provided by BOLD was used to retrieve BIN species and BIN countries for every OTU, and the Hit-%-IDs were aggregated over OTUs that found a hit in the same BIN and shown in the corresponding column as % range. To validate the BOLD BLAST results, a separate BLAST search was carried out in Geneious (using the same parameters) against a local copy of the NCBI nucleotide database downloaded from ftp://ftp.ncbi.nlm.nih.gov/blast/db/. Interactive Krona charts were produced from the taxonomic information using KronaTools v1.3 (Ondov et al. 2011Ondov B. D., Bergman N. H., Phillippy A. M. 2011. Interactive metagenomic visualization in a Web browser. BMC Bioinform. 12: 1-10. https://doi.org/10.1186/1471-2105-12-385 ). Species identification was based on the HTS of OTUs, before blasting and assignment to BINs (Ratnasingham and Hebert 2013Ratnasingham S., Hebert P. D. 2013. A DNA-based registry for all animal species: The Barcode Index Number (BIN) system. PloS ONE 8: e66213. https://doi.org/10.1371/journal.pone.0066213 ) which are considered to be a good proxy for species numbers (Hausmann et al. 2013Hausmann A., Godfray H. C.J., Huemer P., et al. 2013. Genetic patterns in European geometrid moths revealed by the Barcode Index Number (BIN) system. PloS ONE 8: e84518. https://doi.org/10.1371/journal.pone.0084518 , Ratnasingham and Hebert 2013Ratnasingham S., Hebert P. D. 2013. A DNA-based registry for all animal species: The Barcode Index Number (BIN) system. PloS ONE 8: e66213. https://doi.org/10.1371/journal.pone.0066213 ).

Analyses

 

Generated sequence data were further analysed with a focus on three objectives: 1) assessment of species diversity using ABGD molecular species delineation (Puillandre et al. 2012Puillandre N., Lambert A., Brouillet S., et al. 2012. ABGD, Automatic Barcode Gap Discovery for primary species delimitation. Mol. Ecol. Resour. 21: 1864-1877. https://doi.org/10.1111/j.1365-294X.2011.05239.x ); 2) discovery of new species or potentially cryptic species assemblages; and 3) testing of distribution ranges of the respective lineages, especially in regions where pteropod diversity remains poorly understood so far.

In the final analysis, publicly available sequence data from GenBank and BOLD were included for phylogenetic testing. To code the COI gene, the sequences were first aligned in protein and then converted into nucleotide using ClustalW implemented in the software package MEGA Version 3.0. This method allowed us to maximize the homology between nucleotide positions when amino acid deletion/insertion occurred.

RESULTS

 

Barcode sequences were obtained with an average length of 100-268 bp. We obtained 69997 sequence clusters (coverage ≥CD-HIT-EST, min. 90.9% to 90.9%, max. 100% to 100%) that were blasted against 270000 DNA barcodes of identified specimens on the BOLD database BLAST (2019). This resulted in the detection of 206 BINs fitting the criterion of at least 90% sequence identity (supplementary material). This results in BINs that overlap with large groups at a phylum level: Arthropoda, Chaetognatha, Chordata, Cnidaria, Heterokontophytes, Mollusca, Nematoda, Porifera and Rotifera. For Mollusca we were able to identify 26 BINs (% identity: highest matches: 1.00, lowest 0.74; BOLD database BLAST) (Supplementary Table 1 a, b). Of these total sequence data, 6% were assigned to Gastropoda (Supplementary Table 2). Out of the gastropod sequence data, 46% matched with pteropod sequences (Table 2), 37% with thecosome and 9% with gymnosome data. Seven BINs were identified for Pteropoda (% identity: highest match, 1.00; lowest match, 0.909). Thirty-seven percent of snail sequence data matched with thecosome species. The sequence data matched with the euthecosome group Cavolinoidea, with the family of Creseidae (Creseis acicula (Rang, 1828) and Creseis virgula (Rang, 1828)) and Cavoliniidae (Cavolinia inflexa (Lesueur, 1813). BIN sharing was observed for OTU_3752 (Creseis_chierchiae|Creseis_virgula) and OTU_13187 (Creseis_conica|Creseis_virgula) (Supplementary Table 1a).

Table 2.  - Results of BLAST tool: BOLD (including BIN information) and GenBank.
BOLD database results of BLAST tool BIN sharing BIN location GenBank/NCBI database results of BLAST tool
Gymnosomata No No location Gymnosomata_sp.
Gymnosomata No No location Gymnosomata_sp.
Cavolinia inflexa No Belize|Mexico Cavolinia_inflexa
Creseis_acicula No No location Creseis_acicula
Creseis ”clava” No Bermuda Creseis_acicula
Creseis_virgula Creseis_chierchiae|Creseis_virgula Atlantic_Ocean|Belize|Mexico Creseis_virgula
Creseis_virgula Creseis_conica|Creseis_virgula Atlantic_Ocean|Belize|Bermuda|Mexico Creseis_virgula
Creseis_virgula No United_States Creseis_virgula

No correlation between OTU size and percentage species identity was observed (Fig. S1). ABGD analyses with cavoliniid sequence data grouped Creseis clava (note: outdated synonym) OTUs together with Creseis virgula OTUs. The Cavolinia inflexa OTU was distanced from the Creseis acicula OTU (initial partition (1-10) with prior maximal distance P=1.00e-03 - P=1.00e-01; barcode gap distance = 0.148 - barcode gap distance = 0.279; Jukes-Cantor JC69 distance MinSlope=1.500000) (Fig. S2).

Nine percent of total sequence data was assigned to gymnosome origin but not further assignable on family or species level, ABGD analyses revealed low genetic distance (range initial partition (1-10) with prior maximal distance P=1.00e-03 P=1.00e-01; barcode gap distance = 0.095 Barcode gap distance = 0.299, Jukes-Cantor JC69 distance, MinSlope=1.500000), indicating intraspecific assignment of gymnosome specimens (Fig. S3).

