1932

Abstract

The last century has witnessed progress in the study of ancient infectious disease from purely medical descriptions of past ailments to dynamic interpretations of past population health that draw upon multiple perspectives. The recent adoption of high-throughput DNA sequencing has led to an expanded understanding of pathogen presence, evolution, and ecology across the globe. This genomic revolution has led to the identification of disease-causing microbes in both expected and unexpected contexts, while also providing for the genomic characterization of ancient pathogens previously believed to be unattainable by available methods. In this review we explore the development of DNA-based ancient pathogen research, the specialized methods and tools that have emerged to authenticate and explore infectious disease of the past, and the unique challenges that persist in molecular paleopathology. We offer guidelines to mitigate the impact of these challenges, which will allow for more reliable interpretations of data in this rapidly evolving field of investigation.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-micro-090817-062436
2019-09-08
2024-04-20
Loading full text...

Full text loading...

/deliver/fulltext/micro/73/1/annurev-micro-090817-062436.html?itemId=/content/journals/10.1146/annurev-micro-090817-062436&mimeType=html&fmt=ahah

Literature Cited

  1. 1. 
    Achtman M, Morelli G, Zhu P, Wirth T, Diehl I et al. 2004. Microevolution and history of the plague bacillus, Yersinia pestis. PNAS 101:17837–42
    [Google Scholar]
  2. 2. 
    Allentoft ME, Sikora M, Sjögren K-G, Rasmussen S, Rasmussen M et al. 2015. Population genomics of Bronze Age Eurasia. Nature 522:167
    [Google Scholar]
  3. 3. 
    Allison MJ, Mendoza D, Pezzia A 1973. Documentation of a case of tuberculosis in pre-Columbian America. Am. Rev. Respir. Dis. 107:985–91
    [Google Scholar]
  4. 4. 
    Angel JL. 1981. History and development of paleopathology. Am. J. Phys. Anthropol. 56:509–15
    [Google Scholar]
  5. 5. 
    Armelagos GJ. 2009. The Paleolithic disease-scape, the hygiene hypothesis, and the second epidemiological transition. The Hygiene Hypothesis and Darwinian Medicine G Rook 29–43 Basel, Switz: Springer
    [Google Scholar]
  6. 6. 
    Arora N, Schuenemann VJ, Jäger G, Peltzer A, Seitz A et al. 2017. Origin of modern syphilis and emergence of a pandemic Treponema pallidum cluster. Nat. Microbiol. 2:16245
    [Google Scholar]
  7. 7. 
    Aufderheide AC, Rodríguez-Martín C, Langsjoen O 1998. The Cambridge Encyclopedia of Human Paleopathology Cambridge, UK: Cambridge Univ. Press
  8. 8. 
    Ávila-Arcos MC, Cappellini E, Romero-Navarro JA, Wales N, Moreno-Mayar JV et al. 2011. Application and comparison of large-scale solution-based DNA capture-enrichment methods on ancient DNA. Sci. Rep. 1:74
    [Google Scholar]
  9. 9. 
    Baker O, Lee OY-C, Wu HH, Besra GS, Minnikin DE et al. 2015. Human tuberculosis predates domestication in ancient Syria. Tuberculosis 95:S4–12
    [Google Scholar]
  10. 10. 
    Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M et al. 2012. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J. Comput. Biol. 19:455–77
    [Google Scholar]
  11. 11. 
    Bar‐Gal GK, Kim MJ, Klein A, Shin DH, Oh CS et al. 2012. Tracing hepatitis B virus to the 16th century in a Korean mummy. Hepatology 56:1671–80
    [Google Scholar]
  12. 12. 
    Barrett R, Kuzawa CW, McDade T, Armelagos GJ 1998. Emerging and re-emerging infectious diseases: the third epidemiologic transition. Annu. Rev. Anthropol. 27:247–71Presents a theoretical framework for linking changes in disease landscape to social and ecological factors.
    [Google Scholar]
  13. 13. 
    Benedictow OJ. 2004. The Black Death, 1346–1353: The Complete History Woodbridge, UK: Boydell Brewer
  14. 14. 
    Benjak A, Avanzi C, Singh P, Loiseau C, Girma S et al. 2018. Phylogenomics and antimicrobial resistance of the leprosy bacillus Mycobacterium leprae. Nat. Commun 9:352
    [Google Scholar]
  15. 15. 
    Black FL. 1992. Why did they die?. Science 258:1739–41
    [Google Scholar]
  16. 16. 
    Boisvert S, Raymond F, Godzaridis É, Laviolette F, Corbeil J 2012. Ray Meta: scalable de novo metagenome assembly and profiling. Genome Biol 13:R122
    [Google Scholar]
  17. 17. 
    Bos KI, Harkins KM, Herbig A, Coscolla M, Weber N et al. 2014. Pre-Columbian mycobacterial genomes reveal seals as a source of New World human tuberculosis. Nature 514:494
    [Google Scholar]
  18. 18. 
    Bos KI, Herbig A, Sahl J, Waglechner N, Fourment M et al. 2016. Eighteenth century Yersinia pestis genomes reveal the long-term persistence of an historical plague focus. eLife 5:e12994
    [Google Scholar]
  19. 19. 
    Bos KI, Schuenemann VJ, Golding GB, Burbano HA, Waglechner N et al. 2011. A draft genome of Yersinia pestis from victims of the Black Death. Nature 478:506Publication of the first ancient pathogen genome.
    [Google Scholar]
  20. 20. 
