A universal tool for marine metazoan species identification: towards best practices in proteomic fingerprinting.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
13 Jan 2024
13 Jan 2024
Historique:
received:
30
08
2023
accepted:
02
01
2024
medline:
14
1
2024
pubmed:
14
1
2024
entrez:
13
1
2024
Statut:
epublish
Résumé
Proteomic fingerprinting using MALDI-TOF mass spectrometry is a well-established tool for identifying microorganisms and has shown promising results for identification of animal species, particularly disease vectors and marine organisms. And thus can be a vital tool for biodiversity assessments in ecological studies. However, few studies have tested species identification across different orders and classes. In this study, we collected data from 1246 specimens and 198 species to test species identification in a diverse dataset. We also evaluated different specimen preparation and data processing approaches for machine learning and developed a workflow to optimize classification using random forest. Our results showed high success rates of over 90%, but we also found that the size of the reference library affects classification error. Additionally, we demonstrated the ability of the method to differentiate marine cryptic-species complexes and to distinguish sexes within species.
Identifiants
pubmed: 38218969
doi: 10.1038/s41598-024-51235-z
pii: 10.1038/s41598-024-51235-z
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1280Subventions
Organisme : Deutsche Forschungsgemeinschaft
ID : RE2808/3-1
Organisme : Deutsche Forschungsgemeinschaft,Germany
ID : RE2808/3-2
Organisme : The Federal Ministry of Education and Research
ID : 03F0499A
Organisme : Niedersächsisches Ministerium für Wissenschaft und Kultur
ID : ZN3285
Organisme : Volkswagen Foundation
ID : ZN3285
Informations de copyright
© 2024. The Author(s).
Références
Bailey, R. C., Norris, R. H. & Reynoldson, T. B. Taxonomic resolution of benthic macroinvertebrate communities in bioassessments. J. N. Am. Benthol. Soc. 20, 280–286 (2001).
doi: 10.2307/1468322
Timms, L. L., Bowden, J. J., Summerville, K. S. & Buddle, C. M. Does species-level resolution matter? Taxonomic sufficiency in terrestrial arthropod biodiversity studies. Insect Conserv. Divers. 6, 453–462 (2013).
doi: 10.1111/icad.12004
Rossel, S., Khodami, S. & Martínez Arbizu, P. Comparison of rapid biodiversity assessment of meiobenthos using MALDI-TOF MS and metabarcoding. Front. Mar. Sci. 6, 659 (2019).
doi: 10.3389/fmars.2019.00659
Singhal, N., Kumar, M., Kanaujia, P. K. & Virdi, J. S. MALDI-TOF mass spectrometry: An emerging technology for microbial identification and diagnosis. Front. Microbiol. 6, 791 (2015).
pubmed: 26300860
pmcid: 4525378
doi: 10.3389/fmicb.2015.00791
Fenselau, C. & Demirev, P. A. Characterization of intact microorganisms by MALDI mass spectrometry. Mass Spectrom. Rev. 20, 157–171 (2001).
pubmed: 11835304
doi: 10.1002/mas.10004
Sandrin, T. R., Goldstein, J. E. & Schumaker, S. MALDI TOF MS profiling of bacteria at the strain level: A review. Mass Spectrom. Rev. 32, 188–217 (2013).
pubmed: 22996584
doi: 10.1002/mas.21359
Calderaro, A. et al. Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry applied to virus identification. Sci. Rep. 4, 6803 (2014).
pubmed: 25354905
pmcid: 4213803
doi: 10.1038/srep06803
Mazzeo, M. F. et al. Fish authentication by MALDI-TOF mass spectrometry. J. Agric. Food Chem. 56, 11071–11076 (2008).
pubmed: 19007297
doi: 10.1021/jf8021783
Flaudrops, C., Armstrong, N., Raoult, D. & Chabrière, E. Determination of the animal origin of meat and gelatin by MALDI-TOF-MS. J. Food Compos. Anal. 41, 104–112 (2015).
doi: 10.1016/j.jfca.2015.02.009
Sassi, M., Arena, S. & Scaloni, A. MALDI-TOF-MS platform for integrated proteomic and peptidomic profiling of milk samples allows rapid detection of food adulterations. J. Agric. Food Chem. 63, 6157–6171 (2015).
pubmed: 26098723
doi: 10.1021/acs.jafc.5b02384
Laakmann, S. et al. Comparison of molecular species identification for North Sea calanoid copepods (Crustacea) using proteome fingerprints and DNA sequences. Mol. Ecol. Resour. 13, 862–876 (2013).
pubmed: 23848968
doi: 10.1111/1755-0998.12139
Kaiser, P. et al. High-resolution community analysis of deep-sea copepods using MALDI-TOF protein fingerprinting. Deep-Sea Res. Part Oceanogr. Res. Pap. 138, 122–130 (2018).
