Library Preparation and Sequencing Platform Introduce Bias in Metagenomic-Based Characterizations of Microbiomes

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Standard

Library Preparation and Sequencing Platform Introduce Bias in Metagenomic-Based Characterizations of Microbiomes. / Poulsen, Casper S; Ekstrøm, Claus T; Aarestrup, Frank M; Pamp, Sünje J.

In: Microbiology Spectrum, Vol. 10, No. 2, e0009022, 2022.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Poulsen, CS, Ekstrøm, CT, Aarestrup, FM & Pamp, SJ 2022, 'Library Preparation and Sequencing Platform Introduce Bias in Metagenomic-Based Characterizations of Microbiomes', Microbiology Spectrum, vol. 10, no. 2, e0009022. https://doi.org/10.1128/spectrum.00090-22

APA

Poulsen, C. S., Ekstrøm, C. T., Aarestrup, F. M., & Pamp, S. J. (2022). Library Preparation and Sequencing Platform Introduce Bias in Metagenomic-Based Characterizations of Microbiomes. Microbiology Spectrum, 10(2), [e0009022]. https://doi.org/10.1128/spectrum.00090-22

Vancouver

Poulsen CS, Ekstrøm CT, Aarestrup FM, Pamp SJ. Library Preparation and Sequencing Platform Introduce Bias in Metagenomic-Based Characterizations of Microbiomes. Microbiology Spectrum. 2022;10(2). e0009022. https://doi.org/10.1128/spectrum.00090-22

Author

Poulsen, Casper S ; Ekstrøm, Claus T ; Aarestrup, Frank M ; Pamp, Sünje J. / Library Preparation and Sequencing Platform Introduce Bias in Metagenomic-Based Characterizations of Microbiomes. In: Microbiology Spectrum. 2022 ; Vol. 10, No. 2.

Bibtex

@article{c9bacea1efb54967b474ea4cb2c892ae,
title = "Library Preparation and Sequencing Platform Introduce Bias in Metagenomic-Based Characterizations of Microbiomes",
abstract = "Metagenomics is increasingly used to describe microbial communities in biological specimens. Ideally, the steps involved in the processing of the biological specimens should not change the microbiome composition in a way that it could lead to false interpretations of inferred microbial community composition. Common steps in sample preparation include sample collection, storage, DNA isolation, library preparation, and DNA sequencing. Here, we assess the effect of three library preparation kits and two DNA sequencing platforms. Of the library preparation kits, one involved a PCR step (Nextera), and two were PCR free (NEXTflex and KAPA). We sequenced the libraries on Illumina HiSeq and NextSeq platforms. As example microbiomes, two pig fecal samples and two sewage samples of which aliquots were stored at different storage conditions (immediate processing and storage at -80°C) were assessed. All DNA isolations were performed in duplicate, totaling 80 samples, excluding controls. We found that both library preparation and sequencing platform had systematic effects on the inferred microbial community composition. The different sequencing platforms introduced more variation than library preparation and freezing the samples. The results highlight that all sample processing steps need to be considered when comparing studies. Standardization of sample processing is key to generating comparable data within a study, and comparisons of differently generated data, such as in a meta-analysis, should be performed cautiously. IMPORTANCE Previous research has reported effects of sample storage conditions and DNA isolation procedures on metagenomics-based microbiome composition; however, the effect of library preparation and DNA sequencing in metagenomics has not been thoroughly assessed. Here, we provide evidence that library preparation and sequencing platform introduce systematic biases in the metagenomic-based characterization of microbial communities. These findings suggest that library preparation and sequencing are important parameters to keep consistent when aiming to detect small changes in microbiome community structure. Overall, we recommend that all samples in a microbiome study are processed in the same way to limit unwanted variations that could lead to false conclusions. Furthermore, if we are to obtain a more holistic insight from microbiome data generated around the world, we will need to provide more detailed sample metadata, including information about the different sample processing procedures, together with the DNA sequencing data at the public repositories. ",
keywords = "Animals, Bacteria/genetics, Bias, DNA, High-Throughput Nucleotide Sequencing/methods, Metagenomics/methods, Microbiota/genetics, Sequence Analysis, DNA/methods, Swine",
author = "Poulsen, {Casper S} and Ekstr{\o}m, {Claus T} and Aarestrup, {Frank M} and Pamp, {S{\"u}nje J}",
year = "2022",
doi = "10.1128/spectrum.00090-22",
language = "English",
volume = "10",
journal = "Microbiology spectrum",
issn = "2165-0497",
publisher = "American Society for Microbiology",
number = "2",

}

RIS

TY - JOUR

T1 - Library Preparation and Sequencing Platform Introduce Bias in Metagenomic-Based Characterizations of Microbiomes

