This report examines the potential for using the total human microbiota, including bacteria, fungi, and viruses found on human-touched objects as microbial signatures for forensic human identification.
The author reports on a project that had three objectives relating to the utilization of human skin microbiomes as trace evidence for forensic applications: the first objective, to identify trace evidence suitable for the microbiome-based forensic application, hypothesizing that the objects that humans touch can be classified or categorized based on the transferability of the microbiome from the human skin; the second objective, to determine the total microbiome as trace evidence left on human-touched objects, hypothesizing that the structure and composition of the total microbiome from touched objects may have higher inter-individual variability and can be used to distinguish individuals and, as a result, determine human identity; and the third objective, to identify core/variable/transient microbiome associated with different post-contact intervals, hypothesizing that the structure and microbiome left on the objects may be changed over time after contact, and may serve as a tool for determining the elapsed time since contact and post-contact intervals (PCI). For their research, the author developed the reverse lifting method as a non-invasive fingerprint lifting method to identify human-touched objects suitable for both fingerprint and microbiome-based analysis. DNA was extracted, quantified, and amplified for amplified for amplicon sequencing and quantitative PCR (polymerase chain reaction) assay. As a result, the author suggests that microbiome-based forensic identification may provide an alternative method to identify individuals associated with a crime scene.
- A Randomized Controlled Trial of the Impact of Body-Worn Cameras in the Loudoun County, VA, Adult Detention Center
- Automation of Sexual Assault DNA Processing Increases Efficiency
- A quantifiler™ trio-based HRM screening assay for the accurate prediction of single source versus mixed biological samples