doi: 10.1016/j.dsr.2018.06.005
Rossel, S. & Martínez Arbizu, P. Revealing higher than expected diversity of Harpacticoida (Crustacea: Copepoda) in the North Sea using MALDI-TOF MS and molecular barcoding. Sci. Rep. 9, 9182 (2019).
pubmed: 31235850
pmcid: 6591307
doi: 10.1038/s41598-019-45718-7
Renz, J. et al. Proteomic fingerprinting facilitates biodiversity assessments in understudied ecosystems: A case study on integrated taxonomy of deep sea copepods. Mol. Ecol. Resour. 21, 1936 (2021).
pubmed: 33900025
doi: 10.1111/1755-0998.13405
Yeom, J., Park, N., Jeong, R. & Lee, W. Integrative description of cryptic tigriopus species from Korea using MALDI-TOF MS and DNA barcoding. Front. Mar. Sci. 8, 495 (2021).
doi: 10.3389/fmars.2021.648197
Peters, J., Laakmann, S., Rossel, S., Martínez Arbizu, P. & Renz, J. Perspectives of species identification by MALDI-TOF MS in monitoring—Stability of proteomic fingerprints in marine epipelagic copepods. Mol. Ecol. Resour. https://doi.org/10.1111/1755-0998.13779 (2023).
doi: 10.1111/1755-0998.13779
pubmed: 37417794
Rossel, S. et al. Proteomic fingerprinting enables quantitative biodiversity assessments of species and ontogenetic stages in Calanus congeners (Copepoda, Crustacea) from the Arctic Ocean. Mol. Ecol. Resour. 23, 382 (2022).
pubmed: 36114815
doi: 10.1111/1755-0998.13714
Kürzel, K. et al. Correct species identification and its implications for conservation using Haploniscidae (Crustacea, Isopoda) in icelandic waters as a proxy. Front. Mar. Sci. 8, 196 (2022).
doi: 10.3389/fmars.2021.795196
Paulus, E. et al. Recent speciation and hybridization in Icelandic deep-sea isopods: An integrative approach using genomics and proteomics. Mol. Ecol. 31, 313–330 (2022).
pubmed: 34676606
doi: 10.1111/mec.16234
Holst, S., Heins, A. & Laakmann, S. Morphological and molecular diagnostic species characters of Staurozoa (Cnidaria) collected on the coast of Helgoland (German Bight, North Sea). Mar. Biodivers. https://doi.org/10.1007/s12526-019-00943-1 (2019).
doi: 10.1007/s12526-019-00943-1
Park, N., Yeom, J., Jeong, R. & Lee, W. Novel attempt at discrimination of a bullet-shaped siphonophore (Family Diphyidae) using matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-ToF MS). Sci. Rep. 11, 19077 (2021).
pubmed: 34561535
pmcid: 8463557
doi: 10.1038/s41598-021-98724-z
Korfhage, S. A. et al. Species delimitation of hexacorallia and octocorallia around Iceland using nuclear and mitochondrial DNA and proteome fingerprinting. Front. Mar. Sci. 9, 201 (2022).
doi: 10.3389/fmars.2022.838201
Wilke, T., Renz, J., Hauffe, T., Delicado, D. & Peters, J. Proteomic fingerprinting discriminates cryptic gastropod species. Malacologia 63, 131–137 (2020).
doi: 10.4002/040.063.0113
Volta, P., Riccardi, N., Lauceri, R. & Tonolla, M. Discrimination of freshwater fish species by matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS): A pilot study. J. Limnol. 71, e17 (2012).
doi: 10.4081/jlimnol.2012.e17
Yssouf, A. et al. Matrix-assisted laser desorption ionization–time of flight mass spectrometry for rapid identification of tick vectors. J. Clin. Microbiol. 51, 522–528 (2013).
pubmed: 23224087
pmcid: 3553915
doi: 10.1128/JCM.02665-12
Chavy, A. et al. Identification of French Guiana sand flies using MALDI-TOF mass spectrometry with a new mass spectra library. PLoS Negl. Trop. Dis. 13, e0007031 (2019).
pubmed: 30707700
pmcid: 6373979
doi: 10.1371/journal.pntd.0007031
Rakotonirina, A. et al. MALDI-TOF MS: Optimization for future uses in entomological surveillance and identification of mosquitoes from New Caledonia. Parasit. Vectors 13, 1–12 (2020).
doi: 10.1186/s13071-020-04234-8
Rakotonirina, A. et al. MALDI-TOF MS: An effective tool for a global surveillance of dengue vector species. PLoS ONE 17, e0276488 (2022).
pubmed: 36264911
pmcid: 9584457
doi: 10.1371/journal.pone.0276488
Nabet, C. et al. New assessment of Anopheles vector species identification using MALDI-TOF MS. Malar. J. 20, 1–16 (2021).
doi: 10.1186/s12936-020-03557-2
Laakmann, S., Boos, K., Knebelsberger, T., Raupach, M. J. & Neumann, H. Species identification of echinoderms from the North Sea by combining morphology and molecular data. Helgol. Mar. Res. 70, 5 (2016).
