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Comparison of extraction methods for recovering ancient microbial DNA from paleofeces
Author(s) -
Hagan Richard W.,
Hofman Courtney A.,
Hübner Alexander,
Reinhard Karl,
Schnorr Stephanie,
Lewis Cecil M.,
Sankaranarayanan Krithivasan,
Warinner Christina G.
Publication year - 2020
Publication title -
american journal of physical anthropology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.146
H-Index - 119
eISSN - 1096-8644
pISSN - 0002-9483
DOI - 10.1002/ajpa.23978
Subject(s) - ancient dna , metagenomics , microbiome , dna extraction , gut microbiome , biology , dna , evolutionary biology , computational biology , shotgun , human microbiome project , ecology , human microbiome , bioinformatics , genetics , gene , polymerase chain reaction , population , demography , sociology
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.