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Emergence of human-adapted Salmonella enterica is linked to the Neolithization process

Nature Ecology & Evolution volume 4, pages 324–333 (2020)Cite this article

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Abstract

It has been hypothesized that the Neolithic transition towards an agricultural and pastoralist economy facilitated the emergence of human-adapted pathogens. Here, we recovered eight Salmonella enterica subsp. enterica genomes from human skeletons of transitional foragers, pastoralists and agropastoralists in western Eurasia that were up to 6,500 yr old. Despite the high genetic diversity of S. enterica, all ancient bacterial genomes clustered in a single previously uncharacterized branch that contains S. enterica adapted to multiple mammalian species. All ancient bacterial genomes from prehistoric (agro-)pastoralists fall within a part of this branch that also includes the human-specific S. enterica Paratyphi C, illustrating the evolution of a human pathogen over a period of 5,000 yr. Bacterial genomic comparisons suggest that the earlier ancient strains were not host specific, differed in pathogenic potential and experienced convergent pseudogenization that accompanied their downstream host adaptation. These observations support the concept that the emergence of human-adapted S. enterica is linked to human cultural transformations.

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Fig. 1: Geographic location and radiocarbon age of ancient human individuals infected with S. enterica.
Fig. 2: Phylogenetic relationships of reconstructed ancient and modern S. enterica core genomes.
Fig. 3: AESB topology, divergence times and gain–loss events.
Fig. 4: Pseudogenes and evolution of host adaptation across the AESB.

Data availability

Raw metagenomic data used to reconstruct ancient S. enterica genomes, as well as unpublished ancient human DNA, are available from the European Nucleotide Archive (Accession no. PRJEB35216; see also Supplementary Data 2). The molecular dating archive containing files specifying the BEAST analysis of the two 50-taxon (argo-)pastoralist datasets, as well as the thinned posterior distributions of all parameters and the maximum clade consensus trees, are available at https://doi.org/10.6084/m9.figshare.10052084.v1.

References

  1. Fowler, C., Harding, J. & Hofmann, D. The Oxford Handbook of Neolithic Europe (OUP, 2015).

  2. Cockburn, T. A. Infectious diseases in ancient populations. Curr. Anthropol. 12, 45–62 (1971).

    Article  CAS  PubMed  Google Scholar 

  3. Armelagos, G. J. & Cohen, M. N. Paleopathology at the Origins of Agriculture (Academic Press, 1984).

  4. Larsen, C. S. et al. Bioarchaeology of Neolithic Çatalhöyük reveals fundamental transitions in health, mobility, and lifestyle in early farmers. Proc. Natl Acad. Sci. USA 116, 12615–12623 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Barrett, R., Kuzawa, C. W., McDade, T. & Armelagos, G. J. Emerging and re-emerging infectious diseases: the third epidemiologic transition. Annu. Rev. Anthropol. 27, 247–271 (1998).

    Article  Google Scholar 

  6. Spyrou, M. A., Bos, K. I., Herbig, A. & Krause, J. Ancient pathogen genomics as an emerging tool for infectious disease research. Nat. Rev. Genet. 20, 323–340 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. 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 

  8. Vågene, A. J. et al. Salmonella enterica genomes from victims of a major sixteenth-century epidemic in Mexico. Nat. Ecol. Evol. 2, 520–528 (2018).

    Article  PubMed  Google Scholar 

  9. Zhou, Z. et al. Pan-genome Analysis of Ancient and Modern Salmonella enterica Demonstrates Genomic Stability of the Invasive Para C Lineage for Millennia. Curr. Biol. 28, 2420–2428.e10 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Alikhan, N.-F., Zhou, Z., Sergeant, M. J. & Achtman, M. A genomic overview of the population structure of Salmonella. PLoS Genet. 14, e1007261 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  11. Kirk, M. D. et al. World Health Organization estimates of the global and regional disease burden of 22 foodborne bacterial, protozoal, and viral diseases, 2010: a data synthesis. PLoS Med. 12, e1001921 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Kingsley, R. A. & Bäumler, A. J. Host adaptation and the emergence of infectious disease: the Salmonella paradigm. Mol. Microbiol. 36, 1006–1014 (2000).

    Article  CAS  PubMed  Google Scholar 

  13. Kingsley, R. A. et al. Epidemic multiple drug resistant Salmonella typhimurium causing invasive disease in sub-Saharan Africa have a distinct genotype. Genome Res. 19, 2279–2287 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Barrow, P. A. & Methner, U. Salmonella in Domestic Animals (CABI, 2013).