Han, H., Guo, X. & Yu, H. Variable selection using mean decrease accuracy and mean decrease gini based on random forest. In 2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS) 219–224 (IEEE, 2016).
Dieme, C. et al. Accurate identification of Culicidae at aquatic developmental stages by MALDI-TOF MS profiling. Parasit. Vectors 7, 544 (2014).
pubmed: 25442218
pmcid: 4273427
doi: 10.1186/s13071-014-0544-0
Yssouf, A. et al. Identification of flea species using MALDI-TOF/MS. Comp. Immunol. Microbiol. Infect. Dis. 37, 153–157 (2014).
pubmed: 24878069
doi: 10.1016/j.cimid.2014.05.002
Mazzeo, M. F. & Siciliano, R. A. Proteomics for the authentication of fish species. J. Proteom. 147, 119–124 (2016).
doi: 10.1016/j.jprot.2016.03.007
Maász, G., Takács, P., Boda, P., Várbiró, G. & Pirger, Z. Mayfly and fish species identification and sex determination in bleak (Alburnus alburnus) by MALDI-TOF mass spectrometry. Sci. Total Environ. 601, 317–325 (2017).
pubmed: 28558278
doi: 10.1016/j.scitotenv.2017.05.207
Rossel, S. et al. Rapid species level identification of fish eggs by proteome fingerprinting using MALDI-TOF MS. J. Proteom. 231, 103993 (2020).
doi: 10.1016/j.jprot.2020.103993
Hynek, R. et al. Identification of freshwater zooplankton species using protein profiling and principal component analysis. Limnol. Oceanogr. Methods 16, 199–204 (2018).
doi: 10.1002/lom3.10238
Vega-Rúa, A. et al. Improvement of mosquito identification by MALDI-TOF MS biotyping using protein signatures from two body parts. Parasit. Vectors 11, 574 (2018).
pubmed: 30390691
pmcid: 6215610
doi: 10.1186/s13071-018-3157-1
Loaiza, J. R. et al. Application of matrix-assisted laser desorption/ionization mass spectrometry to identify species of Neotropical Anopheles vectors of malaria. Malar. J. 18, 95 (2019).
pubmed: 30902057
pmcid: 6431007
doi: 10.1186/s12936-019-2723-0
Feltens, R., Görner, R., Kalkhof, S., Gröger-Arndt, H. & von Bergen, M. Discrimination of different species from the genus Drosophila by intact protein profiling using matrix-assisted laser desorption ionization mass spectrometry. BMC Evol. Biol. 10, 1 (2010).
doi: 10.1186/1471-2148-10-95
Tran, A., Alby, K., Kerr, A., Jones, M. & Gilligan, P. H. Cost savings realized by implementation of routine microbiological identification by matrix-assisted laser desorption ionization—Time of flight mass spectrometry. J. Clin. Microbiol. 53, 2473–2479 (2015).
pubmed: 25994167
pmcid: 4508454
doi: 10.1128/JCM.00833-15
Müller, P. et al. Identification of cryptic Anopheles mosquito species by molecular protein profiling. PLoS ONE 8, e57486 (2013).
pubmed: 23469000
pmcid: 3585343
doi: 10.1371/journal.pone.0057486
Rossel, S. & Martínez Arbizu, P. Effects of sample fixation on specimen identification in biodiversity assemblies based on proteomic data (MALDI-TOF). Front. Mar. Sci. 5, 149 (2018).
doi: 10.3389/fmars.2018.00149
Lohman, D. J., Prawiradilaga, D. M. & Meier, R. Improved COI barcoding primers for Southeast Asian perching birds (Aves: Passeriformes). Mol. Ecol. Resour. 9, 37–40 (2009).
pubmed: 21564563
doi: 10.1111/j.1755-0998.2008.02221.x
Toumi, F. et al. Development of two species-specific primer sets to detect the cereal cyst nematodes Heterodera avenae and Heterodera filipjevi. Eur. J. Plant Pathol. 136, 613–624 (2013).
doi: 10.1007/s10658-013-0192-9
Jeverica, S., Nagy, E., Mueller-Premru, M. & Papst, L. Sample preparation method influences direct identification of anaerobic bacteria from positive blood culture bottles using MALDI-TOF MS. Anaerobe 54, 231–235 (2018).
pubmed: 29861277
doi: 10.1016/j.anaerobe.2018.05.003
Wang, J. et al. Evaluation of three sample preparation methods for the identification of clinical strains by using two MALDI-TOF MS systems. J. Mass Spectrom. 56, e4696 (2021).
