Browsing by Subject "16S rRNA gene"
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Item Assessment of Oxford Nanopore Technologies as a Sequencing Platform for Increased Taxonomic Resolution of Microbial Communities(2019-05) Valenti, Kiana L.; Planz, John V.; Allen, Michael S.; Roane, Brandy M.; Zascavage, Roxanne R.Microbiome profiling for forensic identification is an emerging area of research. Profiling the microbiome of trace evidence for forensic cases will become more prevalent as more reliable, accurate, and efficient methodology is developed. Sequencing the V4 region of the 16S rRNA gene using second-generation sequencing methods has traditionally been the means of characterizing the microbiome of microbial samples, however this method often does not garner species-level resolution. In this study, the MinION[TM] device from Oxford Nanopore Technologies, an instrument capable of sequencing the entire length of the 16S rRNA gene was used. The main goal of this was to determine whether using the MinION[TM] device is a more viable means of obtaining deeper yet still accurate taxonomic resolution of a mixed microbial standard that contains species of bacteria that might be found in a casework sample.Item Use of ATCC[R] MSA-2002[TM] for Validation of Extraction and Amplification Techniques in 16S Microbial Community Profiling(2018-05) Foley, Brianna A.; Allen, Michael; Warren, Joseph; Zhang, Yan; Maddux, Scott D.The implementation of microbiome analysis is an emerging area of focus in forensic research. However, microbiome analysis is not well validated for use in forensic analyses and there is no standard protocol in place. In this research a comprehensive analysis of extraction and amplification techniques employed during investigation of microbial communities was performed using ATCC[R] MSA-2002[TM] as a mock microbial community. Comparison of DNA extraction protocols was performed followed by an analysis of commercially-available polymerases. Samples were pooled for sequencing of the V4 region of 16S ribosomal RNA gene using the Illumina MiSeq System, and subsequently analyzed for community composition. The results were compared with the known genomic data of the mock microbial community and statistical methods were employed to determine the extent of deviation.