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Selective whole genome amplification and sequencing of Coxiella burnetii directly from environmental samples.

Authors :
Cocking, Jill Hager
Deberg, Michael
Schupp, Jim
Sahl, Jason
Wiggins, Kristin
Porty, Ariel
Hornstra, Heidie M.
Hepp, Crystal
Jardine, Claire
Furstenau, Tara N.
Schulte-Hostedde, Albrecht
Fofanov, Viacheslav Y.
Pearson, Talima
Source :
Genomics. Mar2020, Vol. 112 Issue 2, p1872-1878. 7p.
Publication Year :
2020

Abstract

Whole genome sequencing (WGS) is a widely available, inexpensive means of providing a wealth of information about an organism's diversity and evolution. However, WGS for many pathogenic bacteria remain limited because they are difficult, slow and/or dangerous to culture. To avoid culturing, metagenomic sequencing can be performed directly on samples, but the sequencing effort required to characterize low frequency organisms can be expensive. Recently developed methods for selective whole genome amplification (SWGA) can enrich target DNA to provide efficient sequencing. We amplified Coxiella burnetii (a bacterial select agent and human/livestock pathogen) from 3 three environmental samples that were overwhelmed with host DNA. The 68- to 147-fold enrichment of the bacterial sequences provided enough genome coverage for SNP analyses and phylogenetic placement. SWGA is a valuable tool for the study of difficult-to-culture organisms and has the potential to facilitate high-throughput population characterizations as well as targeted epidemiological or forensic investigations. • Selective whole genome amplification (SWGA) enables culture-free whole genome sequencing. • We used SWGA to sequence C. burnetii (a bacterial pathogen and select agent) from complex environmental samples. • We validate SWGA sequencing for SNP analyses and high-resolution phylogenetic placement • SWGA can facilitate high-throughput population characterizations for epidemiological and forensic investigations. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
08887543
Volume :
112
Issue :
2
Database :
Academic Search Index
Journal :
Genomics
Publication Type :
Academic Journal
Accession number :
141755339
Full Text :
https://doi.org/10.1016/j.ygeno.2019.10.022