Metagenomic surveillance for bacterial tick-borne pathogens using nanopore adaptive sampling

Evan J. Kipp; Laramie L. Lindsey; Benedict Khoo; Christopher Faulk; Jonathan D. Oliver; Peter A. Larsen

doi:10.1038/s41598-023-37134-9

Metagenomic surveillance for bacterial tick-borne pathogens using nanopore adaptive sampling

Evan J. Kipp, Laramie L. Lindsey, Benedict Khoo, Christopher Faulk, Jonathan D. Oliver, Peter A. Larsen

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

Technological and computational advancements in the fields of genomics and bioinformatics are providing exciting new opportunities for pathogen discovery and genomic surveillance. In particular, single-molecule nucleotide sequence data originating from Oxford Nanopore Technologies (ONT) sequencing platforms can be bioinformatically leveraged, in real-time, for enhanced biosurveillance of a vast array of zoonoses. The recently released nanopore adaptive sampling (NAS) strategy facilitates immediate mapping of individual nucleotide molecules to a given reference as each molecule is being sequenced. User-defined thresholds then allow for the retention or rejection of specific molecules, informed by the real-time reference mapping results, as they are physically passing through a given sequencing nanopore. Here, we show how NAS can be used to selectively sequence DNA of multiple bacterial tick-borne pathogens circulating in wild populations of the blacklegged tick vector, Ixodes scapularis.

Original language	English (US)
Article number	10991
Journal	Scientific reports
Volume	13
Issue number	1
DOIs	https://doi.org/10.1038/s41598-023-37134-9
State	Published - Dec 2023

Bibliographical note

Funding Information:
We thank Suzanne Stone for logistical support of the research performed herein. The Minnesota Supercomputing Institute (MSI) at the University of Minnesota provided key resources to support bioinformatic analyses and data storage. The University of Minnesota Genomic Center (UMGC) performed Illumina library preparation and 16S sequencing. We thank Trevor Gould of the UMGC for bioinformatic analyses of 16S data. Figure 1 was partially generated using BioRender and with kind assistance from Tonya Seiler. Funding was provided by MN Futures proposal 253632 awarded to J.D.O., start-up funds awarded to P.A.L. through the Minnesota Agricultural, Research, Education, Extension and Technology Transfer (AGREETT) program, and NIH Grant R01AI155472 jointly awarded to J.D.O. and P.A.L.

Funding Information:
We thank Suzanne Stone for logistical support of the research performed herein. The Minnesota Supercomputing Institute (MSI) at the University of Minnesota provided key resources to support bioinformatic analyses and data storage. The University of Minnesota Genomic Center (UMGC) performed Illumina library preparation and 16S sequencing. We thank Trevor Gould of the UMGC for bioinformatic analyses of 16S data. Figure was partially generated using BioRender and with kind assistance from Tonya Seiler. Funding was provided by MN Futures proposal 253632 awarded to J.D.O., start-up funds awarded to P.A.L. through the Minnesota Agricultural, Research, Education, Extension and Technology Transfer (AGREETT) program, and NIH Grant R01AI155472 jointly awarded to J.D.O. and P.A.L.

Publisher Copyright:
© 2023, The Author(s).

PubMed: MeSH publication types

Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

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title = "Metagenomic surveillance for bacterial tick-borne pathogens using nanopore adaptive sampling",

abstract = "Technological and computational advancements in the fields of genomics and bioinformatics are providing exciting new opportunities for pathogen discovery and genomic surveillance. In particular, single-molecule nucleotide sequence data originating from Oxford Nanopore Technologies (ONT) sequencing platforms can be bioinformatically leveraged, in real-time, for enhanced biosurveillance of a vast array of zoonoses. The recently released nanopore adaptive sampling (NAS) strategy facilitates immediate mapping of individual nucleotide molecules to a given reference as each molecule is being sequenced. User-defined thresholds then allow for the retention or rejection of specific molecules, informed by the real-time reference mapping results, as they are physically passing through a given sequencing nanopore. Here, we show how NAS can be used to selectively sequence DNA of multiple bacterial tick-borne pathogens circulating in wild populations of the blacklegged tick vector, Ixodes scapularis.",