    Bouckaert R, Heled J, Kühnert D, Vaughan T, Wu C-H et al. 2014. BEAST 2: a software platform for Bayesian evolutionary analysis. PLOS Comput. Biol. 10:e1003537
    [Google Scholar]
  21. 21. 
    Bouckaert R, Vaughan TG, Barido-Sottani J, Duchene S, Fourment M et al. 2018. BEAST 2.5: an advanced software platform for Bayesian evolutionary analysis. bioRxiv 474296. https://doi.org/10.1101/474296
    [Crossref]
  22. 22. 
    Bouwman AS, Brown TA. 2005. The limits of biomolecular palaeopathology: ancient DNA cannot be used to study venereal syphilis. J. Archaeol. Sci. 32:703–13
    [Google Scholar]
  23. 23. 
    Brosch R, Gordon SV, Marmiesse M, Brodin P, Buchrieser C et al. 2002. A new evolutionary scenario for the Mycobacterium tuberculosis complex. PNAS 99:3684–89
    [Google Scholar]
  24. 24. 
    Bryant J, Chewapreecha C, Bentley SD 2012. Developing insights into the mechanisms of evolution of bacterial pathogens from whole-genome sequences. Future Microbiol 7:1283–96
    [Google Scholar]
  25. 25. 
    Burbano HA, Hodges E, Green RE, Briggs AW, Krause J et al. 2010. Targeted investigation of the Neandertal genome by array-based sequence capture. Science 328:723–25First application of targeted enrichment for genomic analysis of an archaeological specimen.
    [Google Scholar]
  26. 26. 
    Caldwell JC. 2001. Population health in transition. Bull. World Health Organ. 79:159–60
    [Google Scholar]
  27. 27. 
    Cattaneo C, Gelsthorpe K, Phillips P, Sokol R 1992. Reliable identification of human albumin in ancient bone using ELISA and monoclonal antibodies. Am. J. Phys. Anthropol. 87:365–72
    [Google Scholar]
  28. 28. 
    Chain PS, Carniel E, Larimer FW, Lamerdin J, Stoutland P et al. 2004. Insights into the evolution of Yersinia pestis through whole-genome comparison with Yersinia pseudotuberculosis. PNAS 101:13826–31
    [Google Scholar]
  29. 29. 
    Comas I, Coscolla M, Luo T, Borrell S, Holt KE et al. 2013. Out-of-Africa migration and Neolithic coexpansion of Mycobacterium tuberculosis with modern humans. Nat. Genet. 45:1176
    [Google Scholar]
  30. 30. 
    Cook ND. 1998. Born to Die: Disease and New World Conquest, 1492–1650 Cambridge, UK: Cambridge Univ. Press
  31. 31. 
    Cooper A, Poinar HN. 2000. Ancient DNA: Do it right or not at all. Science 289:1139
    [Google Scholar]
  32. 32. 
    Cui Y, Yu C, Yan Y, Li D, Li Y et al. 2013. Historical variations in mutation rate in an epidemic pathogen, Yersinia pestis. PNAS 110:577–82
    [Google Scholar]
  33. 33. 
    Cunha BA. 2004. The cause of the plague of Athens: plague, typhoid, typhus, smallpox, or measles?. Infect. Dis. Clin. 18:29–43
    [Google Scholar]
  34. 34. 
    Daley T, Smith AD. 2013. Predicting the molecular complexity of sequencing libraries. Nat. Methods 10:325
    [Google Scholar]
  35. 35. 
    de Barros Damgaard P, Marchi N, Rasmussen S, Peyrot M, Renaud G et al. 2018. 137 ancient human genomes from across the Eurasian steppes. Nature 557:369
    [Google Scholar]
  36. 36. 
    DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR et al. 2011. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43:491
    [Google Scholar]
  37. 37. 
    Devault AM, McLoughlin K, Jaing C, Gardner S, Porter TM et al. 2014. Ancient pathogen DNA in archaeological samples detected with a Microbial Detection Array. Sci. Rep. 4:4245
    [Google Scholar]
  38. 38. 
    Devault AM, Mortimer TD, Kitchen A, Kiesewetter H, Enk JM et al. 2017. A molecular portrait of maternal sepsis from Byzantine Troy. eLife 6:e20983
    [Google Scholar]
  39. 39. 
    Devignat R. 1951. Variétés de l'espèce Pasteurella pestis: nouvelle hypothèse. Bull. World Health Organ. 4:247
    [Google Scholar]
  40. 40. 
    Didelot X, Wilson DJ. 2015. ClonalFrameML: efficient inference of recombination in whole bacterial genomes. PLOS Comput. Biol. 11:e1004041
    [Google Scholar]
  41. 41. 
    Drancourt M, Aboudharam G, Signoli M, Dutour O, Raoult D 1998. Detection of 400-year-old Yersinia pestis DNA in human dental pulp: an approach to the diagnosis of ancient septicemia. PNAS 95:12637–40
    [Google Scholar]
  42. 42. 
    Drummond AJ, Bouckaert RR. 2015. Bayesian Evolutionary Analysis with BEAST Cambridge, UK: Cambridge Univ. Press
  43. 43. 
    Drummond AJ, Pybus OG, Rambaut A, Forsberg R, Rodrigo AG 2003. Measurably evolving populations. Trends Ecol. Evol. 18:481–88
    [Google Scholar]
  44. 44. 
    Drummond AJ, Rambaut A. 2007. BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evol. Biol. 7:214
    [Google Scholar]
  45. 45. 
    Drummond AJ, Rambaut A, Shapiro B, Pybus OG 2005. Bayesian coalescent inference of past population dynamics from molecular sequences. Mol. Biol. Evol. 22:1185–92
    [Google Scholar]
  46. 46. 
