Impact of Sample Type and DNA Isolation Procedure on Genomic Inference of Microbiome Composition

Berith Elkær Knudsen, Lasse Bergmark, Patrick Munk, Oksana Lukjancenko, Anders Priemé, Frank Møller Aarestrup, Sünje Johanna Pamp

Research output: Contribution to journal › Journal article › Research › peer-review

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Abstract

Explorations of complex microbiomes using genomics greatly enhance our understanding about their diversity, biogeography, and function. The isolation of DNA from microbiome specimens is a key prerequisite for such examinations, but challenges remain in obtaining sufficient DNA quantities required for certain sequencing approaches, achieving accurate genomic inference of microbiome composition, and facilitating comparability of findings across specimen types and sequencing projects. These aspects are particularly relevant for the genomics-based global surveillance of infectious agents and antimicrobial resistance from different reservoirs. Here, we compare in a stepwise approach a total of eight commercially available DNA extraction kits and 16 procedures based on these for three specimentypes (human feces, pig feces, and hospital sewage). We assess DNA extraction using spike-in controls and different types of beads for bead beating, facilitating cell lysis. We evaluate DNA concentration, purity, and stability and microbial community composition using 16S rRNA gene sequencing and for selected samples using shotgun metagenomic sequencing. Our results suggest that inferred community composition was dependent on inherent specimen properties as well as DNA extraction method. We further show that bead beating or enzymatic treatment can increase the extraction of DNA from Gram-positive bacteria. Final DNA quantities could be increased by isolating DNA from a larger volume of cell lysate than that in standard protocols. Based on this insight, we designed an improved DNA isolation procedure optimized for microbiome genomics that can be used for the three examined specimen types and potentially also for other biological specimens. A standard operating procedure is available from https://dx.doi.org/10.6084/m9.figshare.3475406.
Original languageEnglish
Article numbere00095-16
JournalmSystems
Volume1
Issue number5
Number of pages15
ISSN2379-5077
DOIs
Publication statusPublished - 2016

Keywords

  • 16S rRNA gene profiling
  • DNA isolation
  • Metagenomics
  • Microbial ecology
  • Microbiome
  • Next-generation sequencing

Cite this

Knudsen, Berith Elkær ; Bergmark, Lasse ; Munk, Patrick ; Lukjancenko, Oksana ; Priemé, Anders ; Aarestrup, Frank Møller ; Pamp, Sünje Johanna. / Impact of Sample Type and DNA Isolation Procedure on Genomic Inference of Microbiome Composition. In: mSystems. 2016 ; Vol. 1, No. 5.
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title = "Impact of Sample Type and DNA Isolation Procedure on Genomic Inference of Microbiome Composition",
abstract = "Explorations of complex microbiomes using genomics greatly enhance our understanding about their diversity, biogeography, and function. The isolation of DNA from microbiome specimens is a key prerequisite for such examinations, but challenges remain in obtaining sufficient DNA quantities required for certain sequencing approaches, achieving accurate genomic inference of microbiome composition, and facilitating comparability of findings across specimen types and sequencing projects. These aspects are particularly relevant for the genomics-based global surveillance of infectious agents and antimicrobial resistance from different reservoirs. Here, we compare in a stepwise approach a total of eight commercially available DNA extraction kits and 16 procedures based on these for three specimentypes (human feces, pig feces, and hospital sewage). We assess DNA extraction using spike-in controls and different types of beads for bead beating, facilitating cell lysis. We evaluate DNA concentration, purity, and stability and microbial community composition using 16S rRNA gene sequencing and for selected samples using shotgun metagenomic sequencing. Our results suggest that inferred community composition was dependent on inherent specimen properties as well as DNA extraction method. We further show that bead beating or enzymatic treatment can increase the extraction of DNA from Gram-positive bacteria. Final DNA quantities could be increased by isolating DNA from a larger volume of cell lysate than that in standard protocols. Based on this insight, we designed an improved DNA isolation procedure optimized for microbiome genomics that can be used for the three examined specimen types and potentially also for other biological specimens. A standard operating procedure is available from https://dx.doi.org/10.6084/m9.figshare.3475406.",
keywords = "16S rRNA gene profiling, DNA isolation, Metagenomics, Microbial ecology, Microbiome, Next-generation sequencing",
author = "Knudsen, {Berith Elk{\ae}r} and Lasse Bergmark and Patrick Munk and Oksana Lukjancenko and Anders Priem{\'e} and Aarestrup, {Frank M{\o}ller} and Pamp, {S{\"u}nje Johanna}",
year = "2016",
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language = "English",
volume = "1",
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Knudsen, BE, Bergmark, L, Munk, P, Lukjancenko, O, Priemé, A, Aarestrup, FM & Pamp, SJ 2016, 'Impact of Sample Type and DNA Isolation Procedure on Genomic Inference of Microbiome Composition', mSystems, vol. 1, no. 5, e00095-16. https://doi.org/10.1128/mSystems.00095-16

Impact of Sample Type and DNA Isolation Procedure on Genomic Inference of Microbiome Composition. / Knudsen, Berith Elkær; Bergmark, Lasse; Munk, Patrick; Lukjancenko, Oksana; Priemé, Anders; Aarestrup, Frank Møller; Pamp, Sünje Johanna.

