Selection of Appropriate Metagenome Taxonomic Classifiers for Ancient Microbiome Research

ABSTRACT Metagenomics enables the study of complex microbial communities from myriad sources, including the remains of oral and gut microbiota preserved in archaeological dental calculus and paleofeces, respectively. While accurate taxonomic assignment is essential to this process, DNA damage charac...

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Autores principales:	Irina M. Velsko, Laurent A. F. Frantz, Alexander Herbig, Greger Larson, Christina Warinner
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Lenguaje:	EN
Publicado:	American Society for Microbiology 2018
Materias:	ancient DNA metagenomics microbiome taxonomy Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/e267d42c43b9432da832be3900f8c3f2
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spelling	oai:doaj.org-article:e267d42c43b9432da832be3900f8c3f22021-12-02T18:15:43ZSelection of Appropriate Metagenome Taxonomic Classifiers for Ancient Microbiome Research10.1128/mSystems.00080-182379-5077https://doaj.org/article/e267d42c43b9432da832be3900f8c3f22018-08-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00080-18https://doaj.org/toc/2379-5077ABSTRACT Metagenomics enables the study of complex microbial communities from myriad sources, including the remains of oral and gut microbiota preserved in archaeological dental calculus and paleofeces, respectively. While accurate taxonomic assignment is essential to this process, DNA damage characteristic of ancient samples (e.g., reduction in fragment size and cytosine deamination) may reduce the accuracy of read taxonomic assignment. Using a set of in silico-generated metagenomic data sets, we investigated how the addition of ancient DNA (aDNA) damage patterns influences microbial taxonomic assignment by five widely used profilers: QIIME/UCLUST, MetaPhlAn2, MIDAS, CLARK-S, and MALT. In silico-generated data sets were designed to mimic dental plaque, consisting of 40, 100, and 200 microbial species/strains, both with and without simulated aDNA damage patterns. Following taxonomic assignment, the profiles were evaluated for species presence/absence, relative abundance, alpha diversity, beta diversity, and specific taxonomic assignment biases. Unifrac metrics indicated that both MIDAS and MetaPhlAn2 reconstructed the most accurate community structure. QIIME/UCLUST, CLARK-S, and MALT had the highest number of inaccurate taxonomic assignments; false-positive rates were highest by CLARK-S and QIIME/UCLUST. Filtering out species present at <0.1% abundance greatly increased the accuracy of CLARK-S and MALT. All programs except CLARK-S failed to detect some species from the input file that were in their databases. The addition of ancient DNA damage resulted in minimal differences in species detection and relative abundance between simulated ancient and modern data sets for most programs. Overall, taxonomic profiling biases are program specific rather than damage dependent, and the choice of taxonomic classification program should be tailored to specific research questions. IMPORTANCE Ancient biomolecules from oral and gut microbiome samples have been shown to be preserved in the archaeological record. Studying ancient microbiome communities using metagenomic techniques offers a unique opportunity to reconstruct the evolutionary trajectories of microbial communities through time. DNA accumulates specific damage over time, which could potentially affect taxonomic classification and our ability to accurately reconstruct community assemblages. It is therefore necessary to assess whether ancient DNA (aDNA) damage patterns affect metagenomic taxonomic profiling. Here, we assessed biases in community structure, diversity, species detection, and relative abundance estimates by five popular metagenomic taxonomic classification programs using in silico-generated data sets with and without aDNA damage. Damage patterns had minimal impact on the taxonomic profiles produced by each program, while false-positive rates and biases were intrinsic to each program. Therefore, the most appropriate classification program is one that minimizes the biases related to the questions being addressed.Irina M. VelskoLaurent A. F. FrantzAlexander HerbigGreger LarsonChristina WarinnerAmerican Society for Microbiologyarticleancient DNAmetagenomicsmicrobiometaxonomyMicrobiologyQR1-502ENmSystems, Vol 3, Iss 4 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	ancient DNA metagenomics microbiome taxonomy Microbiology QR1-502
spellingShingle	ancient DNA metagenomics microbiome taxonomy Microbiology QR1-502 Irina M. Velsko Laurent A. F. Frantz Alexander Herbig Greger Larson Christina Warinner Selection of Appropriate Metagenome Taxonomic Classifiers for Ancient Microbiome Research