  15. Drancourt, M., Aboudharam, G., Signoli, M., Dutour, O. & Raoult, D. Detection of 400-year-old Yersinia pestis DNA in human dental pulp: an approach to the diagnosis of ancient septicemia. Proc. Natl Acad. Sci. USA 95, 12637–12640 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Anthony, D. W. The Horse, The Wheel, and Language: How Bronze-Age Riders from the Eurasian Steppes Shaped the Modern World (Princeton Univ. Press, 2010).

  17. Schulting, R. J. & Richards, M. P. in A Bronze Age Landscape in the Russian Steppes. The Samara Valley Project (eds Anthony, D. W. et al.) 127–149 (Cotsen Institute of Archaeology Press, 2016).

  18. Didelot, X. et al. Recombination and population structure in Salmonella enterica. PLoS Genet. 7, e1002191 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Haase, J. K. et al. Population genetic structure of 4,12:a:− Salmonella enterica strains from harbor porpoises. Appl. Environ. Microbiol. 78, 8829–8833 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Uzzau, S. et al. Host-adapted serotypes of Salmonella enterica. Epidemiol. Infect. 125, 229–255 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Taylor, J. & Douglas, S. H. Salmonella birkenhead: a new Salmonella type causing food poisoning in man. J. Clin. Pathol. 1, 237–239 (1948).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Rambaut, A., Lam, T. T., Max Carvalho, L. & Pybus, O. G. Exploring the temporal structure of heterochronous sequences using TempEst (formerly Path-O-Gen). Virus Evol. 2, vew007 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Hedge, J. & Wilson, D. J. Bacterial phylogenetic reconstruction from whole genomes is robust to recombination but demographic inference is not. mBio 5, e02158–02114 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Duchêne, S., Duchêne, D., Holmes, E. C. & Ho, S. Y. The performance of the date-randomization test in phylogenetic analyses of time-structured virus data. Mol. Biol. Evol. 32, 1895–1906 (2015).

    Article  PubMed  CAS  Google Scholar 

  25. Bouckaert, R. et al. BEAST 2: a software platform for Bayesian evolutionary analysis. PLoS Comput. Biol. 10, e1003537 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  26. Rhen, M. & Mastroeni, P. Salmonella: Molecular Biology and Pathogenesis (Horizon Scientific Press, 2007).

  27. Guiney, D. G. & Fierer, J. The role of the spv genes in Salmonella pathogenesis. Front. Microbiol. 2, 129 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Gulig, P. A. et al. Molecular analysis of spv virulence genes of the salmonella virulence plasmids. Mol. Microbiol. 7, 825–830 (1993).

    Article  CAS  PubMed  Google Scholar 

  29. Rotger, R. & Casadesús, J. The virulence plasmids of Salmonella. Int. Microbiol. 2, 177–184 (1999).

    CAS  PubMed  Google Scholar 

  30. Hackett, J., Wyk, P., Reeves, P. & Mathan, V. Mediation of serum resistance in Salmonella typhimurium by an 11-kilodalton polypeptide encoded by the cryptic plasmid. J. Infectious Dis. 155, 540–549 (1987).

    Article  CAS  Google Scholar 

  31. Langridge, G. C. et al. Patterns of genome evolution that have accompanied host adaptation in Salmonella. Proc. Natl Acad. Sci. USA 112, 863–868 (2015).

    Article  CAS  PubMed  Google Scholar 

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

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  33. Thomson, N. R. et al. Comparative genome analysis of Salmonella enteritidis PT4 and Salmonella gallinarum 287/91 provides insights into evolutionary and host adaptation pathways. Genome Res. 18, 1624–1637 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Parkhill, J. et al. Complete genome sequence of a multiple drug-resistant Salmonella enterica serovar Typhi CT18. Nature 413, 848 (2001).

    Article  CAS  PubMed  Google Scholar 

  35. Lee, S.-J. et al. Identification of a common immune signature in murine and human systemic salmonellosis. Proc. Natl Acad. Sci. USA 109, 4998–5003 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Seth-Smith, H. M. SPI-7: Salmonella’s Vi-encoding pathogenicity island. J. Infect. Dev. Cries 2, 267–271 (2008).

