Evidence map›Paper›PMID 34090519›Full record

ArticleMicrobiome2021

Diurnal variation in the human skin microbiome affects accuracy of forensic microbiome matching.

David Wilkins, Xinzhao Tong, Marcus H Y Leung, Christopher E Mason, Patrick K H Lee

Abstract readVideo-Audio Media
In one paragraph

Article in Microbiome, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. [Advances in the Application of Forensic Microbiome Analysis in Tissue Source Inference].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2025
    Pooled it
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  12. Explore variation of salivary bacteria across time and geolocations.International journal of legal medicine · 2024
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  15. Article
  16. Article
  17. Application of Microbiome in Forensics.Genomics, proteomics & bioinformatics · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

David WilkinsSchool of Energy and Environment, City University of Hong Kong, Hong Kong SAR, China.
Xinzhao TongSchool of Energy and Environment, City University of Hong Kong, Hong Kong SAR, China.
Marcus H Y LeungSchool of Energy and Environment, City University of Hong Kong, Hong Kong SAR, China.
Christopher E MasonDepartment of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.
Patrick K H LeeSchool of Energy and Environment, City University of Hong Kong, Hong Kong SAR, China. patrick.kh.lee@cityu.edu.hk.ORCID 0000-0003-0911-5317

Funding

Metagenomic profiling of urinary cell-free DNA to monitor urinary tract infection after kidney transplantationR01AI151059 · NIAID · CORNELL UNIVERSITY · PI DADHANIA, DARSHANA, DE VLAMINCK, IWIJN · 2020 to 2024
$3.4M
NIAID NIH HHS R01 AI151059
6 · The paper itself

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. Video Abstract.

Indexed as

MicrobiotaBayes TheoremHong KongHumansMetagenomicsBuilt environmentForensicsMicrobiotaSkinSurface

Identifiers

PMID34090519
PMCPMC8180031

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.