Pathogens and host immunity in the ancient human oral cavity

Christina Warinner1,2, João F Matias Rodrigues3,4, Rounak Vyas3,4, Christian Trachsel5, Natallia Shved1, Jonas Grossmann5, Anita Radini6,7, Y Hancock8, Raul Y Tito2, Sarah Fiddyment6, Camilla Speller6, Jessica Hendy6, Sophy Charlton6, Hans Ulrich Luder9, Domingo C Salazar-García10–12, Elisabeth Eppler13,14, Roger Seiler1, Lars Hansen15,16, José Alfredo Samaniego Castruita17, Simon Barkow-Oesterreicher5, Kai Yik Teoh6, Christian D Kelstrup18, Jesper V Olsen18, Paolo Nanni5, Toshihisa Kawai19,20, Eske Willerslev17, Christian von Mering3,4, Cecil M Lewis Jr2, Matthew J Collins6, M Thomas P Gilbert17,21, Frank Rühli1,22 & Enrico Cappellini17,22

Calcified dental plaque (dental calculus) preserves for millennia and entraps biomolecules from all domains of life and viruses. We report the first, to our knowledge, high-resolution taxonomic and protein functional characterization of the ancient oral microbiome and demonstrate that the oral cavity has long served as a reservoir for bacteria implicated in both local and systemic disease. We characterize (i) the ancient oral microbiome in a diseased state, (ii) 40 opportunistic pathogens, (iii) ancient human–associated putative antibiotic resistance genes, (iv) a genome reconstruction of the periodontal pathogen Tannerella forsythia, (v) 239 bacterial and 43 human proteins, allowing confirmation of a long-term association between host immune factors, ‘red complex’ pathogens and periodontal disease, and (vi) DNA sequences matching dietary sources. Directly datable and nearly ubiquitous, dental calculus permits the simultaneous investigation of pathogen activity, host immunity and diet, thereby extending direct investigation of common diseases into the human evolutionary past.

Unlike other human microbiomes, the oral microbiome will cause

dental calculus using targeted PCR12, quantitative PCR (qPCR)11 disease in a majority of people during their lifetime, suggesting that it

and immunohistochemistry13. However, phylum-level community is currently in a state of dysbiosis rather than symbiosis1,2. The human

analysis and single-species targeted amplification are insufficient to oral microbiome comprises more than 2,000 bacterial taxa, including

characterize oral health and disease states, as this requires a deeper a large number of opportunistic pathogens involved in periodontal,

taxonomic and functional understanding of microbiome ecology14. respiratory, cardiovascular and systemic diseases3–7. Dental calculus, a

We present the first detailed analysis to our knowledge of ancient oral complex, calcified bacterial biofilm formed from dental plaque, saliva

microbiome ecology and function at the genus and species levels, leading and gingival crevicular fluid8, is emerging as a potential substrate for

to a deeper understanding of recent evolution of the human oral microbi- the direct investigation of the evolution of the oral microbiome and

ome. Focusing on the dental tissues of four adult human skeletons (G12, associated measures of oral health and diet9,10. Recently, a DNA-based

B17, B61 and B78) with evidence of mild to severe periodontal disease 16S rRNA phylotyping study identified the major bacterial phyla in

from the medieval monastic site of Dalheim, Germany (c. 950–1200 CE) dental calculus and argued for shifts in microbial diversity associated

(Supplementary Fig. 1), as well as modern dental calculus from nine with the origins of agriculture and industrialization11, and, so far, five

individuals with known dental histories, we demonstrate for the first time, common oral bacteria have been identified in historic and prehistoric

to our knowledge, that the human oral microbiome has long served as a

1Centre for Evolutionary Medicine, Institute of Anatomy, University of Zürich, Zürich, Switzerland. 2Department of Anthropology, University of Oklahoma, Norman, Oklahoma, USA. 3Institute of Molecular Life Sciences, University of Zürich, Zürich, Switzerland. 4Swiss Institute of Bioinformatics, Lausanne, Switzerland. 5Functional Genomics Center Zürich, University of Zürich/Swiss Federal Institute of Technology (ETH) Zürich, Zürich, Switzerland. 6BioArCh, Department of Archaeology, University of York, York, UK. 7University of Leicester Archaeological Services (ULAS), School of Archaeology and Ancient History, University of Leicester, Leicester, UK. 8Department of Physics, University of York, York, UK. 9Centre of Dental Medicine, Institute of Oral Biology, University of Zürich, Zürich, Switzerland. 10Research Group on Plant Foods in Hominin Dietary Ecology, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany. 11Department of Human Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany. 12Department of Prehistory and Archaeology, University of Valencia, Valencia, Spain. 13Research Group Neuro-Endocrine-Immune Interactions, Institute of Anatomy, University of Zürich, Zürich, Switzerland. 14Zürich Center for Integrative Human Physiology, University of Zürich, Zürich, Switzerland. 15Department of Biology, Microbiology, University of Copenhagen, Copenhagen, Denmark. 16Department of Environmental Science, Aarhus Universitet, Roskilde, Denmark. 17Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Copenhagen, Denmark. 18Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. 19Department of Immunology and Infectious Diseases, Forsyth Institute, Cambridge, Massachusetts, USA. 20Department of Oral Medicine, Infection and Immunity, Harvard School of Dental Medicine, Harvard University, Boston, Massachusetts, USA. 21Ancient DNA Laboratory, Murdoch University, Perth, Western Australia, Australia. 22These authors jointly directed this work. Correspondence should be addressed to C.W. ( or E.C. (

Received 31 May 2013; accepted 3 February 2014; published online 23 February 2014; doi:10.1038/ng.2906



reservoir for a broad suite of opportunistic pathogens implicated in both local and systemic disease and harbored a diverse range of putative anti- biotic resistance genes. We confirm the long-term role of host immune activity and red complex pathogen virulence in periodontal pathogenesis, despite major changes in lifestyle, hygiene and diet over the past millen- nium. We reconstruct the genome of a major periodontal pathogen and present the first evidence, to our knowledge, of dietary biomolecules to be recovered from ancient dental calculus. Finally, we further validate our findings by applying multiple microscopic, genetic and proteomic analy- ses in parallel, providing a systematic biomolecular evaluation of ancient dental calculus preservation, taphonomy and contamination.

RESULTS The ancient oral microbiome Applying shotgun DNA sequencing to dental calculus for the first time, we found that it was strongly dominated by bacterial DNA, with minor contributions from human, viral, dietary and fungal sources (Fig. 1a). Using both targeted and shotgun 16S rRNA sequences (n = 509,067), we identified a total of 2,699 microbial operational taxonomic units (OTUs) in the ancient dental calculus, with the 100 most abundant taxa accounting for 86.6% of the total reads (Fig. 1b and Supplementary Fig. 2). One archaeal and nine bacterial phyla were dominant in ancient dental calculus (Supplementary Table 1): Firmicutes (49.5 ± 10.6%), Actinobacteria (12.0 ± 6.1%), Proteobacteria (11.5 ± 8.6%), Bacteroidetes (6.6 ± 3.6%), TM7 (4.6 ± 4.0%), Synergistetes (3.3 ± 2.6%), Chloroflexi (2.7 ± 1.5%), Fusobacteria (2.1 ± 1.8%), Spirochetes (0.6 ± 0.3%) and Euryarchaeota (0.4 ± 0.6%), all of which are also dominant in the human oral microbiome today4. Notably rare in ancient dental calculus was Acidobacteria, a ubiqui- tous and abundant bacterial phylum in soil15.

