IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v13y2022i1d10.1038_s41467-022-30097-x.html
   My bibliography  Save this article

SPIN enables high throughput species identification of archaeological bone by proteomics

Author

Listed:
  • Patrick Leopold Rüther

    (University of Copenhagen)

  • Immanuel Mirnes Husic

    (University of Copenhagen)

  • Pernille Bangsgaard

    (University of Copenhagen)

  • Kristian Murphy Gregersen

    (Royal Danish Academy)

  • Pernille Pantmann

    (Museum Nordsjælland)

  • Milena Carvalho

    (University of Algarve
    University of New Mexico)

  • Ricardo Miguel Godinho

    (University of Algarve)

  • Lukas Friedl

    (University of Algarve
    Dept. of Anthropology University of West Bohemia)

  • João Cascalheira

    (University of Algarve)

  • Alberto John Taurozzi

    (University of Copenhagen)

  • Marie Louise Schjellerup Jørkov

    (University of Copenhagen)

  • Michael M. Benedetti

    (University of Algarve
    University of North Carolina Wilmington)

  • Jonathan Haws

    (University of Algarve
    University of Louisville)

  • Nuno Bicho

    (University of Algarve)

  • Frido Welker

    (University of Copenhagen)

  • Enrico Cappellini

    (University of Copenhagen)

  • Jesper Velgaard Olsen

    (University of Copenhagen)

Abstract

Species determination based on genetic evidence is an indispensable tool in archaeology, forensics, ecology, and food authentication. Most available analytical approaches involve compromises with regard to the number of detectable species, high cost due to low throughput, or a labor-intensive manual process. Here, we introduce “Species by Proteome INvestigation” (SPIN), a shotgun proteomics workflow for analyzing archaeological bone capable of querying over 150 mammalian species by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Rapid peptide chromatography and data-independent acquisition (DIA) with throughput of 200 samples per day reduce expensive MS time, whereas streamlined sample preparation and automated data interpretation save labor costs. We confirm the successful classification of known reference bones, including domestic species and great apes, beyond the taxonomic resolution of the conventional peptide mass fingerprinting (PMF)-based Zooarchaeology by Mass Spectrometry (ZooMS) method. In a blinded study of degraded Iron-Age material from Scandinavia, SPIN produces reproducible results between replicates, which are consistent with morphological analysis. Finally, we demonstrate the high throughput capabilities of the method in a high-degradation context by analyzing more than two hundred Middle and Upper Palaeolithic bones from Southern European sites with late Neanderthal occupation. While this initial study is focused on modern and archaeological mammalian bone, SPIN will be open and expandable to other biological tissues and taxa.