    Google Scholar 

  37. Omran, A. R. The epidemiologic transition: a theory of the epidemiology of population change. Milbank Q. 83, 731–757 (2005).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Pinhasi, R. & Stock, J. T. Human Bioarchaeology of the Transition to Agriculture (John Wiley & Sons, 2011).

  39. Miller, L. & Hurley, K. Infectious Disease Management in Animal Shelters (John Wiley & Sons, 2009).

  40. Schuster, C. J. et al. Infectious disease outbreaks related to drinking water in Canada, 1974–2001. Can. J. Public Health 96, 254–258 (2005).

  41. 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 

  42. Rohland, N., Harney, E., Mallick, S., Nordenfelt, S. & Reich, D. Partial uracil-DNA-glycosylase treatment for screening of ancient DNA. Philos. Trans. R. Soc. Lond. B 370, 20130624 (2015).

    Article  CAS  Google Scholar 

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

    Article  PubMed  Google Scholar 

  44. Gansauge, M.-T. et al. Single-stranded DNA library preparation from highly degraded DNA using T4 DNA ligase. Nucleic Acids Res. 45, e79 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. 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  CAS  Google Scholar 

  46. Haak, W. et al. Massive migration from the steppe was a source for Indo-European languages in Europe. Nature 522, 207–211 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Hübler, R. et al. HOPS: automated detection and authentication of pathogen DNA in archaeological remains. Genome Biol. 20, 280 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  48. Briggs, A. W. et al. Patterns of damage in genomic DNA sequences from a Neandertal. Proc. Natl Acad. Sci. USA 104, 14616–14621 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Peltzer, A. et al. EAGER: efficient ancient genome reconstruction. Genome Biol. 17, 60 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  51. Kircher, M. in Ancient DNA. Methods in Molecular Biology (Methods and Protocols) Vol. 480 (eds Shapiro, B. & Hofreiter, M.) 197–228 (Humana Press, 2012).

  52. Jolley, K. A. et al. Ribosomal multilocus sequence typing: universal characterization of bacteria from domain to strain. Microbiology 158, 1005–1015 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. 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 

  54. 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 

  55. Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2—approximately maximum-likelihood trees for large alignments. PLoS ONE 5, e9490 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. Moran, A. B. & Edwards, P. Three new Salmonella types: S. richmond, S. daytona and S. tallahassee. Proc. Soc. Exp. Biol. Med. 62, 294–296 (1946).

    Article  CAS  PubMed  Google Scholar 

  57. Van der Walt, M. L., Huchzermeyer, F. & Steyn, H. C. Salmonella isolated from crocodiles and other reptiles during the period 1985–1994 in South Africa. Onderstepoort J. Vet. Res. 64, 277–283 (1997).

    PubMed  Google Scholar 

  58. Paton, J. & Mirfattahi, M. Salmonella meningitis acquired from pet snakes. Arch. Dis. Child. 77, 91 (1997).

    Article  PubMed Central  Google Scholar 

  59. Pedersen, K., Sørensen, G., Szabo, I., Hächler, H. & Le Hello, S. Repeated isolation of Salmonella enterica Goverdhan, a very rare serovar, from Danish poultry surveillance samples. Vet. Microbiol. 174, 596–599 (2014).

    Article  PubMed  Google Scholar 

  60. Sharma, V., Rohde, R., Garg, D. & Kumar, A. Toads as natural reservoir of salmonella. Zentralbl. Bakteriol. Orig. A 239, 172–177 (1977).

    CAS  PubMed  Google Scholar 

  61. Sharma, V. & Singh, C. Salmonella goverdhan, a new serotype from sewage. Int. J. Syst. Evol. Microbiol. 17, 41–42 (1967).

    Google Scholar 

  62. Zhou, Z. et al. The EnteroBase user's guide, with case studies on Salmonella transmissions, Yersinia pestis phylogeny, and Escherichia core genomic diversity. Genome Res. 30, 138–152 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  63. Pagel, M. Detecting correlated evolution on phylogenies: a general method for the comparative analysis of discrete characters. Proc. R. Soc. Lond. B 255, 37–45 (1994).

