Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Salmonella enterica genomes from victims of a major sixteenth-century epidemic in Mexico

Abstract

Indigenous populations of the Americas experienced high mortality rates during the early contact period as a result of infectious diseases, many of which were introduced by Europeans. Most of the pathogenic agents that caused these outbreaks remain unknown. Through the introduction of a new metagenomic analysis tool called MALT, applied here to search for traces of ancient pathogen DNA, we were able to identify Salmonella enterica in individuals buried in an early contact era epidemic cemetery at Teposcolula-Yucundaa, Oaxaca in southern Mexico. This cemetery is linked, based on historical and archaeological evidence, to the 1545–1550 ce epidemic that affected large parts of Mexico. Locally, this epidemic was known as ‘cocoliztli’, the pathogenic cause of which has been debated for more than a century. Here, we present genome-wide data from ten individuals for Salmonella enterica subsp. enterica serovar Paratyphi C, a bacterial cause of enteric fever. We propose that S. Paratyphi C be considered a strong candidate for the epidemic population decline during the 1545 cocoliztli outbreak at Teposcolula-Yucundaa.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Overview of Teposcolula-Yucundaa.
Fig. 2: MALT analysis and pathogen screening of shotgun data.
Fig. 3: Maximum likelihood trees for S. enterica subsp. enterica phylogeny.

Similar content being viewed by others

References

  1. Ubelaker, D. H. Prehistoric New World population size: historical review and current appraisal of North American estimates. Am. J. Phys. Anthropol. 45, 661–665 (1976).

    Article  Google Scholar 

  2. Crosby, A. W. Virgin soil epidemics as a factor in the aboriginal depopulation in America. William Mary Q. 33, 289–299 (1976).

    Article  CAS  PubMed  Google Scholar 

  3. Dobyns, H. F. Disease transfer at contact. Annu. Rev. Anthropol. 22, 273–291 (1993).

  4. Acuna-Soto, R., Stahle, D. W., Therrell, M. D., Griffin, R. D. & Cleaveland, M. K. When half of the population died: the epidemic of hemorrhagic fevers of 1576 in Mexico. FEMS Microbiol. Lett. 240, 1–5 (2004).

    Article  CAS  PubMed  Google Scholar 

  5. Llamas, B. et al. Ancient mitochondrial DNA provides high-resolution time scale of the peopling of the Americas. Sci. Adv. 2, e1501385 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Lindo, J. et al. A time transect of exomes from a Native American population before and after European contact. Nat. Commun. 7, 13175 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Cook, N. D. & Lovell, W. G. Secret Judgments of God: Old World Disease in Colonial Spanish America (Univ. Oklahoma Press, Norman, 2001).

  8. Fields, S. L. Pestilence and Headcolds: Encountering Illness in Colonial Mexico (Columbia Univ. Press, New York, 2008).

  9. Ortner, D. J. Identification of Pathological Conditions in Human Skeletal Remains 2nd edn (Academic Press, Cambridge, 2003).

  10. Walker, R. S., Sattenspiel, L. & Hill, K. R. Mortality from contact-related epidemics among indigenous populations in Greater Amazonia. Sci. Rep. 5, 14032 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Joralemon, D. New World depopulation and the case of disease. J. Anthropol. Res. 38, 108–127 (1982).

    Article  CAS  PubMed  Google Scholar 

  12. Larsen, C. S. In the wake of Columbus: native population biology in the postcontact Americas. Am. J. Phys. Anthropol. 37, 109–154 (1994).

    Article  Google Scholar 

  13. Bos, K. I. et al. Pre-Columbian mycobacterial genomes reveal seals as a source of New World human tuberculosis. Nature 514, 494–497 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Schuenemann, V. J. et al. Genome-wide comparison of medieval and modern Mycobacterium leprae. Science 341, 179–183 (2013).

    Article  CAS  PubMed  Google Scholar 

  15. Warinner, C. et al. Pathogens and host immunity in the ancient human oral cavity. Nat. Genet. 46, 336–344 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Bos, K. I. et al. A draft genome of Yersinia pestis from victims of the Black Death. Nature 478, 506–510 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Maixner, F. et al. The 5300-year-old Helicobacter pylori genome of the Iceman. Science 351, 162–165 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Devault, A. M. et al. Ancient pathogen DNA in archaeological samples detected with a microbial detection array. Sci. Rep. 4, 4245 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Bos, K. I. et al. Parallel detection of ancient pathogens via array-based DNA capture. Phil. Trans. R. Soc. B 370, 20130375 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Devault, A. M. et al. A molecular portrait of maternal sepsis from Byzantine Troy. eLife 6, e20983 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Warinner, C. et al. A robust framework for microbial archaeology. Annu. Rev. Genomics Hum. Genet. 18, 321–356 (2017).

