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Benchmarking Metagenomic Classifiers on Simulated Ancient and Modern Metagenomic Data

Taxonomic profiling of ancient metagenomic samples is challenging due to the accumulation of specific damage patterns on DNA over time. Although a number of methods for metagenome profiling have been developed, most of them have been assessed on modern metagenomes or simulated metagenomes mimicking...

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Autores principales: Pusadkar, Vaidehi, Azad, Rajeev K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10609333/
https://www.ncbi.nlm.nih.gov/pubmed/37894136
http://dx.doi.org/10.3390/microorganisms11102478
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author Pusadkar, Vaidehi
Azad, Rajeev K.
author_facet Pusadkar, Vaidehi
Azad, Rajeev K.
author_sort Pusadkar, Vaidehi
collection PubMed
description Taxonomic profiling of ancient metagenomic samples is challenging due to the accumulation of specific damage patterns on DNA over time. Although a number of methods for metagenome profiling have been developed, most of them have been assessed on modern metagenomes or simulated metagenomes mimicking modern metagenomes. Further, a comparative assessment of metagenome profilers on simulated metagenomes representing a spectrum of degradation depth, from the extremity of ancient (most degraded) to current or modern (not degraded) metagenomes, has not yet been performed. To understand the strengths and weaknesses of different metagenome profilers, we performed their comprehensive evaluation on simulated metagenomes representing human dental calculus microbiome, with the level of DNA damage successively raised to mimic modern to ancient metagenomes. All classes of profilers, namely, DNA-to-DNA, DNA-to-protein, and DNA-to-marker comparison-based profilers were evaluated on metagenomes with varying levels of damage simulating deamination, fragmentation, and contamination. Our results revealed that, compared to deamination and fragmentation, human and environmental contamination of ancient DNA (with modern DNA) has the most pronounced effect on the performance of each profiler. Further, the DNA-to-DNA (e.g., Kraken2, Bracken) and DNA-to-marker (e.g., MetaPhlAn4) based profiling approaches showed complementary strengths, which can be leveraged to elevate the state-of-the-art of ancient metagenome profiling.
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spelling pubmed-106093332023-10-28 Benchmarking Metagenomic Classifiers on Simulated Ancient and Modern Metagenomic Data Pusadkar, Vaidehi Azad, Rajeev K. Microorganisms Article Taxonomic profiling of ancient metagenomic samples is challenging due to the accumulation of specific damage patterns on DNA over time. Although a number of methods for metagenome profiling have been developed, most of them have been assessed on modern metagenomes or simulated metagenomes mimicking modern metagenomes. Further, a comparative assessment of metagenome profilers on simulated metagenomes representing a spectrum of degradation depth, from the extremity of ancient (most degraded) to current or modern (not degraded) metagenomes, has not yet been performed. To understand the strengths and weaknesses of different metagenome profilers, we performed their comprehensive evaluation on simulated metagenomes representing human dental calculus microbiome, with the level of DNA damage successively raised to mimic modern to ancient metagenomes. All classes of profilers, namely, DNA-to-DNA, DNA-to-protein, and DNA-to-marker comparison-based profilers were evaluated on metagenomes with varying levels of damage simulating deamination, fragmentation, and contamination. Our results revealed that, compared to deamination and fragmentation, human and environmental contamination of ancient DNA (with modern DNA) has the most pronounced effect on the performance of each profiler. Further, the DNA-to-DNA (e.g., Kraken2, Bracken) and DNA-to-marker (e.g., MetaPhlAn4) based profiling approaches showed complementary strengths, which can be leveraged to elevate the state-of-the-art of ancient metagenome profiling. MDPI 2023-10-02 /pmc/articles/PMC10609333/ /pubmed/37894136 http://dx.doi.org/10.3390/microorganisms11102478 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Pusadkar, Vaidehi
Azad, Rajeev K.
Benchmarking Metagenomic Classifiers on Simulated Ancient and Modern Metagenomic Data
title Benchmarking Metagenomic Classifiers on Simulated Ancient and Modern Metagenomic Data
title_full Benchmarking Metagenomic Classifiers on Simulated Ancient and Modern Metagenomic Data
title_fullStr Benchmarking Metagenomic Classifiers on Simulated Ancient and Modern Metagenomic Data
title_full_unstemmed Benchmarking Metagenomic Classifiers on Simulated Ancient and Modern Metagenomic Data
title_short Benchmarking Metagenomic Classifiers on Simulated Ancient and Modern Metagenomic Data
title_sort benchmarking metagenomic classifiers on simulated ancient and modern metagenomic data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10609333/
https://www.ncbi.nlm.nih.gov/pubmed/37894136
http://dx.doi.org/10.3390/microorganisms11102478
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