Dental calculus (calcified dental plaque) is a cross-cultural biological matrix that is emerging as a critical source of information for anthropologists and oral health professionals. It contains a multitude of diverse biomolecules, providing information about an individual’s culture, diet, ancestry, and health. Most researchers who study archaeological dental calculus use genomic or proteomic approaches, although a wide range of other techniques are now available. However, few studies have utilized efficient multiomic protocols. This lack of integration is problematic, as such approaches in other fields have proven to improve results and strengthen interpretations. Our review discusses three multiomic approaches: (1) interactions between the metaproteome and metagenome; (2) relationships between the host genome and oral metagenome; and, (3) associations between the epigenome and metagenome. We draw from multiomic studies on soil, plant, gut, and modern oral microbiomes to demonstrate how such integration can provide insights that are not attainable with single-omic approaches.

The taxonomic characterization of ancient microbiomes is a key step in the rapidly growing field of paleomicrobiology. While PCR amplification of the 16S ribosomal RNA (rRNA) gene is a widely used technique in modern microbiota studies, this method has systematic biases when applied to ancient microbial DNA. Shotgun metagenomic sequencing has proven to be the most effective method in reconstructing taxonomic profiles of ancient dental calculus samples. Nevertheless, shotgun sequencing approaches come with inherent limitations that could be addressed through hybridization enrichment capture. When employed together, shotgun sequencing and hybridization capture have the potential to enhance the characterization of ancient microbial communities. Here, we develop, test, and apply a hybridization enrichment capture technique to selectively target 16S rRNA gene fragments from the libraries of ancient dental calculus samples generated with shotgun techniques. We simulated data sets generated from hybridization enrichment capture, indicating that taxonomic identification of fragmented and damaged 16S rRNA gene sequences was feasible. Applying this enrichment approach to 15 previously published ancient calculus samples, we observed a 334-fold increase of ancient 16S rRNA gene fragments in the enriched samples when compared to unenriched libraries. Our results suggest that 16S hybridization capture is less prone to the effects of background contamination than 16S rRNA amplification, yielding a higher percentage of on-target recovery. While our enrichment technique detected low abundant and rare taxa within a given sample, these assignments may not achieve the same level of specificity as those achieved by unenriched methods.

Ancient DNA (aDNA) analysis of archaeological dental calculus has provided a wealth of insights into ancient health, demography and lifestyles. However, the workflow for ancient metagenomics is still evolving, raising concerns about reproducibility. Few systematic investigations have examined how DNA extraction methods and library preparation protocols influence ancient oral microbiome recovery, despite evidence from modern populations suggesting that they do. This leaves a gap in our understanding of how wet‐lab protocols impact aDNA recovery from dental calculus. In this study, we apply two DNA extraction and two library preparation methods in the aDNA field on dental calculus samples from Hungary and Niger. Samples from each context have similar chronological ages, but differences in their levels of aDNA preservation are notable, providing additional insights into how the efficacy of wet‐lab protocols is impacted by sample preservation. Several metrics were employed to assess intra‐ and inter‐sample variability, such as DNA fragment length recovery, GC content, clonality, endogenous content, DNA deamination and microbial composition. Our findings indicate that both DNA extraction and library preparation protocols can considerably impact ancient DNA recovery from archaeological dental calculus. Furthermore, no single protocol consistently outperformed the others across all assessments, and the effectiveness of specific protocol combinations depended on the preservation of the sample. These findings highlight the challenges of meta‐analyses and underscore the need to account for technical variability. Lastly, our study raises the question of whether the field should strive to standardise methods for comparability or optimise protocols based on sample preservation and specific research objectives.

Periodontal disease is a widespread chronic condition linked to systemic illnesses such as cardiovascular disease, diabetes, and adverse pregnancy outcomes. Despite its global burden, population-specific studies on its risk factors remain limited, particularly in Central and Eastern Europe. The SANA-biome Project is a cross-sectional, community-based study designed to investigate the biological and social determinants of periodontal disease in Romania, a country with disproportionately high oral disease rates and minimal microbiome data. This protocol will integrate metagenomic, proteomic, and metabolomic data of the oral microbiome from saliva and dental calculus samples with detailed sociodemographic and lifestyle data collected through a structured 44-question survey. This study is grounded in two complementary frameworks: the IMPEDE model, which conceptualizes inflammation as both a driver and a consequence of microbial dysbiosis, and Ecosocial Theory, which situates disease within social and structural contexts. Our aims are as follows: (1) to identify lifestyle and behavioral predictors of periodontal disease; (2) to characterize the oral microbiome in individuals with and without periodontal disease; and (3) to evaluate the predictive value of combined microbial and sociodemographic features using statistical and machine learning approaches. Power calculations based on pilot data indicate a target enrollment of 120 participants. This integrative approach will help disentangle the complex interplay between microbiological and structural determinants of periodontal disease and inform culturally relevant prevention strategies. By focusing on an underrepresented population, this work contributes to a more equitable and interdisciplinary model of oral health research and supports the development of future precision public health interventions.