DISCUSSION

 

Experimental approach

 

Standard DNA barcoding approaches for pteropod gastropods have already been successfully applied (e.g. Hunt et al. 2010, Jennings et al. 2010) and provide a suitable tool for assessing large-scale biodiversity (Makiola et al. 2020Makiola A., Compson Z.G., Baird D.J., et al. 2020. Key questions for next-generation biomonitoring. Front. Environ. Sci. 7: 197. https://doi.org/10.3389/fenvs.2019.00197 , Chimeno et al. 2022Chimeno C., Hübner J., Seifert L., et al. 2022. Depicting environmental gradients from Malaise trap samples: Is ethanol‐based DNA metabarcoding enough? Insect Conservation and Diversity. https://doi.org/10.1111/icad.12609 ). With our approach we established a feasible protocol that overcomes current obstacles of having to sort the visible specimens or tissues. The sediment on the bottom of the provided plankton samples contained enough organic material (torn body parts, mucus and other secretions) to extract DNA. By using the dreg of the bottom, this method accelerates taxonomic procedures as the specimens in the sample jar remained unharmed and therefore stayed in suitable condition for further morphologic studies that might be of interest. This protocol might also be suitable in processing older collection material and therefore serves in the growing field of museomics, here enhancing comparative studies with modern and historical DNA material.

Quality of data

 

This non-destructive method is based on the use of scarce material. The quantity of DNA material is already limited by the relatively small size of our targeted specimens as well as their restricted geographical and circadian presence in the field. DNA degradation, collection age, preparation treatment and storage conditions have a big impact on the quality and quantity of the already limited DNA material (Janik et al. 2020Janik P., Ronikier M., Ronikier A. 2020. New protocol for successful isolation and amplification of DNA from exiguous fractions of specimens: a tool to overcome the basic obstacle in molecular analyses of myxomycetes. PeerJ 8: e8406. https://doi.org/10.7717/peerj.8406 ). Nevertheless, we were able to detect targeted molluscan and pteropod DNA. Many benthic marine gastropod species have pelagic larvae, so they may be encountered in traces in any plankton samples (e.g. Pulmonata, Caenogastropoda s.o and Stylommatophora). Surprisingly, we found quite a large amount of DNA of terrestrial specimens in our samples, even though secure laboratory guidelines applied in order to avoid cross contamination during extraction and amplification were reasonable. Cross contamination with land snail material in the field due to net storage ashore is possible. Contamination is ruled out regarding the amount and diversity of terrestrial gastropods in our data set. Scarce availability of DNA material in combination with too many PCR amplification cycles can lead to formation of chimeric products (Fonseca et al. 2012Fonseca V. G., Nichols B., Lallias D., et al. 2012. Sample richness and genetic diversity as drivers of chimera formation in nSSU metagenetic analyses. Nucleic Acids Res. 40: e66. https://doi.org/10.1093/nar/gks002 ). Using a smaller number of PCR cycles served as a precaution of formation of such chimeric DNA fragments here, so we discard this as a main explanation. Terrestrial DNA matches with species identity percentages of 0.787% to 0.837%. This might be due to a lack of comparative data as it is well known that the likelihood of finding matches in public databases for invertebrates is lower than for vertebrates (Harris et al. 2016Harris D. J., Rosado D., Xavier R. 2016. DNA barcoding reveals extensive mislabeling in seafood sold in Portuguese supermarkets. J. Aquat. Food Prod. Technol. 25: 1375-1380. https://doi.org/10.1080/10498850.2015.1067267 ). This could lead to mis-assignment of a barcode to the wrong species with high confidence. Missing target taxa on reference databases leads to the risk of making both false positive and false negative taxonomic assignments. False positives occur due to mis-assignment of a barcode to the wrong species with high confidence because the target species is missing in the database, and false negatives occur because of gaps in the database resulting in low confidence assignments (Porter and Hajibabaei 2018Porter T. M., Hajibabaei M. 2018. Over 2.5 million COI sequences in GenBank and growing. PloS ONE 13: e0200177. https://doi.org/10.1371/journal.pone.0200177 ). Matches to terrestrial data were not as high as those of our data assigned to marine snail DNA (0.93-1). As organisms in our samples varied in size, shape and anatomy (e.g. crustaceans vs. molluscans), we expected a disproportion in organismic material and therefore in the presence of usable DNA material. Length of the sequences is ruled out as they had a satisfying length of >221 bp. For further analyses the application of more sensitive and stricter quality filters seems a beneficial recommendation to avoid a trade-off between quality and quantity, low-input DNA material and bioinformatic obstacles (chimera), and most importantly, to eradicate statistical imbalances of species material in the dreg and preservation medium to avoid such statistic outbreaks in the future.

Notes on systematics of Pteropoda with a focus on euthecosome Cavolinioidea

 

