Evaluation of Hand Bacteria as a Human Biometric Identifier

Molecular biometrics is an advancing field that involves the analysis of a person's unique biological markers at a molecular level to ascertain identity. Bacteria communities found on the skin of the human hand have shown to be highly diverse and to have a low percentage of similarity between individuals. The goal of this research effort is to see if a person's demographics, primarily ethnicity, share a relationship with the bacteria communities that reside on their hand. A sample collection was carried out in which the left and right inner palms of 250 individuals were swabbed to obtain a total of 500 bacteria samples. Of these, 82 samples covering a range of age, gender, and ethnicity of participants were sequenced using 150 paired-end multiplex reads on an Illumina MiSeq to analyze the hyper variable V3 region of the 16S rRNA gene. Sequences were analyzed using a combination of commercial and custom bioinformatics tools. Results indicate that women that participated in the sample collection had a 9% higher diversity of bacteria at the genus level than men. Using a support vector machine with a 60% train and 40% test approach, ethnicities of individuals who provided samples could be classified with a range of 64-93% accuracy depending on the method used. Principal coordinate plots generated by using the unique fraction (UniFrac) algorithm devised by Lozupone et al at University of Colorado at Boulder showed that similar clustering appeared with people of Turkish, Asian Indian, and Middle Eastern descent and less clustering with people of Caucasian and African American descent. Although focused on a small subset of the human population with no temporal variance in bacterial diversity explored, these results provide a basis for performing identification based on human bacteria that can be expanded upon using time varying sampling and other regions of the 16S rRNA gene.