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Detecting Personal Microbiota Signatures at Artificial Crime Scenes

  • Jarrad T. Hampton-Marcell
  • , Peter Larsen
  • , Tifani Anton
  • , Lauren Cralle
  • , Naseer Sangwan
  • , Simon Lax
  • , Neil Gottel
  • , Mariana Salas-Garcia
  • , Candace Young
  • , George Duncan
  • , Jose Lopez
  • , Jack A. Gilbert

Research output: Contribution to journalArticlepeer-review

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.

Original languageAmerican English
Article number110351
JournalForensic Science International
Volume313
Issue number2020
DOIs
StatePublished - Aug 2020

Bibliographical note

Publisher Copyright:
© 2020 The Authors

Funding

This work was sponsored by National Institutes of Justice award 2015-DN-BX-K430 . We thank members of the Gilbert and Lopez Lab (Kyle Roebuck) in assisting in collection and de-identification samples and their compositional data, as well as assisting in data analysis. We thank all volunteers who provided consent for mock burglaries at their residence. The human study reported here was approved under Institutional Review Board (IRB) Approval Number IRB16-0129 at the University of Chicago and IRB Approval Number # 2016-106-NSU at Nova Southeastern University.

FundersFunder number
National Institute of Justice2015-DN-BX-K430

    ASJC Scopus Subject Areas

    • Pathology and Forensic Medicine

    Keywords

    • Forensic microbiology
    • Built-environment
    • Host-microbe
    • Trace evidence
    • Human microbiome

    Disciplines

    • Biology
    • Life Sciences

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