Three suborders divide the euthyneurian order Pteropoda Cuvier 1804 (WoRMs; http://www.marinespecies.org; 2022): Pseudothecosomata Meisenheimer, 1905, Euthecosomata Meisenheimer, 1905 and Gymnosomata Blainville, 1824. Peijinenburg et al. (2020) argued against the recent classification of Bouchet et al. (2017)Bouchet P., Rocroi J.-P., Hausdorf B., et al. 2017. Revised classification, nomenclator and typification of gastropod and monoplacophoran families. Malacologia 61: 1-526. and advocated two suborders, Gymnosomata and Thecosomata, where the latter is divided into Euthecosomata and Pseudothecosomata. Unfortunately, neither Pseudothecosomata nor Gymnosomata are represented in this study, so we further focus on Euthecosomata. Within Euthecosomata there are two superfamilies; Limacinioidea Gray, 1840 and Cavolinioidea Gray, 1850 (Note: it is commented with “(1815)” in WoRMs). Cavolinioidea comprises eight families, out of which two are represented in this study: Cavoliniidae Gray, 1850 (Note: it is also commented with “(1815)” in WoRMs) and Creseidae Rampal, 1973. Creseidae comprise i.a. the genera: Boasia Dall, 1889 (Boasia chierchiae (Boas, 1886)) and Creseis Rang, 1828, which will be further investigated here. Creseidae seems to be polyphyletic (Klussmann-Kolb and Dinapoli 2006Klussmann‐Kolb A., Dinapoli A. 2006. Systematic position of the pelagic Thecosomata and Gymnosomata within Opisthobranchia (Mollusca, Gastropoda)-revival of the Pteropoda. J. Zool. Syst. Evol. Res. 44: 118-129. https://doi.org/10.1111/j.1439-0469.2006.00351.x , Corse et al. 2013Corse E., Rampal J., Cuoc C., et al. 2013. Phylogenetic analysis of Thecosomata Blainville, 1824 (Holoplanktonic Opisthobranchia) using morphological and molecular data. PLoS ONE 8: e59439. https://doi.org/10.1371/journal.pone.0059439 , Burridge et al. 2017aBurridge A.K., Hörnlein C., Janssen A.W., et al. 2017a. Time-calibrated molecular phylogeny of pteropods. PloS ONE 12: e0177325. https://doi.org/10.1371/journal.pone.0177325 ); current molecular studies place the genera Styliola Gray, 1847 and Hyalocylis Fol, 1875 apart from Creseidae (Corse et al. 2013Corse E., Rampal J., Cuoc C., et al. 2013. Phylogenetic analysis of Thecosomata Blainville, 1824 (Holoplanktonic Opisthobranchia) using morphological and molecular data. PLoS ONE 8: e59439. https://doi.org/10.1371/journal.pone.0059439 , Burridge et al. 2017aBurridge A.K., Hörnlein C., Janssen A.W., et al. 2017a. Time-calibrated molecular phylogeny of pteropods. PloS ONE 12: e0177325. https://doi.org/10.1371/journal.pone.0177325 ). The complicated history of Creseis nomenclature was discussed in Gasca and Janssen (2014)Gasca R., Janssen A. W. 2014. Taxonomic review, molecular data and key to the species of Creseidae from the Atlantic Ocean. J. Molluscan Stud. 80: 35-42. https://doi.org/10.1093/mollus/eyt038 and Janssen (2018)Janssen A. W. 2018. Notes on the systematics, morphology and biostratigraphy of holoplanktic Mollusca, 25 (1). Once more: the correct name for the type species of the genus Creseis Rang, 1828 (Pteropoda, Euthecosomata, Creseidae). Basteria 82: 110-112.. Since their original descriptions, species of Creseis have been synonymized or separated into several formae (Janssen 2006Janssen A. 2006. Notes on the systematics, morphology and biostratigraphy of fossil holoplanktonic Mollusca. On the status of some pteropods (Gastropoda, Euthecosomata) from the Miocene of New Zealand, referred to as species of Vaginella. Basteria 70: 71-83., 2007Janssen A.W. 2007. Holoplanktonic Mollusca (Gastropoda: Pterotracheoidea, Janthinoidea, Thecosomata and Gymnosomata) from the Pliocene of Pangasinan (Luzon, Philippines). Scr. Geol. 135: 29-177., 2012Janssen A. 2012. Early Pliocene heteropods and pteropods (Mollusca, Gastropoda) from Le Puget-sur-Argens (Var), France. Cainozoic Res. 9: 145-166.). Especially the interpretations of Creseis acicula (Rang, 1828) and C. clava (Rang, 1828) have been confusing (Janssen 2018Janssen A. W. 2018. Notes on the systematics, morphology and biostratigraphy of holoplanktic Mollusca, 25 (1). Once more: the correct name for the type species of the genus Creseis Rang, 1828 (Pteropoda, Euthecosomata, Creseidae). Basteria 82: 110-112.). The status of C. clava is unaccepted (Janssen 2018Janssen A. W. 2018. Notes on the systematics, morphology and biostratigraphy of holoplanktic Mollusca, 25 (1). Once more: the correct name for the type species of the genus Creseis Rang, 1828 (Pteropoda, Euthecosomata, Creseidae). Basteria 82: 110-112.); it acts as synonym for Creseis acicula (Rang, 1828) (accepted, WoRMs) and will be referred to as such in the following.

We hope to contribute to and update the state of knowledge by proceeding with future investigations on interoceanic differences among the available sampling material on Cavolinia inflexa, Creseis acicula and Creseis virgula, as so far molecular backup is missing (e.g. Gasca and Janssen 2014Gasca R., Janssen A. W. 2014. Taxonomic review, molecular data and key to the species of Creseidae from the Atlantic Ocean. J. Molluscan Stud. 80: 35-42. https://doi.org/10.1093/mollus/eyt038 ). We plan to use more markers and longer barcodes in our future studies and to investigate the respective collection jars and pursue morphological studies if necessary.

Gymnosomata

 

Shelled pteropod taxa have been in focus because of their usefulness in studying global climate change (i.e. ocean acidification), but unshelled pteropods have not yet been examined to the same extent. Some work has been done on an ecological and anatomic level, but little on genetics despite an increase in the recent years (e.g. Stromek et al. 2015Stromek L., Lasota R., Szymelfenig M., Wolowicz M. 2015. Genetic evidence for the existence of two species of the “bipolar” pelagic mollusk Clione limacinae. Am. Malacol. Bull. 33: 118-120. https://doi.org/10.4003/006.033.0108 , Yamazaki et al. 2017Yamazaki T., Kuwahara T. 2017. A new species of Clione distinguished from sympatric Clione limacina (Gastropoda: Gymnosomata) in the southern Okhotsk Sea, Japan, with remarks on the taxonomy of the genus. J. Molluscan Stud. 83: 19-26. https://doi.org/10.1093/mollus/eyw032 , Kohnert et al. 2020Kohnert P.C., Cerwenka A.F., Brandt A., Schrödl M. 2020. Pteropods from the Kuril-Kamchatka Trench and the sea of Okhotsk (Euopisthobranchia; Gastropoda). Prog. Oceanogr. 181:102259. https://doi.org/10.1016/j.pocean.2019.102259 ). Gymnosomes are less abundant than thecosomes, but they are ecologically very important because of their feeding manners, primarily predating on thecosomes (Lalli and Gilmer 1989Lalli C.M., Gilmer R.W. 1989. Pelagic snails: the biology of holoplanktonic gastropod mollusks. Palo Alto, Stanford Univ. Press. https://doi.org/10.1515/9781503623088 ). Interestingly, some of our sequenced material from samples from a free water day catch in the Indian Ocean (roughly 28° S, 66° E) was assigned to Gymnosomata sp. According to Burridge et al. (2017b)Burridge A.K., Goetze E., Wall-Palmer D., et al. 2017b. Diversity and abundance of pteropods and heteropods along a latitudinal gradient across the Atlantic Ocean. Prog. Oceanogr. 158: 213-223. https://doi.org/10.1016/j.pocean.2016.10.001 , the presence of gymnosomes (and thecosomes) in their sampling material came from (sub)tropical free waters within a longitude gradient of ∼28°N and ∼28°S (Atlantic Ocean), and were most abundant in sub-Antarctic waters and rather less in warmer waters (e.g. Weldrick et al. 2019Weldrick C. K., Trebilco R., Davies D. M., Swadling K. M. 2019. Trophodynamics of Southern Ocean pteropods on the southern Kerguelen Plateau. Ecol. Evol. 9: 8119-8132. https://doi.org/10.1002/ece3.5380 ). Burridge et al. (2017b)Burridge A.K., Goetze E., Wall-Palmer D., et al. 2017b. Diversity and abundance of pteropods and heteropods along a latitudinal gradient across the Atlantic Ocean. Prog. Oceanogr. 158: 213-223. https://doi.org/10.1016/j.pocean.2016.10.001 did not assign any species level. In our study, comparative data from online databanks were lacking at lower levels beyond order. To our knowledge, emergence of gymnosomes in our sampling locality (oceanic free water) is rather rare. Putatively, a connection between migration via the Agulhas current and influences by cold waters from the circumpolar current led to the appearance in our material.

