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Automated High-Throughput Biological Sex Identification from Archeological Human Dental Enamel Using Targeted Proteomics.

Authors :
Koenig C
Bortel P
Paterson RS
Rendl B
Madupe PP
Troché GB
Hermann NV
Martínez de Pinillos M
Martinón-Torres M
Mularczyk S
Schjellerup Jørkov ML
Gerner C
Kanz F
Martinez-Val A
Cappellini E
Olsen JV
Source :
Journal of proteome research [J Proteome Res] 2024 Nov 01; Vol. 23 (11), pp. 5107-5121. Date of Electronic Publication: 2024 Sep 26.
Publication Year :
2024

Abstract

Biological sex is key information for archeological and forensic studies, which can be determined by proteomics. However, the lack of a standardized approach for fast and accurate sex identification currently limits the reach of proteomics applications. Here, we introduce a streamlined mass spectrometry (MS)-based workflow for the determination of biological sex using human dental enamel. Our approach builds on a minimally invasive sampling strategy by acid etching, a rapid online liquid chromatography (LC) gradient coupled to a high-resolution parallel reaction monitoring (PRM) assay allowing for a throughput of 200 samples per day (SPD) with high quantitative performance enabling confident identification of both males and females. Additionally, we developed a streamlined data analysis pipeline and integrated it into a Shiny interface for ease of use. The method was first developed and optimized using modern teeth and then validated in an independent set of deciduous teeth of known sex. Finally, the assay was successfully applied to archeological material, enabling the analysis of over 300 individuals. We demonstrate unprecedented performance and scalability, speeding up MS analysis by 10-fold compared to conventional proteomics-based sex identification methods. This work paves the way for large-scale archeological or forensic studies enabling the investigation of entire populations rather than focusing on individual high-profile specimens. Data are available via ProteomeXchange with the identifier PXD049326.

Details

Language :
English
ISSN :
1535-3907
Volume :
23
Issue :
11
Database :
MEDLINE
Journal :
Journal of proteome research
Publication Type :
Academic Journal
Accession number :
39324540
Full Text :
https://doi.org/10.1021/acs.jproteome.4c00557