author = "Kipp, {Evan J.} and Lindsey, {Laramie L.} and Benedict Khoo and Christopher Faulk and Oliver, {Jonathan D.} and Larsen, {Peter A.}",

note = "Funding Information: We thank Suzanne Stone for logistical support of the research performed herein. The Minnesota Supercomputing Institute (MSI) at the University of Minnesota provided key resources to support bioinformatic analyses and data storage. The University of Minnesota Genomic Center (UMGC) performed Illumina library preparation and 16S sequencing. We thank Trevor Gould of the UMGC for bioinformatic analyses of 16S data. Figure 1 was partially generated using BioRender and with kind assistance from Tonya Seiler. Funding was provided by MN Futures proposal 253632 awarded to J.D.O., start-up funds awarded to P.A.L. through the Minnesota Agricultural, Research, Education, Extension and Technology Transfer (AGREETT) program, and NIH Grant R01AI155472 jointly awarded to J.D.O. and P.A.L. Funding Information: We thank Suzanne Stone for logistical support of the research performed herein. The Minnesota Supercomputing Institute (MSI) at the University of Minnesota provided key resources to support bioinformatic analyses and data storage. The University of Minnesota Genomic Center (UMGC) performed Illumina library preparation and 16S sequencing. We thank Trevor Gould of the UMGC for bioinformatic analyses of 16S data. Figure was partially generated using BioRender and with kind assistance from Tonya Seiler. Funding was provided by MN Futures proposal 253632 awarded to J.D.O., start-up funds awarded to P.A.L. through the Minnesota Agricultural, Research, Education, Extension and Technology Transfer (AGREETT) program, and NIH Grant R01AI155472 jointly awarded to J.D.O. and P.A.L. Publisher Copyright: {\textcopyright} 2023, The Author(s).",

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doi = "10.1038/s41598-023-37134-9",

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AU - Oliver, Jonathan D.

AU - Larsen, Peter A.

N1 - Funding Information: We thank Suzanne Stone for logistical support of the research performed herein. The Minnesota Supercomputing Institute (MSI) at the University of Minnesota provided key resources to support bioinformatic analyses and data storage. The University of Minnesota Genomic Center (UMGC) performed Illumina library preparation and 16S sequencing. We thank Trevor Gould of the UMGC for bioinformatic analyses of 16S data. Figure 1 was partially generated using BioRender and with kind assistance from Tonya Seiler. Funding was provided by MN Futures proposal 253632 awarded to J.D.O., start-up funds awarded to P.A.L. through the Minnesota Agricultural, Research, Education, Extension and Technology Transfer (AGREETT) program, and NIH Grant R01AI155472 jointly awarded to J.D.O. and P.A.L. Funding Information: We thank Suzanne Stone for logistical support of the research performed herein. The Minnesota Supercomputing Institute (MSI) at the University of Minnesota provided key resources to support bioinformatic analyses and data storage. The University of Minnesota Genomic Center (UMGC) performed Illumina library preparation and 16S sequencing. We thank Trevor Gould of the UMGC for bioinformatic analyses of 16S data. Figure was partially generated using BioRender and with kind assistance from Tonya Seiler. Funding was provided by MN Futures proposal 253632 awarded to J.D.O., start-up funds awarded to P.A.L. through the Minnesota Agricultural, Research, Education, Extension and Technology Transfer (AGREETT) program, and NIH Grant R01AI155472 jointly awarded to J.D.O. and P.A.L. Publisher Copyright: © 2023, The Author(s).

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Metagenomic surveillance for bacterial tick-borne pathogens using nanopore adaptive sampling

Abstract

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