Thecosomata

 

Thecosome material indicates presence of the “usual suspects” in the sample jars: the cosmopolite species Creseis acicula, Creseis virgula and Cavolinia inflexa (Lesueur, 1813). Present in almost all the world’s oceans, these species are mostly found in warm water territories. C. inflexa was the most dominant we had in our samples, which we anticipated, as it is in general the most common representative of Cavolinia in the Atlantic Ocean. Our findings (appearance/detection of C. inflexa in spacious, scattered samples) agree with the accepted knowledge that C. inflexa is common and distributed widely and provide further input in the ongoing discussions about its taxonomic status, as it is a putative species complex (Rampal 2002Rampal J. 2002. Biodiversité et biogéographie chez les Cavoliniidae (Mollusca, Gastropoda, Opisthobranchia, Euthecosomata). Régions faunistiques marines, Zoosystema 24 :209-258., Janssen et al. 2019Janssen A.W., Bush S.L., Bednaršek N. 2019. The shelled pteropods of the northeast Pacific Ocean (Mollusca: Heterobranchia, Pteropoda). Zoosymposia 13: 305-346. https://doi.org/10.11646/zoosymposia.13.1.22 ). The same is true for Creseis acicula and Creseis virgula. Morphological distinctions of Creseis species have always been subject to many controversies, as can be seen in Frontier (1965)Frontier S.1965. Le problème des Creseis. Océanographie (Nosy-Bé), Cah. ORSTOM. Sér. Sci. Hum. 3:11-17., Rampal (1985Rampal J. 1985. Systématique du genre Creseis (Mollusques, Thécosomes), Rapport de la Commission Internationale pour l’Exploration Scientifique de la Mer Méditerranée. Bull. Comm. Int. Explor. Sci. Mer Mediterr. 29: 259-263., 2002)Rampal J. 2002. Biodiversité et biogéographie chez les Cavoliniidae (Mollusca, Gastropoda, Opisthobranchia, Euthecosomata). Régions faunistiques marines, Zoosystema 24 :209-258., Janssen (2007)Janssen A.W. 2007. Holoplanktonic Mollusca (Gastropoda: Pterotracheoidea, Janthinoidea, Thecosomata and Gymnosomata) from the Pliocene of Pangasinan (Luzon, Philippines). Scr. Geol. 135: 29-177., Gasca and Janssen (2014)Gasca R., Janssen A. W. 2014. Taxonomic review, molecular data and key to the species of Creseidae from the Atlantic Ocean. J. Molluscan Stud. 80: 35-42. https://doi.org/10.1093/mollus/eyt038 . Genetic studies (e.g. Klussmann-Kolb and Dinapoli (2006)Klussmann‐Kolb A., Dinapoli A. 2006. Systematic position of the pelagic Thecosomata and Gymnosomata within Opisthobranchia (Mollusca, Gastropoda)-revival of the Pteropoda. J. Zool. Syst. Evol. Res. 44: 118-129. https://doi.org/10.1111/j.1439-0469.2006.00351.x and Corse et al. (2013)Corse E., Rampal J., Cuoc C., et al. 2013. Phylogenetic analysis of Thecosomata Blainville, 1824 (Holoplanktonic Opisthobranchia) using morphological and molecular data. PLoS ONE 8: e59439. https://doi.org/10.1371/journal.pone.0059439 ) did help to build a more solid classification, but it is still open for taxonomic debates.

E-DNA barcoding approach for Pteropoda

 

Using tools like BOLD and GenBank allows quick and easy barcode and phylogenetic analysis. But there are persisting issues. Identification errors found in already published sequence data are rarely re-evaluated. Using standard procedures there is a 95% probability of finding incorrectly described metazoan sequences in GenBank, ranging from 1% (Mollusca and Arthropoda) to 6.9% (Gastrotricha). Consequently, the increasing popularity of DNA barcoding and metabarcoding analysis may lead to overestimation of species diversity (e.g. Mioduchowska et al. 2018Mioduchowska M., Czyż M.J., Gołdyn B., et al. 2018. Instances of erroneous DNA barcoding of metazoan invertebrates: Are universal cox1 gene primers too “universal”? PLoS ONE. 13: e0199609. https://doi.org/10.1371/journal.pone.0199609 ). Lack of species-specific comparative data and misidentifications/ incorrect sequence data in previously and newly published data are due to amplification of non-target taxa and insufficient analysis of the obtained sequences (Mioduchowska et al. 2018Mioduchowska M., Czyż M.J., Gołdyn B., et al. 2018. Instances of erroneous DNA barcoding of metazoan invertebrates: Are universal cox1 gene primers too “universal”? PLoS ONE. 13: e0199609. https://doi.org/10.1371/journal.pone.0199609 ). The difficult taxonomic history of Creseis is still mirrored in our bioinformatic analyses (current study: Bold and Genbank). Unfortunately, outdated synonyms are still used for certain taxa, in our case C. acicula, which was wrongly assigned to C. clava. Furthermore, BIN sharing in two samples occurred. This is correctable on a small scale, but for a bigger approach it might lead to problematic consequences and therefore shows the need for updates.

Barcoding as a tool for monitoring

 

We advocate using collection material from previous expeditions to monitor environmentally influenced changes in pteropod abundance/behaviour, using it as a benchmark for the occurrence of common traits or derivations. In addition to measuring biodiversity by monitoring species availability, putative changes in behaviour might also help to understand the effects of climate change on these marine organisms. Diel vertical migration is a known phenomenon for most thecosome species, and in our samples we found DNA material in night and day hauls in anticipated quantities. Swimming and sinking behaviour by these pelagic snails is important in their ecology, predator-prey interaction, and vertical distribution (Karakas et al. 2020Karakas F., Wingate J., Blanco-Bercial L. et al. 2020. Swimming and Sinking Behavior of Warm Water Pelagic Snails. Front. Mar. Sci. 7:749. https://doi.org/10.3389/fmars.2020.556239 ). Despite the costs, benefits like niche partitioning, metabolic advantage due to colder temperatures at depth, avoidance of light, high temperatures and predators seem to advocate this behaviour (Hays 2003Hays G. C. 2003. A review of the adaptive significance and ecosystem consequences of zooplankton diel vertical migrations. Migrations and dispersal of marine organisms. Hydrobiologia 503: 163-170. https://doi.org/10.1007/978-94-017-2276-6_18 , Antezana 2009Antezana T. 2009. Species-specific patterns of diel migration into the Oxygen Minimum Zone by euphausiids in the Humboldt Current Ecosystem. Prog. Oceanogr. 83: 228-236. https://doi.org/10.1016/j.pocean.2009.07.039 ). Factors such as ocean acidification might harmfully affect the migrating ability by altering shell condition (and thickness), leading to misbalancing in factors involved in locomotion and buoyancy processes, as already shown for other thecosomes (Limacina retroversa, here: Manno et al. 2012Manno C., Morata N., Primicerio R. 2012. Limacina retroversa’s response to combined effects of ocean acidification and sea water freshening. Estuar. Coast. Shelf Sci. 113: 163-171. https://doi.org/10.1016/j.ecss.2012.07.019 , Adhikari et al. 2016Adhikari D., Webster D. R., Yen J. 2016. Portable tomographic PIV measurements of swimming shelled Antarctic pteropods. Exp. Fluids. 57: 1-17. https://doi.org/10.1007/s00348-016-2269-7 ). This will have fatal consequences for the individuals and will potentially result in ecological cascades in the long run. This process will be mirrored by the catch success in future plankton hauls. Thus, if data are accessible for longer time periods and large geographic areas, comparisons and statements about harmful effects and future developments can be made for certain ecological key species, as in our case thecosome pteropods.

CONCLUSION

 

In this pioneering study we applied a non-invasive, next-generation environmental barcoding approach to several selected (meso)zooplankton bulk samples collected during the 2010 Malaspina global circumnavigation. On a small scale we were able to support existing knowledge of the distribution of Cavolinia inflexa, C. virgula and C. acicula, and we made surprising findings about the putative broader distribution of gymnosomes hypothesized today. Environmental DNA approaches may streamline the search for new pteropod species in unsorted museum jars and streamline historic and future monitoring efforts. Limitations to our approach are related to the lack of comparative barcoding data from pteropods, especially of gymnosome data, and outdated use of synonyms and potential misidentifications in online sequence bases, which call for re-evaluation and up-dating of existing published data. With more and taxonomically broader barcoding sequences available in public databases, our environmental barcoding approach will improve our understanding of global species diversity and distribution patterns of Pteropoda and other planktonic organisms.

ACKNOWLEDGEMENTS

 

We wish to thank the Malacological Society of London (YRA) for funding this project. Special thanks go to Juan Ignacio González-Gordillo (University of Cádiz) for his support and help in choosing and gathering suitable samples. Stefan Filser and Andrew Brodie are thanked for their constructive input. Special thanks are due for providing the samples to the project “Expedición de circumnavegación Malaspina 2010: Cambio global y exploración de la biodiversidad del Oceano global (CSD2008-00077)”, funded by the Spanish Ministry of Economy and Competiveness.

REFERENCES

 

Adhikari D., Webster D. R., Yen J. 2016. Portable tomographic PIV measurements of swimming shelled Antarctic pteropods. Exp. Fluids. 57: 1-17. https://doi.org/10.1007/s00348-016-2269-7

Antezana T. 2009. Species-specific patterns of diel migration into the Oxygen Minimum Zone by euphausiids in the Humboldt Current Ecosystem. Prog. Oceanogr. 83: 228-236. https://doi.org/10.1016/j.pocean.2009.07.039

Bucklin A., Steinke D., Blanco-Bercial L. 2011. DNA barcoding of marine metazoa. Annu. Rev. Mar. Science 3: 471-508. https://doi.org/10.1146/annurev-marine-120308-080950

Bucklin A., Peijnenburg K.T., Kosobokova K.N., et al. 2021. Toward a global reference database of COI barcodes for marine zooplankton. Mar. Biol. 168: 1-26. https://doi.org/10.1007/s00227-021-03887-y

Burridge A.K., Hörnlein C., Janssen A.W., et al. 2017a. Time-calibrated molecular phylogeny of pteropods. PloS ONE 12: e0177325. https://doi.org/10.1371/journal.pone.0177325

Burridge A.K., Goetze E., Wall-Palmer D., et al. 2017b. Diversity and abundance of pteropods and heteropods along a latitudinal gradient across the Atlantic Ocean. Prog. Oceanogr. 158: 213-223. https://doi.org/10.1016/j.pocean.2016.10.001

Bouchet P., Rocroi J.-P., Hausdorf B., et al. 2017. Revised classification, nomenclator and typification of gastropod and monoplacophoran families. Malacologia 61: 1-526.

Chimeno C., Hübner J., Seifert L., et al. 2022. Depicting environmental gradients from Malaise trap samples: Is ethanol‐based DNA metabarcoding enough? Insect Conservation and Diversity. https://doi.org/10.1111/icad.12609

Corse E., Rampal J., Cuoc C., et al. 2013. Phylogenetic analysis of Thecosomata Blainville, 1824 (Holoplanktonic Opisthobranchia) using morphological and molecular data. PLoS ONE 8: e59439. https://doi.org/10.1371/journal.pone.0059439

Di Capua I., D’Angiolo R., Piredda R., et al. 2022. From Phenotypes to Genotypes and Back: Toward an Integrated Evaluation of Biodiversity in Calanoid Copepods. Front. Mar. Sci. 75. https://doi.org/10.3389/fmars.2022.833089

Fonseca V. G., Nichols B., Lallias D., et al. 2012. Sample richness and genetic diversity as drivers of chimera formation in nSSU metagenetic analyses. Nucleic Acids Res. 40: e66. https://doi.org/10.1093/nar/gks002

Frontier S.1965. Le problème des Creseis. Océanographie (Nosy-Bé), Cah. ORSTOM. Sér. Sci. Hum. 3:11-17.

