Project description:Archaeological dental calculus has emerged as a rich source of ancient biomolecules, including proteins. Previous analyses of proteins extracted from ancient dental calculus revealed the presence of the dietary milk protein β-lactoglobulin, providing direct evidence of dairy consumption in the archaeological record. However, the potential for calculus to preserve other food-related proteins has not yet been systematically explored. Here we analyse shotgun metaproteomic data from 100 archaeological dental calculus samples ranging from the Iron Age to the post-medieval period (8thC BC - 19thC AD) in Britain, as well as dental calculus from contemporary dental patients and recently deceased individuals, to characterise the range and extent of dietary proteins preserved in dental calculus. In addition to milk proteins, we detected proteomic evidence of foodstuffs such as cereals and plant products, as well as the digestive enzyme salivary amylase. We discuss the importance of optimized protein extraction methods, data analysis approaches, and authentication strategies in the identification of dietary proteins from archaeological dental calculus. Our ability to detect dietary proteins, although limited, demonstrates the potential of these methods to robustly identify foodstuffs in the archaeological record that are under-represented due to their poor preservation.
Project description:The purpose of this study was to investigate oral microbiome and host proteins in archaeological human dental tissues using a shotgun proteomics approach. The research focuses on dental calculus (mineralized plaque), dentine, a carious lesion, and an alveolar bone abscess from the medieval site of Dalheim, Germany (ca. AD 950-1200). For comparison, proteins were also analyzed from archaeological faunal dental tissues and human dental calculus samples from modern Swiss dental patient controls. Protein extraction and generation of tryptic peptides from tooth and dental calculus specimens was performed using a filter-aided sample preparation (FASP) protocol, modified for mineralized and degraded samples. Total protein extraction was performed on a total of fourteen samples: four ancient human calculus samples (indicated as: G12, B71, B61, and B78), four ancient human tooth root samples (indicated as: G12, B17, B61, and B78), one carious lesion (indicated as: B17), one alveolar bone abscess (indicated as: B17), two ancient fauna crown cementum/calculus samples (indicated as: F1 [sheep] and F5 [cattle]), and two modern dental calculus samples from clinical patients (indicated as: P1 and P2). All samples were extracted at the Centre for Evolutionary Medicine (ZEM) at the University of Zürich with the exception of dental calculus from G12, P1, and P2, which were extracted at the Center for GeoGenetics (CGG) at the University of Copenhagen. Two samples (G12 and B61 calculus) were extracted a second time in an independent laboratory at the University of York (YORK) for comparison. Sample extracts were then sequenced (LC-MS/MS) at the Functional Genomics Center Zürich (FGCZ) using an LTQ-Orbitrap Velos, at the Novo Nordisk Foundation Center for Protein Research (CPR) using a Q-Exactive Hybrid Quadrupole Orbitrap, and at the University of York’s Proteomics and Analytical Biochemistry Laboratories (PABL) using a MaXis UHR-Qq-TOF.
Project description:The purpose of this study was to investigate oral microbiome and host proteins in archaeological human dental tissues using a shotgun proteomics approach. The research focuses on dental calculus (mineralized plaque), dentine, a carious lesion, and an alveolar bone abscess from the medieval site of Dalheim, Germany (ca. AD 950-1200). For comparison, proteins were also analyzed from archaeological faunal dental tissues and human dental calculus samples from modern Swiss dental patient controls. Protein extraction and generation of tryptic peptides from tooth and dental calculus specimens was performed using a filter-aided sample preparation (FASP) protocol, modified for mineralized and degraded samples. Total protein extraction was performed on a total of fourteen samples: four ancient human calculus samples (indicated as: G12, B71, B61, and B78), four ancient human tooth root samples (indicated as: G12, B17, B61, and B78), one carious lesion (indicated as: B17), one alveolar bone abscess (indicated as: B17), two ancient fauna crown cementum/calculus samples (indicated as: F1 [sheep] and F5 [cattle]), and two modern dental calculus samples from clinical patients (indicated as: P1 and P2). All samples were extracted at the Centre for Evolutionary Medicine (ZEM) at the University of Zürich with the exception of dental calculus from G12, P1, and P2, which were extracted at the Center for GeoGenetics (CGG) at the University of Copenhagen. Two samples (G12 and B61 calculus) were extracted a second time in an independent laboratory at the University of York (YORK) for comparison. Sample extracts were then sequenced (LC-MS/MS) at the Functional Genomics Center Zürich (FGCZ) using an LTQ-Orbitrap Velos, at the Novo Nordisk Foundation Center for Protein Research (CPR) using a Q-Exactive Hybrid Quadrupole Orbitrap, and at the University of York’s Proteomics and Analytical Biochemistry Laboratories (PABL) using a MaXis UHR-Qq-TOF.
Project description:The composition of the ancient oral microbiome has recently become possible to investigate by using advanced biomolecular methods such as metagenomics and metaproteomics. This study presents a look at the individuality of the metaproteomes from 22 medieval Danish dental calculus samples. The proteomics data suggest two distinct groups; a healthy and disease-susceptible. Comparison to modern healthy calculus samples supports this hypothesis. The osteological inspections of the samples does not immediately support the grouping made by proteomics data, making us believe that this will add a new and exciting level of information. We identify 3671 protein-groups across all medieval samples and thus expanding the depth of previous studies more than ten times. As a part of future perspective for further depth in these types of samples we performed offline high pH fractionation in combination with TMT labelling and achieved ~30% more protein identifications and reduced costly mass spectrometry time.