    Duchêne S, Duchêne D, Holmes EC, Ho SY 2015. The performance of the date-randomization test in phylogenetic analyses of time-structured virus data. Mol. Biol. Evol. 32:1895–906
    [Google Scholar]
  47. 47. 
    Duchêne S, Holt KE, Weill F-X, Le Hello S, Hawkey J et al. 2016. Genome-scale rates of evolutionary change in bacteria. Microbial Genom 2:e000094
    [Google Scholar]
  48. 48. 
    Duggan AT, Perdomo MF, Piombino-Mascali D, Marciniak S, Poinar D et al. 2016. 17th century variola virus reveals the recent history of smallpox. Curr. Biol. 26:3407–12
    [Google Scholar]
  49. 49. 
    Falush D, Stephens M, Pritchard JK 2003. Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164:1567–87
    [Google Scholar]
  50. 50. 
    Fan Y, Wu R, Chen M-H, Kuo L, Lewis PO 2010. Choosing among partition models in Bayesian phylogenetics. Mol. Biol. Evol. 28:523–32
    [Google Scholar]
  51. 51. 
    Feldman M, Harbeck M, Keller M, Spyrou MA, Rott A et al. 2016. A high-coverage Yersinia pestis genome from a sixth-century Justinianic Plague victim. Mol. Biol. Evol. 33:2911–23
    [Google Scholar]
  52. 52. 
    Felsenstein J. 1978. Cases in which parsimony or compatibility methods will be positively misleading. Syst. Zool. 27:401–10
    [Google Scholar]
  53. 53. 
    Fu Q, Meyer M, Gao X, Stenzel U, Burbano HA et al. 2013. DNA analysis of an early modern human from Tianyuan Cave, China. PNAS 110:2223–27
    [Google Scholar]
  54. 54. 
    Fumagalli M, Sironi M, Pozzoli U, Ferrer-Admettla A, Pattini L, Nielsen R 2011. Signatures of environmental genetic adaptation pinpoint pathogens as the main selective pressure through human evolution. PLOS Genet 7:e1002355
    [Google Scholar]
  55. 55. 
    Gagneux S. 2018. Ecology and evolution of Mycobacterium tuberculosis. Nat. Rev. Microbiol 16:202
    [Google Scholar]
  56. 56. 
    Gamba C, Jones ER, Teasdale MD, McLaughlin RL, Gonzalez-Fortes G et al. 2014. Genome flux and stasis in a five millennium transect of European prehistory. Nat. Commun. 5:5257
    [Google Scholar]
  57. 57. 
    Garamszegi LZ. 2014. Global distribution of malaria-resistant MHC-HLA alleles: the number and frequencies of alleles and malaria risk. Malaria J 13:349
    [Google Scholar]
  58. 58. 
    Gelabert P, Sandoval-Velasco M, Olalde I, Fregel R, Rieux A et al. 2016. Mitochondrial DNA from the eradicated European Plasmodium vivax and P. falciparum from 70-year-old slides from the Ebro Delta in Spain. PNAS 113:11495–500
    [Google Scholar]
  59. 59. 
    Giacani L, Lukehart SA. 2014. The endemic treponematoses. Clin. Microbiol. Rev. 27:89–115
    [Google Scholar]
  60. 60. 
    Gogarten JF, Düx A, Schuenemann VJ, Nowak K, Boesch C et al. 2016. Tools for opening new chapters in the book of Treponema pallidum evolutionary history. Clin. Microbiol. Infect. 22:916–21
    [Google Scholar]
  61. 61. 
    Green RE, Krause J, Briggs AW, Maricic T, Stenzel U et al. 2010. A draft sequence of the Neandertal genome. Science 328:710–22
    [Google Scholar]
  62. 62. 
    Guellil M, Kersten O, Namouchi A, Bauer EL, Derrick M et al. 2018. Genomic blueprint of a relapsing fever pathogen in 15th century Scandinavia. PNAS 115:10422–27
    [Google Scholar]
  63. 63. 
    Guindon S, Dufayard J-F, Lefort V, Anisimova M, Hordijk W, Gascuel O 2010. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst. Biol. 59:307–21
    [Google Scholar]
  64. 64. 
    Gurevich A, Saveliev V, Vyahhi N, Tesler G 2013. QUAST: quality assessment tool for genome assemblies. Bioinformatics 29:1072–75
    [Google Scholar]
  65. 65. 
    Gutierrez MC, Brisse S, Brosch R, Fabre M, Omaïs B et al. 2005. Ancient origin and gene mosaicism of the progenitor of Mycobacterium tuberculosis. PLOS Pathog 1:e5
    [Google Scholar]
  66. 66. 
    Haak W, Lazaridis I, Patterson N, Rohland N, Mallick S et al. 2015. Massive migration from the steppe was a source for Indo-European languages in Europe. Nature 522:207
    [Google Scholar]
  67. 67. 
    Haensch S, Bianucci R, Signoli M, Rajerison M, Schultz M et al. 2010. Distinct clones of Yersinia pestis caused the black death. PLOS Pathog 6:e1001134
    [Google Scholar]
  68. 68. 
    Hansen HB, Damgaard PB, Margaryan A, Stenderup J, Lynnerup N et al. 2017. Comparing ancient DNA preservation in petrous bone and tooth cementum. PLOS ONE 12:e0170940
    [Google Scholar]
  69. 69. 
    Hasegawa M, Kishino H, Yano T-A 1985. Dating of the human-ape splitting by a molecular clock of mitochondrial DNA. J. Mol. Evol. 22:160–74
    [Google Scholar]
  70. 70. 
