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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...

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Autores principales: Kumar, Aditi, Gravdal, Kristin, Segal, Jonathan P., Steed, Helen, Brookes, Matthew J., Al-Hassi, Hafid O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
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.
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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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