Suggested Citation

  • Patrick Leopold Rüther & Immanuel Mirnes Husic & Pernille Bangsgaard & Kristian Murphy Gregersen & Pernille Pantmann & Milena Carvalho & Ricardo Miguel Godinho & Lukas Friedl & João Cascalheira & Albe, 2022. "SPIN enables high throughput species identification of archaeological bone by proteomics," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-30097-x
    DOI: 10.1038/s41467-022-30097-x
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-30097-x
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-022-30097-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Frido Welker & Jazmín Ramos-Madrigal & Martin Kuhlwilm & Wei Liao & Petra Gutenbrunner & Marc de Manuel & Diana Samodova & Meaghan Mackie & Morten E. Allentoft & Anne-Marie Bacon & Matthew J. Collins , 2019. "Enamel proteome shows that Gigantopithecus was an early diverging pongine," Nature, Nature, vol. 576(7786), pages 262-265, December.
    2. Rosa R. Jersie-Christensen & Liam T. Lanigan & David Lyon & Meaghan Mackie & Daniel Belstrøm & Christian D. Kelstrup & Anna K. Fotakis & Eske Willerslev & Niels Lynnerup & Lars J. Jensen & Enrico Capp, 2018. "Quantitative metaproteomics of medieval dental calculus reveals individual oral health status," Nature Communications, Nature, vol. 9(1), pages 1-12, December.
    3. Jessica Hendy & Andre C. Colonese & Ingmar Franz & Ricardo Fernandes & Roman Fischer & David Orton & Alexandre Lucquin & Luke Spindler & Jana Anvari & Elizabeth Stroud & Peter F. Biehl & Camilla Spell, 2018. "Ancient proteins from ceramic vessels at Çatalhöyük West reveal the hidden cuisine of early farmers," Nature Communications, Nature, vol. 9(1), pages 1-10, December.
    4. Yangyang Bian & Runsheng Zheng & Florian P. Bayer & Cassandra Wong & Yun-Chien Chang & Chen Meng & Daniel P. Zolg & Maria Reinecke & Jana Zecha & Svenja Wiechmann & Stephanie Heinzlmeir & Johannes Sch, 2020. "Robust, reproducible and quantitative analysis of thousands of proteomes by micro-flow LC–MS/MS," Nature Communications, Nature, vol. 11(1), pages 1-12, December.
    5. Frido Welker & Jazmín Ramos-Madrigal & Petra Gutenbrunner & Meaghan Mackie & Shivani Tiwary & Rosa Rakownikow Jersie-Christensen & Cristina Chiva & Marc R. Dickinson & Martin Kuhlwilm & Marc Manuel & , 2020. "Author Correction: The dental proteome of Homo antecessor," Nature, Nature, vol. 584(7820), pages 19-19, August.
    6. Ruedi Aebersold & Matthias Mann, 2003. "Mass spectrometry-based proteomics," Nature, Nature, vol. 422(6928), pages 198-207, March.
    7. Viviane Slon & Fabrizio Mafessoni & Benjamin Vernot & Cesare Filippo & Steffi Grote & Bence Viola & Mateja Hajdinjak & Stéphane Peyrégne & Sarah Nagel & Samantha Brown & Katerina Douka & Tom Higham & , 2018. "The genome of the offspring of a Neanderthal mother and a Denisovan father," Nature, Nature, vol. 561(7721), pages 113-116, September.
    8. Frido Welker & Jazmín Ramos-Madrigal & Petra Gutenbrunner & Meaghan Mackie & Shivani Tiwary & Rosa Rakownikow Jersie-Christensen & Cristina Chiva & Marc R. Dickinson & Martin Kuhlwilm & Marc Manuel & , 2020. "The dental proteome of Homo antecessor," Nature, Nature, vol. 580(7802), pages 235-238, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fabrice Demeter & Clément Zanolli & Kira E. Westaway & Renaud Joannes-Boyau & Philippe Duringer & Mike W. Morley & Frido Welker & Patrick L. Rüther & Matthew M. Skinner & Hugh McColl & Charleen Gaunit, 2022. "A Middle Pleistocene Denisovan molar from the Annamite Chain of northern Laos," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    2. Kertcher, Zack & Venkatraman, Rohan & Coslor, Erica, 2020. "Pleasingly parallel: Early cross-disciplinary work for innovation diffusion across boundaries in grid computing," Journal of Business Research, Elsevier, vol. 116(C), pages 581-594.
    3. Naomi S Hachiya, 2017. "Unfoldin, A Novel Tool for the Analysis of Protein Misfolding or Neurodegenerative Diseases," Open Access Journal of Neurology & Neurosurgery, Juniper Publishers Inc., vol. 6(3), pages 40-44, October.
    4. Alexander Kaever & Manuel Landesfeind & Kirstin Feussner & Burkhard Morgenstern & Ivo Feussner & Peter Meinicke, 2014. "Meta-Analysis of Pathway Enrichment: Combining Independent and Dependent Omics Data Sets," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-12, February.
