Assessing alignment-based taxonomic classification of ancient microbial DNA

Raphael Eisenhofer, Laura Susan Weyrich

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

The field of palaeomicrobiology-the study of ancient microorganisms-is rapidly growing due to recent methodological and technological advancements. It is now possible to obtain vast quantities of DNA data from ancient specimens in a high-throughput manner and use this information to investigate the dynamics and evolution of past microbial communities. However, we still know very little about how the characteristics of ancient DNA influence our ability to accurately assign microbial taxonomies (i.e. identify species) within ancient metagenomic samples. Here, we use both simulated and published metagenomic data sets to investigate how ancient DNA characteristics affect alignment-based taxonomic classification. We find that nucleotide-to-nucleotide, rather than nucleotide-to-protein, alignments are preferable when assigning taxonomies to short DNA fragment lengths routinely identified within ancient specimens (<60 bp). We determine that deamination (a form of ancient DNA damage) and random sequence substitutions corresponding to ∼100,000 years of genomic divergence minimally impact alignment-based classification. We also test four different reference databases and find that database choice can significantly bias the results of alignment-based taxonomic classification in ancient metagenomic studies. Finally, we perform a reanalysis of previously published ancient dental calculus data, increasing the number of microbial DNA sequences assigned taxonomically by an average of 64.2-fold and identifying microbial species previously unidentified in the original study. Overall, this study enhances our understanding of how ancient DNA characteristics influence alignment-based taxonomic classification of ancient microorganisms and provides recommendations for future palaeomicrobiological studies.

Original languageEnglish (US)
Article numbere6594
JournalPeerJ
Volume2019
Issue number3
DOIs
StatePublished - 2019

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

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