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Comparison of extraction methods for recovering ancient microbial DNA from paleofeces

MPG-Autoren
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Hagan,  Richard
Archaeogenetics, Max Planck Institute for the Science of Human History, Max Planck Society;

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Hübner,  Alexander
Archaeogenetics, Max Planck Institute for the Science of Human History, Max Planck Society;

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Warinner,  Christina G.
Archaeogenetics, Max Planck Institute for the Science of Human History, Max Planck Society;

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Zitation

Hagan, R., Hofman, C. A., Hübner, A., Reinhard, K., Schnorr, S., Lewis Jr, C. M., et al. (2019). Comparison of extraction methods for recovering ancient microbial DNA from paleofeces. American Journal of Physical Anthropology, 171(2), 275-284. doi:10.1002/ajpa.23978.


Zitierlink: https://hdl.handle.net/21.11116/0000-0007-2F93-F
Zusammenfassung
Abstract Objectives Paleofeces are valuable to archeologists and evolutionary biologists for their potential to yield health, dietary, and host information. As a rich source of preserved biomolecules from host-associated microorganisms, they can also provide insights into the recent evolution and changing ecology of the gut microbiome. However, there is currently no standard method for DNA extraction from paleofeces, which combine the dual challenges of complex biological composition and degraded DNA. Due to the scarcity and relatively poor preservation of paleofeces when compared with other archeological remains, it is important to use efficient methods that maximize ancient DNA (aDNA) recovery while also minimizing downstream taxonomic biases. Methods In this study, we use shotgun metagenomics to systematically compare the performance of five DNA extraction methods on a set of well-preserved human and dog paleofeces from Mexico (~1,300 BP). Results Our results show that all tested DNA extraction methods yield a consistent microbial taxonomic profile, but that methods optimized for ancient samples recover significantly more DNA. Conclusions These results show promise for future studies that seek to explore the evolution of the human gut microbiome by comparing aDNA data with those generated in modern studies.