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Design and optimization of a 16S microbial qPCR multiplex for the presumptive identification of feces, saliva, vaginal and menstrual secretions
Molecular methods for body fluid identification have been extensively researched in the forensic community over the last decade, mostly focusing on RNA‐based methods. Microbial DNA analysis has long been used for forensic applications, such as postmortem interval estimations, but only recently has i...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9310585/ https://www.ncbi.nlm.nih.gov/pubmed/35352345 http://dx.doi.org/10.1111/1556-4029.15029 |
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author | Lewis, Carolyn Seashols‐Williams, Sarah J. |
author_facet | Lewis, Carolyn Seashols‐Williams, Sarah J. |
author_sort | Lewis, Carolyn |
collection | PubMed |
description | Molecular methods for body fluid identification have been extensively researched in the forensic community over the last decade, mostly focusing on RNA‐based methods. Microbial DNA analysis has long been used for forensic applications, such as postmortem interval estimations, but only recently has it been applied to body fluid identification. High‐throughput sequencing of the 16S ribosomal RNA gene by previous research groups revealed that microbial signatures and abundances vary across human body fluids at the genus and/or species taxonomic level. Since quantitative PCR is still the current technique used in forensic DNA analysis, the purpose of this study was to design a qPCR multiplex targeting the 16S gene of Bacteroides uniformis, Streptococcus salivarius, and Lactobacillus crispatus that can distinguish between feces, saliva, and vaginal/menstrual secretions, respectively. Primers and probes were designed at the species level because these bacteria are highly abundant within their respective fluid. The validated 16S triplex was evaluated in DNA extracts from thirty donors of each body fluid. A classification regression tree model resulted in 96.5% classification accuracy of the population data, which demonstrates the ability of this 16S triplex to presumptively identify these fluids with high confidence at the quantification step of the forensic workflow using minimal input volume of DNA extracted from evidentiary samples. |
format | Online Article Text |
id | pubmed-9310585 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93105852022-07-29 Design and optimization of a 16S microbial qPCR multiplex for the presumptive identification of feces, saliva, vaginal and menstrual secretions Lewis, Carolyn Seashols‐Williams, Sarah J. J Forensic Sci Technical Notes Molecular methods for body fluid identification have been extensively researched in the forensic community over the last decade, mostly focusing on RNA‐based methods. Microbial DNA analysis has long been used for forensic applications, such as postmortem interval estimations, but only recently has it been applied to body fluid identification. High‐throughput sequencing of the 16S ribosomal RNA gene by previous research groups revealed that microbial signatures and abundances vary across human body fluids at the genus and/or species taxonomic level. Since quantitative PCR is still the current technique used in forensic DNA analysis, the purpose of this study was to design a qPCR multiplex targeting the 16S gene of Bacteroides uniformis, Streptococcus salivarius, and Lactobacillus crispatus that can distinguish between feces, saliva, and vaginal/menstrual secretions, respectively. Primers and probes were designed at the species level because these bacteria are highly abundant within their respective fluid. The validated 16S triplex was evaluated in DNA extracts from thirty donors of each body fluid. A classification regression tree model resulted in 96.5% classification accuracy of the population data, which demonstrates the ability of this 16S triplex to presumptively identify these fluids with high confidence at the quantification step of the forensic workflow using minimal input volume of DNA extracted from evidentiary samples. John Wiley and Sons Inc. 2022-03-30 2022-07 /pmc/articles/PMC9310585/ /pubmed/35352345 http://dx.doi.org/10.1111/1556-4029.15029 Text en © 2022 The Authors. Journal of Forensic Sciences published by Wiley Periodicals LLC on behalf of American Academy of Forensic Sciences. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Technical Notes Lewis, Carolyn Seashols‐Williams, Sarah J. Design and optimization of a 16S microbial qPCR multiplex for the presumptive identification of feces, saliva, vaginal and menstrual secretions |
title | Design and optimization of a 16S microbial qPCR multiplex for the presumptive identification of feces, saliva, vaginal and menstrual secretions |
title_full | Design and optimization of a 16S microbial qPCR multiplex for the presumptive identification of feces, saliva, vaginal and menstrual secretions |
title_fullStr | Design and optimization of a 16S microbial qPCR multiplex for the presumptive identification of feces, saliva, vaginal and menstrual secretions |
title_full_unstemmed | Design and optimization of a 16S microbial qPCR multiplex for the presumptive identification of feces, saliva, vaginal and menstrual secretions |
title_short | Design and optimization of a 16S microbial qPCR multiplex for the presumptive identification of feces, saliva, vaginal and menstrual secretions |
title_sort | design and optimization of a 16s microbial qpcr multiplex for the presumptive identification of feces, saliva, vaginal and menstrual secretions |
topic | Technical Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9310585/ https://www.ncbi.nlm.nih.gov/pubmed/35352345 http://dx.doi.org/10.1111/1556-4029.15029 |
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