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Comparative analysis of Sanger and next generation sequencing methods for 16S rDNA analysis of post-mortem specimens.

Authors :
Cho, Yoonjung
Lee, Min Ho
Kim, Hyo Sook
Park, Moonhee
Kim, Min-Hee
Kwon, Hansol
Kim, Jong-Bae
Lee, Yang Han
Lee, Dong Sub
Source :
Australian Journal of Forensic Sciences. Aug2019, Vol. 51 Issue 4, p426-445. 20p.
Publication Year :
2019

Abstract

Forensic microbiology is widely applied to identify people at crime scenes and determine the cause and time of deaths by examination of trace evidence. In particular, identification of bacteria from post-mortem specimens is important because the cause of death could be an infection with clinically significant bacteria that results in a fatal outcome, such as sepsis. The MicroSEQ 500 16S rDNA Bacteria Identification system (MicroSeq ID) from Applied Biosystems is a molecular technique for profiling of bacteria isolated by cultures, based on Sanger sequencing of the bacterial 16S rDNA gene. The MiSeq Illumina platform uses next-generation sequencing (NGS) for metagenomic analysis of 16S rDNA and culture-independent identification of bacteria. In this study, we analysed 65 post-mortem specimens by both methods and compared the workflows involved with regard to methodology, time-efficiency, cost-efficiency, and performance to determine the limitations and benefits of these techniques for forensic application. We found that MiSeq is more time-efficient, and exhibits superior cost-efficiency when more than 30 samples are analysed. In addition, MiSeq has a number of other advantages over MicroSeq ID, including a simpler identification of bacteria that are difficult to culture and use of a larger library of 16S rDNA, allowing more precise identification of bacterial species. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00450618
Volume :
51
Issue :
4
Database :
Academic Search Index
Journal :
Australian Journal of Forensic Sciences
Publication Type :
Academic Journal
Accession number :
136555265
Full Text :
https://doi.org/10.1080/00450618.2017.1402957