  22. Key, F. M., Posth, C., Krause, J., Herbig, A. & Bos, K. I. Mining metagenomic data sets for ancient DNA: recommended protocols for authentication. Trends Genet. 33, 508–520 (2017).

    Article  CAS  PubMed  Google Scholar 

  23. Jonsson, H., Ginolhac, A., Schubert, M., Johnson, P. L. & Orlando, L. mapDamage2.0: fast approximate Bayesian estimates of ancient DNA damage parameters. Bioinformatics 29, 1682–1684 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Prufer, K. et al. Computational challenges in the analysis of ancient DNA. Genome Biol. 11, R47 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990).

    Article  CAS  PubMed  Google Scholar 

  26. Peabody, M. A., Van Rossum, T., Lo, R. & Brinkman, F. S. Evaluation of shotgun metagenomics sequence classification methods using in silico and in vitro simulated communities. BMC Bioinforma. 16, 363 (2015).

    Article  Google Scholar 

  27. Lindgreen, S., Adair, K. L. & Gardner, P. P. An evaluation of the accuracy and speed of metagenome analysis tools. Sci. Rep. 6, 19233 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Huson, D. H. et al. MEGAN community edition—interactive exploration and analysis of large-scale microbiome sequencing data. PLoS. Comput. Biol. 12, e1004957 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Spores, R. & Robles García, N. A prehispanic (postclassic) capital center in colonial transition: excavations at Yucundaa Pueblo Viejo de Teposcolula, Oaxaca, Mexico. Lat. Am. Antiq. 18, 333–353 (2007).

    Article  Google Scholar 

  30. Warinner, C., Robles García, N., Spores, R. & Tuross, N. Disease, demography, and diet in early colonial New Spain: investigation of a sixteenth-century Mixtec cemetery at Teposcolula Yucundaa. Lat. Am. Antiq. 23, 467–489 (2012).

    Article  Google Scholar 

  31. Tuross, N., Warinner, C. & Robles García, N. in Yucundaa: La Cuidad Mixteca Yucundaa-Pueblo Viejo de Teposcolula y su Transformación Prehispánica-Colonial Vol. 2 (eds Spores, R. & Robles García, N.) 541–546 (Instituto Nacional de Antropología e Historia, Mexico City, 2014).

  32. Acuna-Soto, R., Stahle, D. W., Cleaveland, M. K. & Therrell, M. D. Megadrought and megadeath in 16th century Mexico. Emerg. Infect. Dis. 8, 360–362 (2002).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Pickard, D. et al. Molecular characterization of the Salmonella enterica serovar Typhi Vi-typing bacteriophage E1. J. Bacteriol. 190, 2580–2587 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Burbano, H. A. et al. Targeted investigation of the Neandertal genome by array-based sequence capture. Science 328, 723–725 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Fu, Q. et al. DNA analysis of an early modern human from Tianyuan Cave, China. Proc. Natl. Acad. Sci. USA 110, 2223–2227 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Campbell, J. W., Morgan-Kiss, R. M. & Cronan, J. E. Jr A new Escherichia coli metabolic competency: growth on fatty acids by a novel anaerobic beta-oxidation pathway. Mol. Microbiol. 47, 793–805 (2003).

  37. Rivera-Chavez, F. et al. Salmonella uses energy taxis to benefit from intestinal inflammation. PLoS. Pathog. 9, e1003267 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Liu, W. Q. et al. Salmonella Paratyphi C: genetic divergence from Salmonella choleraesuis and pathogenic convergence with Salmonella typhi. PLoS ONE 4, e4510 (2009).