    Herbig A, Maixner F, Bos K, Zink A, Krause J, Huson D 2016. MALT: fast alignment and analysis of metagenomic DNA sequence data applied to the Tyrolean Iceman. bioRxiv 050559. https://doi.org/10.1101/050559
    [Crossref]
  71. 71. 
    Hershberg R, Lipatov M, Small PM, Sheffer H, Niemann S et al. 2008. High functional diversity in Mycobacterium tuberculosis driven by genetic drift and human demography. PLOS Biol 6:e311
    [Google Scholar]
  72. 72. 
    Ho SY, Lanfear R, Bromham L, Phillips MJ, Soubrier J et al. 2011. Time‐dependent rates of molecular evolution. Mol. Ecol. 20:3087–101
    [Google Scholar]
  73. 73. 
    Hodges E, Smith A, Kendall J, Xuan Z, Ravi K et al. 2009. High definition profiling of mammalian DNA methylation by array capture and single molecule bisulfite sequencing. Genome Res 19:1593–605
    [Google Scholar]
  74. 74. 
    Holladay AJ, Poole JCF. 1979. Thucydides and the Plague of Athens. Classical Q 29:282–300
    [Google Scholar]
  75. 75. 
    Huebler R, Key FMM, Warinner C, Bos KI, Krause J, Herbig A 2019. HOPS: Automated detection and authentication of pathogen DNA in archaeological remains. bioRxiv 534198. https://doi.org/10.1101/534198
    [Crossref]
  76. 76. 
    Huson DH, Beier S, Flade I, Górska A, El-Hadidi M et al. 2016. MEGAN community edition-interactive exploration and analysis of large-scale microbiome sequencing data. PLOS Comput. Biol. 12:e1004957
    [Google Scholar]
  77. 77. 
    Jankute M, Nataraj V, Lee OY-C, Wu HH, Ridell M et al. 2017. The role of hydrophobicity in tuberculosis evolution and pathogenicity. Sci. Rep. 7:1315
    [Google Scholar]
  78. 78. 
    Jónsson H, Ginolhac A, Schubert M, Johnson PL, Orlando L 2013. mapDamage2.0: fast approximate Bayesian estimates of ancient DNA damage parameters. Bioinformatics 29:1682–84A popular program for quantitating ancient DNA damage for the purpose of authentication.
    [Google Scholar]
  79. 79. 
    Kamerbeek J, Schouls L, Kolk A, Van Agterveld M, Van Soolingen D et al. 1997. Simultaneous detection and strain differentiation of Mycobacterium tuberculosis for diagnosis and epidemiology. J. Clin. Microbiol. 35:907–14
    [Google Scholar]
  80. 80. 
    Kawash JK, Smith SD, Karaiskos S, Grigoriev A 2018. ARIADNA: machine learning method for ancient DNA variant discovery. DNA Res 25:619–27
    [Google Scholar]
  81. 81. 
    Kay GL, Sergeant MJ, Giuffra V, Bandiera P, Milanese M et al. 2014. Recovery of a medieval Brucella melitensis genome using shotgun metagenomics. mBio 5:e01337–14
    [Google Scholar]
  82. 82. 
    Kay GL, Sergeant MJ, Zhou Z, Chan JZ-M, Millard A et al. 2015. Eighteenth-century genomes show that mixed infections were common at time of peak tuberculosis in Europe. Nat. Commun. 6:6717
    [Google Scholar]
  83. 83. 
    Keller M, Spyrou MA, Scheib CL, Kröpelin A, Haas-Gebhard B et al. 2018. Ancient Yersinia pestis genomes from across Western Europe reveal early diversification during the First Pandemic (541–750). bioRxiv 481226. https://doi.org/10.1101/481226
    [Crossref]
  84. 84. 
    Key FM, Posth C, Krause J, Herbig A, Bos KI 2017. Mining metagenomic data sets for ancient DNA: recommended protocols for authentication. Trends Genet 33:508–20
    [Google Scholar]
  85. 85. 
    Kingman JFC. 1982. The coalescent. Stoch. Process. Appl. 13:235–48
    [Google Scholar]
  86. 86. 
    Korber B, Muldoon M, Theiler J, Gao F, Gupta R et al. 2000. Timing the ancestor of the HIV-1 pandemic strains. Science 288:1789–96
    [Google Scholar]
  87. 87. 
    Krause-Kyora B, Nutsua M, Boehme L, Pierini F, Pedersen DD et al. 2018. Ancient DNA study reveals HLA susceptibility locus for leprosy in medieval Europeans. Nat. Commun. 9:1569Provides a first exploration of the genetic basis of host immunity in the context of ancient pathogen genomic data.
    [Google Scholar]
  88. 88. 
    Krause-Kyora B, Susat J, Key FM, Kühnert D, Bosse E et al. 2018. Neolithic and medieval virus genomes reveal complex evolution of hepatitis B. eLife 7:e36666
    [Google Scholar]
  89. 89. 
    Kühnert D, Stadler T, Vaughan TG, Drummond AJ 2016. Phylodynamics with migration: a computational framework to quantify population structure from genomic data. Mol. Biol. Evol. 33:2102–16
    [Google Scholar]
  90. 90. 
    Kumar S, Stecher G, Tamura K 2016. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol. Biol. Evol. 33:1870–74
    [Google Scholar]
  91. 91. 
    Lander ES, Waterman MS. 1988. Genomic mapping by fingerprinting random clones: a mathematical analysis. Genomics 2:231–39
    [Google Scholar]
  92. 92. 