In: mSystems, Vol. 1, No. 5, e00095-16, 2016.

Research output: Contribution to journal › Journal article › Research › peer-review

TY - JOUR

T1 - Impact of Sample Type and DNA Isolation Procedure on Genomic Inference of Microbiome Composition

AU - Knudsen, Berith Elkær

AU - Bergmark, Lasse

AU - Munk, Patrick

AU - Lukjancenko, Oksana

AU - Priemé, Anders

AU - Aarestrup, Frank Møller

AU - Pamp, Sünje Johanna

PY - 2016

Y1 - 2016

N2 - Explorations of complex microbiomes using genomics greatly enhance our understanding about their diversity, biogeography, and function. The isolation of DNA from microbiome specimens is a key prerequisite for such examinations, but challenges remain in obtaining sufficient DNA quantities required for certain sequencing approaches, achieving accurate genomic inference of microbiome composition, and facilitating comparability of findings across specimen types and sequencing projects. These aspects are particularly relevant for the genomics-based global surveillance of infectious agents and antimicrobial resistance from different reservoirs. Here, we compare in a stepwise approach a total of eight commercially available DNA extraction kits and 16 procedures based on these for three specimentypes (human feces, pig feces, and hospital sewage). We assess DNA extraction using spike-in controls and different types of beads for bead beating, facilitating cell lysis. We evaluate DNA concentration, purity, and stability and microbial community composition using 16S rRNA gene sequencing and for selected samples using shotgun metagenomic sequencing. Our results suggest that inferred community composition was dependent on inherent specimen properties as well as DNA extraction method. We further show that bead beating or enzymatic treatment can increase the extraction of DNA from Gram-positive bacteria. Final DNA quantities could be increased by isolating DNA from a larger volume of cell lysate than that in standard protocols. Based on this insight, we designed an improved DNA isolation procedure optimized for microbiome genomics that can be used for the three examined specimen types and potentially also for other biological specimens. A standard operating procedure is available from https://dx.doi.org/10.6084/m9.figshare.3475406.

AB - Explorations of complex microbiomes using genomics greatly enhance our understanding about their diversity, biogeography, and function. The isolation of DNA from microbiome specimens is a key prerequisite for such examinations, but challenges remain in obtaining sufficient DNA quantities required for certain sequencing approaches, achieving accurate genomic inference of microbiome composition, and facilitating comparability of findings across specimen types and sequencing projects. These aspects are particularly relevant for the genomics-based global surveillance of infectious agents and antimicrobial resistance from different reservoirs. Here, we compare in a stepwise approach a total of eight commercially available DNA extraction kits and 16 procedures based on these for three specimentypes (human feces, pig feces, and hospital sewage). We assess DNA extraction using spike-in controls and different types of beads for bead beating, facilitating cell lysis. We evaluate DNA concentration, purity, and stability and microbial community composition using 16S rRNA gene sequencing and for selected samples using shotgun metagenomic sequencing. Our results suggest that inferred community composition was dependent on inherent specimen properties as well as DNA extraction method. We further show that bead beating or enzymatic treatment can increase the extraction of DNA from Gram-positive bacteria. Final DNA quantities could be increased by isolating DNA from a larger volume of cell lysate than that in standard protocols. Based on this insight, we designed an improved DNA isolation procedure optimized for microbiome genomics that can be used for the three examined specimen types and potentially also for other biological specimens. A standard operating procedure is available from https://dx.doi.org/10.6084/m9.figshare.3475406.

KW - 16S rRNA gene profiling

KW - DNA isolation

KW - Metagenomics

KW - Microbial ecology

KW - Microbiome

KW - Next-generation sequencing

U2 - 10.1128/mSystems.00095-16

DO - 10.1128/mSystems.00095-16

M3 - Journal article

VL - 1

JO - mSystems

JF - mSystems

SN - 2379-5077

IS - 5

M1 - e00095-16

ER -

Knudsen BE, Bergmark L, Munk P, Lukjancenko O, Priemé A, Aarestrup FM et al. Impact of Sample Type and DNA Isolation Procedure on Genomic Inference of Microbiome Composition. mSystems. 2016;1(5). e00095-16. https://doi.org/10.1128/mSystems.00095-16

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