  39. Tam, C. K., Morris, C. & Hackett, J. The Salmonella enterica serovar Typhi type IVB self-association pili are detached from the bacterial cell by the PilV minor pilus proteins. Infect. Immun. 74, 5414–5418 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Tam, C. K., Hackett, J. & Morris, C. Salmonella enterica serovar Paratyphi C carries an inactive shufflon. Infect. Immun. 72, 22–28 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Campana, M. G., Robles Garcia, N., Ruhli, F. J. & Tuross, N. False positives complicate ancient pathogen identifications using high-throughput shotgun sequencing. BMC Res. Notes 7, 111 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  42. Wood, D. E. & Salzberg, S. L. Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biol. 15, R46 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Segata, N. et al. Metagenomic microbial community profiling using unique clade-specific marker genes. Nat. Methods 9, 811–814 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Singer, M. & Clair, S. Syndemics and public health: reconceptualizing disease in bio-social context. Med. Anthropol. Q. 17, 423–441 (2003).

    Article  PubMed  Google Scholar 

  45. Herring, D. A. & Sattenspiel, L. Social contexts, syndemics, and infectious disease in northern Aboriginal populations. Am. J. Hum. Biol. 19, 190–202 (2007).

    Article  PubMed  Google Scholar 

  46. Guy, P. L. Prospects for analyzing ancient RNA in preserved materials. Wiley Interdiscip. Rev. RNA 5, 87–94 (2014).

    Article  CAS  PubMed  Google Scholar 

  47. Gal-Mor, O., Boyle, E. C. & Grassl, G. A. Same species, different diseases: how and why typhoidal and non-typhoidal Salmonella enterica serovars differ. Front. Microbiol. 5, 391 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  48. Wain, J., Hendriksen, R. S., Mikoleit, M. L., Keddy, K. H. & Ochiai, R. L. Typhoid fever. Lancet 385, 1136–1145 (2015).

    Article  PubMed  Google Scholar 

  49. Monack, D. M., Mueller, A. & Falkow, S. Persistent bacterial infections: the interface of the pathogen and the host immune system. Nat. Rev. Microbiol. 2, 747–765 (2004).

    Article  CAS  PubMed  Google Scholar 

  50. de Sahagún, B. General History of the Things of New Spain: Florentine Codex (School of American Research, Santa Fe, 1950–1982).

  51. Zhou, Z. et al. Millennia of genomic stability within the invasive Para C lineage of Salmonella enterica. Preprint at https://www.biorxiv.org/content/early/2017/02/14/105759 (2017).

  52. Achtman, M. et al. Multilocus sequence typing as a replacement for serotyping in Salmonella enterica. PLoS. Pathog. 8, e1002776 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. National Typhoid and Paratyphoid Fever Surveillance Annual Summary, 2014 (CDC, 2016).

  54. Acuna-Soto, R., Romero, L. C. & Maguire, J. H. Large epidemics of hemorrhagic fevers in Mexico 1545–1815. Am. J. Trop. Med. Hyg. 62, 733–739 (2000).

    Article  CAS  PubMed  Google Scholar 

  55. Smith, D. C. Gerhard’s distinction between typhoid and typhus and its reception in America, 1833–1860. Bull. Hist. Med. 54, 368–385 (1980).

    CAS  PubMed  Google Scholar 

  56. Crump, J. A., Luby, S. P. & Mintz, E. D. The global burden of typhoid fever. Bull. World Health Organ. 82, 346–353 (2004).

    PubMed  PubMed Central  Google Scholar 

  57. Typhoid Fever—Uganda(WHO, 2015); http://who.int/csr/don/17-march-2015-uganda/en/

  58. Burkhardt, S. & Kärkkäinen, J. in Combinatorial Pattern Matching: 12th Annual Symposium, CPM 2001 Jerusalem, Israel, July 1–4, 2001 Proceedings (eds Amihood, A. & Landau, G. M.) 73–85 (Springer, Berlin, 2001).

  59. Ma, B., Tromp, J. & Li, M. PatternHunter: faster and more sensitive homology search. Bioinformatics 18, 440–445 (2002).

    Article  CAS  PubMed  Google Scholar 

  60. Buchfink, B., Xie, C. & Huson, D. H. Fast and sensitive protein alignment using DIAMOND. Nat. Methods 12, 59–60 (2015).

    Article  CAS  PubMed  Google Scholar 

  61. Ning, Z., Cox, A. J. & Mullikin, J. C. SSAHA: a fast search method for large DNA databases. Genome Res. 11, 1725–1729 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Chao, K. M., Pearson, W. R. & Miller, W. Aligning two sequences within a specified diagonal band. Comput. Appl. Biosci. 8, 481–487 (1992).