    Larsen CS. 2006. The agricultural revolution as environmental catastrophe: Implications for health and lifestyle in the Holocene. Quat. Int. 150:12–20
    [Google Scholar]
  93. 93. 
    Lartillot N, Philippe H. 2006. Computing Bayes factors using thermodynamic integration. Syst. Biol. 55:195–207
    [Google Scholar]
  94. 94. 
    Lathem WW, Price PA, Miller VL, Goldman WE 2007. A plasminogen-activating protease specifically controls the development of primary pneumonic plague. Science 315:509–13
    [Google Scholar]
  95. 95. 
    Lazaridis I, Patterson N, Mittnik A, Renaud G, Mallick S et al. 2014. Ancient human genomes suggest three ancestral populations for present-day Europeans. Nature 513:409
    [Google Scholar]
  96. 96. 
    Leaché AD, Banbury BL, Felsenstein J, De Oca AN-M, Stamatakis A 2015. Short tree, long tree, right tree, wrong tree: new acquisition bias corrections for inferring SNP phylogenies. Syst. Biol. 64:1032–47
    [Google Scholar]
  97. 97. 
    Lees JA, Kendall M, Parkhill J, Colijn C, Bentley SD, Harris SR 2018. Evaluation of phylogenetic reconstruction methods using bacterial whole genomes: a simulation based study. Wellcome Open Res 3:33
    [Google Scholar]
  98. 98. 
    Li D, Liu C-M, Luo R, Sadakane K, Lam T-W 2015. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics 31:1674–76
    [Google Scholar]
  99. 99. 
    Li H, Handsaker B, Wysoker A, Fennell T, Ruan J et al. 2009. The sequence alignment/map format and SAMtools. Bioinformatics 25:2078–79
    [Google Scholar]
  100. 100. 
    Lindahl T. 1993. Instability and decay of the primary structure of DNA. Nature 362:709
    [Google Scholar]
  101. 101. 
    Lindo J, Huerta-Sanchez E, Nakagome S, Rasmussen M, Petzelt B et al. 2016. Demographic and immune-based selection shifts before and after European contact inferred from 50 ancient and modern exomes from the Northwest Coast of North America. bioRxiv 051078. https://doi.org/10.1101/051078
    [Crossref]
  102. 102. 
    Link V, Kousathanas A, Veeramah K, Sell C, Scheu A, Wegmann D 2017. ATLAS: analysis tools for low-depth and ancient samples. bioRxiv 105346. https://doi.org/10.1101/105346
    [Crossref]
  103. 103. 
    Liu W, Li Y, Shaw KS, Learn GH, Plenderleith LJ et al. 2014. African origin of the malaria parasite Plasmodium vivax. Nat. Commun 5:3346
    [Google Scholar]
  104. 104. 
    Louvel G, Der Sarkissian C, Hanghøj K, Orlando L 2016. metaBIT, an integrative and automated metagenomic pipeline for analysing microbial profiles from high‐throughput sequencing shotgun data. Mol. Ecol. Resour. 16:1415–27
    [Google Scholar]
  105. 105. 
    Luhmann N, Doerr D, Chauve C 2017. Comparative scaffolding and gap filling of ancient bacterial genomes applied to two ancient Yersinia pestis genomes. Microbial Genom 3:e000123
    [Google Scholar]
  106. 106. 
    Lukoschek V, Keogh JS, Avise JC 2011. Evaluating fossil calibrations for dating phylogenies in light of rates of molecular evolution: a comparison of three approaches. Syst. Biol. 61:22–43
    [Google Scholar]
  107. 107. 
    Luo R, Liu B, Xie Y, Li Z, Huang W et al. 2012. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Gigascience 1:18 Erratum. 2015 Gigascience 4:30
    [Google Scholar]
  108. 108. 
    Maixner F, Krause-Kyora B, Turaev D, Herbig A, Hoopmann MR et al. 2016. The 5300-year-old Helicobacter pylori genome of the Iceman. Science 351:162–65
    [Google Scholar]
  109. 109. 
    Mann AE, Sabin S, Ziesemer K, Vågene ÅJ, Schroeder H et al. 2018. Differential preservation of endogenous human and microbial DNA in dental calculus and dentin. Sci. Rep. 8:9822
    [Google Scholar]
  110. 110. 
    Marciniak S, Prowse TL, Herring DA, Klunk J, Kuch M et al. 2016. Plasmodium falciparum malaria in 1st–2nd century CE southern Italy. Curr. Biol. 26:R1220–22
    [Google Scholar]
  111. 111. 
    Maricic T, Whitten M, Pääbo S 2010. Multiplexed DNA sequence capture of mitochondrial genomes using PCR products. PLOS ONE 5:e14004
    [Google Scholar]
  112. 112. 
    Mathieson I, Lazaridis I, Rohland N, Mallick S, Patterson N et al. 2015. Genome-wide patterns of selection in 230 ancient Eurasians. Nature 528:499
    [Google Scholar]
  113. 113. 
    Maturana Russel P, Brewer BJ, Klaere S, Bouckaert RR 2019. Model selection and parameter inference in phylogenetics using Nested Sampling. Syst. Biol. 68:219–33
    [Google Scholar]
  114. 114. 
    Mbanefo EC, Ahmed AM, Titouna A, Elmaraezy A, Trang NTH et al. 2017. Association of glucose-6-phosphate dehydrogenase deficiency and malaria: a systematic review and meta-analysis. Sci. Rep. 7:45963
    [Google Scholar]
  115. 115. 
    McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K et al. 2010. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 20:1297–303
    [Google Scholar]
  116. 116. 
    McNally A, Thomson NR, Reuter S, Wren BW 2016. ‘Add, stir and reduce’: Yersinia spp. as model bacteria for pathogen evolution. Nat. Rev. Microbiol. 14:177
    [Google Scholar]
  117. 117. 
    Mendum TA, Schuenemann VJ, Roffey S, Taylor GM, Wu H et al. 2014. Mycobacterium leprae genomes from a British medieval leprosy hospital: towards understanding an ancient epidemic. BMC Genom 15:270
    [Google Scholar]
  118. 118. 
    Millar BC, Moore JE. 2006. Emerging pathogens in infectious diseases: definitions, causes and trends. Rev. Med. Microbiol. 17:101–6
    [Google Scholar]
  119. 119. 
    Morgulis A, Gertz EM, Schäffer AA, Agarwala R 2006. A fast and symmetric DUST implementation to mask low-complexity DNA sequences. J. Comput. Biol. 13:1028–40
    [Google Scholar]
  120. 120. 
    Mühlemann B, Jones TC, de Barros Damgaard P, Allentoft ME, Shevnina I et al. 2018. Ancient hepatitis B viruses from the Bronze Age to the Medieval period. Nature 557:418–23 Correction. 2018 Nature 562:E4
    [Google Scholar]
  121. 121. 
    Mühlemann B, Margaryan A, de Barros Damgaard P, Allentoft ME, Vinner L et al. 2018. Ancient human parvovirus B19 in Eurasia reveals its long-term association with humans. PNAS 115:7557–62
    [Google Scholar]
  122. 122. 
    Müller NF, Stadler T, Rasmussen D 2018. MASCOT: parameter and state inference under the marginal structured coalescent approximation. Bioinformatics 34:3843–48
    [Google Scholar]
  123. 123. 
    Namiki T, Hachiya T, Tanaka H, Sakakibara Y 2012. MetaVelvet: an extension of Velvet assembler to de novo metagenome assembly from short sequence reads. Nucleic Acids Res 40:e155
    [Google Scholar]
  124. 124. 
    Navascués M, Emerson BC. 2009. Elevated substitution rate estimates from ancient DNA: model violation and bias of Bayesian methods. Mol. Ecol. 18:4390–97
    [Google Scholar]
  125. 125. 
    Nguyen L-T, Schmidt HA, von Haeseler A, Minh BQ 2014. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32:268–74
    [Google Scholar]
  126. 126. 
    Nurk S, Meleshko D, Korobeynikov A, Pevzner PA 2017. metaSPAdes: a new versatile metagenomic assembler. Genome Res 27:824–34
    [Google Scholar]
  127. 127. 
    Ochman H, Moran NA. 2001. Genes lost and genes found: evolution of bacterial pathogenesis and symbiosis. Science 292:1096–99
    [Google Scholar]
  128. 128. 
    Ortner DJ 2003. Identification of Pathological Conditions in Human Skeletal Remains San Diego, CA: Academic
  129. 129. 
    Pääbo S. 1989. Ancient DNA: extraction, characterization, molecular cloning, and enzymatic amplification. PNAS 86:1939–43
    [Google Scholar]
  130. 130. 
    Papagrigorakis MJ, Yapijakis C, Synodinos PN, Baziotopoulou-Valavani E 2006. DNA examination of ancient dental pulp incriminates typhoid fever as a probable cause of the Plague of Athens. Int. J. Infect. Dis. 10:206–14
    [Google Scholar]
  131. 131. 
    Pepperell CS, Granka JM, Alexander DC, Behr MA, Chui L et al. 2011. Dispersal of Mycobacterium tuberculosis via the Canadian fur trade. PNAS 108:6526–31
    [Google Scholar]
  132. 132. 
    Price MN, Dehal PS, Arkin AP 2010. FastTree 2—approximately maximum-likelihood trees for large alignments. PLOS ONE 5:e9490
    [Google Scholar]
  133. 133. 
    Pritchard JK, Stephens M, Donnelly P 2000. Inference of population structure using multilocus genotype data. Genetics 155:945–59
    [Google Scholar]
  134. 134. 
    Prüfer K. 2018. snpAD: an ancient DNA genotype caller. Bioinformatics 34:4165–71
    [Google Scholar]
  135. 135. 
    Ramsden C, Holmes EC, Charleston MA 2008. Hantavirus evolution in relation to its rodent and insectivore hosts: no evidence for codivergence. Mol. Biol. Evol. 26:143–53
    [Google Scholar]
  136. 136. 
    Rascovan N, Sjögren K-G, Kristiansen K, Nielsen R, Willerslev E et al. 2018. Emergence and spread of basal lineages of Yersinia pestis during the Neolithic decline. Cell 176:295–305.e10
    [Google Scholar]
  137. 137. 
    Rasmussen S, Allentoft ME, Nielsen K, Orlando L, Sikora M et al. 2015. Early divergent strains of Yersinia pestis in Eurasia 5,000 years ago. Cell 163:571–82
    [Google Scholar]
  138. 138. 
    Reich D, Green RE, Kircher M, Krause J, Patterson N et al. 2010. Genetic history of an archaic hominin group from Denisova Cave in Siberia. Nature 468:1053
    [Google Scholar]
  139. 139. 
    Rieux A, Balloux F. 2016. Inferences from tip‐calibrated phylogenies: a review and a practical guide. Mol. Ecol. 25:1911–24
    [Google Scholar]
  140. 140. 