Gasca R., Janssen A. W. 2014. Taxonomic review, molecular data and key to the species of Creseidae from the Atlantic Ocean. J. Molluscan Stud. 80: 35-42. https://doi.org/10.1093/mollus/eyt038

Harris D. J., Rosado D., Xavier R. 2016. DNA barcoding reveals extensive mislabeling in seafood sold in Portuguese supermarkets. J. Aquat. Food Prod. Technol. 25: 1375-1380. https://doi.org/10.1080/10498850.2015.1067267

Hausmann A., Godfray H. C.J., Huemer P., et al. 2013. Genetic patterns in European geometrid moths revealed by the Barcode Index Number (BIN) system. PloS ONE 8: e84518. https://doi.org/10.1371/journal.pone.0084518

Hausmann A., Segerer A.H., Greifenstein T., et al. 2020. Toward a standardized quantitative and qualitative insect monitoring scheme. Ecol. Evol. 10: 4009-4020. https://doi.org/10.1002/ece3.6166

Hays G. C. 2003. A review of the adaptive significance and ecosystem consequences of zooplankton diel vertical migrations. Migrations and dispersal of marine organisms. Hydrobiologia 503: 163-170. https://doi.org/10.1007/978-94-017-2276-6_18

Hajibabaei M., Singer G.A., Hebert P.D., et al. 2007. DNA barcoding: how it complements taxonomy, molecular phylogenetics and population genetics. Trends Genet. 23: 167-172. https://doi.org/10.1016/j.tig.2007.02.001

Janik P., Ronikier M., Ronikier A. 2020. New protocol for successful isolation and amplification of DNA from exiguous fractions of specimens: a tool to overcome the basic obstacle in molecular analyses of myxomycetes. PeerJ 8: e8406. https://doi.org/10.7717/peerj.8406

Janssen A. 2006. Notes on the systematics, morphology and biostratigraphy of fossil holoplanktonic Mollusca. On the status of some pteropods (Gastropoda, Euthecosomata) from the Miocene of New Zealand, referred to as species of Vaginella. Basteria 70: 71-83.

Janssen A.W. 2007. Holoplanktonic Mollusca (Gastropoda: Pterotracheoidea, Janthinoidea, Thecosomata and Gymnosomata) from the Pliocene of Pangasinan (Luzon, Philippines). Scr. Geol. 135: 29-177.

Janssen A. 2012. Early Pliocene heteropods and pteropods (Mollusca, Gastropoda) from Le Puget-sur-Argens (Var), France. Cainozoic Res. 9: 145-166.

Janssen A. W. 2018. Notes on the systematics, morphology and biostratigraphy of holoplanktic Mollusca, 25 (1). Once more: the correct name for the type species of the genus Creseis Rang, 1828 (Pteropoda, Euthecosomata, Creseidae). Basteria 82: 110-112.

Janssen A.W., Bush S.L., Bednaršek N. 2019. The shelled pteropods of the northeast Pacific Ocean (Mollusca: Heterobranchia, Pteropoda). Zoosymposia 13: 305-346. https://doi.org/10.11646/zoosymposia.13.1.22

Karakas F., Wingate J., Blanco-Bercial L. et al. 2020. Swimming and Sinking Behavior of Warm Water Pelagic Snails. Front. Mar. Sci. 7:749. https://doi.org/10.3389/fmars.2020.556239

Klussmann‐Kolb A., Dinapoli A. 2006. Systematic position of the pelagic Thecosomata and Gymnosomata within Opisthobranchia (Mollusca, Gastropoda)-revival of the Pteropoda. J. Zool. Syst. Evol. Res. 44: 118-129. https://doi.org/10.1111/j.1439-0469.2006.00351.x

Kohnert P.C., Cerwenka A.F., Brandt A., Schrödl M. 2020. Pteropods from the Kuril-Kamchatka Trench and the sea of Okhotsk (Euopisthobranchia; Gastropoda). Prog. Oceanogr. 181:102259. https://doi.org/10.1016/j.pocean.2019.102259

Lalli C.M., Gilmer R.W. 1989. Pelagic snails: the biology of holoplanktonic gastropod mollusks. Palo Alto, Stanford Univ. Press. https://doi.org/10.1515/9781503623088

Leray M., Yang J.Y., Meyer C.P., et al. 2013. A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: application for characterizing coral reef fish gut contents. Front. Zool. 10: 1-14. https://doi.org/10.1186/1742-9994-10-34

Makiola A., Compson Z.G., Baird D.J., et al. 2020. Key questions for next-generation biomonitoring. Front. Environ. Sci. 7: 197. https://doi.org/10.3389/fenvs.2019.00197

Martin M. 2011. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17:10-12. https://doi.org/10.14806/ej.17.1.200

Manno C., Morata N., Primicerio R. 2012. Limacina retroversa’s response to combined effects of ocean acidification and sea water freshening. Estuar. Coast. Shelf Sci. 113: 163-171. https://doi.org/10.1016/j.ecss.2012.07.019

Morinière J., Cancian de Araujo B., Lam A. W., et al. 2016. Species identification in malaise trap samples by DNA barcoding based on NGS technologies and a scoring matrix. PloS ONE 11: e0155497. https://doi.org/10.1371/journal.pone.0155497

Mioduchowska M., Czyż M.J., Gołdyn B., et al. 2018. Instances of erroneous DNA barcoding of metazoan invertebrates: Are universal cox1 gene primers too “universal”? PLoS ONE. 13: e0199609. https://doi.org/10.1371/journal.pone.0199609

Ondov B. D., Bergman N. H., Phillippy A. M. 2011. Interactive metagenomic visualization in a Web browser. BMC Bioinform. 12: 1-10. https://doi.org/10.1186/1471-2105-12-385

Porter T. M., Hajibabaei M. 2018. Over 2.5 million COI sequences in GenBank and growing. PloS ONE 13: e0200177. https://doi.org/10.1371/journal.pone.0200177

Puillandre N., Lambert A., Brouillet S., et al. 2012. ABGD, Automatic Barcode Gap Discovery for primary species delimitation. Mol. Ecol. Resour. 21: 1864-1877. https://doi.org/10.1111/j.1365-294X.2011.05239.x

Rampal J. 1985. Systématique du genre Creseis (Mollusques, Thécosomes), Rapport de la Commission Internationale pour l’Exploration Scientifique de la Mer Méditerranée. Bull. Comm. Int. Explor. Sci. Mer Mediterr. 29: 259-263.