    CAS  PubMed  Google Scholar 

  63. Smith, T. F. & Waterman, M. S. Identification of common molecular subsequences. J. Mol. Biol. 147, 195–197 (1981).

    Article  CAS  PubMed  Google Scholar 

  64. Needleman, S. B. & Wunsch, C. D. A general method applicable to the search for similarities in the amino acid sequence of two proteins. J. Mol. Biol. 48, 443–453 (1970).

    Article  CAS  PubMed  Google Scholar 

  65. Benson, D. A. et al. GenBank. Nucleic Acids Res. 41, D36–D42 (2013).

    Article  CAS  PubMed  Google Scholar 

  66. Dabney, J. et al. Complete mitochondrial genome sequence of a Middle Pleistocene cave bear reconstructed from ultrashort DNA fragments. Proc. Natl. Acad. Sci. USA 110, 15758–15763 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Meyer, M. & Kircher, M. Illumina sequencing library preparation for highly multiplexed target capture and sequencing. Cold Spring Harb. Protoc. 2010, prot5448 (2010).

    Article  Google Scholar 

  68. Kircher, M., Sawyer, S. & Meyer, M. Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform. Nucleic Acids Res. 40, e3 (2012).

    Article  CAS  PubMed  Google Scholar 

  69. Briggs, A. W. et al. Removal of deaminated cytosines and detection of in vivo methylation in ancient DNA. Nucleic Acids Res. 38, e87 (2010).

    Article  PubMed  Google Scholar 

  70. Hodges, E. et al. Hybrid selection of discrete genomic intervals on custom-designed microarrays for massively parallel sequencing. Nat. Protoc. 4, 960–974 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Tamura, K., Stecher, G., Peterson, D., Filipski, A. & Kumar, S. MEGA6: Molecular Evolutionary Genetics Analysis version 6.0. Mol. Biol. Evol. 30, 2725–2729 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. R Development Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna, 2013).

  74. Connor, T. R. et al. What’s in a name? Species-wide whole-genome sequencing resolves invasive and noninvasive lineages of Salmonella enterica serotype Paratyphi B. mBio 7, e00527-16 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  75. Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, New York, 2009).

Download references

Acknowledgements

This work was supported by the Max Planck Society (J.K.), the European Research Council (ERC) starting grant APGREID (to J.K.), Social Sciences and Humanities Research Council of Canada postdoctoral fellowship grant 756-2011-501 (to K.I.B.) and the Mäxi Foundation (M.G.C.). We thank the Archaeology Council at Mexico’s INAH and the Teposcolula-Yucundaa Archaeological Project for sampling permissions. We are grateful to A. Wissgott, G. Brandt and V. Schuenemann for assistance with laboratory work, A. Günzel for providing graphical support for Fig. 1 and Supplementary Fig. 10, and R. Barquera, J. Hackett and M. Pi for thoughts and discussion on the manuscript. Part of the data storage and analysis was performed on the computational resource bwGRiD Cluster Tübingen funded by the Ministry of Science, Research and the Arts Baden-Württemberg, and the Universities of the State of Baden-Württemberg, Germany, within the framework programme bwHPC. We thank the MALT user community for helpful comments and bug reports.

Author information

Authors and Affiliations

Authors

Contributions

K.I.B., M.G.C., A.H., N.T. and J.K. conceived the investigation. K.I.B., A.H. Å.J.V., M.G.C. and J.K. designed the experiments. N.M.R.G. provided archaeological information and drawings, submitted INAH permits and assisted in the sampling processes. Å.J.V., M.G.C., S.S., M.A.S. and K.I.B. performed the laboratory work. Å.J.V., A.H., K.I.B., C.W. and A.A.V. performed the analyses. D.H. implemented the MALT algorithm. A.H., J.K. and D.H. designed and set up the MALT ancient DNA analysis pipeline. C.W. performed the ethnohistorical analyses. Å.J.V. and K.I.B. wrote the manuscript with contributions from all authors.

Corresponding author

Correspondence to Alexander Herbig.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Vågene, Å.J., Herbig, A., Campana, M.G. et al. Salmonella enterica genomes from victims of a major sixteenth-century epidemic in Mexico. Nat Ecol Evol 2, 520–528 (2018). https://doi.org/10.1038/s41559-017-0446-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41559-017-0446-6

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing