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Cited by 609

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Forensic identification using skin bacterial communities

Open access
Fierer, Noah, Lauber, Christian L., Zhou, Nick, McDonald, Daniel, Costello, Elizabeth K., Knight, Rob·2010·Proceedings of the National Academy of Sciences

Abstract

Recent work has demonstrated that the diversity of skin-associated bacterial communities is far higher than previously recognized, with a high degree of interindividual variability in the composition of bacterial communities. Given that skin bacterial communities are personalized, we hypothesized that we could use the residual skin bacteria left on objects for forensic identification, matching the bacteria on the object to the skin-associated bacteria of the individual who touched the object. Here we describe a series of studies de-monstrating the validity of this approach. We show that skin-associated bacteria can be readily recovered from surfaces (including single computer keys and computer mice) and that the structure of these communities can be used to differentiate objects handled by different individuals, even if those objects have been left untouched for up to 2 weeks at room temperature. Furthermore, we demonstrate that we can use a high-throughput pyrosequencing-based ap-proach to quantitatively compare the bacterial communities on objects and skin to match the object to the individual with a high degree of certainty. Although additional work is needed to further establish the utility of this approach, this series of studies introduces a forensics approach that could eventually be used to independently evaluate results obtained using more traditional forensic practices.

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Metadata

Authors
Fierer, N., Lauber, C. L., Zhou, N., McDonald, D., Costello, E. K., & Knight, R.
Venue
Proceedings of the National Academy of Sciences
Published
2010-03-15
Volume
107
Issue
14
Pages
6477-6481
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2066011810
Cited by
609
References
3
FWCI
45.53
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Forensic identification using skin bacterial communities. https://app.cochat.ai/papers/10.1073/pnas.1000162107
The paper
Fierer, N., Lauber, C. L., Zhou, N., McDonald, D., Costello, E. K., & Knight, R. (2010). Forensic identification using skin bacterial communities. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1000162107

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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