    Article  Google Scholar 

  64. Zhou, Z. et al. Transient Darwinian selection in Salmonella enterica serovar Paratyphi A during 450 years of global spread of enteric fever. Proc. Natl Acad. Sci. USA 111, 12199–12204 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Jónsson, 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  PubMed  PubMed Central  CAS  Google Scholar 

  66. Renaud, G., Slon, V., Duggan, A. T. & Kelso, J. Schmutzi: estimation of contamination and endogenous mitochondrial consensus calling for ancient DNA. Genome Biol. 16, 224 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  67. Vianello, D. et al. HAPLOFIND: a new method for high‐throughput mtDNA Haplogroup assignment. Hum. Mutat. 34, 1189–1194 (2013).

    Article  PubMed  Google Scholar 

  68. Korneliussen, T. S., Albrechtsen, A. & Nielsen, R. ANGSD: analysis of next generation sequencing data. BMC Bioinformatics 15, 356 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Lazaridis, I. et al. Ancient human genomes suggest three ancestral populations for present-day Europeans. Nature 513, 409–413 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Patterson, N., Price, A. L. & Reich, D. Population structure and eigenanalysis. PLoS Genet. 2, e190 (2006).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  71. Alexander, D. H., Novembre, J. & Lange, K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 19, 1655–1664 (2009).

  72. Ramsden, C. et al. High rates of molecular evolution in Hantaviruses. Mol. Biol. Evol. 25, 1488–1492 (2008).

    Article  CAS  PubMed  Google Scholar 

  73. Stadler, T., Kühnert, D., Bonhoeffer, S. & Drummond, A. J. Birth–death skyline plot reveals temporal changes of epidemic spread in HIV and hepatitis C virus (HCV). Proc. Natl Acad. Sci. USA 110, 228–233 (2013).

    Article  CAS  PubMed  Google Scholar 

  74. Reimer, P. J. et al. IntCal13 and Marine13 radiocarbon age calibration curves 0–50,000 years cal BP. Radiocarbon 55, 1869–1887 (2013).

    Article  CAS  Google Scholar 

  75. Yoon, S. H., Park, Y.-K. & Kim, J. F. PAIDB v2. 0: exploration and analysis of pathogenicity and resistance islands. Nucleic Acids Res. 43, D624–D630 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  76. Fuentes, J. A., Villagra, N., Castillo-Ruiz, M. & Mora, G. C. The Salmonella Typhi hlyE gene plays a role in invasion of cultured epithelial cells and its functional transfer to S. Typhimurium promotes deep organ infection in mice. Res. Microbiol. 159, 279–287 (2008).

    Article  CAS  PubMed  Google Scholar 

  77. Vernikos, G. S. & Parkhill, J. Interpolated variable order motifs for identification of horizontally acquired DNA: revisiting the Salmonella pathogenicity islands. Bioinformatics 22, 2196–2203 (2006).

    Article  CAS  PubMed  Google Scholar 

  78. Blondel, C. J., Jiménez, J. C., Contreras, I. & Santiviago, C. A. Comparative genomic analysis uncovers 3 novel loci encoding type six secretion systems differentially distributed in Salmonella serotypes. BMC Genomics 10, 354 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  79. Elder, J. R. et al. The Salmonella pathogenicity island 13 contributes to pathogenesis in streptomycin pre-treated mice but not in day-old chickens. Gut Pathog. 8, 16 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  80. Shah, D. H. et al. Identification of Salmonella gallinarum virulence genes in a chicken infection model using PCR-based signature-tagged mutagenesis. Microbiology 151, 3957–3968 (2005).

    Article  CAS  PubMed  Google Scholar 

  81. Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. Preprint at https://arxiv.org/abs/1303.3997 (2013).

  82. 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 

  83. McKenna, A. et al. The genome analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).

  84. Fellows Yates, J. A. et al. Central European woolly mammoth population dynamics: insights from Late Pleistocene mitochondrial genomes. Sci. Rep. 7, 17714 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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Acknowledgements

We thank the Pathogenomics group at MPI SHH and the Lieberman laboratory at MIT for critical discussions. We thank M. O’Reilly for support in graphical design. Funding for this study came from the Max Planck Society and the European Research Council (grant agreement no. 771234 PALEoRIDER). F.M.K. was supported by DFG (grant no. KE 2408/1-1) and a generous MPI EVA guest office. I.S. is supported by SNF (grant no. CR31I3L_157024). EnteroBase was supported by BBSRC (no. BB/L020319/1). N.-F.A., Z.Z. and M.A. were supported by the Wellcome Trust (grant no. 202792/Z/ 16/Z).