To address biases resulting from the sequencing approach and the 16S rRNA gene hypervariable region (V3, V5, V6) primer choice (Supplementary Fig. 3), we visualized evidence for each OTU sepa- rately for each targeted and shotgun 16S rRNA detection method, as well as for shotgun metagenomic and metaproteomic data (Fig. 1b). Most OTUs were detected using multiple methods. OTUs detected from targeted V3 and shotgun data generally showed good agree- ment, whereas V5 and V6 primers showed clear evidence of primer bias and OTU dropout. Shotgun metagenomic data showed excel- lent agreement with consensus 16S rRNA OTUs when reference genomes were available. Shotgun metaproteomic data also showed good agreement with the OTUs identified on the basis of genetic data, and agreement is expected to improve as protein databases grow to include more predicted proteins and epigenetic variants. Because ancient DNA and proteins undergo different taphonomic processes and have different contamination risks, the high degree of



Figure 1 Taxonomic and phylogenetic characterization of ancient dental calculus. (a) Relative proportions of bacterial, archaeal, eukaryotic and viral DNA in ancient calculus estimated from assembled whole-metagenome shotgun sequences of two individuals. (b) Phylogenetic tree of the 100 most abundant OTUs in ancient dental calculus samples from 4 pooled individuals. Evidence for the presence and abundance of each microbial OTU is represented by colored, size-scaled circles for each targeted 16S rRNA hypervariable region (V3, V5, V6), shotgun 16S rRNA sequences (S) and other genes (G) and proteins (P) assigned to that OTU. OTUs for which no reference genome exists or for which insufficient proteome data have been validated for inclusion in the protein search databases are marked with gray squares, as no hits could be matched to those OTUs. The tree scale bar indicates nucleotide substitutions per site. Relative phylum abundance (normalized mean of all genetic data generated from 16S rRNA sequences) is represented by a column chart showing the phyla represented in the top 100 OTUs (colored), remaining phyla (dark gray) and unidentified OTUs (light gray).

0.002% other 0.002% animal 0.005% fungi 0.008% plant 0.062% virus 0.068% archaea 0.529% human

99.3% bacteria

0.7% other
























s e t e id o r e t c a


7 M T

ia r e t c a b o e t o r P

a i r e t c a b o n i t c A


Chloroflexi Spirochetes


s e t u c i m r i F


phylogenetic consensus observed for data generated from independ- ent extractions, using different methods and targeting different bio- molecular types, demonstrates that an endogenous oral microbiome can be robustly and reliably recovered from ancient dental calculus.

Carriage of specific pathogens The normal human oral flora includes a large number of endogenous cariogenic, periodontal and other opportunistic pathogens. Although these taxa generally do not cause extraoral disease in healthy subjects, they nevertheless pose a serious risk for the elderly and immunocom- promised16,17 and are known to be involved in the etiology of chronic systemic diseases, including cardiovascular disease18. As the detection of particular species from metagenomic sequence data is an open area of research, we applied a conservative contig assembly and BLAST strategy and screened our results against the Pathosystems Resource



Integration Center (PATRIC) database19 to

table 1 Putative pathogens identified from assembled metagenomic and metaproteomic identify 40 putative opportunistic patho-

sequences in ancient dental calculus gens in ancient dental calculus (Table 1), of which only 5 had been previously reported

Pathogensa in ancient samples11–13. We also identified phage DNA sequences specific to particular bacteria (Table 1), including Streptococcus mitis phage SM1, which has been previously shown to mediate S. mitis attachment to platelets and to increase bacterial virulence in the endocardium20.

Both DNA and proteins from the perio- dontal pathogens T. forsythia, Porphyromonas gingivalis and Treponema denticola were particularly abundant in our ancient den- tal calculus samples, demonstrating that these so-called red complex bacteria21 were strongly associated with periodontal disease during the medieval period, just as they are today, despite substantial changes in oral hygiene, diet and lifestyle. Additionally, all three of these pathogens were found at substantially higher frequency in our ancient dental calculus samples than in the Human Microbiome Project (HMP)3 healthy cohort (Supplementary Fig. 4a–c and Supplementary Table 2), consistent with expectations for periodontal disease. We also identified several oral taxa (for exam- ple, Aggregatibacter actinomycetemcomitans, Streptococcus mutans and S. mitis) that have been shown to cause bacteremia and infec- tive endocarditis7,18, demonstrating that the human oral microbiome has long harbored pathogens that contribute to risk of cardio- vascular disease. Additional pathogens included those implicated in acute dental infections (for example, Actinomyces odonto- lyticus), caries (S. mutans) and opportunistic upper and lower respiratory illness (for exam- ple, Streptococcus pneumoniae, Streptococcus pyogenes and Haemophilus influenzae). Of interest, all ancient dental calculus samples were also found to contain disordered carbon (microcharcoal), a respiratory irritant. Two obligate human taxa, Neisseria meningitidis and Neisseria gonorrhoeae, causative agents of bacterial meningitis and gonorrhea, respec- tively, were also observed. N. meningitidis and N. gonorrhoeae form a recently diverged pathogenic clade of Neisseria, a genus comprising many commensal species inhabiting the mucosa and dental surfaces of animals22, and both are prevalent members of the human oral microbiome. Genital N. gonorrhoeae strains can infect the pharynx and engage in genetic exchange with other Neisseria species;23 however, oral strains are not known to cause genital infection. Oral N. meningitidis is a lead- ing cause of bacterial meningitis, although disease susceptibility is determined by a combination of host genetics and strain virulence24. Finally, we observed two additional oral taxa present at substantially higher frequency in at least one ancient dental calculus sample com- pared to the HMP healthy cohort: Filifactor alocis and Olsenella uli

Genes (contigs)

