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Article
Detecting Personal Microbiota Signatures at Artificial Crime Scenes
Forensic Science International
  • Jarrad T. Hampton-Marcell, Argonne National Laboratory; University of Illinois at Chicago; University of Chicago
  • Peter Larsen, Argonne National Laboratory
  • Tifani Anton, Argonne National Laboratory
  • Lauren Cralle, University of Chicago
  • Naseer Sangwan, Cleveland Clinic
  • Simon Lax, Mssachusetts Institute of Technology
  • Neil Gottel, University of California - San Diego
  • Mariana Salas-Garcia, University of California - San Diego
  • Candace Young, Chicago State University
  • George Duncan, Nova Oceanographic
  • Jose Lopez, Nova Southeastern University
  • Jack A. Gilbert, Argonne National Laboratory; University of California - San Diego
Document Type
Article
Publication Date
5-30-2020
Keywords
  • Forensic microbiology,
  • Built-environment,
  • Host-microbe,
  • Trace evidence,
  • Human microbiome
Disciplines
Abstract

When mapped to the environments we interact with on a daily basis, the 36 million microbial cells per hour that humans emit leave a trail of evidence that can be leveraged for forensic analysis. We employed 16S rRNA amplicon sequencing to map unique microbial sequence variants between human skin and building surfaces in three experimental conditions: over time during controlled and uncontrolled incidental interactions with a door handle, and during multiple mock burglaries in ten real residences. We demonstrate that humans (n = 30) leave behind microbial signatures that can be used to track interaction with various surfaces within a building, but the likelihood of accurately detecting the specific burglar for a given home was between 20-25%. Also, the human microbiome contains rare microbial taxa that can be combined to create a unique microbial profile, which when compared to 600 other individuals can improve our ability to link an individual ‘burglar’ to a residence. In total, 5,512 discriminating, non-singleton unique exact sequence variants (uESVs) were identified as unique to an individual, with a minimum of 1 and a maximum of 568, suggesting some people maintain a greater degree of unique taxa compared to our population of 600. Approximate 60-77% of the unique exact sequence variants originated from the hands of participants, and these microbial discriminators spanned 36 phyla but were dominated by the Proteobacteria (34%). A fitted regression generated to determine whether an intruder’s uESVs found on door handles in an office decayed over time in the presence or absence of office workers, found no significant shift in proportion of uESVs over time irrespective of the presence of office workers. While it was possible to detect the correct burglars’ microbiota as having contributed to the invaded space, the predictions were very weak in comparison to accepted forensic standards. This suggests that at this time 16S rRNA amplicon sequencing of the built environment microbiota cannot be used as a reliable trace evidence standard for criminal investigations.

Comments

©2020 Published by Elsevier B.V.

Additional Comments
National Institutes of Justice award #: 2015-DN-BX-K430
Creative Commons License
Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International
ORCID ID
0000-0002-4931-5316, 0000-0002-1637-4125
ResearcherID
F-8809-2011
DOI
10.1016/j.forsciint.2020.110351
Citation Information
Jarrad T. Hampton-Marcell, Peter Larsen, Tifani Anton, Lauren Cralle, et al.. "Detecting Personal Microbiota Signatures at Artificial Crime Scenes" Forensic Science International (2020) p. 1 - 21 ISSN: 0379-0738
Available at: http://works.bepress.com/jose-lopez/255/