DOI: 10.5061/dryad.hdr7sqvk0
title: MALDI-TOF MS data: Species delimitation of Hexacorallia and Octocorallia around Iceland using nuclear and mitochondrial DNA and proteome fingerprinting

description: Cold-water corals build up reef structures or coral gardens and play an
 important role for many organisms in the deep sea. Climate change,
 deep-sea mining, and bottom trawling are severely compromising these
 ecosystems, making it all the more important to document the diversity,
 distribution, and impacts on corals. This goes hand in hand with species
 identification, which is morphologically and genetically challenging for
 Hexa- and Octocorallia. Morphological variation and slowly evolving
 molecular markers both contribute to the difficulty of species
 identification. In this study, a fast and cheap species delimitation tool
 for Octocorallia and Scleractinia of the Northeast Atlantic was tested
 based on 49 specimens. Two nuclear markers (ITS2 and 28S rDNA) and two
 mitochondrial markers (COI and mtMutS) were sequenced. The sequences
 formed the basis of a reference library for comparison to the results of
 species delimitation based on proteomic analysis using the MALDI-TOF MS
 method. The genetic methods were able to distinguish 17 of 18 presumed
 species. The MALDI-TOF MS method was able to distinguish 7 species.
 Species that could not be distinguished from one another still achieved
 good signals but were not represented by enough specimens for comparison.
 Therefore, it is predicted that with an extensive reference library of
 proteome spectra for Scleractinia and Octocorallia, MALDI-TOF MS may
 provide a rapid and cost-effective alternative for species discrimination
 in corals.
description: Sampling The specimens were
 collected by the ROV Kiel 6000 between 19<sup>th</sup> June
 and 27<sup>th</sup> July 2020 in Icelandic waters during the
 IceAGE 3 cruise SO276/MerMet17-6 (with RV SONNE) and by the ROV PHOCA
 during the IceAGE RR cruise MSM75 between 29th June and 8th August 2018
 (RV MS MERIAN). Stations were located around Iceland, in the Norwegian
 Basin, the Norwegian Sea, and the Reykjanes Ridge in 207.1 m to 2,040.8 m
 depth. The collected corals were photographed with an HD camera system of
 the ROV Kiel 6000 in the habitat and with a DLSR camera system (Canon EOS
 5D Mark IV with Canon MP-E 65mm f/2.8 1-5x Macro Photo lens and Canon
 Compact-Macro Lens EF 50mm 1:25) on board. Samples were preserved in 96%
 undenatured ethanol which was changed after 24h on board. Larger samples
 were preserved in 3% formol solution where subsamples were taken and
 preserved in 96% undenatured ethanol. Samples were stored at -20 °C at the
 German Centre for Marine Biodiversity Research (DZMB) in Hamburg,
 Germany.   MALDI-TOF MS analysis
 In total,
 one square millimeter of tissue of 49 ethanol-preserved individuals were
 separated into 1.5 ml microcentrifuge tubes. After ethanol evaporation,
 1.5 µl of a matrix solution containing α-Cyano-4-hydroxycinnamic acid
 (HCCA) as a saturated solution in 50% acetonitrile, 47.5% molecular grade
 water, and 2.5% trifluoroacetic acid was added. The solution was incubated
 for 5 to 90 min and was applied to one spot for crystallization on the
 target plate. The Microflex LT/SH System (Bruker Daltonics) measured the
 samples by using the flexControl 3.4. (Bruker Daltonics) software. Masses
 were measured from 2 to 20k Dalton. A centroid peak detection algorithm
 was carried out for peak evaluation by analyzing the mass peak range from
 2 to 20k Dalton. Furthermore, peak evaluation was carried out by a
 signal-to-noise threshold of two and a minimum intensity threshold of 600
 with a peak resolution higher than 400. To validate fuzzy control, the
 proteins/oligonucleotide method was employed by maximal resolution of ten
 times above the threshold. The obtained dataset was analyzed as described
 by (Rossel and Martínez Arbizu, 2018a)in R, version 1.4.1106 (R Core Team,
 2020) using the packages MALDIquant (Gibb, 2012)and MALDIquantForeign
 (Gibb, 2019). Protein mass spectra were trimmed to an identical range from
 2,000 to 20,000 m/z and smoothed by using the Saviztky-Golay method
 (Savitzky and Golay, 1964) with half window size (HWS) of 10. The SNIP
 baseline estimation method (Ryan et al., 1988) was applied to remove the
 baseline, and the TIC method in MALDIquant was used to normalize the
 spectra. A signal-to-noise ratio (SNR) of 5 was applied to reduce the
 noise of the spectra, and a half window size of 10 was used for peak
 detection. The peaks of the spectra were binned several times by using the
 function binpeaks in MALDIquant with a tolerance of 0.002 in a strict
 approach. To apply further analysis, a Hellinger transformation (Legendre
 and Gallagher, 2001) was applied to the resulting intensity matrix. A
 dendrogram was generated by hierarchical cluster analysis with Ward’s D
 clustering algorithm (Ward and Joe, 1963), Euclidean distances, and 1,000
 bootstrap repeats. Furthermore, a
 RandomForest (RF) model (Breiman, 2001) using R-package randomForest (Liaw
 and Wiener, 2002) was generated to investigate applicability of mass
 spectra in classification approaches. The RF analysis is based on an
 intensity matrix by using bins as predictors and species names as
 multi-level target factors. The RF analysis was carried out on Hellinger
 transformed data (Legendre and Gallagher, 2001) using 35 predictors (mtry)
 and 2,000 trees. A t-SNE plot (Van der Maaten and Hinton, 2008), based on
 the raw data matrix probability of each specimen was applied. Here, the
 R-package t-SNE (Krijthe and Van der Maaten, 2015) was used. The t-SNE
 plot was constructed by using a perplexity of 10 and a number of
 iterations of 4,000.