Proteins (peptides) Virulence

Drug resistanceb Plasmid

CTn or phage

Actinomyces odontolyticusc 3 (4) 3 (34) Aggregatibacter


50 (68) 0 + +

Campylobacter concisus 10 (20) 0 + Campylobacter curvus 12 (11) 0 Campylobacter rectusc 3 (9) 3 (15) ++ Campylobacter showaec 3 (13) 1 (2) Capnocytophaga gingivalisc 2 (11) 3 (7) + Capnocytophaga ochracea 938 (4,909) 0 + + + + Capnocytophaga sputigenac 2 (2) 0 + Clostridium difficiled,e 30 (76) 0 + + Corynebacterium matruchotiic 2 (15) 12 (89) Eikenella corrodensc 11 (38) 2 (11) + Fusobacterium nucleatum 656 (1,525) 4 (21) ++ + + + Fusobacterium periodonticumc 3 (6) 3 (8) + Gemella morbillorumc 9 (38) 0 Gordonibacter pamelaed 3 (30) 0 Haemophilus influenzae 19 (43) 1 (4) + Histophilus somnid,f 9 (18) 0 + Leptotrichia buccalis 492 (1,104) 0 + + + + Neisseria gonorrhoeae 127 (250) 1 (2) + + Neisseria meningitidis 336 (821) 1 (2) + + + Neisseria siccac 3 (8) 4 (35) Neisseria subflavac 4 (12) 0 Porphyromonas gingivalis 802 (2,588) 7 (72) ++ + + Rothia mucilaginosa 24 (17) 1 (2) + Streptobacillus moniliformisd,f 8 (23) 0 Streptococcus agalactiae 7 (27) 0 + + Streptococcus dysgalactiaed 2 (8) 0 + Streptococcus equid,f 29 (101) 0 + + Streptococcus gallolyticusd,f 8 (11) 0 + Streptococcus gordonii 882 (3,397) 1 (8) + + + + Streptococcus mitis 88 (161) 1 (37) ++ + + Streptococcus mutans 21 (67) 0 Streptococcus pneumoniae 144 (339) 1 (8) + + + Streptococcus pyogenes 14 (32) 1 (8) + + Streptococcus sanguinis 850 (3,272) 1 (4) + + Streptococcus suisd,f 2 (3) 0 + Tannerella forsythia 1,099 (11,279) 10 (137) ++ + + Treponema denticola 917 (6,106) 3 (15) ++ + + + Veillonella parvula 96 (109) 0 +

Metagenomic data from G12 and B61 and proteomic data from G12, B17, B61 and B78. +, gene(s) detected; ++, gene(s) and protein(s) detected. aIncludes only pathogens with valid entries in the PATRIC database. Only taxa represented by more than one DNA contig are shown. All pathogens are known inhabitants of the human oral cavity, as confirmed by cross-referencing with HMP data for supragingival dental plaque. bPutative function based on gene homology and NCBI annotation; functionality was not independently validated. cReference genome sequencing and annotation incomplete. dNot a prevalent inhabitant of the oral cavity; not present in the Human Oral Microbiome Database (HOMD). eTentative identification; sequences correspond almost exclusively to mobile genetic elements. fPutative zoonosis.

(Supplementary Fig. 4e,f). Although not classified as pathogens in the PATRIC database, these bacteria have recently been associated with periodontitis and endodontic infections, respectively25,26.

Virulence To further characterize the pathogens detected in ancient human dental calculus, we compared information on the functional features of putative genes and proteins associated with virulence, drug resist- ance, plasmids, transposons and phages to the information available in NCBI records. Although not exhaustive, a preliminary list of well- supported virulence-associated genes and proteins was compiled





b 0 4,092





using this method (Table 1 and Supplementary Table 3), show- ing a wide range of virulence factors associated with adhesion and aggregation (for example, adhesins and lectins) and parasitism (for example, phospholipases, hemagglutinins and hemolysins), as well as extensive machinery for horizontal gene transfer (for example, pilin, CTn and phage sequences). In several cases, we detected both the virulence-associated gene and its protein product, for example, Msp and major sheath protein in T. denticola and Rgp and Arg-gingipain in P. gingivalis. Arg-gingipain and Lys-gingipain, another extracellular cysteine proteinase identified by proteomic evidence, are highly anti- genic and extremely abundant in P. gingivalis, accounting for 10% of the total protein produced by the organism27. Notably, we also detected type IV fimbrilin, an outer membrane protein variant associ- ated with virulent P. gingivalis strains28.

Antibiotic resistance The human microbiome is an important site of horizontal gene transfer and a potential reservoir of antimicrobial resistance29. Metagenomic studies of modern dental plaque have found a wide range of predicted genes related to resistance to diverse antibiotics and toxic compounds30. The antiquity of bacterial antibiotic resist- ance genes has recently been tested in permafrost soils dating to the Pleistocene31, but, until now, the antiquity of antibiotic resistance in human microbiota before the use of therapeutic antibiotics had not been investigated.

Using both automated and manual search strategies, we identi- fied within ancient dental calculus numerous DNA sequences with homology to antibiotic resistance genes found in oral and pathogenic bacteria, including genes for multidrug efflux pumps and native resist- ance genes to aminoglycosides, β-lactams, bacitracin, bacteriocins

TF2663, tfsB


mgsA dppIV

TF2663, tfsB* TF2661-62, tfsA*








0 TF2663, tfsB



TF2417 TF2381 phg TF2339*

tra island

rteC tetQ siaHI

gdhA TF2116




Coverage 100% identity BspA

97% identity


95% identity

Figure 2 Genomic coverage plot for the periodontal pathogen T. forsythia, with details of gene and protein coverage of the virulence factor TF2663, tfsB, from medieval human dental calculus (G12). (a) Plot of the T. forsythia genome with depth of coverage (0- to 30-fold) shown in red and identity shown in purple. Gene locations of the major virulence factors present (black) or absent (gray) in the assembly are indicated in the outer ring. Notably absent are two transposon-related tra pathogenicity islands containing putative tetracycline resistance genes in the T. forsythia ATCC 43037 reference strain. Proteins identified by MS/MS are indicated in blue by an asterisk at the corresponding gene locus. (b) Enlarged view of forward (blue) and reverse (red) DNA reads mapped to gene TF2663, which encodes the surface layer B protein tfsB. (c) Enlarged view of peptide coverage for tfsB, a species-diagnostic virulence factor involved in hemagglutination, adherence and host tissue invasion. (d) Example of a tandem mass spectrum indicating the measured mass-to-charge ratios (m/z) of the fragments supporting the identification of the tfsB peptide VSIDPDLYLIR (arrowhead in c).

and macrolides, among others, as well as a near-complete plasmid- encoded conjugative transposon carrying efflux pump genes with high homology to CTn5 of Clostridium difficile (Supplementary Table 4). Although the exact function of these genes in our samples is unclear, their presence nevertheless demonstrates that the biomo- lecular machinery for broad-spectrum, low-level antibiotic resistance has long been present in the human microbiome, illustrating how the oral microbiome functions as both a source and a reservoir of new antibiotic resistance23.

Pathogen genome reconstruction: T. forsythia T. forsythia (formerly Bacteroides forsythus and Tannerella forsythensis) is an anaerobic, Gram-negative member of the phylum Bacteroidetes and is a known inhabitant of supragingival and subgingival plaque32. It is associated with advanced forms of periodontal disease and has been reported in atherosclerotic lesions7. On the basis of 16S rRNA gene data, T. forsythia was observed to be at moderate abundance (0.09–0.84%) in the dental calculus of one individual (G12) and, as a pathogen of interest, was selected for genome reconstruction.

