Cited by 100

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Quantitative metaproteomics of medieval dental calculus reveals individual oral health status

Jersie-Christensen, Rosa R., Lanigan, Liam T., Lyon, David, Mackie, Meaghan, Belstrøm, Daniel, Kelstrup, Christian D., Fotakis, Anna K., Willerslev, Eske, Lynnerup, Niels, Jensen, Lars J., Cappellini, Enrico, Olsen, Jesper V.·2018·Nature Communications

Abstract

The composition of ancient oral microbiomes has recently become accessible owing to advanced biomolecular methods such as metagenomics and metaproteomics, but the utility of metaproteomics for such analyses is less explored. Here, we use quantitative metaproteomics to characterize the dental calculus associated with the remains of 21 humans retrieved during the archeological excavation of the medieval (ca. 1100–1450 CE) cemetery of Tjærby, Denmark. We identify 3671 protein groups, covering 220 bacterial species and 81 genera across all medieval samples. The metaproteome profiles of bacterial and human proteins suggest two distinct groups of archeological remains corresponding to health-predisposed and oral disease-susceptible individuals, which is supported by comparison to the calculus metaproteomes of healthy living individuals. Notably, the groupings identified by metaproteomics are not apparent from the bioarchaeological analysis, illustrating that quantitative metaproteomics has the potential to provide additional levels of molecular information about the oral health status of individuals from archeological contexts.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41467-018-07148-3

Cites

9 of 9 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Jersie-Christensen et al. identified two groups of individuals from medieval Denmark based on bacterial taxa: one showing evidence of microbiome dysbiosis and one showing a healthy microbiome.

    “On the basis of bacterial taxa, the study identified two groups of individuals: one showing evidence of microbiome dysbiosis (a disruption of a healthy state oral microbiome) and one group showing a healthy microbiome.”

    From Ancient protein analysis in archaeology (2021) · cites this paper as [61]

  • Most studies of ancient human remains work with historic dental calculus, a stable long-term reservoir of proteins.

    “When it comes to analyzing ancient human remains, most studies work with historic dental calculus [11, 15, 22-26], as it is a stable, long-term reservoir of proteins [27].”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 55