Rampal J. 2002. Biodiversité et biogéographie chez les Cavoliniidae (Mollusca, Gastropoda, Opisthobranchia, Euthecosomata). Régions faunistiques marines, Zoosystema 24 :209-258.

Ratnasingham S., Hebert P. D. 2013. A DNA-based registry for all animal species: The Barcode Index Number (BIN) system. PloS ONE 8: e66213. https://doi.org/10.1371/journal.pone.0066213

Rognes T., Flouri T., Nichols B., et al. 2016. VSEARCH: a versatile open source tool for metagenomics. PeerJ 4: e2584. https://doi.org/10.7717/peerj.2584

Stromek L., Lasota R., Szymelfenig M., Wolowicz M. 2015. Genetic evidence for the existence of two species of the “bipolar” pelagic mollusk Clione limacinae. Am. Malacol. Bull. 33: 118-120. https://doi.org/10.4003/006.033.0108

Wang S., Yan Z., Hänfling B., et al. 2021. Methodology of fish eDNA and its applications in ecology and environment. Sci. Total Environ. 755: 142622. https://doi.org/10.1016/j.scitotenv.2020.142622

Weldrick C. K., Trebilco R., Davies D. M., Swadling K. M. 2019. Trophodynamics of Southern Ocean pteropods on the southern Kerguelen Plateau. Ecol. Evol. 9: 8119-8132. https://doi.org/10.1002/ece3.5380

Yamazaki T., Kuwahara T. 2017. A new species of Clione distinguished from sympatric Clione limacina (Gastropoda: Gymnosomata) in the southern Okhotsk Sea, Japan, with remarks on the taxonomy of the genus. J. Molluscan Stud. 83: 19-26. https://doi.org/10.1093/mollus/eyw032