Using a conservative mapping strategy, a total of 10,991 contigs were recruited to the ancient T. forsythia genome reconstruction, at a mean nucleotide depth of coverage of 5.7 (Fig. 2a). Ninety-one percent of T. forsythia genes (n = 2,799) were mapped by at least one contig, and unmapped genes included 94 transposases, transfer factors and other mobilization genes that may be specific to the T. forsythia ATCC 43037 reference genome strain used for alignment. The largest gap in our genome reconstruction, which spanned ~48,000 bp and 53 genes, corresponded to a complete conjugative transposon carrying putative tetracycline resistance genes that was absent in our reconstructed ancient T. forsythia genome. In addition to genetic sequences, tandem





ampC BspA



oxyR hexA


3,200 kb 3,400 kb

200 kb



3,000 kb

400 kb


2,800 kb

600 kb

2,600 kb

Tannerella forsythia

800 kb


3.4 Mb

2,400 kb

1,000 kb

rteC tra island

2,200 kb

1,200 kb

2,000 kb

1,400 kb

1,800 kb

1,600 kb *





TF1331, omp41*


BspA TF1458 TF1439









H (parent error: 4.7 ppm)

1,302.72 AMU,

) % ( y t i s n e t in e iv t a l e

0 250 500 750 1,000 1,250 m/z












b2 b3








Figure 3 Metaproteomic comparison of human

a proteins in modern and ancient dental samples. (a) Functional characterization of human proteins identified in modern dental calculus (two individuals), ancient dental calculus (four individuals) and ancient tooth roots (four individuals). (b) Venn diagram of shared

Modern calculus

human proteins by sample type. (c) STRING network representation of human proteins


identified in ancient dental calculus; nodes are labeled by protein name and colored in accordance with functional categories and connections (gray) to predicted functional

Modern calculus partners. The network is set to medium confidence (0.4) for all active prediction methods. (d) Gene ontology categories

Ancient tooth root with significant enrichment (P < 0.001, FDR-corrected) in ancient dental calculus

c for biological processes (black) and molecular functions (white) related to

SERPINB4 proteinase regulation, substrate binding and innate immune function. Enrichment is calculated relative to the human genome


SERPINB10 SERPINB8 using the STRING-embedded AmiGO term enrichment tool.


mass spectrometry (MS/MS) identified 118 peptides belonging to 10 T. forsythia proteins (Fig. 2a). Of these proteins, nine were outer membrane or S-layer proteins, seven had a known function, and four were antigenic: T. forsythia surface protein A (TF2661-2, tfsA), T. forsythia surface protein B (TF2663, tfsB), outer membrane protein 41 (TF1331, omp41) and one hypothetical protein (TF2339)33.

Several virulence factors and antigenic proteins have been identified in T. forsythia (Fig. 2a), including Bacteroides surface protein A (BspA), dipeptidyl peptidase-4 (dppIV), tfsA and tfsB, among others27,33. The genes encoding each of these virulence factors were present in our reconstruction. The glycosylated T. forsythia S-layer proteins tfsA and tfsB are directly involved in hemagglutination, adhesion and tissue invasion34. They are also unique and are species diagnostic, as they have no homology to other known S-layer proteins or glycoproteins35. DNA and protein coverage of tfsA and tfsB was high in our data set; for example, 10 contigs comprising 116 reads mapped to the TF2663 (tfsB) gene (Fig. 2b), and we identified 65 spectra belonging to 27 unique tfsB peptides (Fig. 2c,d). Given that functional T. forsythia S-layer protein is essential for host immune evasion and biofilm coaggregation34, the dis- covery of abundant, well-preserved S-layer gene and protein sequences makes ancient dental calculus an excellent candidate for investigating the evolution of periodontal pathogenesis in humans.

MS/MS analysis of host immunity and disease pathogenesis Despite dense microbial colonization and the regular introduction of foreign substances, the oral cavity is effective at preventing most infections. At least 45 antimicrobial gene products acting as early responders of the innate immune system have been identified in saliva and gingival crevicular fluid36. We identified 43 human proteins within ancient dental calculus, of which 25 are involved in the innate immune system (Fig. 3a). Eight of these proteins have demonstrated antimicrobial properties and include cationic peptides (α-defensin and azurocidin), metal ion chelators (calgranulin A, calgranulin B and lactoferrin), protease inhibitors (myeloperoxidase) and bacteri- cidal proteins (bactericidal permeability-increasing protein, lysozyme C and peptidoglycan recognition protein 1). Expression of many of these proteins is specific to a particular cell type and even a particular

subcellular component (for example, azurocidin is specific to neu- trophil lysozomic azurophilic granules), allowing highly resolved char- acterization of the immune system response. Approximately one-third of the identified human proteins were shared by ancient and modern calculus (Fig. 3b), and functional profiles were highly similar (Fig. 3a). In contrast, ancient tooth roots were distinct, both in protein com- position and function and being dominated by collagens and other proteins involved in mineralized tissue (biglycan, periostin) and vas- cular (prothrombin) development and maintenance.

The STRING resource37 was used to investigate functional inter- action networks among the human proteins in ancient dental cal- culus. A large number of functional interactions were predicted (Fig. 3c), and 79% of proteins (n = 34) were functionally connected to at least one other protein in the network. Immunoglobulin heavy chain (IgA and IgG) and light chain (kappa) peptides were detected in ancient calculus, as was α-amylase, a salivary enzyme that breaks down dietary starch; however, the majority of proteins were related to the innate immune system. Human proteins in ancient dental calculus were strongly enriched in extracellular (P value of 3.2 × 10−12, false discovery rate (FDR)-corrected) and secretory (P value of 4.3 × 10−9, FDR-corrected) proteins, mostly of neutrophilic origin. Extravasated neutrophils are recruited to sites of injury by IgG and have a life span of less than 24 h38; thus, neutrophil proteins are only released into calcifying dental plaques during active infection and inflammation. Relatively few human cellular proteins were found, suggesting that immune cells do not invade the calcifying plaque but rather release antimicrobial substances from the junctional and pocket epithelia, a process that is consistent with neutrophil ‘frustrated phagocytosis’ (ref. 39) and NETosis40. Human proteins in ancient calculus were significantly enriched in biological processes related to inflammation, innate immunity and host defense, as well as in molecular functions such as cell surface, protease and glycosaminoglycan binding (Fig. 3d). The observation of an abundance of inflammatory (myeloperoxidase, azurocidin, lysozyme, calprotectin and elastase) and anti-inflammatory (α-1-antitrypsin and α-1-antichymotrypsin) innate immune system








Ancient tooth root

19 18


5 1 0


Ancient calculus













Ancient calculus













P d (FDR-corrected)




8 6 4 2 0

Negative regulation of endopeptidase activity Negative regulation of peptidase activity Response to bacterium Regulation of proteolysis Negative regulation of hydrolase activity Regulation of endopeptidase activity Response to biotic stimulus Regulation of peptidase activity GGH

Response to other organism Cell surface binding Defense response to bacterium Glycosaminoglycan binding Protease binding Polysaccharide binding Pattern binding Defense response


Heparin binding Acute inflammatory response Negative regulation of catalytic activity Immune system process

Innate immune system Adaptive immune system Blood coagulation Digestion Structure and support Other





Sus verrucosus GQ338936.1*

proteins in ancient dental calculus, coupled with morphological evi- dence of attachment loss and alveolar recession, is strongly supportive of active periodontal inflammation and disease.

In addition to this host immunological data, we identified oral patho- gens and bacterial virulence proteins in ancient and modern dental calculus known to provoke strong immunological reaction and to con- tribute to periodontal pathogenesis (Supplementary Table 3), most notably P. gingivalis (gingipains), T. forsythia (S-layer proteins) and T. denticola (major sheath protein). P. gingivalis has recently been shown to stimulate neutrophils to release resistin, a protein implicated in acquired insulin resistance41. Resistin may exacerbate the progres- sion of type 2 diabetes42, and, interestingly, we identified resistin on the basis of reasonably abundant evidence (36 spectra, 9 unique peptides) in ancient dental calculus. Resistin was also identified in modern calculus (seven spectra, five unique peptides) but not in ancient tooth roots.

