Bioarchaeological proteomic analysis of skin samples from an ancient Egyptian child mummy

Prathiba Ravishankar, Dylan Multari, Ronika Power, Paul Haynes

Research output: Chapter in Book/Report/Conference proceedingConference abstract


Introduction: Analysing ancient proteins has some advantages over ancient DNA analysis, because proteins are more resilient molecules when compared to DNA. Mass spectrometry - based proteomics involves the analysis of the protein profile of a given sample material, which generates large scale data from miniscule amounts of material. Archaeological research is often limited to tiny amounts of sample available for scientific analysis. However, there is no validated proteomics workflow in the published literature that could be applied to ancient human skin tissue samples. This project deals with the optimization and application of sample preparation methods for mass spectrometric analysis of ancient Egyptian skin samples.

Methods: We first used modern human skin tissue as a surrogate material. We have tested two different grinding techniques, glass bead grinding and liquid nitrogen grinding, in the process of protein extraction. We tested two different protein digestion techniques, SDS-PAGE and in-gel digestion, and filter-aided sample preparation (FASP) with in-solution digestion. Peptides were separated, fragmented and analysed using a Q Exactive orbitrap mass spectrometer couple to a reversed phase nanoflow liquid chromatography system. Peptide to spectrum matching and protein identification were performed using XTandem and Sequest. Using an optimized approach, we have subsequently performed a shotgun proteomics analysis to investigate the protein profile of a set of four ancient human skin samples.

Preliminary Data: A total of 297 proteins were identified from a set of four skin samples from an Old Kingdom Egyptian mummy, which is the sum of all the proteins identified from all samples without the elimination of redundancy. The peptide false discovery rate was 0.01% within the triplicate analyses of each of the samples. Identification of such a relatively sparse number of proteins clearly indicates that many of the proteins have been degraded in the samples, which implies that the cell proteome of the ancient child mummy is, unsurprisingly, degraded to a considerable extent. Out of the 297 proteins identified, 49 proteins were keratins and 20 proteins were collagens, which is 1/4 of the total proteins identified. The non – redundant data set contains 14 immune and inflammatory response proteins and among them dermcidin and neutrophil defensin 1 were identified across all four samples. Most of the other proteins identified include extra cellular matrix proteins, desmosomal proteins, S100 proteins, ribosomal proteins, serpins, ribosomal proteins and proteases. Our results revealed that it was indeed possible to use our optimised analytical workflow to identify proteins from skin tissues of an Egyptian child mummy belonging to the ancient Egyptian Old Kingdom (c.2686-2181 BC). The bioarchaeological information that we have obtained from the preliminary data provides insights into the preservation state and physiological state of the remains, and also an indication of the possible cause of death of the individual.

Novel Aspect: Development of a novel pipeline of shotgun proteomics analysis, from preparing ancient skin samples to analysing results for bioarchaeological information.
Original languageEnglish
Title of host publicationProceedings of the 68th American Society for Mass Spectrometry Conference on Mass Spectrometry and Allied Topics
Place of PublicationSanta Fe, NM
PublisherAmerican Society for Mass Spectrometry (ASMS)
Number of pages1
Publication statusPublished - 2020
Event68th American Society for Mass Spectrometry Conference on Mass Spectrometry and Allied Topics - Originally Houston, then moved online due to Covid., Houston, United States
Duration: 1 Jun 202012 Jun 2020


Conference68th American Society for Mass Spectrometry Conference on Mass Spectrometry and Allied Topics
Abbreviated titleASMS 2020 Reboot
Country/TerritoryUnited States


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