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Variability in the Pre-Analytical Stages Influences Microbiome Laboratory Analyses
Introduction: There are numerous confounding variables in the pre-analytical steps in the analysis of gut microbial composition that affect data consistency and reproducibility. This study compared two DNA extraction methods from the same faecal samples to analyse differences in microbial compositio...
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/PMC9223004/ https://www.ncbi.nlm.nih.gov/pubmed/35741831 http://dx.doi.org/10.3390/genes13061069 |
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author | Kumar, Aditi Gravdal, Kristin Segal, Jonathan P. Steed, Helen Brookes, Matthew J. Al-Hassi, Hafid O. |
author_facet | Kumar, Aditi Gravdal, Kristin Segal, Jonathan P. Steed, Helen Brookes, Matthew J. Al-Hassi, Hafid O. |
author_sort | Kumar, Aditi |
collection | PubMed |
description | Introduction: There are numerous confounding variables in the pre-analytical steps in the analysis of gut microbial composition that affect data consistency and reproducibility. This study compared two DNA extraction methods from the same faecal samples to analyse differences in microbial composition. Methods: DNA was extracted from 20 faecal samples using either (A) chemical/enzymatic heat lysis (lysis buffer, proteinase K, 95 °C + 70 °C) or (B) mechanical and chemical/enzymatic heat lysis (bead-beating, lysis buffer, proteinase K, 65 °C). Gut microbiota was mapped through the 16S rRNA gene (V3–V9) using a set of pre-selected DNA probes targeting >300 bacteria on different taxonomic levels. Apart from the pre-analytical DNA extraction technique, all other parameters including microbial analysis remained the same. Bacterial abundance and deviations in the microbiome were compared between the two methods. Results: Significant variation in bacterial abundance was seen between the different DNA extraction techniques, with a higher yield of species noted in the combined mechanical and heat lysis technique (B). The five predominant bacteria seen in both (A) and (B) were Bacteroidota spp. and Prevotella spp. (p = NS), followed by Bacillota (p = 0.005), Lachhnospiraceae (p = 0.0001), Veillonella spp. (p < 0.0001) and Clostridioides (p < 0.0001). Conclusion: As microbial testing becomes more easily and commercially accessible, a unified international consensus for optimal sampling and DNA isolation procedures must be implemented for robustness and reproducibility of the results. |
format | Online Article Text |
id | pubmed-9223004 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-92230042022-06-24 Variability in the Pre-Analytical Stages Influences Microbiome Laboratory Analyses Kumar, Aditi Gravdal, Kristin Segal, Jonathan P. Steed, Helen Brookes, Matthew J. Al-Hassi, Hafid O. Genes (Basel) Article Introduction: There are numerous confounding variables in the pre-analytical steps in the analysis of gut microbial composition that affect data consistency and reproducibility. This study compared two DNA extraction methods from the same faecal samples to analyse differences in microbial composition. Methods: DNA was extracted from 20 faecal samples using either (A) chemical/enzymatic heat lysis (lysis buffer, proteinase K, 95 °C + 70 °C) or (B) mechanical and chemical/enzymatic heat lysis (bead-beating, lysis buffer, proteinase K, 65 °C). Gut microbiota was mapped through the 16S rRNA gene (V3–V9) using a set of pre-selected DNA probes targeting >300 bacteria on different taxonomic levels. Apart from the pre-analytical DNA extraction technique, all other parameters including microbial analysis remained the same. Bacterial abundance and deviations in the microbiome were compared between the two methods. Results: Significant variation in bacterial abundance was seen between the different DNA extraction techniques, with a higher yield of species noted in the combined mechanical and heat lysis technique (B). The five predominant bacteria seen in both (A) and (B) were Bacteroidota spp. and Prevotella spp. (p = NS), followed by Bacillota (p = 0.005), Lachhnospiraceae (p = 0.0001), Veillonella spp. (p < 0.0001) and Clostridioides (p < 0.0001). Conclusion: As microbial testing becomes more easily and commercially accessible, a unified international consensus for optimal sampling and DNA isolation procedures must be implemented for robustness and reproducibility of the results. MDPI 2022-06-15 /pmc/articles/PMC9223004/ /pubmed/35741831 http://dx.doi.org/10.3390/genes13061069 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 | Article Kumar, Aditi Gravdal, Kristin Segal, Jonathan P. Steed, Helen Brookes, Matthew J. Al-Hassi, Hafid O. Variability in the Pre-Analytical Stages Influences Microbiome Laboratory Analyses |
title | Variability in the Pre-Analytical Stages Influences Microbiome Laboratory Analyses |
title_full | Variability in the Pre-Analytical Stages Influences Microbiome Laboratory Analyses |
title_fullStr | Variability in the Pre-Analytical Stages Influences Microbiome Laboratory Analyses |
title_full_unstemmed | Variability in the Pre-Analytical Stages Influences Microbiome Laboratory Analyses |
title_short | Variability in the Pre-Analytical Stages Influences Microbiome Laboratory Analyses |
title_sort | variability in the pre-analytical stages influences microbiome laboratory analyses |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9223004/ https://www.ncbi.nlm.nih.gov/pubmed/35741831 http://dx.doi.org/10.3390/genes13061069 |
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