Ancient dietary reconstruction Given current challenges in nutritional health and obesity43, a growing interest in dietary aspects of the hygiene hypothesis44 and a recent study suggesting shifts in the ancient oral microbiome associated with periods

Ovis sp., chromosome X, microsatellite, E value 2.0 × 10


Sus sp., mtDNA, 12S rRNA, E value 5.0 × 10


Brassica sp., mtDNA, intergenic, E value 3.0 × 10

e f

g h

j k

Cervidae, n = 4*

Mystacina tuberculata, n = 2*

Monodon monoceros AJ554062.1*

Platanista minor AJ554058.1*

Sylvisorex lunaris AY691816.1*

Ovis aries U62384.1 Capra hircus Y11529.1*

Hippotragus equinus AF285415.1

G12 dental calculus NODE 2850554

Delphinidae, n = 94*

Ovis sp. X01839.1*

Capra hircus X57335.1*

Capra hircus X98875.1

Lemur catta, n = 3*

Capra hircus AB591529.1

Physeter macrocephalus AJ27709.2*

Uropsilus gracilus JX034737.1*

G12 calculus HWI-ST575:67:C03NFABXX:7: 1203:18844:163366

Capra hircus X74986.1

Budorcas taxicolor, n = 3* Ovis aries Z17215.1* Ovis sp. X00434.1*

Ovis aries X96874.1*

Ovis canadensis X56076.1* Ovis amon X96873.1*

Ovis aries U24090.1*

Episoriculus Babyrousa babyrussa macrurus, GQ338943.1*

n = 2*

Potamochoerus spp., n = 3* Hylochoerus meinertzhageni GQ338941.1* Phacochoerus africanus, n = 2*

Ovis dalli X59242.1*

Sus scrofa DQ867008.1*

Ovis aries U24089.1* Ovis aries Z18528.1*



Mysticeti, n = 11*

Ovis aries U10122.1*

Ovis aries Z18540.1* Ovis aries U25964.1*

Porcula sativa, n = 3*



Sus scrofa AF034253.1*

Sus scrofa DQ466081.2*

Sus scrofa, n = 108*


Iron 12



–22 –18 δ

Ovis aries Z18541.1*

Sus celebensis GQ338937.1*

Sus barbatus GQ338935.1*


Early medieval




Vitis vinifera AM484255.1

Raphanus sativus AB694743.1*

Raphanus sativus AB694744.1*

Brassica rapa AC172860.1*


Triticum aestivum, Total E value score 9 ×10

147; –33

query ; mtDNA, intergenic

coverage 100%; maximum identity 100%

Brassica carinata JF920287.1*

total score of next best hit 41

Triticum aestivum EU534409.1 Brassica napus AP006444.1*

Brassica napus FR715249.1*

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Brassica rapa JF920285.1*

Triticum aestivum EU534409.1 Triticum aestivum AP008982.1

Brassica juncea JF920288.1*

G12 dental calculus HWI-St575:67: C03NFABXX:7:2201:14733:93454 Brassica oleracea JF920286.1*

G12 dental calculus, HWI-ST575:68:

Triticum aestivum EU534409.1 Triticum aestivum AP008982.1 C03NFABXX:7:2106:18963:47488

G12 dental calculus HWI-St575:67: C03NFABXX:7:2201:14733:93454

Figure 4 Genetic, microfossil, zooarcheological and stable isotopic evidence for the medieval human diet at Dalheim, Germany. (a–c) Neighbor- joining trees for GenBank sequences aligning to putative dietary sheep (a), crucifer (b) and pig or boar (c) sequences. Trees include accessions with alignment scores of >45, except for c, which is limited to the top 250 alignments; highly significant alignments (E value < 1 × 10−30) are indicated with an asterisk. BLAST top hits for each dietary sequence are highlighted. The maximum fraction of mismatched bases is 0.75 for tree generation, and distance was calculated using a Jukes-Cantor substitution model. Tree scale bars indicate nucleotide substitutions per site. mtDNA, mitochondrial DNA. (d) One sequence aligned to two accessions of bread wheat only. (e–h) The microfossils recovered from ancient human dental calculus yielded morphological matches to animal collagen fibers (e), a smooth long-cell phytolith (f) and starch granules of the grass tribe Triticeae (g) and the legume family Fabaceae (h). Characteristic starch granule birefringence is shown under polarized light in the insets in g,h. Scale bars, 50 μm in e, 25 μm in f–h. (i) C and N stable isotopic values for human bone collagen (black circles) fall within 2 s.d. (boxes) of those measured for other Central European populations and are consistent with a diet of mixed C


terrestrial plant and animal resources. Isotopic values are reported in delta notation: δ15N = (15N/14N)




− 1, with the air (AIR) standard; δ13C = (13C/12C)




− 1, with the Vienna Pee Dee Belemnite (VPDB) standard. (j,k) Recovered food waste includes skeletal material from Sus species (j) and Caprinae (k).

of agricultural transition11, there is great interest in better understand- ing the evolutionary history of the human diet. However, paleodietary reconstruction is made difficult by the generally poor preservation of plants and small animals in the archaeological record. Stable isotope analysis of human bone and dental calculus–based plant microfossil research have broadened our knowledge of past dietary practices, but these tools are insufficient to characterize many major dietary compo- nents at high taxonomic resolution. Ancient DNA–based approaches offer great advantages and have been used to identify dietary compo- nents from archaeological feces (coprolites), as well as to investigate plant remains directly45. However, as coprolites and preserved plant remains are relatively rare, we sought to characterize dietary information from dental calculus using both biomolecular and conventional methods.

From our metagenomic sequence reads, a total of 487 reads (0.0003%) were confidently identified as eukaryotic organelle sequences; of these, 266 were assigned to the kingdom Viridiplantae, and 21 were assigned to the kingdom Animalia. Within these kingdoms, most of the organelle reads mapped ambiguously to multiple organisms or genera, leaving only 20 reads that could be positively identified at a subfamily level. Of these 20 reads, 17 were of host origin, and the remaining 3 reads



matched diagnostic mitochondrial sequences for pig/boar (Sus spe- cies), crucifer (Brassica species) and bread wheat (Triticum aestivum). Analysis of assembled contigs additionally identified one putative sheep (Ovis species) and several human (n = 326) nuclear genomic sequences (Fig. 4a–d). Although previous studies have reported trace animal domesticate DNA contamination (from cattle, pig and chicken) in some PCR reagents46, we found no evidence of such contamination, and addi- tionally wheat, crucifers and sheep are not part of this supply chain. The discovery of preserved dietary biomolecules is consistent with previous observations of intact dietary microfossils, such as starch granules, in archaeological dental calculus10 and with reports of wheat and cas- sava (tapioca) chloroplast DNA in the dental plaque of living subjects4. Turning to proteins, we identified one putative dietary plant protein, chloroplast glyceraldehyde 3-phosphate dehydrogenase (GAPDH), in ancient calculus, but disambiguation below the phylum Viridiplantae was not possible. Faunal proteins were not confidently identified within ancient dental calculus, but we did identify bovine β-lactoglobulin, a milk protein, in modern dental calculus, demonstrating that recovery of dietary animal proteins from dental calculus is possible.

