The Significance of Robustly Identifying Microbes in Archaeological Samples of Humans and Domesticated Animals

Summary

This is an abstract from the "HumAnE Archaeology" session, at the 84th annual meeting of the Society for American Archaeology.

Genetic species identification of archaeological specimens is difficult due to low DNA content and degradation. Yet specific and accurate identification of microbes is essential not only for identifying how diseases affect human health, but also the health of domesticated animals. Therefore, we created a method for identifying microbes via aDNA, that quantifies the confidence of the performed identification. We present two case studies to highlight the utility of our pipeline in archaeological studies of microbiomes.

By using ancient dental calculus samples from an English Victorian-era population, we have attempted to identify bacterial species within the sequences generated from the substrate. Thus far, we have detected positive signatures for the causative agents of diphtheria and pertussis. Our findings highlight the potential of ancient dental calculus to act as a reservoir for respiratory pathogens, that can be indicative of the health status of past human societies.

In search for ancient animal pathogens, examining the non-endogenous DNA of ancient chicken, pig and dog samples allowed us to identify the causative agents of diseases, that became prevalent in a post industrial revolution world. These findings are indicative of how human activity can reshape the landscape of animal diseases, through altering the natural environment.

Cite this Record

The Significance of Robustly Identifying Microbes in Archaeological Samples of Humans and Domesticated Animals. Evangelos Dimopoulos, Irina Velsko, Evan Irving Pease, Laurent Frantz, Greger Larson. Presented at The 84th Annual Meeting of the Society for American Archaeology, Albuquerque, NM. 2019 ( tDAR id: 451577)

Spatial Coverage

min long: -13.711; min lat: 35.747 ; max long: 8.965; max lat: 59.086 ;

Record Identifiers

Abstract Id(s): 24960