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Post-Mortem Interval and Microbiome Analysis through 16S rRNA Analysis: A Systematic Review
The determination of the Post-Mortem Interval (PMI) is an issue that has always represented a challenge in the field of forensic science. Different innovative approaches, compared to the more traditional ones, have been tried over the years, without succeeding in being validated as successful method...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689864/ https://www.ncbi.nlm.nih.gov/pubmed/36359484 http://dx.doi.org/10.3390/diagnostics12112641 |
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author | Tozzo, Pamela Amico, Irene Delicati, Arianna Toselli, Federico Caenazzo, Luciana |
author_facet | Tozzo, Pamela Amico, Irene Delicati, Arianna Toselli, Federico Caenazzo, Luciana |
author_sort | Tozzo, Pamela |
collection | PubMed |
description | The determination of the Post-Mortem Interval (PMI) is an issue that has always represented a challenge in the field of forensic science. Different innovative approaches, compared to the more traditional ones, have been tried over the years, without succeeding in being validated as successful methods for PMI estimation. In the last two decades, innovations in sequencing technologies have made it possible to generate large volumes of data, allowing all members of a bacterial community to be sequenced. The aim of this manuscript is to provide a review regarding new advances in PMI estimation through cadaveric microbiota identification using 16S rRNA sequencing, in order to correlate specific microbiome profiles obtained from different body sites to PMI. The systematic review was performed according to PRISMA guidelines. For this purpose, 800 studies were identified through database searching (Pubmed). Articles that dealt with PMI estimation in correlation with microbiome composition and contained data about species, body site of sampling, monitoring time and sequencing method were selected and ultimately a total of 25 studies were considered. The selected studies evaluated the contribution of the various body sites to determine PMI, based on microbiome sequencing, in human and animal models. The results of this systematic review highlighted that studies conducted on both animals and humans yielded results that were promising. In order to fully exploit the potential of the microbiome in the estimation of PMI, it would be desirable to identify standardized body sampling sites and specific sampling methods in order to align data obtained by different research groups. |
format | Online Article Text |
id | pubmed-9689864 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96898642022-11-25 Post-Mortem Interval and Microbiome Analysis through 16S rRNA Analysis: A Systematic Review Tozzo, Pamela Amico, Irene Delicati, Arianna Toselli, Federico Caenazzo, Luciana Diagnostics (Basel) Systematic Review The determination of the Post-Mortem Interval (PMI) is an issue that has always represented a challenge in the field of forensic science. Different innovative approaches, compared to the more traditional ones, have been tried over the years, without succeeding in being validated as successful methods for PMI estimation. In the last two decades, innovations in sequencing technologies have made it possible to generate large volumes of data, allowing all members of a bacterial community to be sequenced. The aim of this manuscript is to provide a review regarding new advances in PMI estimation through cadaveric microbiota identification using 16S rRNA sequencing, in order to correlate specific microbiome profiles obtained from different body sites to PMI. The systematic review was performed according to PRISMA guidelines. For this purpose, 800 studies were identified through database searching (Pubmed). Articles that dealt with PMI estimation in correlation with microbiome composition and contained data about species, body site of sampling, monitoring time and sequencing method were selected and ultimately a total of 25 studies were considered. The selected studies evaluated the contribution of the various body sites to determine PMI, based on microbiome sequencing, in human and animal models. The results of this systematic review highlighted that studies conducted on both animals and humans yielded results that were promising. In order to fully exploit the potential of the microbiome in the estimation of PMI, it would be desirable to identify standardized body sampling sites and specific sampling methods in order to align data obtained by different research groups. MDPI 2022-10-31 /pmc/articles/PMC9689864/ /pubmed/36359484 http://dx.doi.org/10.3390/diagnostics12112641 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Systematic Review Tozzo, Pamela Amico, Irene Delicati, Arianna Toselli, Federico Caenazzo, Luciana Post-Mortem Interval and Microbiome Analysis through 16S rRNA Analysis: A Systematic Review |
title | Post-Mortem Interval and Microbiome Analysis through 16S rRNA Analysis: A Systematic Review |
title_full | Post-Mortem Interval and Microbiome Analysis through 16S rRNA Analysis: A Systematic Review |
title_fullStr | Post-Mortem Interval and Microbiome Analysis through 16S rRNA Analysis: A Systematic Review |
title_full_unstemmed | Post-Mortem Interval and Microbiome Analysis through 16S rRNA Analysis: A Systematic Review |
title_short | Post-Mortem Interval and Microbiome Analysis through 16S rRNA Analysis: A Systematic Review |
title_sort | post-mortem interval and microbiome analysis through 16s rrna analysis: a systematic review |
topic | Systematic Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689864/ https://www.ncbi.nlm.nih.gov/pubmed/36359484 http://dx.doi.org/10.3390/diagnostics12112641 |
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