Hand bacteria as an identifier: a biometric evaluation


Molecular and soft bio-molecular biometrics are 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 exist 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, 104 samples from 52 individuals (left and right hands) covering a range of age, gender, and ethnicity of the participants were sequenced using 150 paired-end multiplex reads on an Illumina MiSeq. The reads contained the third hypervariable region DNA of the microbial 16S rRNA gene commonly used for microbial identification. Sequences were analyzed using a combination of commercial and custom bioinformatics tools. Results indicated that women who participated in the sample collection had a 15.7 % 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 72–94 % accuracy depending on the method used. Principal coordinate plots generated 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.

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This work was supported by DOJ contract no. 2010-DD-BX-0161 and the Center for Identification Technology Research (CITeR http://www.citer.wvu.edu), an NSF-funded I/UCRC. Holly Whitelam participated in this project as part of the summer 2013 CITeR Research Experience for Undergraduates (REU) Program. We would like to acknowledge the use of the West Virginia University Genomics Core Facility for sequencing and assistance in bioinformatics methods.

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Correspondence to Jeremy M. Dawson.

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The authors declare that they have no conflict of interest associated with the work presented herein.

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This manuscript has not been submitted to any other journal for review. This submission is an expansion of a conference paper presented at BIBE 2014, submitted to this journal upon request from Reda Alhajj, who outlined the conditions for submission as a journal via email; specifically, 40 % new material. In compliance with these conditions, it contains a significantly expanded introductory section, and an expanded data analysis performed on samples obtained from a larger cohort of subjects than what was considered in the conference paper. All work presented herein, none of which has been fabricated or falsified, is original to the authors listed above. All authors have contributed to the described research, and gave their consent to be listed. The samples used in this research were obtained from consenting participants under WVU IRB protocol H-23693.

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Holly Whitelam participated in the project as part of the Summer 2013 CITeR Research Experience for Undergraduates (REU) Program.

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Holbert, A.B., Whitelam, H.P., Sooter, L.J. et al. Hand bacteria as an identifier: a biometric evaluation. Netw Model Anal Health Inform Bioinforma 4, 22 (2015). https://doi.org/10.1007/s13721-015-0095-0

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  • Ethnicity
  • Identification of persons
  • Bio-molecular biometrics
  • Next-generation sequencing
  • Skin bacteria