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Authors and Affiliations

  1. Department of Archaeogenetics, Max Planck Institute for the Science of Human History, Jena, Germany

    Felix M. Key, Cosimo Posth, Ron Hübler, Maria A. Spyrou, Gunnar U. Neumann, Susanna Sabin, Marta Burri, Antje Wissgott, Aditya Kumar Lankapalli, Åshild J. Vågene, Rezeda Tukhbatova, Philipp W. Stockhammer, Kirsten Bos, Wolfgang Haak, Alexander Herbig & Johannes Krause

  2. Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA

    Felix M. Key

  3. Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Felix M. Key

  4. Transmission, Infection, Diversification & Evolution Group, Max Planck Institute for the Science of Human History, Jena, Germany

    Luis R. Esquivel-Gomez & Denise Kühnert

  5. Institute for Archaeological Sciences, Archaeo- and Palaeogenetics, University of Tuebingen, Tuebingen, Germany

    Anja Furtwängler

  6. Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany

    Matthias Meyer & Sarah Nagel

  7. Laboratory of Structural Biology, Kazan Federal University, Kazan, Russian Federation

    Rezeda Tukhbatova

  8. Samara State University of Social Sciences and Education, Samara, Russian Federation

    Aleksandr Khokhlov

  9. Institute of Archaeology named after A.Kh. Khalikov of the Academy of Sciences of the Republic of Tatarstan, Kazan, Russian Federation

    Andrey Chizhevsky

  10. Eurasia Department, German Archaeological Institute, Berlin, Germany

    Svend Hansen & Sabine Reinhold

  11. ‘Nasledie’ Cultural Heritage Unit, Stavropol, Russian Federation

    Andrey B. Belinsky & Alexey Kalmykov

  12. Department of Archaeology, Faculty of History, Lomonosov Moscow State University, Moscow, Russian Federation

    Anatoly R. Kantorovich

  13. Institute of Archaeology RAS, Moscow, Russian Federation

    Vladimir E. Maslov

  14. Institute for Pre- and Protohistoric Archaeology and Archaeology of the Roman Provinces, Ludwig Maximilian University Munich, Munich, Germany

    Philipp W. Stockhammer

  15. Department of Biology, University of Florence, Florence, Italy

    Stefania Vai, Alessandro Riga & David Caramelli

  16. Museum of Anthropology and Ethnology, Museum System of the University of Florence, Florence, Italy

    Monica Zavattaro

  17. Department of Archaeology, Durham University, Durham, UK

    Robin Skeates & Jessica Beckett

  18. School of Archaeology and Ancient History, Leicester University, Leicester, UK

    Maria Giuseppina Gradoli

  19. Institute of Archaeological Sciences and Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland

    Noah Steuri & Albert Hafner

  20. Archaeological Service of the Canton of Bern, Bern, Switzerland

    Marianne Ramstein

  21. Department of Physical Anthropology Institute of Forensic Medicine, University of Bern, Bern, Switzerland

    Inga Siebke & Sandra Lösch

  22. Department of Anthropology, Hacettepe University, Ankara, Turkey

    Yilmaz Selim Erdal

  23. Warwick Medical School, University of Warwick, Coventry, UK

    Nabil-Fareed Alikhan, Zhemin Zhou & Mark Achtman

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  1. Felix M. Key
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Contributions

F.M.K., A. Herbig and J.K. conceptualized the study. The original draft was written by F.M.K., which was then reviewed and edited by F.M.K., C.P., K.B., S.R., D.K., W.H., M.A., A. Herbig and J.K. F.M.K., C.P., L.R.E.-G. and D.K. carried out the formal analysis. F.M.K., C.P., M.A.S., G.U.N., A.F., S.S., M.B., A.W., M.M., S.N., R.T. and Z.Z. handled the investigation. F.M.K., R.H., Å.J.V., A.K.L., A. Khokhlov, A.C., S.H., A.B.B., A. Kalmykov, A.R.K., V.E.M., P.W.S., S.V., M.Z., A.R., D.C., R.S., J.B., M.G.G., N.S., A. Hafner, M.R., I.S., S.L., Y.S.E., N.-F.A., Z.Z., M.A., S.R. and W.H. contributed resources. A. Herbig and J.K. supervised.

Corresponding authors

Correspondence to Felix M. Key, Alexander Herbig or Johannes Krause.