    Ross ZP, Klunk J, Fornaciari G, Giuffra V, Duchêne S et al. 2018. The paradox of HBV evolution as revealed from a 16th century mummy. PLOS Pathog 14: e1006750. Correction. 2018 PLOS Pathog 14:e1006887
    [Google Scholar]
  141. 141. 
    Rothschild BM, Martin LD, Lev G, Bercovier H, Bar-Gal GK et al. 2001. Mycobacterium tuberculosis complex DNA from an extinct bison dated 17,000 years before the present. Clin. Infect. Dis. 33:305–11
    [Google Scholar]
  142. 142. 
    Sabeti PC, Walsh E, Schaffner SF, Varilly P, Fry B et al. 2005. The case for selection at CCR5-Δ32. PLOS Biol 3:e378
    [Google Scholar]
  143. 143. 
    Salo WL, Aufderheide AC, Buikstra J, Holcomb TA 1994. Identification of Mycobacterium tuberculosis DNA in a pre-Columbian Peruvian mummy. PNAS 91:2091–94
    [Google Scholar]
  144. 144. 
    Sanderson MJ, McMahon MM, Steel M 2010. Phylogenomics with incomplete taxon coverage: the limits to inference. BMC Evol. Biol. 10:155
    [Google Scholar]
  145. 145. 
    Sawyer S, Krause J, Guschanski K, Savolainen V, Pääbo S 2012. Temporal patterns of nucleotide misincorporations and DNA fragmentation in ancient DNA. PLOS ONE 7:e34131
    [Google Scholar]
  146. 146. 
    Schmidt HA, Strimmer K, Vingron M, von Haeseler A 2002. TREE-PUZZLE: maximum likelihood phylogenetic analysis using quartets and parallel computing. Bioinformatics 18:502–4
    [Google Scholar]
  147. 147. 
    Schuenemann VJ, Avanzi C, Krause-Kyora B, Seitz A, Herbig A et al. 2018. Ancient Mycobacterium leprae genomes reveal an unexpected diversity of leprosy in medieval Europe. Am. J. Phys. Anthropol. 165:245
    [Google Scholar]
  148. 148. 
    Schuenemann VJ, Bos K, DeWitte S, Schmedes S, Jamieson J et al. 2011. Targeted enrichment of ancient pathogens yielding the pPCP1 plasmid of Yersinia pestis from victims of the Black Death. PNAS 108:E746–52
    [Google Scholar]
  149. 149. 
    Schuenemann VJ, Lankapalli AK, Barquera R, Nelson EA, Hernández DI et al. 2018. Historic Treponema pallidum genomes from Colonial Mexico retrieved from archaeological remains. PLOS Neglected Trop. Dis. 12:e0006447
    [Google Scholar]
  150. 150. 
    Schuenemann VJ, Singh P, Mendum TA, Krause-Kyora B, Jäger G et al. 2013. Genome-wide comparison of medieval and modern Mycobacterium leprae. Science 341:179–83
    [Google Scholar]
  151. 151. 
    Sczyrba A, Hofmann P, Belmann P, Koslicki D, Janssen S et al. 2017. Critical assessment of metagenome interpretation—a benchmark of metagenomics software. Nat. Methods 14:1063
    [Google Scholar]
  152. 152. 
    Shapiro B, Rambaut A, Gilbert MTP 2006. No proof that typhoid caused the Plague of Athens (a reply to Papagrigorakis et al.). Int. J. Infect. Dis. 10:334–35
    [Google Scholar]
  153. 153. 
    Shennan S, Downey SS, Timpson A, Edinborough K, Colledge S et al. 2013. Regional population collapse followed initial agriculture booms in mid-Holocene Europe. Nat. Commun. 4:2486
    [Google Scholar]
  154. 154. 
    Sims D, Sudbery I, Ilott NE, Heger A, Ponting CP 2014. Sequencing depth and coverage: key considerations in genomic analyses. Nat. Rev. Genet. 15:121
    [Google Scholar]
  155. 155. 
    Spyrou MA, Tukhbatova RI, Feldman M, Drath J, Kacki S et al. 2016. Historical Y. pestis genomes reveal the European Black Death as the source of ancient and modern plague pandemics. Cell Host Microbe 19:874–81
    [Google Scholar]
  156. 156. 
    Spyrou MA, Tukhbatova RI, Wang C-C, Valtueña AA, Lankapalli AK et al. 2018. Analysis of 3800-year-old Yersinia pestis genomes suggests Bronze Age origin for bubonic plague. Nat. Commun. 9:2234
    [Google Scholar]
  157. 157. 
    Sreevatsan S, Pan X, Stockbauer KE, Connell ND, Kreiswirth BN et al. 1997. Restricted structural gene polymorphism in the Mycobacterium tuberculosis complex indicates evolutionarily recent global dissemination. PNAS 94:9869–74
    [Google Scholar]
  158. 158. 
    Stadler T, Kühnert D, Bonhoeffer S, Drummond AJ 2013. Birth–death skyline plot reveals temporal changes of epidemic spread in HIV and hepatitis C virus (HCV). PNAS 110:228–33
    [Google Scholar]
  159. 159. 
    Stamatakis A. 2014. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30:1312–13
    [Google Scholar]
  160. 160. 
    Steinbock RT. 1976. Paleopathological Diagnosis and Interpretation: Bone Diseases in Ancient Human Populations Springfield, IL: Charles C Thomas
  161. 161. 
    Stephens JC, Reich DE, Goldstein DB, Shin HD, Smith MW et al. 1998. Dating the origin of the CCR5-Δ32 AIDS-resistance allele by the coalescence of haplotypes. Am. J. Hum. Genet. 62:1507–15
    [Google Scholar]
  162. 162. 
