Detecting personal microbiota signatures at artificial crime scenes.


Journal

Forensic science international
ISSN: 1872-6283
Titre abrégé: Forensic Sci Int
Pays: Ireland
ID NLM: 7902034

Informations de publication

Date de publication:
Aug 2020
Historique:
received: 16 03 2020
revised: 13 05 2020
accepted: 26 05 2020
pubmed: 20 6 2020
medline: 10 2 2021
entrez: 20 6 2020
Statut: ppublish

Résumé

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, 5512 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.

Identifiants

pubmed: 32559614
pii: S0379-0738(20)30213-9
doi: 10.1016/j.forsciint.2020.110351
pii:
doi:

Substances chimiques

RNA, Ribosomal, 16S 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

110351

Informations de copyright

Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.

Auteurs

Jarrad T Hampton-Marcell (JT)

Biosciences Division, Argonne National Laboratory, Lemont, IL, United States; Department of Biological Sciences, University of Illinois at Chicago, Chicago, IL, United States; Department of Surgery, University of Chicago, Chicago, IL, United States. Electronic address: jarrad.marcell@gmail.com.

Peter Larsen (P)

Biosciences Division, Argonne National Laboratory, Lemont, IL, United States.

Tifani Anton (T)

Biosciences Division, Argonne National Laboratory, Lemont, IL, United States.

Lauren Cralle (L)

Department of Surgery, University of Chicago, Chicago, IL, United States.

Naseer Sangwan (N)

Department of Cardiovascular and Metabolic Sciences, Cleveland Clinic, Cleveland, OH, United States.

Simon Lax (S)

Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, United States.

Neil Gottel (N)

Department of Pediatrics and Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, United States.

Mariana Salas-Garcia (M)

Department of Pediatrics and Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, United States.

Candace Young (C)

Department of Chemistry, Physics and Engineering Studies, Chicago State University, Chicago, IL, United States.

George Duncan (G)

Department of Biological Sciences, Nova Southeastern University, Fort Lauderdale, FL, United States.

Jose V Lopez (JV)

Department of Biological Sciences, Nova Southeastern University, Fort Lauderdale, FL, United States.

Jack A Gilbert (JA)

Biosciences Division, Argonne National Laboratory, Lemont, IL, United States; Department of Pediatrics and Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, United States.

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Classifications MeSH