Abstract

High-throughput proteomic analysis of archaeological skeletal remains provides information about past fauna community compositions and species dispersals in time and space. Archaeological skeletal remains are a finite resource, however, and therefore it becomes relevant to optimize methods of skeletal proteome extraction. Ancient proteins in bone specimens can be highly degraded and consequently, extraction methods for well-preserved or modern bone might be unsuitable for the processing of highly degraded skeletal proteomes. In this study, we compared six proteomic extraction methods on Late Pleistocene remains with variable levels of proteome preservation. We tested the accuracy of species identification, protein sequence coverage, deamidation, and the number of post-translational modifications per method. We find striking differences in obtained proteome complexity and sequence coverage, highlighting that simple acid-insoluble proteome extraction methods perform better in highly degraded contexts. For well-preserved specimens, the approach using EDTA demineralization and protease-mix proteolysis yielded a higher number of identified peptides. The protocols presented here allowed protein extraction from ancient bone with a minimum number of working steps and equipment and yielded protein extracts within three working days. We expect further development along this route to benefit large-scale screening applications of relevance to archaeological and human evolution research.

Details

Title
Comparing extraction method efficiency for high-throughput palaeoproteomic bone species identification
Author
Mylopotamitaki, Dorothea 1 ; Harking, Florian S. 2 ; Taurozzi, Alberto J. 3 ; Fagernäs, Zandra 3 ; Godinho, Ricardo M. 4 ; Smith, Geoff M. 5 ; Weiss, Marcel 6 ; Schüler, Tim 7 ; McPherron, Shannon P. 8 ; Meller, Harald 9 ; Cascalheira, João 4 ; Bicho, Nuno 4 ; Olsen, Jesper V. 2 ; Hublin, Jean-Jacques 1 ; Welker, Frido 3 

 CIRB (UMR 7241–U1050), Collège de France, Chaire de Paléoanthropologie, Paris, France (GRID:grid.410533.0) (ISNI:0000 0001 2179 2236); Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany (GRID:grid.419518.0) (ISNI:0000 0001 2159 1813) 
 University of Copenhagen, Center for Protein Research, Copenhagen, Denmark (GRID:grid.5254.6) (ISNI:0000 0001 0674 042X) 
 University of Copenhagen, Globe Institute, Copenhagen, Denmark (GRID:grid.5254.6) (ISNI:0000 0001 0674 042X) 
 University of Algarve, Interdisciplinary Center for Archaeology and Evolution of Human Behaviour, Faro, Portugal (GRID:grid.7157.4) (ISNI:0000 0000 9693 350X) 
 Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany (GRID:grid.419518.0) (ISNI:0000 0001 2159 1813); University of Kent, School of Anthropology and Conservation, Kent, UK (GRID:grid.9759.2) (ISNI:0000 0001 2232 2818) 
 Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany (GRID:grid.419518.0) (ISNI:0000 0001 2159 1813); Friedrich-Alexander-Universität, Institut für Ur- und Frühgeschichte, Erlangen, Germany (GRID:grid.5330.5) (ISNI:0000 0001 2107 3311) 
 Thuringian State Office for the Preservation of Historical Monuments and Archaeology, Weimar, Germany (GRID:grid.5330.5) 
 Department of Human Origins, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany (GRID:grid.419518.0) (ISNI:0000 0001 2159 1813) 
 Saxony-Anhalt—State Museum of Prehistory, State Office for Heritage Management and Archaeology, Halle (Saale), Germany (GRID:grid.419518.0) 
Pages
18345
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2882127995
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.