Because our discovery of dietary biomolecules in dental calculus is new, we sought to validate our results using independent paleodietary

methods. Microfossil analysis of ancient dental calculus yielded mor- phological matches to animal connective tissue fragments (n = 2; Fig. 4e), an unidentified monocot phytolith (Fig. 4f), plant bast fibers (n = 3) and starch granules consistent with the cereal tribe Triticeae (n = 27; Fig. 4g) and the legume family Fabaceae (n = 1; Fig. 4h), among other debris (Supplementary Fig. 5). Stable isotope analysis of human bone collagen (Fig. 4i) from the four ancient human individuals indicated a mixed diet of C


terrestrial plant and animal resources typical of Central European populations from the late Mesolithic through the medieval period47–50. Zooarcheological analysis of food waste at the site confirmed the presence of pig or boar (Sus species; Fig. 4j) and sheep or goat (Caprinae; Fig. 4k), as well as cattle (Bos species) and equids (Equus species).

Biomolecular analysis of dental calculus thus yields complementary dietary information compared to conventional methods, as well as new findings. The high taxonomic precision of genetic approaches allows closely related taxa (for example, Caprinae) to be distinguished in the absence of diagnostic skeletal elements, and underrepresented plant taxa, such as Brassica, can be identified without the biological and taphonomic biases that compromise macro- and microfossil pres- ervation of leafy greens and vegetables.

Figure 5 Evidence of microscopic and biomolecular preservation of ancient dental calculus. (a) Labiolingual section of a mandibular incisor with dental calculus (arrow) on the labial crown surface; both dentine and cementum within the tooth root show extensive evidence of postmortem alteration. Scale bar, 2 mm. (b) EDS visualization of calcium (red) and silicon (green) shows that silicon is restricted to the surface except for one biogenic silicon inclusion (arrow). Scale bar, 200 μm. (c) Detail of dental calculus, which exhibits a layered structure suggesting outward-downward incremental growth. Scale bar, 100 μm. (d) Detail of a stained section showing Gram-negative (red) and Gram-positive (blue) bacteria. Scale bar, 10 μm. (e) Detail of a Hoechst-stained section showing abundant in situ double-stranded DNA. Scale bar, 20 μm. (f) Detail of the calculus matrix containing numerous lacunae of filamentous microorganisms (arrow), some of which are mineralized (arrowhead). (g) In another area, the matrix contains both unmineralized (arrow) and mineralized (arrowhead) lacunae of microorganisms resembling cocci. Scale bars, 5 μm. (h) Proportions of human and bacterial proteins identified in ancient and modern samples. (i) DNA extraction yields from modern (M) and ancient dental calculus (red), dentine (blue and orange) and alveolar bone samples (yellow). (j) Comparison of microbial communities in ancient dental samples (squares) to those in diverse publicly available samples (circles). 16S rRNA data were generated by shotgun sequencing (S) and targeted amplification and sequencing of hypervariable regions (V3, V5, V6), followed by OTU clustering. Ancient metagenomes (n = 38) were plotted within a network where distance scales with OTU community similarity. Modern metagenomes with >20% shared community are shown connected by black lines, and ancient metagenomes with >20% shared community are connected by green lines. A total of 315 GenBank studies were recruited to the network. Ancient metagenomes segregate into two distinct groups: ancient dental calculus samples cluster tightly together, are connected by thick lines and show similarity to modern metagenomes of primarily human and oral origin, and ancient dentine and abscessed bone tissue samples form a more diffuse cluster and recruit primarily soil and environmental metagenomes. Carious dentine forms an intermediate cluster that shares OTUs with both human-associated and environmental sources.


a b


c f



3S S S S 5

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d Healthy tooth

Diseased tooth

Targeted 16S rRNA

3 = V3 region 5 = V5 region 6 = V6 region S = Shotgun sequencing

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s n i e t o r p d e fi i t n e d I






n o c

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Taphonomy and contamination Postmortem taphonomy and contamination pose challenges in ancient biomolecular research. To address these potential problems in our data set, we employed multiple protocols for authenticating our data, including scanning electron microscopy (SEM), energy- dispersive X-ray spectroscopy (EDS), optical microscopy, Raman spectroscopy, protein damage analysis, genetic network analysis and probabilistic genetic source tracking.

After death, environmental microbes are known to infiltrate the dentition, causing substantial tissue degradation, loss of organic matter and altered mineralization patterns in dentine and cementum (Supplementary Fig. 6)51. We observed, however, little evidence of postmortem alteration in ancient dental calculus samples (Fig. 5a). EDS imaging showed a thin deposit of silicon-rich soil matrix only on the dental calculus surface (Fig. 5b), and no evidence of altered min- eralization was observed within ancient dental calculus, a finding that we confirmed by Raman spectroscopic comparison with modern con- trols (Supplementary Fig. 7). During life, growth of dental calculus is appositional8,52, resulting in a laminar cross-sectional structure char- acterized by alternating bands of Gram-positive and Gram-negative bacteria (Supplementary Fig. 8), a pattern we also observed in ancient calculus (Fig. 5c,d). DNA fluorescent dye showed a similar distri- bution of double-stranded DNA in ancient and modern calculus, in many cases resolving to individual cells (Fig. 5e and Supplementary Fig. 9) corresponding to a diverse range of in situ bacteria embedded within undisturbed dental calculus matrix (Fig. 5f,g).

Ancient dental calculus yielded microbial (n = 239) and human (n = 43) proteins in the same relative proportion and with similar functions as in modern controls (Figs. 3a and 5h, and Supplementary Fig. 10), whereas only human proteins (n = 53) were confidently iden- tified from tooth roots and bone. Damage analysis of dental calculus proteins showed a higher proportion of spontaneous, non-enzymatic post-translational modifications in ancient samples compared to modern controls; however, both modern and ancient dental calculus peptides exhibited relatively high proportions of non-tryptic cleavage (>10%), an observation consistent with in vivo exposure to bacterial and immune system proteases (Supplementary Fig. 11).

Total DNA recovery from ancient dental calculus (5–437 ng DNA/mg calculus) was comparable to that for modern calculus and one to three orders of magnitude greater than from paired dentine (0.3–0.5 ng/mg), carious dentine (0.2 ng/mg) and abscessed bone (0.4 ng/mg) (Fig. 5i). Analysis of 16S rRNA phylotypes using a new network analysis tool developed for this study showed that the bac- terial communities within ancient dental calculus closely resembled published human oral microbiomes and were distinct from the com- munities observed in ancient dentine and bone, which clustered primarily with published soil samples, indicating environmental contamination after death (Fig. 5j and Supplementary Fig. 12). This pattern was found to be robust to extraction method, decontamina- tion method, primer selection, sequencing method and interindi- vidual variation. Reanalysis of our data using the methods employed by HMP3 yielded equivalent results (Supplementary Figs. 13–15) that were also confirmed using the Bayesian tool SourceTracker53 (Supplementary Fig. 16). Ancient dental calculus is thus shown to be a remarkably well-preserved biological material that allows direct and detailed investigations of the ancient oral microbiome.

