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Forensic Microbiome Database: A Tool for Forensic Geolocation Meta-Analysis Using Publicly Available 16S rRNA Microbiome Sequencing

The human microbiome has been proposed as a tool to investigate different forensic questions, including for the identification of multiple personal information. However, the fragmented state of the publicly available data has retarded the development of analysis techniques and, therefore, the implem...

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Autores principales: Singh, Harinder, Clarke, Thomas, Brinkac, Lauren, Greco, Chris, Nelson, Karen E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8022992/
https://www.ncbi.nlm.nih.gov/pubmed/33833745
http://dx.doi.org/10.3389/fmicb.2021.644861
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author Singh, Harinder
Clarke, Thomas
Brinkac, Lauren
Greco, Chris
Nelson, Karen E.
author_facet Singh, Harinder
Clarke, Thomas
Brinkac, Lauren
Greco, Chris
Nelson, Karen E.
author_sort Singh, Harinder
collection PubMed
description The human microbiome has been proposed as a tool to investigate different forensic questions, including for the identification of multiple personal information. However, the fragmented state of the publicly available data has retarded the development of analysis techniques and, therefore, the implementation of microbiomes as a forensic tool. To address this, we introduce the forensic microbiome database (FMD), which is a collection of 16S rRNA data and associated metadata generated from publicly available data. The raw data was further normalized and processed using a pipeline to create a standardized data set for downstream analysis. We present a website allowing for the exploration of geolocation signals in the FMD. The website allows users to investigate the taxonomic differences between microbiomes harvested from different locations and to predict the geolocation of their data based on the FMD sequences. All the results are presented in dynamic graphics to allow for a rapid and intuitive investigation of the taxonomic distributions underpinning the geolocation signals and prediction between locations. Apart from the forensic aspect, the database also allows exploration and comparison of microbiome samples from different geolocation and between different body sites. The goal of the FMD is to provide the scientific and non-scientific communities with data and tools to explore the possibilities of microbiomes to answer forensic questions and serve as a model for any future such databases.
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spelling pubmed-80229922021-04-07 Forensic Microbiome Database: A Tool for Forensic Geolocation Meta-Analysis Using Publicly Available 16S rRNA Microbiome Sequencing Singh, Harinder Clarke, Thomas Brinkac, Lauren Greco, Chris Nelson, Karen E. Front Microbiol Microbiology The human microbiome has been proposed as a tool to investigate different forensic questions, including for the identification of multiple personal information. However, the fragmented state of the publicly available data has retarded the development of analysis techniques and, therefore, the implementation of microbiomes as a forensic tool. To address this, we introduce the forensic microbiome database (FMD), which is a collection of 16S rRNA data and associated metadata generated from publicly available data. The raw data was further normalized and processed using a pipeline to create a standardized data set for downstream analysis. We present a website allowing for the exploration of geolocation signals in the FMD. The website allows users to investigate the taxonomic differences between microbiomes harvested from different locations and to predict the geolocation of their data based on the FMD sequences. All the results are presented in dynamic graphics to allow for a rapid and intuitive investigation of the taxonomic distributions underpinning the geolocation signals and prediction between locations. Apart from the forensic aspect, the database also allows exploration and comparison of microbiome samples from different geolocation and between different body sites. The goal of the FMD is to provide the scientific and non-scientific communities with data and tools to explore the possibilities of microbiomes to answer forensic questions and serve as a model for any future such databases. Frontiers Media S.A. 2021-03-23 /pmc/articles/PMC8022992/ /pubmed/33833745 http://dx.doi.org/10.3389/fmicb.2021.644861 Text en Copyright © 2021 Singh, Clarke, Brinkac, Greco and Nelson. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Microbiology
Singh, Harinder
Clarke, Thomas
Brinkac, Lauren
Greco, Chris
Nelson, Karen E.
Forensic Microbiome Database: A Tool for Forensic Geolocation Meta-Analysis Using Publicly Available 16S rRNA Microbiome Sequencing
title Forensic Microbiome Database: A Tool for Forensic Geolocation Meta-Analysis Using Publicly Available 16S rRNA Microbiome Sequencing
title_full Forensic Microbiome Database: A Tool for Forensic Geolocation Meta-Analysis Using Publicly Available 16S rRNA Microbiome Sequencing
title_fullStr Forensic Microbiome Database: A Tool for Forensic Geolocation Meta-Analysis Using Publicly Available 16S rRNA Microbiome Sequencing
title_full_unstemmed Forensic Microbiome Database: A Tool for Forensic Geolocation Meta-Analysis Using Publicly Available 16S rRNA Microbiome Sequencing
title_short Forensic Microbiome Database: A Tool for Forensic Geolocation Meta-Analysis Using Publicly Available 16S rRNA Microbiome Sequencing
title_sort forensic microbiome database: a tool for forensic geolocation meta-analysis using publicly available 16s rrna microbiome sequencing
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8022992/
https://www.ncbi.nlm.nih.gov/pubmed/33833745
http://dx.doi.org/10.3389/fmicb.2021.644861
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