Abstract

BackgroundThe human skin microbiome has been recently investigated as a potential forensic tool, as people leave traces of their potentially unique microbiomes on objects and surfaces with which they interact. In this metagenomic study of four people in Hong Kong, their homes, and public surfaces in their neighbourhoods, we investigated the stability and identifiability of these microbiota traces on a timescale of hours to days.ResultsUsing a Canberra distance-based method of comparing skin and surface microbiomes, we found that a person could be accurately matched to their household in 84% of tests and to their neighbourhood in 50% of tests, and that matching accuracy did not decay for household surfaces over the 10-day study period, although it did for public surfaces. The time of day at which a skin or surface sample was taken affected matching accuracy, and 160 species across all sites were found to have a significant variation in abundance between morning and evening samples. We hypothesised that daily routines drive a rhythm of daytime dispersal from the pooled public surface microbiome followed by normalisation of a person’s microbiome by contact with their household microbial reservoir, and Dynamic Bayesian Networks (DBNs) supported dispersal from public surfaces to skin as the major dispersal route among all sites studied.ConclusionsThese results suggest that in addition to considering the decay of microbiota traces with time, diurnal patterns in microbiome exposure that contribute to the human skin microbiome assemblage must also be considered in developing this as a potential forensic method.3rx_gMdDV2df1kQKP4s232Video

Highlights

  • A central aim of forensic science is to accurately identify people from the trace evidence they leave behind whilst moving through and interacting with an environment

  • In a previous study of microbiota matching of people to their homes over a time scale of months, we found that taxa that were more useful in identifying people were more likely to be lost from both skin microbiomes and surface traces over time, and less likely to be dispersed from skin to surfaces in the first place [11]

  • Person 1 was noted to have a high abundance of Micrococcaceae compared to the other people in the study; person 2 was characterised by Dermacoccaceae; person 3 a mix of families including Gordoniaceae, Dietziaceae and Dermacoccaceae; and person 4 Dermabacteraceae. These distinctive profiles were reflected in the surface microbiomes from the respective homes, with residence 1 having a substantial abundance of Micrococcaceae, residence 2 a high abundance of Dermacoccaceae on the door knob, residence 3 a high abundance of Gordoniaceae on both the door knob and bed headboard and residence 4 a high abundance of Dermabacteraceae. This pattern of locality-specific families was not as evident for the public surface samples, which are likely to reflect microbiota input pooled from the local population and environmental sources

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Summary

Introduction

A central aim of forensic science is to accurately identify people from the trace evidence they leave behind whilst moving through and interacting with an environment. Low-abundance taxa may be more valuable in identifying individuals compared to abundant taxa [11, 17], but may be more susceptible to elimination and more likely to be the result of deposition events (‘transients’) rather than being well adapted to the skin environment and established in microbial community networks (‘residents’) The nature of these low-abundance taxa, the processes that cause the loss of identifying features and the time scale on which this loss occurs are poorly understood. The human skin microbiome has been recently investigated as a potential forensic tool, as people leave traces of their potentially unique microbiomes on objects and surfaces with which they interact In this metagenomic study of four people in Hong Kong, their homes, and public surfaces in their neighbourhoods, we investigated the stability and identifiability of these microbiota traces on a timescale of hours to days

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