The Bioinformatic Analysis of Hand Bacteria for Forensic Identification using QIIME 2

Sarah L. Schmitz* and Jeremy M. Dawson, Benjamin M. Statler College of Engineering and Mineral Resources, West Virginia University, Morgantown, WV 26506

Field (Broad Category): Forensics-Bioinformatics (Physical Sciences & Engineering) 

Student’s Major: Forensic Biology 

Modern DNA sequencing technologies have allowed researchers to examine the ability of microbiome research to be able to be applied to biometrics and forensic identification via DNA analysis and matching. Using the hypervariable V3 region of the 16S rRNA gene, DNA sequences of various species of bacteria found in a microbiome can be identified to the genus level by comparing the sequences recognized to those already recorded in an online database. However, the goal of this research is to investigate the possibility of using the makeup of a person’s bacterial microbiome as biometric identifier by directly comparing the sequences of two or more samples and analyzing the degree of dissimilarity. In previous studies, a program known as QIIME has been utilized as a bioinformatics platform in microbiome research. QIIME takes sequencing data from Illumina or other sequencing platforms and performs statistical analyses in order to determine what types of bacteria are present in a given sample along with data that relates each sample to one other based on phylogeny and sequence alignment. In January of 2018, QIIME 2 was released; a reengineered and rewritten bioinformatics system that overcomes several of the limitations of QIIME and features even more tools for analysis. In this study, DNA sequence data samples from human palm swabs collected in a previous study will be re-analyzed using QIIME 2 in order to update the results of the study and reassess the potential for the contents of a person’s microbiome to be used as a biometric identifier. 

Funding: 

Program/mechanism supporting research/creative efforts: WVU's Research Apprenticeship Program (RAP) & accompanying HONR 297-level course