AU - Poulsen, Casper S

AU - Ekstrøm, Claus T

AU - Aarestrup, Frank M

AU - Pamp, Sünje J

PY - 2022

Y1 - 2022

N2 - Metagenomics is increasingly used to describe microbial communities in biological specimens. Ideally, the steps involved in the processing of the biological specimens should not change the microbiome composition in a way that it could lead to false interpretations of inferred microbial community composition. Common steps in sample preparation include sample collection, storage, DNA isolation, library preparation, and DNA sequencing. Here, we assess the effect of three library preparation kits and two DNA sequencing platforms. Of the library preparation kits, one involved a PCR step (Nextera), and two were PCR free (NEXTflex and KAPA). We sequenced the libraries on Illumina HiSeq and NextSeq platforms. As example microbiomes, two pig fecal samples and two sewage samples of which aliquots were stored at different storage conditions (immediate processing and storage at -80°C) were assessed. All DNA isolations were performed in duplicate, totaling 80 samples, excluding controls. We found that both library preparation and sequencing platform had systematic effects on the inferred microbial community composition. The different sequencing platforms introduced more variation than library preparation and freezing the samples. The results highlight that all sample processing steps need to be considered when comparing studies. Standardization of sample processing is key to generating comparable data within a study, and comparisons of differently generated data, such as in a meta-analysis, should be performed cautiously. IMPORTANCE Previous research has reported effects of sample storage conditions and DNA isolation procedures on metagenomics-based microbiome composition; however, the effect of library preparation and DNA sequencing in metagenomics has not been thoroughly assessed. Here, we provide evidence that library preparation and sequencing platform introduce systematic biases in the metagenomic-based characterization of microbial communities. These findings suggest that library preparation and sequencing are important parameters to keep consistent when aiming to detect small changes in microbiome community structure. Overall, we recommend that all samples in a microbiome study are processed in the same way to limit unwanted variations that could lead to false conclusions. Furthermore, if we are to obtain a more holistic insight from microbiome data generated around the world, we will need to provide more detailed sample metadata, including information about the different sample processing procedures, together with the DNA sequencing data at the public repositories.

AB - Metagenomics is increasingly used to describe microbial communities in biological specimens. Ideally, the steps involved in the processing of the biological specimens should not change the microbiome composition in a way that it could lead to false interpretations of inferred microbial community composition. Common steps in sample preparation include sample collection, storage, DNA isolation, library preparation, and DNA sequencing. Here, we assess the effect of three library preparation kits and two DNA sequencing platforms. Of the library preparation kits, one involved a PCR step (Nextera), and two were PCR free (NEXTflex and KAPA). We sequenced the libraries on Illumina HiSeq and NextSeq platforms. As example microbiomes, two pig fecal samples and two sewage samples of which aliquots were stored at different storage conditions (immediate processing and storage at -80°C) were assessed. All DNA isolations were performed in duplicate, totaling 80 samples, excluding controls. We found that both library preparation and sequencing platform had systematic effects on the inferred microbial community composition. The different sequencing platforms introduced more variation than library preparation and freezing the samples. The results highlight that all sample processing steps need to be considered when comparing studies. Standardization of sample processing is key to generating comparable data within a study, and comparisons of differently generated data, such as in a meta-analysis, should be performed cautiously. IMPORTANCE Previous research has reported effects of sample storage conditions and DNA isolation procedures on metagenomics-based microbiome composition; however, the effect of library preparation and DNA sequencing in metagenomics has not been thoroughly assessed. Here, we provide evidence that library preparation and sequencing platform introduce systematic biases in the metagenomic-based characterization of microbial communities. These findings suggest that library preparation and sequencing are important parameters to keep consistent when aiming to detect small changes in microbiome community structure. Overall, we recommend that all samples in a microbiome study are processed in the same way to limit unwanted variations that could lead to false conclusions. Furthermore, if we are to obtain a more holistic insight from microbiome data generated around the world, we will need to provide more detailed sample metadata, including information about the different sample processing procedures, together with the DNA sequencing data at the public repositories.

KW - Animals

KW - Bacteria/genetics

KW - Bias

KW - DNA

KW - High-Throughput Nucleotide Sequencing/methods

KW - Metagenomics/methods

KW - Microbiota/genetics

KW - Sequence Analysis, DNA/methods

KW - Swine

U2 - 10.1128/spectrum.00090-22

DO - 10.1128/spectrum.00090-22

M3 - Journal article

C2 - 35289669

VL - 10

JO - Microbiology spectrum

JF - Microbiology spectrum

SN - 2165-0497

IS - 2

M1 - e0009022

ER -

ID: 314012985