    Sullivan J, Joyce P. 2005. Model selection in phylogenetics. Annu. Rev. Ecol. Evol. Syst. 36:445–66
    [Google Scholar]
  163. 163. 
    Tavaré S. 1986. Some probabilistic and statistical problems in the analysis of DNA sequences. Lect. Math. Life Sci. 17:57–86
    [Google Scholar]
  164. 164. 
    Taylor GM, Widdison S, Brown IN, Young D, Molleson T 2000. A mediaeval case of lepromatous leprosy from 13–14th century Orkney, Scotland. J. Archaeol. Sci. 27:1133–38
    [Google Scholar]
  165. 165. 
    Taylor SM, Cerami C, Fairhurst RM 2013. Hemoglobinopathies: slicing the Gordian knot of Plasmodium falciparum malaria pathogenesis. PLOS Pathog 9:e1003327
    [Google Scholar]
  166. 166. 
    Truong DT, Franzosa EA, Tickle TL, Scholz M, Weingart G et al. 2015. MetaPhlAn2 for enhanced metagenomic taxonomic profiling. Nat. Methods 12:902
    [Google Scholar]
  167. 167. 
    Vågene ÅJ, Herbig A, Campana MG, Robles García NM, Warinner C et al. 2018. Salmonella enterica genomes from victims of a major sixteenth-century epidemic in Mexico. Nat. Ecol. Evol. 2:520–28An example of a nonselective screening method for the identification of ancient pathogens.
    [Google Scholar]
  168. 168. 
    Valtueña AA, Mittnik A, Key FM, Haak W, Allmäe R et al. 2017. The Stone Age plague and its persistence in Eurasia. Curr. Biol. 27:3683–91.e8
    [Google Scholar]
  169. 169. 
    Van der Walt AJ, Van Goethem MW, Ramond J-B, Makhalanyane TP, Reva O, Cowan DA 2017. Assembling metagenomes, one community at a time. BMC Genom 18:521
    [Google Scholar]
  170. 170. 
    Vernikos G, Medini D, Riley DR, Tettelin H 2015. Ten years of pan-genome analyses. Curr. Opin. Microbiol. 23:148–54
    [Google Scholar]
  171. 171. 
    Von Hunnius TE, Yang D, Eng B, Waye JS, Saunders SR 2007. Digging deeper into the limits of ancient DNA research on syphilis. J. Archaeol. Sci. 34:2091–100
    [Google Scholar]
  172. 172. 
    Wagner DM, Klunk J, Harbeck M, Devault A, Waglechner N et al. 2014. Yersinia pestis and the Plague of Justinian 541–543 AD: a genomic analysis. Lancet Infect. Dis. 14:319–26
    [Google Scholar]
  173. 173. 
    Warinner C, Herbig A, Mann A, Fellows Yates JA, Weiß CL et al. 2017. A robust framework for microbial archaeology. Annu. Rev. Genom. Hum. Genet. 18:321–56
    [Google Scholar]
  174. 174. 
    Wiens JJ. 2006. Missing data and the design of phylogenetic analyses. J. Biomed. Inform. 39:34–42
    [Google Scholar]
  175. 175. 
    Wirth T, Hildebrand F, Allix-Béguec C, Wölbeling F, Kubica T et al. 2008. Origin, spread and demography of the Mycobacterium tuberculosis complex. PLOS Pathog 4:e1000160
    [Google Scholar]
  176. 176. 
    Wood DE, Salzberg SL. 2014. Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biol 15:R46
    [Google Scholar]
  177. 177. 
    Wood JW, Milner GR, Harpending HC, Weiss KM, Cohen MN et al. 1992. The osteological paradox: problems of inferring prehistoric health from skeletal samples [and comments and reply]. Curr. Anthropol. 33:343–70
    [Google Scholar]
  178. 178. 
    Woolhouse ME, Gowtage-Sequeria S. 2005. Host range and emerging and reemerging pathogens. Emerg. Infect. Dis. 11:1842
    [Google Scholar]
  179. 179. 
    Xi Z, Liu L, Davis CC 2015. The impact of missing data on species tree estimation. Mol. Biol. Evol. 33:838–60
    [Google Scholar]
  180. 180. 
    Xia X, Xie Z, Salemi M, Chen L, Wang Y 2003. An index of substitution saturation and its application. Mol. Phylogenet. Evol. 26:1–7
    [Google Scholar]
  181. 181. 
    Xie W, Lewis PO, Fan Y, Kuo L, Chen M-H 2010. Improving marginal likelihood estimation for Bayesian phylogenetic model selection. Syst. Biol. 60:150–60
    [Google Scholar]
  182. 182. 
    Zerbino D, Birney E. 2008. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res 18:821–29
    [Google Scholar]
  183. 183. 
    Zhou B, Wen S, Wang L, Jin L, Li H, Zhang H 2017. AntCaller: an accurate variant caller incorporating ancient DNA damage. Mol. Genet. Genom. 292:1419–30
    [Google Scholar]
  184. 184. 
    Zhou Z, Lundstrøm I, Tran-Dien A, Duchêne S, Alikhan N-F et al. 2018. Pan-genome analysis of ancient and modern Salmonella enterica demonstrates genomic stability of the invasive Para C lineage for millenia. Curr. Biol. 28:P2420–28
    [Google Scholar]
/content/journals/10.1146/annurev-micro-090817-062436
Loading
/content/journals/10.1146/annurev-micro-090817-062436
Loading

Data & Media loading...

Supplemental Material

Supplementary Data

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error