description	ABSTRACT Metagenomics enables the study of complex microbial communities from myriad sources, including the remains of oral and gut microbiota preserved in archaeological dental calculus and paleofeces, respectively. While accurate taxonomic assignment is essential to this process, DNA damage characteristic of ancient samples (e.g., reduction in fragment size and cytosine deamination) may reduce the accuracy of read taxonomic assignment. Using a set of in silico-generated metagenomic data sets, we investigated how the addition of ancient DNA (aDNA) damage patterns influences microbial taxonomic assignment by five widely used profilers: QIIME/UCLUST, MetaPhlAn2, MIDAS, CLARK-S, and MALT. In silico-generated data sets were designed to mimic dental plaque, consisting of 40, 100, and 200 microbial species/strains, both with and without simulated aDNA damage patterns. Following taxonomic assignment, the profiles were evaluated for species presence/absence, relative abundance, alpha diversity, beta diversity, and specific taxonomic assignment biases. Unifrac metrics indicated that both MIDAS and MetaPhlAn2 reconstructed the most accurate community structure. QIIME/UCLUST, CLARK-S, and MALT had the highest number of inaccurate taxonomic assignments; false-positive rates were highest by CLARK-S and QIIME/UCLUST. Filtering out species present at <0.1% abundance greatly increased the accuracy of CLARK-S and MALT. All programs except CLARK-S failed to detect some species from the input file that were in their databases. The addition of ancient DNA damage resulted in minimal differences in species detection and relative abundance between simulated ancient and modern data sets for most programs. Overall, taxonomic profiling biases are program specific rather than damage dependent, and the choice of taxonomic classification program should be tailored to specific research questions. IMPORTANCE Ancient biomolecules from oral and gut microbiome samples have been shown to be preserved in the archaeological record. Studying ancient microbiome communities using metagenomic techniques offers a unique opportunity to reconstruct the evolutionary trajectories of microbial communities through time. DNA accumulates specific damage over time, which could potentially affect taxonomic classification and our ability to accurately reconstruct community assemblages. It is therefore necessary to assess whether ancient DNA (aDNA) damage patterns affect metagenomic taxonomic profiling. Here, we assessed biases in community structure, diversity, species detection, and relative abundance estimates by five popular metagenomic taxonomic classification programs using in silico-generated data sets with and without aDNA damage. Damage patterns had minimal impact on the taxonomic profiles produced by each program, while false-positive rates and biases were intrinsic to each program. Therefore, the most appropriate classification program is one that minimizes the biases related to the questions being addressed.
format	article
author	Irina M. Velsko Laurent A. F. Frantz Alexander Herbig Greger Larson Christina Warinner
author_facet	Irina M. Velsko Laurent A. F. Frantz Alexander Herbig Greger Larson Christina Warinner
author_sort	Irina M. Velsko
title	Selection of Appropriate Metagenome Taxonomic Classifiers for Ancient Microbiome Research
title_short	Selection of Appropriate Metagenome Taxonomic Classifiers for Ancient Microbiome Research
title_full	Selection of Appropriate Metagenome Taxonomic Classifiers for Ancient Microbiome Research
title_fullStr	Selection of Appropriate Metagenome Taxonomic Classifiers for Ancient Microbiome Research
title_full_unstemmed	Selection of Appropriate Metagenome Taxonomic Classifiers for Ancient Microbiome Research
title_sort	selection of appropriate metagenome taxonomic classifiers for ancient microbiome research
publisher	American Society for Microbiology
publishDate	2018
url	https://doaj.org/article/e267d42c43b9432da832be3900f8c3f2
work_keys_str_mv	AT irinamvelsko selectionofappropriatemetagenometaxonomicclassifiersforancientmicrobiomeresearch AT laurentaffrantz selectionofappropriatemetagenometaxonomicclassifiersforancientmicrobiomeresearch AT alexanderherbig selectionofappropriatemetagenometaxonomicclassifiersforancientmicrobiomeresearch AT gregerlarson selectionofappropriatemetagenometaxonomicclassifiersforancientmicrobiomeresearch AT christinawarinner selectionofappropriatemetagenometaxonomicclassifiersforancientmicrobiomeresearch
_version_	1718378366074093568

Selection of Appropriate Metagenome Taxonomic Classifiers for Ancient Microbiome Research

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