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Data from: Evaluating species richness using proteomic fingerprinting and DNA-barcoding – a case study on meiobenthic copepods from the Clarion Clipperton Fracture Zone

Citation

Rossel, Sven et al. (2022), Data from: Evaluating species richness using proteomic fingerprinting and DNA-barcoding – a case study on meiobenthic copepods from the Clarion Clipperton Fracture Zone, Dryad, Dataset, https://doi.org/10.5061/dryad.qfttdz0m3

Abstract

The Clarion Clipperton Fracture Zone (CCZ) is a vast deep-sea region harboring a highly diverse benthic fauna, which will be affected by potential future deep-sea mining of metal-rich polymetallic nodules. Despite the need for conservation plans and monitoring strategies in this context, the majority of taxonomic groups remains scientifically undescribed. However, molecular rapid assessment methods such as DNA-barcoding and Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) provide the potential to accelerate specimen identification and biodiversity assessment significantly in the deep-sea areas. In this study, we successfully applied both methods to investigate the diversity of meiobenthic copepods in the eastern CCZ, including the first application of MALDI-TOF MS for the identification of these deep-sea organisms. Comparing several different species delimitation tools for both datasets, we found that biodiversity values were very similar, with Pielou’s Evenness varying between 0.97 and 0.99 in all datasets. Still, direct comparisons of species clusters revealed differences between all techniques and methods, which are likely caused by the high number of rare species being represented by only one specimen, despite our extensive dataset of more than 2000 specimens. Hence, we regard our study as a first approach toward setting up a reference library for mass spectrometry data of the CCZ in combination with DNA-barcodes. We conclude that proteome fingerprinting, as well as the more established DNA-barcoding, can be seen as a valuable tool for rapid biodiversity assessments in the future, even when no reference information is available.

Methods

Sediment sampling in the CCZ was conducted using a multicorer during the cruises MANGAN 2018 (SO262:, 05/04 to 29/05/2018, Rühlemann et al., 2019), and MiningImpact2 (SO268/2:, 30/03 to 22/05/2019, Haeckel and Linke, 2021), both on the German research vessel SONNE. The study area is located within the eastern part of the German contract area for the exploration of polymetallic nodules, which has been licensed by the German Federal Institute for Geosciences and Natural Resources (BGR) from the International Seabed Authority (ISA).

Meiofauna was sampled using multicores with an (inner diameter of 94-96 mm. Bottom water was sieved over a 32 µm sieve and fixed with 99.8% ethanol denatured with methyl ethyl ketone together with, in 2018, the upper 3 cm and in 2019 the upper 5 cm of sediment in a Kautex wide-neck bottle (1000 ml). All samples were re-fixed with the same fixative after 24 hours and stored at -20°C. To extract all meiofauna organisms from the sediment, samples were centrifuged according to the differential flotation method (Heip et al., 1985) with the colloidal gel Levasil®. Centrifuged samples were transferred into a Kautex wide-neck bottle (100 ml) and further stored at -20°C in the same fixative. All copepods were sorted out of the supernatant under a dissecting microscope. Prior to molecular processing, all individuals were photographed to document their basic morphology, and the ontogenetic stage was determined.

Further processing was conducted according to two different protocols. In the first approach conducted on 58% of all available specimens, the individual was cut into two pieces. The posterior part was used for DNA-barcoding, while the anterior part was used for investigations with MALDI-TOF MS. In the second, enhanced protocol conducted on 42% of the specimens, the individuals were first prepared for MALDI-TOF MS and then washed with 10 µl molecular grade water before they were processed for DNA-barcoding, to increase biomass used for the MALDI measurements. The change of protocol only influenced the success rate of MALDI-TOF MS, but had no influence on the resulting DNA-barcode or the mass spectrum. Furthermore, the exuviae could be retained for potential morphological investigations in the future.

The tissue was transferred with 5-µl ethanol into a 0.2 ml microcentrifuge tube. After the ethanol had evaporated at room temperature, 2.5-µl α-cyano-4-hydroxycinnamic acid (HCCA) was added and the tissue was incubated for at least 5 min. Thereafter, the extract with the HCCA was transferred to a metallic target plate and measured in a Microflex LT/SH System (Bruker Daltonics) using the method MBTAuto. Peak evaluation was carried out in a mass peak range between 2 k and 10 k Dalton (Da) using a centroid peak detection algorithm, a signal to noise threshold of 2 and a minimum intensity threshold of 600. To create a sum spectrum, 160 satisfactory shots were summed up.

Raw spectra were imported to R and further processed using the R-packages MALDIquantForeign (Gibb, 2015) and MALDIquant (Gibb and Strimmer, Korbinian, 2012). Spectra were square-root transformed, smoothed using the Savitzky Golay method (Savitzky and Golay, 1964), baseline corrected using the Statistics-sensitive Non-linear Iterative Peak-clipping algorithm (SNIP)(Ryan et al., 1988) and spectra normalized using the Total Ion Current (TIC) method. Repeated measurements were averaged by using mean intensities.

Usage Notes

Data was processed in R. Mass spectrometry data can be imported to R using the Package MaldiQuantForeign and further be processed using the package MaldiQuant.

Gibb, S. (2015). MALDIquantForeign: Import/Export routines for MALDIquant. A package for R. https://CRAN.R-project.org/package=MALDIquantForeign

Gibb, S., and Strimmer, Korbinian (2012). MALDIquant: Quantitative Analysis of Mass Spectrometry Data. Bioinformatics 28, 2270--2271. doi: 10.1093/bioinformatics/bts447.

Funding

Bundesministerium für Bildung und Forschung, Award: 03F0812E

Bundesministerium für Bildung und Forschung, Award: 03F0707E

Deutsche Forschungsgemeinschaft, Award: RE2808/3-1

Deutsche Forschungsgemeinschaft, Award: RE2808/3-2