DISCUSSION Dental calculus is among the richest biomolecular sources yet iden- tified in the archaeological record. Given the exceptional preserva- tion of DNA within dental calculus (5–437 ng/mg), next-generation

shotgun sequencing libraries can be built from milligrams of mate- rial, thereby reducing typical sample requirements for ancient DNA analysis by two orders of magnitude. We demonstrate that the red complex pathogens T. forsythia, P. gingivalis and T. denticola have long been associated with periodontal disease, despite changes in lifestyle, hygiene and diet since the medieval period. We confirm the long-term carriage of opportunistic pathogens in the human oral cavity, includ- ing the causative agents of oral and respiratory diseases, as well as bacteria implicated in the progression of cardiovascular disease and the formation of arterial plaques. We find genetic evidence that the human oral cavity has long harbored genes with homology to puta- tive antibiotic resistance genes, the first such demonstration, to our knowledge, in an ancient human–associated sample. We reconstruct the genome of the periodontal pathogen T. forsythia without previ- ous enrichment and identify the absence of a complete conjugative transposon carrying putative tetracycline resistance genes found in the reference strain. We report for the first time, to our knowledge, the presence of well-preserved proteins within ancient dental calculus and show that, although the dental calculus metagenome is domi- nated by bacterial DNA (>99%), the dental calculus metaproteome contains high proportions of both host and microbial proteins of clini- cal significance. Because the growth of calculus is appositional with- out remodeling, it may offer a potential solution to the ‘osteological paradox’ in studies of ancient disease54, and, given that proteins are known to survive longer in the archaeological record than DNA, den- tal calculus may allow the recovery of valuable proteomic data from deep time periods that are out of reach using genomic technologies. Finally, we report the first plant and animal DNA sequences recovered from ancient dental calculus; these sequences allow greater taxonomic precision than is currently possible using microfossil or stable isotope paleodietary techniques. Dental calculus is a robust, long-term bio- molecular reservoir of ancient disease and dietary information, and it has important implications for the fields of medicine, microbiome research, archeology and human evolutionary studies.

URLs. Graphviz package,; GitHub, https://

METhODS Methods and any associated references are available in the online version of the paper.

Accession codes. Illumina and 454 genetic data have been depos- ited in the NCBI Short Read Archive (SRA) under the project acces- sion SRP029257 and sample accessions SRS473742–SRS473771 and SRS480529–SRS480539 and to MG-RAST55 under project accession 365 and accessions 4486524.3, 4486533.3, 4486537.3, 4486539.3, 4486540.3, 4486544.3, 4486613.3, 4486614.3, 4486617.3, 4487224.3– 4487231.3, 4487233.3–4487235.3, 4487237.3–4487248.3, 4488534.3– 4488536.3, 4488542.3, 4517539.3, 4530391.3, 4530438.3, 4530439.3 and 4530473.3–4530475.3. Proteomics data have been deposited in the ProteomeXchange Consortium via the PRIDE partner repository56 with the data set identifier PXD000412 and accessions 34605–34628. Computer source code for the network analysis in Figure 5j has been deposited to GitHub (see URLs).

Note: Any Supplementary Information and Source Data files are available in the online version of the paper.

ACKNOWLEDGMENTS We thank the Kantonale Ethik-Kommission Zürich, the Functional Genomics Center Zürich, the Center for Microscopy and Image Analysis, and the Institute of Oral Biology at the University of Zürich; the PRIDE Team; G. Akgül, K. Alt,



D. Ashford, P. Ashton, H. Barton, A. Bouwman, C. Burger, D. Coulthard, J. Hublin, V. Meskenaite, F. Najar, M. Richards, K. Sankaranarayanan, R. Schlapbach, L. Shillito, T. Stöllner, O. Ullrich and H. Zbinden for assistance with data collection, analysis and management; and M. Carver, F. Dewhirst, A. Tanner, K. Hardy and A. Henry for helpful comments on early drafts and data analyses. This work was supported by the Mäxi Foundation Zürich, the Swiss Foundation for Nutritional Research, Danish Research Foundation grant 29396, Danish Council for Independent Research grant 10-081390, Lundbeck Foundation grants R52-A5062 and R44-A4384, US National Institutes of Health grants R01-HG005172, R01-GM089886, R01-DE018499 and R21- DE018310, European Research Council grant UMICIS/242870, Marie Curie grants EUROTAST FP7-PEOPLE-2010 MC ITN, PALIMPSEST FP7-PEOPLE-2011-IEF 299101 and ORCA FP7-PEOPLE-2011-IOF 299075, a C2D2 Research Priming Fund grant partly funded by Wellcome Trust 097829, Swiss National Science Foundation grant 31003A-135688, the Novartis Foundation, the Novo Nordisk Foundation, the Max Planck Society and the University of York.

AUTHOR CONTRIBUTIONS C.W. conceived the project, with input from M.J.C. R.S. and F.R. contributed samples. C.W., E.C., M.J.C., M.T.P.G., C.v.M., A.R. and Y.H. designed the experiments. C.W., E.C., N.S., C.T., A.R., Y.H., D.C.S.-G., S.C., S.F., H.U.L., P.N., C.D.K., J.V.O., K.Y.T. and E.E. performed the experiments. J.F.M.R., R.V., C.W., C.v.M., J.G., A.R., Y.H., R.Y.T., S.F., C.S., S.C., D.C.S.-G., J.H., J.A.S.C., L.H.H. and T.K. analyzed the data. S.B.-O., Y.H., E.W., C.M.L., M.T.P.G., M.J.C. and F.R. contributed material support to the project. Y.H. wrote the supplementary Raman section. C.W. wrote the manuscript, with critical input from C.M.L., M.T.P.G., M.J.C., C.v.M., E.W., E.C. and the remaining authors.

COMPETING FINANCIAL INTERESTS The authors declare no competing financial interests.

Reprints and permissions information is available online at reprints/index.html.

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ONLINE METhODS Study design and samples. Narrative and graphical overviews of the study design are provided in the Supplementary Note and Supplementary Figure 17. Archaeological material was obtained from the medieval St. Petri church and convent complex in Dalheim, Germany (Supplementary Fig. 18) and radio- carbon dated to c. 950–1200 CE (Supplementary Table 5). The assemblage was evaluated for pathologies (Supplementary Table 6), and dental tis- sues from four well-preserved adult skeletons (G12, B17, B61, B78) and two fauna (F1, F5) were selected for further analysis (Supplementary Figs. 1, 19 and 20). Additionally, dental tissues from nine modern controls (P1–P5, P7, P8, P10, P13) with known dental health histories (Supplementary Table 7) were obtained under informed consent, and protocols were approved by the Zürich Ethics Commission (KEK ZH-Nr. 2012-0119).

Microscopy and spectroscopy. A mandibular incisor from B78 was sectioned longitudinally and examined according to standard protocols with a Tescan VEGA SEM using backscattered electron (BSE) imaging and EDS with a Si(Li) detector. Dental calculus deposits from B78 and P3 were fixed, decalcified and prepared into serial thin sections using modified standard protocols, followed by Gram and Hoechst staining and visualization using a Zeiss Axio Imager M2 and a Leica DMI6000 B microscope. Microfossils were obtained from dental calculus (G12, B17, B61, B78) and dental calculus/crown cementum (F5) deposits (Supplementary Table 8) using an incremental HCl decalcifica- tion protocol (Supplementary Note) and visualized using a Zeiss compound microscope under white and polarized light to identify pollen, phytoliths, starch granules and other debris (Supplementary Table 9) by comparison to reference collections. To evaluate mineralogical composition, Raman spec- troscopy was applied to six calculus (G12, B17, B61, B78, P3, P13), nine den- tine (G12, B17, B61, B78, P4, P5, P7, P8, P10) and five soil matrix (M1–M5) specimens using a HORIBA XploRA instrument (100× magnification and 532-nm laser wavelength) and analyzed for the main PO


Separately, 30 16S rRNA gene amplicon libraries were generated from dental calculus (G12, B17, B61, B78), dentine (G12, B17, B61, B78), carious den- tine (B17) and alveolar bone abscess (B17) ancient DNA extracts generated using extraction buffer A and without previous decontamination. Universal primers targeting variable regions V3, V5 and V6 of the 16S rRNA gene were developed and tested in silico (Supplementary Tables 22 and 23) and in vitro (Supplementary Fig. 22). Each library was generated from a minimum of three amplifications (30–35 cycles) using Phusion HS II enzyme and 454 amplicon Fusion primers with multiplex identifiers (MIDs), and pooled 454 libraries were sequenced with a Roche GS Junior, resulting in 170,807 reads after the removal of low-quality sequences (Roche GS RunProcessor, default settings; Supplementary Table 24).

16S rRNA taxonomic classification. A reference data set containing full-length 16S ribosomal RNA sequences was constructed from the NCBI GenBank data- base, whereby all publicly available 16S ribosomal gene sequences found in the NCBI GenBank database were downloaded, screened for chimeras using uch- ime58, aligned using the INFERNAL aligner59 v1.0.2, trimmed and clustered at a sequence identity cutoff of 98% with a hierarchical clustering algorithm using sequence identity as the measure of distance and single linkage as the cluster metric. This data set has high overlap with both the Greengenes60 (90%) and RDP61 (92%) databases and was constructed to standardize filtering and align- ment methods, as well as to streamline GenBank data retrieval for network analysis. Amplicon and shotgun sample reads were aligned to the reference OTU data set, and reads with a bit score of <40 or negative structure score were discarded. Sample reads were mapped to the reference OTUs by assigning the OTU ID of the most similar reference sequences. Conflicting OTU IDs were discarded. OTUs containing 16S rRNA gene sequences belonging to a refer- ence genome or culture collection were assigned the consensus taxonomy of all such sequences in the OTU. In the case of OTUs that contained no reliable source of taxonomy, the taxonomy of the OTU was inferred by decreasing the clustering threshold until the point at which the OTU was merged with another in which sequences with reliable taxonomy existed.

Network analysis. Network analysis of community similarity was performed to compare the microbial communities of ancient dental samples to each other and to environmental samples deposited in GenBank and MG-RAST (project 128). Only environmental samples with at least 20 OTUs were considered (1,818 of 37,689), and only samples with at least 20% similarity to one of the ancient samples are shown in the network (315 of 1,818). The similarity between a pair of samples was calculated as the number of shared OTUs divided by the total number of different OTUs found in both samples. The network was rendered using the neato program from the graphviz package (see URLs).

Phylogenetic tree. Ancient dental calculus, amplicon and shotgun OTU tables were merged, and a full-length 16S rRNA sequence representative for each OTU was chosen. Phylogenetic relationships were inferred with FastTree62 v2.1.3 (generalized time-reversible model).

Validation of results using the RDP and QIIME pipelines. To confirm that the taxonomic characterization of ancient dental samples was robust to database choice and clustering parameters, the 16S rRNA amplicon data were reanalyzed using the Greengenes database (v.4Feb2011) and the RDP Pyrosequencing61 and QIIME63 pipelines. Only reads of ≥70 bp with 100% identity to both forward and reverse primers were analyzed. OTUs were clus- tered at 97% identity, and singleton OTUs were discarded (Supplementary Table 25). The OTU table was rarefied to 1,265 sequences/sample and ana- lyzed at the L2, L5 and L6 levels. Alpha and beta diversity were calculated using QIIME default parameters. The BIOM file for these data is available as Supplementary Data Set 1. This OTU table was merged with an OTU table generated from the HMP data set using the same parameters, and the two data sets were compared using Principal Coordinates Analysis; the BIOM file for these data is available as Supplementary Data Set 2.

Source tracking. To test for contamination in the ancient dental samples, Bayesian microbial source tracking53 was performed (1,000 ‘burn-in’ iterations


peak position and peak area, as well as the peak intensity ratios of C-H (~2,940 cm−1) I(CH) and main phosphate peak I(P) (Supplementary Table 10).

Isotope ratio mass spectrometry. Rib specimens from G12, B17, B61 and B78 were cleaned by abrasion, and collagen was extracted according to the method of Richards and Hedges57 with an additional ultrafiltration step. Carbon and nitrogen isotopic values were measured in duplicate using a Thermo-Finnighan Delta XP continuous-flow isotope-ratio mass spectrometer following combus- tion in an elemental analyzer FLASH EA 2112 (Supplementary Table 11).

DNA extraction. Ancient samples were extracted in a dedicated ancient DNA laboratory at the University of Zürich Centre for Evolutionary Medicine in accordance with established contamination control precautions and workflows. DNA was extracted from dental calculus (G12, B17, B61, B78, P2), dentine (G12, B17, B61, B78), carious dentine (B17), abscessed alveolar bone (B78) and burial matrix (M1–M5) by phenol-chloroform extraction followed by Qiagen MinElute column purification (Supplementary Tables 12–17). Burial matrix and NaOCl-decontaminated dentine were tested for the presence of endog- enous human DNA using targeted PCR and qPCR (Supplementary Tables 18 and 19). To optimize DNA extraction from dental calculus, five extraction buffers (A–E) and three decontamination methods were tested and compared. Two extraction buffers (A, 0.45 M EDTA, 10% proteinase K; B, 0.1 M EDTA, 10% proteinase K, 10 mM Tris-HCl, 10 mM NaCl, 2% SDS, 5 mM CaCl


, 40 mM DTT) and three decontamination methods (2% NaOCl, 0.5 M EDTA wash, none) were selected for further analysis and were used in combination to produce nine DNA extracts from B61 and G12 dental calculus.

DNA library construction and sequencing. DNA extracts from the optimiza- tion experiment were built into nine shotgun libraries using a NEBNext Quick DNA Library Prep Master Mix Set (e6090) with DNA oligonucleotides con- taining a sample-specific multiplex index sequence (Supplementary Fig. 21 and Supplementary Table 20). Libraries were amplified with Phusion HS II enzyme and sequenced on one lane of an Illumina HiSeq 2000 using single- end 1 × 100-bp chemistry, resulting in 93,677,545 reads after the removal of low-quality sequences (Illumina CASAVA 1.8.0, default settings, sequences <25 bp and/or with Phred scores <35 removed; Supplementary Table 21).

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