    5. Dayle L Sampson & Tony J Parker & Zee Upton & Cameron P Hurst, 2011. "A Comparison of Methods for Classifying Clinical Samples Based on Proteomics Data: A Case Study for Statistical and Machine Learning Approaches," PLOS ONE, Public Library of Science, vol. 6(9), pages 1-11, September.
    6. Leonardo Vallini & Carlo Zampieri & Mohamed Javad Shoaee & Eugenio Bortolini & Giulia Marciani & Serena Aneli & Telmo Pievani & Stefano Benazzi & Alberto Barausse & Massimo Mezzavilla & Michael D. Pet, 2024. "The Persian plateau served as hub for Homo sapiens after the main out of Africa dispersal," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    7. Jiang Tan & Hui-Zhen Fu & Yuh-Shan Ho, 2014. "A bibliometric analysis of research on proteomics in Science Citation Index Expanded," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 1473-1490, February.
    8. Jacques Colinge & Keiryn L Bennett, 2007. "Introduction to Computational Proteomics," PLOS Computational Biology, Public Library of Science, vol. 3(7), pages 1-10, July.
    9. Guler, Arzu Tugce & Waaijer, Cathelijn J.F. & Mohammed, Yassene & Palmblad, Magnus, 2016. "Automating bibliometric analyses using Taverna scientific workflows: A tutorial on integrating Web Services," Journal of Informetrics, Elsevier, vol. 10(3), pages 830-841.
    10. Lei Xin & Rui Qiao & Xin Chen & Hieu Tran & Shengying Pan & Sahar Rabinoviz & Haibo Bian & Xianliang He & Brenton Morse & Baozhen Shan & Ming Li, 2022. "A streamlined platform for analyzing tera-scale DDA and DIA mass spectrometry data enables highly sensitive immunopeptidomics," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    11. Maximilian T. Strauss & Isabell Bludau & Wen-Feng Zeng & Eugenia Voytik & Constantin Ammar & Julia P. Schessner & Rajesh Ilango & Michelle Gill & Florian Meier & Sander Willems & Matthias Mann, 2024. "AlphaPept: a modern and open framework for MS-based proteomics," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    12. Tianhai Tian & Jiangning Song, 2012. "Mathematical Modelling of the MAP Kinase Pathway Using Proteomic Datasets," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-12, August.
    13. Mertens, B.J.A. & van der Burgt, Y.E.M. & Velstra, B. & Mesker, W.E. & Tollenaar, R.A.E.M. & Deelder, A.M., 2011. "On the use of double cross-validation for the combination of proteomic mass spectral data for enhanced diagnosis and prediction," Statistics & Probability Letters, Elsevier, vol. 81(7), pages 759-766, July.
    14. Patrick Cuthbertson & Tobias Ullmann & Christian Büdel & Aristeidis Varis & Abay Namen & Reimar Seltmann & Denné Reed & Zhaken Taimagambetov & Radu Iovita, 2021. "Finding karstic caves and rockshelters in the Inner Asian mountain corridor using predictive modelling and field survey," PLOS ONE, Public Library of Science, vol. 16(1), pages 1-26, January.
    15. Yun Xu & Wolfgang Schrader, 2021. "Studying the Complexity of Biomass Derived Biofuels," Energies, MDPI, vol. 14(8), pages 1-13, April.
    16. Karsten Suhre & Guhan Ram Venkataraman & Harendra Guturu & Anna Halama & Nisha Stephan & Gaurav Thareja & Hina Sarwath & Khatereh Motamedchaboki & Margaret K. R. Donovan & Asim Siddiqui & Serafim Batz, 2024. "Nanoparticle enrichment mass-spectrometry proteomics identifies protein-altering variants for precise pQTL mapping," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    17. Łuksza Marta & Kluge Bogusław & Ostrowski Jerzy & Karczmarski Jakub & Gambin Anna, 2009. "Two-Stage Model-Based Clustering for Liquid Chromatography Mass Spectrometry Data Analysis," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-34, February.
    18. Vadim Demichev & Lukasz Szyrwiel & Fengchao Yu & Guo Ci Teo & George Rosenberger & Agathe Niewienda & Daniela Ludwig & Jens Decker & Stephanie Kaspar-Schoenefeld & Kathryn S. Lilley & Michael Mülleder, 2022. "dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    19. Jinfeng Zou & Guini Hong & Xinwu Guo & Lin Zhang & Chen Yao & Jing Wang & Zheng Guo, 2011. "Reproducible Cancer Biomarker Discovery in SELDI-TOF MS Using Different Pre-Processing Algorithms," PLOS ONE, Public Library of Science, vol. 6(10), pages 1-9, October.
    20. Ling Li & Mingming Niu & Alyssa Erickson & Jie Luo & Kincaid Rowbotham & Kai Guo & He Huang & Yuxin Li & Yi Jiang & Junguk Hur & Chunyu Liu & Junmin Peng & Xusheng Wang, 2022. "SMAP is a pipeline for sample matching in proteogenomics," Nature Communications, Nature, vol. 13(1), pages 1-9, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-30097-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.