Planned intervention: On Thursday 19/09 between 05:30-06:30 (UTC), Zenodo will be unavailable because of a scheduled upgrade in our storage cluster.
Published September 26, 2022 | Version v1
Dataset Open

Data from: Proteomic fingerprinting enables quantitative biodiversity assessments of species and ontogenetic stages in Calanus congeners (Copepoda, Crustacea) from the Arctic Ocean

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.

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 provided by: Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100003207
Award Number: AWI_PS121_05

Funding provided by: Niedersächsisches Ministerium für Wissenschaft und Kultur
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100010570
Award Number: ZN3285

Funding provided by: Deutsche Forschungsgemeinschaft
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100001659
Award Number: RE2808/3-1

Funding provided by: Deutsche Forschungsgemeinschaft
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100001659
Award Number: RE2808/3-2

Files

Raw_Spectra.zip

Files (79.2 MB)

Name Size Download all
md5:f9aa4007ab9cbdf7ed473320ab9e9d6c
628.8 kB Download
md5:0d65bb0d381bd0c89bdb681bb4ea3f68
851.4 kB Download
md5:0686be762e152a0bd395de534fd46254
898.4 kB Download
md5:7586a0a2a7281b6848f3d534d520a78d
76.8 MB Preview Download
md5:1238f638ad127cb0c7a1b18f2bb3f108
2.3 kB Preview Download
md5:0267b5fc9119f861e6961c9b8f8e5dcd
29.3 kB Preview Download