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Extended data

Extended Data Fig. 1 Ancient human population genetic analysis.

a, PCA of newly reported ancient individuals with sufficient data (in red) and selected published ancient and modern individuals are projected onto principal components built with present-day West Eurasian populations (grey dots). b, ADMIXTURE analysis (K=10) of newly reported ancient individuals and relevant published ancient and modern individuals sorted by genetic clusters. Overview ancient human genetic data Supplementary Table 1 and further analysis Extended Data Fig. 2. EHG, Eastern hunter gatherer; E, Early; M, Middle; HG, hunter–gatherer; N, Neolithic; C, Caucasus; S, Scandinavian; W, Western; BA, Bronze Age.

Extended Data Fig. 2 Summary human genetic analysis.

a, ADMIXTURE analysis (K = 3 - 16) of newly reported ancient individuals (bold horizontal text) and published ancient and modern individuals sorted by genetic clusters and geographic origin (Europe, Near East and Caucasus, Asia, America, Africa). Each K was run five times and the replicate with the highest likelihood is reported. Ancient MK3001 shows Asian genetic ancestry components represented by Nganasan, Kankanaey, Atayal, and Ami. b, Box plot of five cross-validations (CV) values for every K calculated in ADMIXTURE. EHG, Eastern hunter gatherer; E, Early; M, Middle; HG, hunter–gatherer; N, Neolithic; C, Caucasus; S, Scandinavian; W, Western; BA, Bronze Age.

Extended Data Fig. 3 Maximum likelihood phylogeny of the AESB based on SNPs in positions present in 95% of strains.

Maximum likelihood tree of the AESB including the high coverage ancient genomes and 463 S. enterica genomes, considering all SNPs covered in at least 95% of strains (130,036 SNPs). New ancient genomes are shown in red, and previously reported ancient genomes (Tepos) in pink.

Extended Data Fig. 4 Recombination rate estimates for the AESB.

Estimated recombination rate is shown as recombination event per mutation event (r/m) and indicated on top of branch and by branch color. Recombination events have been inferred using all positions shared by 95% of strains from the AESB and are here reported for the SNPs shared by all strains on the AESB (correspond to maximum likelihood phylogeny shown in Fig. 2b). Maximum likelihood tree including all SNPs shared by at least 95% of strains from the AESB is shown in Extended Data Fig. 3.

Extended Data Fig. 5 Temporal signal analysis.

Results of the date randomization test for two subsets of the HC2600_1272 cluster. Circles represent mean substitution rate estimations with error bars representing 95% highest posterior density (HPD) intervals. For each subset 10 date randomizations were done. Significant temporal signal is indicated by non-overlapping HPD intervals between real data (red) and the randomizations (black), which is the case for both subsets.

Extended Data Fig. 6

Correlation between pseudogene frequency and time for all ancient genomes with mean genome-wide coverage above 5X.

Extended Data Fig. 7 Proportion of shared pseudogenes between strains across the AESB.

Proportion of pseudogene-sharing (0–100%) between strains on the AESB is shown in tones of red. Strains are ordered by phylogenetic branch and coloured accordingly.

Extended Data Fig. 8

Graphical abstract.

Extended Data Fig. 9 Mismatch distribution along positions at the 5′- and 3′- end of mapped sequencing reads.

C to T changes indicated in red and G to A changes in blue, all other substitutions in grey. IV3002 and MK3001 are UDG-half treated, which leads to observable damage only in the terminal positions. Plots generated with mapDamage2 (Jónsson H. et al, Bioinformatics 2013).

Extended Data Fig. 10 Photographs of archaeological specimens that harboured ancient S. enterica DNA.

(a) MUR009; (b) OBP001; (c) MUR019; (d) IKI003; (e) IV3002; (f) ETR001; (g) SUA004; (h) MK3001.

Supplementary information

Supplementary Information

Supplementary Information

Reporting Summary

Supplementary Data 1 and 2

Supplementary Data 1. Overview of pseudogenes across all genomes of the AESB, detailing branch association, number of pseudogenes, number of pan-genes present and cumulative size10. Supplementary Data 2. Overview of public data. ERR and ERS identifiers for all sequencing datasets generated.

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Key, F.M., Posth, C., Esquivel-Gomez, L.R. et al. Emergence of human-adapted Salmonella enterica is linked to the Neolithization process. Nat Ecol Evol 4, 324–333 (2020). https://doi.org/10.1038/s41559-020-1106-9

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