  1. Adler, C. J. et al. Sequencing ancient calcified dental plaque shows changes in oral microbiota with dietary shifts of the Neolithic and Industrial revolutions. Nat. Genet. 45, 450–455.e1 (2013). · DOI · Paper page
  2. Warinner, C., Speller, C. & Collins, M. J. A new era in palaeomicrobiology: prospects for ancient dental calculus as a long-term record of the human oral microbiome. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 370, 20130376 (2015). · DOI
  3. Weyrich, L. S. et al. Neanderthal behaviour, diet, and disease inferred from ancient DNA in dental calculus. Nature 544, 357–361 (2017). · DOI
  4. Mackie, M. et al. Preservation of the metaproteome: variability of protein preservation in ancient dental calculus. STAR 3, 74–86 (2017). · DOI · Paper page
  5. Warinner, C. et al. Direct evidence of milk consumption from ancient human dental calculus. Sci. Rep. 4, 7104 (2014). · DOI · Paper page
  6. Warinner, C. et al. Pathogens and host immunity in the ancient human oral cavity. Nat. Genet. 46, 336–344 (2014). · DOI · Paper page
  7. Wade, W. G. in The Human Microbiota and Chronic Disease: Dysbiosis as a Cause of Human Pathology (eds Nibali, L. & Henderson, B.) 67–80 (John Wiley & Sons, Hoboken, NJ, 2016). · DOI
  8. Franzosa, E. A. et al. Identifying personal microbiomes using metagenomic codes. Proc. Natl Acad. Sci. USA 112, E2930–E2938 (2015). · DOI
  9. Gomez, A. et al. Host genetic control of the oral microbiome in health and disease. Cell. Host. Microbe 22, 269–278.e3 (2017). · DOI
  10. Aas, J. A., Paster, B. J., Stokes, L. N., Olsen, I. & Dewhirst, F. E. Defining the normal bacterial flora of the oral cavity. J. Clin. Microbiol. 43, 5721–5732 (2005). · DOI · Paper page
  11. Ziesemer, K. A. et al. Intrinsic challenges in ancient microbiome reconstruction using 16S rRNA gene amplification. Sci. Rep. 5, 16498 (2015). · DOI · Paper page
  12. Hyldgård, I. M. Tjærby Ødekirke og Kirkegård (Aarhus Universitetsforlag, Aarhus, 2016). · DOI
  13. Shiau, H. J. & Reynolds, M. A. Sex differences in destructive periodontal disease: exploring the biologic basis. J. Periodontol. 81, 1505–1517 (2010). · DOI
  14. Krustrup, U. & Petersen, P. E. Periodontal conditions in 35–44 and 65–74-year-old adults in Denmark. Acta Odontol. Scand. 64, 65–73 (2006). · DOI
  15. Scannapieco, F. A. & Cantos, A. Oral inflammation and infection, and chronic medical diseases: implications for the elderly. Periodontol. 2000. 72, 153–175 (2016). · DOI
  16. Armitage, G. C. Periodontal diagnoses and classification of periodontal diseases. Periodontol. 2000. 34, 9–21 (2004). · DOI
  17. Ogden, A. in Advances in Human Palaeopathology (eds Pinhas, R. & Mays, S.) 283–307 (John Wiley & Sons, Ltd, Hoboken, NJ, 2008). · DOI
  18. Kelstrup, C. D. et al. Rapid and deep proteomes by faster sequencing on a benchtop quadrupole ultra-high-field Orbitrap mass spectrometer. J. Proteome Res. 13, 6187–6195 (2014). · DOI
  19. Cox, J. & Mann, M. MaxQuant enables high peptide identification rates, individualized ppb-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26, 1367–1372 (2008). · DOI · Paper page
  20. UniProt Consortium. UniProt: a hub for protein information. Nucleic Acids Res. 43, D204–D212 (2015). · DOI · Paper page
  21. Belda-Ferre, P. et al. The human oral metaproteome reveals potential biomarkers for caries disease. Proteomics 15, 3497–3507 (2015). · DOI
  22. Szafranski, S. P. et al. High-resolution taxonomic profiling of the subgingival microbiome for biomarker discovery and periodontitis diagnosis. Appl. Environ. Microbiol. 81, 1047–1058 (2015). · DOI
  23. Oliveira, R. R. D. S. et al. Levels of candidate periodontal pathogens in subgingival biofilm. J. Dent. Res. 95, 711–718 (2016). · DOI
  24. Shaw, L. et al. Distinguishing the signals of gingivitis and periodontitis in supragingival plaque: a cross-sectional cohort study in Malawi. Appl. Environ. Microbiol. 82, 6057–6067 (2016). · DOI
  25. Kumar, P. S., Griffen, A. L., Moeschberger, M. L. & Leys, E. J. Identification of candidate periodontal pathogens and beneficial species by quantitative 16S clonal analysis. J. Clin. Microbiol. 43, 3944–3955 (2005). · DOI
  26. Mysak, J. et al. Porphyromonas gingivalis: major periodontopathic pathogen overview. J. Immunol. Res. 2014, 476068 (2014). · DOI
  27. Lepp, P. W. et al. Methanogenic Archaea and human periodontal disease. Proc. Natl Acad. Sci. USA 101, 6176–6181 (2004). · DOI
  28. Bringuier, A., Khelaifia, S., Richet, H., Aboudharam, G. & Drancourt, M. Real-time PCR quantification of Methanobrevibacter oralis in periodontitis. J. Clin. Microbiol. 51, 993–994 (2013). · DOI
  29. Maruyama, N. et al. Intraindividual variation in core microbiota in peri-implantitis and periodontitis. Sci. Rep. 4, 6602 (2014). · DOI
  30. Liu, G., Tang, C. M. & Exley, R. M. Non-pathogenic Neisseria: members of an abundant, multi-habitat, diverse genus. Microbiology 161, 1297–1312 (2015). · DOI
  31. Richards, V. P. et al. The microbiome of site-specific dental plaque of children with different caries status. Infect. Immun. 85, e00106–17 (2017). · DOI
  32. Warinner, C. et al. A robust framework for microbial archaeology. Annu. Rev. Genom. Hum. Genet. 18, 321–356 (2017). · DOI
  33. Rodriguez, A. M. et al. Physiological and molecular characterization of genetic competence in Streptococcus sanguinis. Mol. Oral. Microbiol. 26, 99–116 (2011). · DOI
  34. Das, M., Badley, A. D., Cockerill, F. R., Steckelberg, J. M. & Wilson, W. R. Infective endocarditis caused by HACEK microorganisms. Annu. Rev. Med. 48, 25–33 (1997). · DOI
  35. Yew, H. S. et al. Association between HACEK bacteraemia and endocarditis. J. Med. Microbiol. 63, 892–895 (2014). · DOI
  36. Eribe, E. R. K. & Olsen, I. Leptotrichia species in human infections II. J. Oral. Microbiol. 9, 1368848 (2017). · DOI
  37. Sohail, M. R., Gray, A. L., Baddour, L. M., Tleyjeh, I. M. & Virk, A. Infective endocarditis due to Propionibacterium species. Clin. Microbiol. Infect. 15, 387–394 (2009). · DOI
  38. Bekker-Jensen, D. B. et al. An optimized shotgun strategy for the rapid generation of comprehensive human proteomes. Cell Syst. 4, 587–599.e4 (2017). · DOI
  39. Paster, B. J., Olsen, I., Aas, J. A. & Dewhirst, F. E. The breadth of bacterial diversity in the human periodontal pocket and other oral sites. Periodontol 2000 42, 80–87 (2006). · DOI
  40. Lazarevic, V. et al. Metagenomic study of the oral microbiota by Illumina high-throughput sequencing. J. Microbiol. Methods 79, 266–271 (2009). · DOI
  41. Bik, E. M. et al. Bacterial diversity in the oral cavity of 10 healthy individuals. Isme. J. 4, 962–974 (2010). · DOI · Paper page
  42. Takahashi, N. & Nyvad, B. The role of bacteria in the caries process: ecological perspectives. J. Dent. Res. 90, 294–303 (2011). · DOI
  43. Belda-Ferre, P. et al. The oral metagenome in health and disease. Isme. J. 6, 46–56 (2012). · DOI
  44. Raja, M., Ummer, F. & Dhivakar, C. P. Aggregatibacter actinomycetemcomitans—a tooth killer. J. Clin. Diagn. Res. 8, ZE13–ZE16 (2014).
  45. Blaser, M. J. Antibiotic use and its consequences for the normal microbiome. Science 352, 544–545 (2016). · DOI · Paper page
  46. Gomez-Arango, L. F. et al. Antibiotic treatment at delivery shapes the initial oral microbiome in neonates. Sci. Rep. 7, 43481 (2017). · DOI
  47. Shaw, L. et al. The human salivary microbiome is shaped by shared environment rather than genetics: evidence from a large family of closely related individuals. mBio 8, e01237–17 (2017). · DOI
  48. Waldron, T. Palaeopathology (Cambridge University Press, Cambridge, 2008). · DOI
  49. Dobney, K. & Brothwell, D. A method for evaluating the amount of dental calculus on teeth from archaeological sites. J. Archaeol. Sci. 14, 343–351 (1987). · DOI
  50. Smith, B. H. Patterns of molar wear in hunter–gatherers and agriculturalists. Am. J. Phys. Anthropol. 63, 39–56 (1984). · DOI
  51. Lanigan, L. T. & Bartlett, D. W. Tooth wear with an erosive component in a Mediaeval Iceland population. Arch. Oral. Biol. 58, 1450–1456 (2013). · DOI
  52. Jersie-Christensen, R. R., Sultan, A. & Olsen, J. V. Simple and reproducible sample preparation for single-shot phosphoproteomics with high sensitivity. Methods Mol. Biol. 1355, 251–260 (2016). · DOI
  53. Demarchi, B. et al. Protein sequences bound to mineral surfaces persist into deep time. eLife 5, e17092 (2016). · DOI · Paper page
  54. Tyanova, S. et al. The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat. Methods 13, 731–740 (2016). · DOI · Paper page
  55. Vizcaíno, J. A. et al. 2016 update of the PRIDE database and its related tools. Nucleic Acids Res. 44, 11033 (2016). · DOI

Cited by

Sorted by citations

Metadata

Authors
Jersie-Christensen, R. R., Lanigan, L. T., Lyon, D., Mackie, M., Belstrøm, D., Kelstrup, C. D., Fotakis, A. K., Willerslev, E., Lynnerup, N., Jensen, L. J., Cappellini, E., & Olsen, J. V.
Venue
Nature Communications
Published
2018-11-20
Volume
9
Issue
1
ISSN
2041-1723
Cited by
100
References
9
Language
en

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review