pubmed: 33421261
pmcid: 7900945
doi: 10.1002/jms.4696
Ressom, H. W. et al. Peak selection from MALDI-TOF mass spectra using ant colony optimization. Bioinformatics 23, 619–626 (2007).
pubmed: 17237065
doi: 10.1093/bioinformatics/btl678
Shin, H., Sampat, M. P., Koomen, J. M. & Markey, M. K. Wavelet-based adaptive denoising and baseline correction for MALDI TOF MS. Omics J. Integr. Biol. 14, 283–295 (2010).
doi: 10.1089/omi.2009.0119
Palarea-Albaladejo, J., Mclean, K., Wright, F. & Smith, D. G. MALDIrppa: Quality control and robust analysis for mass spectrometry data. Bioinformatics 34, 522–523 (2017).
doi: 10.1093/bioinformatics/btx628
Knebelsberger, T. & Thiel, R. Identification of gobies (Teleostei: Perciformes: Gobiidae) from the North and Baltic Seas combining morphological analysis and DNA barcoding. Zool. J. Linn. Soc. 172, 831–845 (2014).
doi: 10.1111/zoj.12189
Knebelsberger, T. et al. A reliable DNA barcode reference library for the identification of the North European shelf fish fauna. Mol. Ecol. Resour. 14, 1060–1071 (2014).
pubmed: 24618145
doi: 10.1111/1755-0998.12238
Markert, A., Raupach, M. J., Segelken-Voigt, A. & Wehrmann, A. Molecular identification and morphological characteristics of native and invasive Asian brush-clawed crabs (Crustacea: Brachyura) from Japanese and German coasts: Hemigrapsus penicillatus (De Haan, 1835) versus Hemigrapsus takanoi Asakura & Watanabe 2005. Org. Divers. Evol. 14, 369–382 (2014).
doi: 10.1007/s13127-014-0176-4
Gebhardt, K. & Knebelsberger, T. Identification of cephalopod species from the North and Baltic Seas using morphology, COI and 18S rDNA sequences. Helgol. Mar. Res. 69, 259 (2015).
doi: 10.1007/s10152-015-0434-7
Raupach, M. J. et al. The application of DNA barcodes for the identification of marine crustaceans from the North Sea and adjacent regions. PLoS ONE 10, e0139421 (2015).
pubmed: 26417993
pmcid: 4587929
doi: 10.1371/journal.pone.0139421
Barco, A., Raupach, M. J., Laakmann, S., Neumann, H. & Knebelsberger, T. Identification of North Sea molluscs with DNA barcoding. Mol. Ecol. Resour. 16, 288–297 (2016).
pubmed: 26095230
doi: 10.1111/1755-0998.12440
Rossel, S., Deli, T. & Raupach, M. J. First insights into the phylogeography and demographic history of the common hermit crab Pagurus bernhardus (Linnaeus, 1758) (Decapoda: Anomura: Paguridae) across the Eastern Atlantic and North Sea. J. Crustac. Biol. 40, 435–449 (2020).
doi: 10.1093/jcbiol/ruaa026
R-Core-Team. R: A Language and Environment for Statistical Computing (2022).
Gibb, S. MALDIquantForeign: Import/Export Routines for MALDIquant. A Package for R. https://CRANR-Project.org (2015).
Gibb, S. & Strimmer, K. MALDIquant: A versatile R package for the analysis of mass spectrometry data. Bioinformatics 28, 2270–2271 (2012).
pubmed: 22796955
doi: 10.1093/bioinformatics/bts447
Savitzky, A. & Golay, M. J. Smoothing and differentiation of data by simplified least squares procedures. Anal. Chem. 36, 1627–1639 (1964).
doi: 10.1021/ac60214a047
Ryan, C., Clayton, E., Griffin, W., Sie, S. & Cousens, D. SNIP, a statistics-sensitive background treatment for the quantitative analysis of PIXE spectra in geoscience applications. Nucl. Instrum. Methods Phys. Res. Sect. B Beam Interact. Mater. At. 34, 396–402 (1988).
doi: 10.1016/0168-583X(88)90063-8
Rossel, S. & Martínez Arbizu, P. Automatic specimen identification of Harpacticoids (Crustacea: Copepoda) using random forest and MALDI-TOF mass spectra, including a post hoc test for false positive discovery. Methods Ecol. Evol. 9, 1421–1434 (2018).
doi: 10.1111/2041-210X.13000
Wickham, H., Francois, R., Henry, L. & Müller, K. dplyr: A Grammar of Data Manipulation. (2022).
Breimann, L. Random forests. Mach. Learn. 45, 5–32 (2001).
doi: 10.1023/A:1010933404324
Martínez Arbizu, P. & Rossel, S. RFtools: Miscellaneous Tools for Random Forest Models (2018).