The dental calculus metabolome in modern and historic samples.

INTRODUCTION: Dental calculus is a mineralized microbial dental plaque biofilm that forms throughout life by precipitation of salivary calcium salts. Successive cycles of dental plaque growth and calcification make it an unusually well-preserved, long-term record of host-microbial interaction in the archaeological record. Recent studies have confirmed the survival of authentic ancient DNA and proteins within historic and prehistoric dental calculus, making it a promising substrate for investigating oral microbiome evolution via direct measurement and comparison of modern and ancient specimens. OBJECTIVE: We present the first comprehensive characterization of the human dental calculus metabolome using a multi-platform approach. METHODS: Ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) quantified 285 metabolites in modern and historic (200 years old) dental calculus, including metabolites of drug and dietary origin. A subset of historic samples was additionally analyzed by high-resolution gas chromatography-MS (GC-MS) and UPLC-MS/MS for further characterization of metabolites and lipids. Metabolite profiles of modern and historic calculus were compared to identify patterns of persistence and loss. RESULTS: Dipeptides, free amino acids, free nucleotides, and carbohydrates substantially decrease in abundance and ubiquity in archaeological samples, with some exceptions. Lipids generally persist, and saturated and mono-unsaturated medium and long chain fatty acids appear to be well-preserved, while metabolic derivatives related to oxidation and chemical degradation are found at higher levels in archaeological dental calculus than fresh samples. CONCLUSIONS: The results of this study indicate that certain metabolite classes have higher potential for recovery over long time scales and may serve as appropriate targets for oral microbiome evolutionary studies

Dental metric standards for sex estimation in archaeological populations from Iran

Sex estimation of skeletal remains is one of the major components of forensic identification of unknown individuals. Teeth are a potential source of information on sex and are often recovered in archaeological or forensic contexts due to their post-mortem longevity. Currently there is limited data on dental sexual dimorphism of archaeological populations from Iran. This dissertation represents the first study to provide a dental sex estimation method for Iron Age populations. The current study was conducted on the skeletal remains of 143 adults from two Iron Age populations in close temporal and geographic proximity in the Solduz Valley (West Azerbaijan Province of Iran). 2D and 3D cervical mesiodistal and buccolingual and root volume measurements of maxillary and mandibular teeth were used to investigate the degree of sexual dimorphism in permanent dentition and to assess their applicability in sex estimation. In total 1327, 457, and 480 anterior and posterior teeth were used to collect 2D cervical, 3D cervical, and root volume measurements respectively. 2D cervical measurements were taken using Hillson-Fitzgerald dental calliper and 3D measurements were collected using CT images provided by Open Research Scan Archive (ORSA) - Penn Museum. 3D models of the teeth were created using manual segmentation in the Amira 6.01 software package. Since tooth density largely differs from crown to apex, root segmentation required two threshold levels: the segmentation of the root from the jaw and the segmentation of the crown from the root. Thresholds used for root segmentation were calculated using the half maximum height protocol of Spoor et al. (1993) for each skull, and thresholds used for crown segmentation were set visually for each tooth separately. Data was analysed using discriminant function analysis and posterior probabilities were calculated for all produced formulae where sex was previously assessed from morphological features of pelvis and skull. Bootstrapping was used to account for small sample sizes in the analysis. Statistical analysis was carried out using SPSS 23. The percentage of sexual dimorphism was also used to quantify the amount of sexual dimorphism in the sample. The results showed that incisors and canines were the most sexually dimorphic teeth, providing percentages of correct sex classification between 80% and 100% depending on the measurement used. Root volume measurement was shown to be the most sexually dimorphic variable providing an accuracy of over 90% in all functions. The present study provided the first dental metric standards for sex estimation using odontometric data in Iranian archaeological populations. Dental measurements, particularly root volume measurements, were found to be of value for sex assessment and the method presented here could be a useful tool for establishing accurate demographic data from skeletal remains of the Iron Age from Iran