Detection of Tick-Borne Bacteria from Whole Blood Using 16S Ribosomal RNA Gene PCR Followed by Next-Generation Sequencing.


Journal

Journal of clinical microbiology
ISSN: 1098-660X
Titre abrégé: J Clin Microbiol
Pays: United States
ID NLM: 7505564

Informations de publication

Date de publication:
20 04 2021
Historique:
received: 14 12 2020
accepted: 15 02 2021
pubmed: 26 2 2021
medline: 9 7 2021
entrez: 25 2 2021
Statut: epublish

Résumé

Reported cases of tick-borne diseases have steadily increased for more than a decade. In the United States, a majority of tick-borne infections are caused by bacteria. Clinical diagnosis may be challenging, as tick-borne diseases can present with similar symptoms. Laboratory diagnosis has historically relied on serologic methods, which have limited utility during the acute phase of disease. Pathogen-specific molecular methods have improved early diagnosis, but can be expensive when bundled together and may miss unexpected or novel pathogens. To address these shortcomings, we developed a 16S rRNA gene PCR with a next-generation sequencing (NGS) approach to detect tick-borne bacteria in whole blood. A workflow was optimized by comparing combinations of two extraction platforms and two primer sets, ultimately pursuing DNA extraction from blood with the MagNA Pure 96 and PCR amplification using dual-priming oligonucleotide primers specific to the V1-V3 region of the 16S rRNA gene. The amplified product underwent modified Illumina 16S metagenomics sequencing library preparation and sequencing on a MiSeq V2 Nano flow cell, with data analysis using Pathogenomix RipSeq NGS software. Results with the developed method were compared to those from a V1-V2 16S rRNA gene primer set described by the Centers for Disease Control and Prevention (CDC). The V1-V3 assay demonstrated equivalent performance to the CDC assay, with each method showing concordance with targeted PCR results in 31 of 32 samples, and detecting 22 of 23 expected organisms. These data demonstrate the potential for using a broad-range bacterial detection approach for diagnosis of tick-borne bacterial infection from blood.

Identifiants

pubmed: 33627320
pii: JCM.03129-20
doi: 10.1128/JCM.03129-20
pmc: PMC8091845
pii:
doi:

Substances chimiques

DNA, Bacterial 0
RNA, Ribosomal, 16S 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2021 American Society for Microbiology.

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Auteurs

Kyle G Rodino (KG)

Division of Clinical Microbiology, Mayo Clinic, Rochester, Minnesota, USA.

Matthew J Wolf (MJ)

Division of Clinical Microbiology, Mayo Clinic, Rochester, Minnesota, USA.

Sarah Sheldon (S)

Centers for Disease Control and Prevention (CDC), Division of Vector-Borne Diseases, Fort Collins, Colorado, USA.

Luke C Kingry (LC)

Centers for Disease Control and Prevention (CDC), Division of Vector-Borne Diseases, Fort Collins, Colorado, USA.

Jeannine M Petersen (JM)

Centers for Disease Control and Prevention (CDC), Division of Vector-Borne Diseases, Fort Collins, Colorado, USA.

Robin Patel (R)

Division of Clinical Microbiology, Mayo Clinic, Rochester, Minnesota, USA.
Division of Infectious Diseases, Mayo Clinic, Rochester, Minnesota, USA.

Bobbi S Pritt (BS)

Division of Clinical Microbiology, Mayo Clinic, Rochester, Minnesota, USA pritt.bobbi@mayo.edu.
Division of Infectious Diseases, Mayo Clinic, Rochester, Minnesota, USA.

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Classifications MeSH