Ancient Pathogen Genomes from Pre- and Early Colonial Epidemics in Mesoamerica and the Evolution of Parathyphi C
Author(s): Johannes Krause
Year: 2019
Summary
This is an abstract from the "Ancient DNA in Service of Archaeology" session, at the 84th annual meeting of the Society for American Archaeology.
Genome wide data from ancient microbes may help to understand mechanisms of pathogen evolution and adaptation for emerging and re-emerging infectious disease. Ancient pathogen genomes provide furthermore the possibility to identify causative agents of past pandemics and therefore elucidate mortality crisis such as the early contact period in the New World. In order to identify the presence of pathogens in past populations we used a novel high-throughput DNA sequence alignment and taxonomic assignment tool MALT (MEGAN ALignment Tool) and were able to identify traces of Salmonella enterica DNA in individuals buried in an early contact era epidemic cemetery at Teposcolula-Yucundaa, Oaxaca in Southern Mexico. This cemetery is linked to the 1545–1550 CE epidemic that affected large parts of Mexico, the pathogenic cause of which has been debated for more than a century. We generated genome-wide data from ten individuals for Salmonella enterica subsp. enterica serovar Paratyphi C, a bacterial cause of enteric fever. We propose S. Paratyphi C as a strong candidate for the epidemic population decline during the 1545 outbreak. We furthermore show that the Paratyphi C lineage has been common in the human population for thousands of years and shows strong signs of human adaptation through time.
Cite this Record
Ancient Pathogen Genomes from Pre- and Early Colonial Epidemics in Mesoamerica and the Evolution of Parathyphi C. Johannes Krause. Presented at The 84th Annual Meeting of the Society for American Archaeology, Albuquerque, NM. 2019 ( tDAR id: 452236)
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Keywords
Geographic Keywords
Mesoamerica: Oaxaca or Southern Highlands
Spatial Coverage
min long: -98.679; min lat: 15.496 ; max long: -94.724; max lat: 18.271 ;
Record Identifiers
Abstract Id(s): 25644