SUPPLEMENTARY MATERIAL

 
medium/medium-SCIMAR-87-02-e061-gfs1.png
Fig. S1.  - Correlation estimation between number of counts per OTU and percentage of species assignment; here, C. virgula.
medium/medium-SCIMAR-87-02-e061-gfs2.png
Fig. S2.  - ABGD Histogram Cavolinidae (Cavolinid sequences): Group [1] n, 1; id, OTU_1636size27. Group [2] n, 1; id, OTU_12743size2. Group [3] n, 11; id, OTU_12626size14 OTU_12747size2 OTU_502size124 OTU_1314size133 OTU_3752size6 OTU_13187size2 OTU_12776size2 OTU_2234size12 OTU_3131size15 OTU_5297size15 OTU_91size326.
medium/medium-SCIMAR-87-02-e061-gfs3.png
Fig. S3.  - ABGD histogram gymnosomes (pteropod sequences): Group [4] n, 2; id, OTU_12723size6 OTU_440size167.
Table S1a.  - Pteropod BOLD BLAST (BIN sharing) / NCBI GenBank BLAST [sum raw reads in sample (after filtering for OTUs with less than 0.01% reads per sample)]
NCBI_nt Species %_identity2 BIN sharing? HIT%IDrange
OTU_12723; size=6 KC774091 Gymnosomata_sp. 0.932 No 93.2%_to_93.9%
OTU_440; size=167 KC774091 Gymnosomata_sp. 0.939 No 93.2%_to_93.9%
OTU_1636; size=27 MF048913 Cavolinia_inflexa 1 No 100%_to_100%
OTU_12743; size=2 KC774054 Creseis_acicula 0.961 No 96.1%_to_96.1%
OTU_12626; size=14 KC774054 Creseis_acicula 0.97 No 97%_to_98.5%
OTU_12747; size=2 KC774054 Creseis_acicula 0.97 No 97%_to_98.5%
OTU_502; size=124 KC774054 Creseis_acicula 0.974 No 97%_to_98.5%
OTU_1314; size=133 KC774054 Creseis_acicula 0.985 No 97%_to_98.5%
OTU_3752; size=6 KC774047 Creseis_virgula 0.985 Yes 98.5%_to_99.2%
OTU_13187; size=2 FJ876889 Creseis_virgula 0.909 Yes 90.9%_to_90.9%
OTU_12776; size=2 HM385051 Creseis_virgula 0.936 No 95.5%_to_97%
OTU_2234; size=12 KC774047 Creseis_virgula 0.951 No 95.5%_to_97%
OTU_3131; size=15 HM385051 Creseis_virgula 0.951 No 95.5%_to_97%
OTU_5297; size=15 KC774047 Creseis_virgula 0.947 No 95.5%_to_97%
OTU_91; size=326 KC774047 Creseis_virgula 0.951 No 95.5%_to_97%
Table S1b.  Abnormalities observed: Stylommatophora (terrestrial slugs and snails).
Pulmonata Bradybaenidae Trishoplita_cretacea
Sorbeoconcha (Caenogastropoda s.o) Potamididae Cerithidea_anticipata
Sorbeoconcha (Caenogastropoda s.o) Thiaridae Brotia_episcopalis
Stylommatophora Arionidae Arion ater
Stylommatophora Arionidae Arion_rufus
Stylommatophora Arionidae Geomalacus_maculosus
Stylommatophora Arionidae Geomalacus_maculosus
Stylommatophora Clausiliidae Cochlodina_laminata
Stylommatophora Limacidae Lehmannia marginata
Stylommatophora Vitrinidae Vitrina angelicae
Vetigastropoda Haliotidae Discus rotundatus
Table S2.  - Collection jars. Sampling locations. Sampling gear.
CODE LEG STAT DATE LATITUDE LONGITUDE SAMPLER
MH005N003S011GGE1 1 3 19/12/2010 29º41’00.0”N 017º17’28.0”W Neuston net
MH010N008S011GGE1 1 8 24/12/2010 20º15’67.0”N 024º15’07.0”W Neuston net
MH011N009S011GGE1 1 9 25/12/2010 16º09’84.0”N 026º01’53.0”W Neuston net
MH012M010C041DGE1 1 10 26/12/2010 14º31’18.0”N 026º00’02.0”W Multinet
MH012M010C101DGE1 1 10 26/12/2010 14º31’18.0”N 026º00’02.0”W Multinet
MH012M010C101DGE2 1 10 26/12/2010 14º31’18.0”N 026º00’02.0”W Multinet
MH012M010C211DGE1 1 10 26/12/2010 14º31’18.0”N 026º00’02.0”W Multinet
MH012N010S011GGE1 1 10 26/12/2010 14º31’18.0”N 026º00’02.0”W Neuston net
MH013N011S011GGE1 1 11 27/12/2010 12º29’90.0”N 025º59’17.0”W Neuston net
MH013N011S012GGE1 1 11 27/12/2010 12º29’90.0”N 025º59’17.0”W Neuston net
MH014N012S011GGE1 1 12 28/12/2010 09º33’82.0”N 025º59’60.0”W Neuston net
MH014N012S012GGE1 1 12 28/12/2010 09º33’82.0”N 025º59’60.0”W Neuston net
MH065N049S011GGE1 3 49 17/02/2011 33º54’43.0”S 037º02’53.0”E Neuston net
MH065N049S012GGE1 3 49 17/02/2011 33º54’43.0”S 037º02’53.0”E Neuston net
MH072N052S011GGE1 3 52 24/02/2011 30º03’30.0”S 061º25’84.0”E Neuston net
MH072N052S012GGE1 3 52 24/02/2011 30º03’30.0”S 061º25’84.0”E Neuston net
MH074N054S011GGE1 3 54 26/02/2011 28º07’65.0”S 066º29’59.0”E Neuston net
MH074N054S012GGE1 3 54 26/02/2011 28º07’65.0”S 066º29’59.0”E Neuston net
MH076N056S011GGE1 3 56 28/02/2011 29º33’63.0”S 072º26’65.0”E Neuston net
MH076N056S012GGE1 3 56 28/02/2011 29º33’63.0”S 072º26’65.0”E Neuston net
MH078N058S012GGE1 3 58 02/03/2011 29º49’65.0”S 079º36’66.0”E Neuston net
MH080M060C101DGE1 3 60 04/03/2011 29º44’93.0”S 086º15’39.0”E Multinet
MH080M060C221DGE1 3 60 04/03/2011 29º44’93.0”S 086º15’39.0”E Multinet
MH080N060S011GGE1 3 60 04/03/2011 29º44’93.0”S 086º15’39.0”E Neuston net
MH080N060S012GGE1 3 60 04/03/2011 29º44’93.0”S 086º15’39.0”E Neuston net
MH082N062S011GGE1 1 62 06/03/2011 29º37’61.0”S 092º59’05.0”E Neuston net
MH084N064S012GGE1 3 64 08/03/2011 30º19’96.0”S 103º18’45.0”E Neuston net
MH190N129S011GGE1 7 129 22/06/2011 15º04’11.0”N 069º17’72.0”W Neuston net
MH191N130S012GGE1 7 130 23/06/2011 15º31’50.0”N 067º00’86.0”W Neuston net
Table S3.  - Gastropod bins identified in dreg of processed bulk samples with %identity and OTUs with cluster size
bin_uri %_identity Seq_length order_name species_name OTU;cluster_size
BOLD:AAD2596 0.759 228 Basommatophora Bulinus truncatus OTU_5390; size=6
BOLD:ACQ2738 0.832 119 Basommatophora Gyraulus_sp. _15911 OTU_313; size=106
BOLD:ADR7487 0.74 192 Caenogastropoda Bittium reticulatum OTU_12183; size=4
BOLD:ACQ5099 0.83 100 Cephalaspidea Chelidonura sandrana OTU_12754; size=2
BOLD:ACI0947 0.932 265 Gymnosomata Not determined OTU_12723; size=6
BOLD:ACI0947 0.939 264 Gymnosomata Not determined OTU_440; size=167
BOLD:ADR2784 0.81 232 Hygrophila Galba truncatula OTU_13162; size=2
BOLD:ACT8286 0.996 266 Lepetellida Not determined OTU_2458; size=17
BOLD:ADH1065 0.992 266 Littorinimorpha Atlanta helicinoidea OTU_2089; size=13
BOLD:ACQ5602 0.985 264 Littorinimorpha Atlanta meteori OTU_2088; size=21
BOLD:ACZ0738 0.936 264 Littorinimorpha Atlanta selvagensis OTU_1833; size=13
BOLD:ADK8167 0.802 268 Littorinimorpha Pseudamnicola moussoni OTU_1937; size=17
BOLD:AAM3343 1 266 Pteropoda Cavolinia inflexa OTU_1636; size=27
BOLD:ACH6682 0.961 181 Pteropoda Creseis acicula OTU_12743; size=2
BOLD:ACZ1440 0.97 266 Pteropoda Creseis clava OTU_12626; size=14
BOLD:ACZ1440 0.974 266 Pteropoda Creseis clava OTU_12747; size=2
BOLD:ACZ1440 0.977 266 Pteropoda Creseis clava OTU_502; size=124
BOLD:ACZ1440 0.985 266 Pteropoda Creseis clava OTU_1314; size=133
BOLD:AAE9544 0.985 264 Pteropoda Creseis virgula OTU_3752; size=6
BOLD:AAC6583 0.909 264 Pteropoda Creseis virgula OTU_13187; size=2
BOLD:ACV0071 0.955 264 Pteropoda Not determined OTU_12776; size=2
BOLD:ACV0071 0.958 264 Pteropoda Not determined OTU_2234; size=12
BOLD:ACV0071 0.97 264 Pteropoda Not determined OTU_3131; size=15
BOLD:ACV0071 0.97 264 Pteropoda Not determined OTU_5297; size=15
BOLD:ACV0071 0.97 264 Pteropoda Not determined OTU_91; size=326
BOLD:ACV8715 0.787 197 Pulmonata Trishoplita cretacea OTU_5200; size=15
BOLD:AAF0822 0.769 221 Sorbeoconcha Cerithidea anticipata OTU_13236; size=2
BOLD:AAF6997 0.821 224 Sorbeoconcha Brotia episcopalis OTU_2842; size=5
BOLD:AAD2027 1 266 Stylommatophora Arion ater OTU_506; size=214
BOLD:AAE6652 1 266 Stylommatophora Arion rufus OTU_1508; size=17
BOLD:ACW0753 0.837 104 Stylommatophora Geomalacus maculosus OTU_13177; size=6
BOLD:ACW0753 0.837 104 Stylommatophora Geomalacus maculosus OTU_1729; size=40
0.996 266 Stylommatophora Cochlodina laminata OTU_3587; size=6
BOLD:AAF1156 1 266 Stylommatophora Lehmannia marginata OTU_478; size=265
BOLD:AAN0223 0.996 266 Stylommatophora Vitrina angelicae OTU_3969; size=7
BOLD:AAI9791 0.989 266 Vetigastropoda Discus rotundatus OTU_1429; size=25