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Benchmarking laboratory processes to characterise low-biomass respiratory microbiota

The low biomass of respiratory samples makes it difficult to accurately characterise the microbial community composition. PCR conditions and contaminating microbial DNA can alter the biological profile. The objective of this study was to benchmark the currently available laboratory protocols to accu...

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Autores principales: Hasrat, Raiza, Kool, Jolanda, de Steenhuijsen Piters, Wouter A. A., Chu, Mei Ling J. N., Kuiling, Sjoerd, Groot, James A., van Logchem, Elske M., Fuentes, Susana, Franz, Eelco, Bogaert, Debby, Bosch, Thijs
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8387476/
https://www.ncbi.nlm.nih.gov/pubmed/34433845
http://dx.doi.org/10.1038/s41598-021-96556-5
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author Hasrat, Raiza
Kool, Jolanda
de Steenhuijsen Piters, Wouter A. A.
Chu, Mei Ling J. N.
Kuiling, Sjoerd
Groot, James A.
van Logchem, Elske M.
Fuentes, Susana
Franz, Eelco
Bogaert, Debby
Bosch, Thijs
author_facet Hasrat, Raiza
Kool, Jolanda
de Steenhuijsen Piters, Wouter A. A.
Chu, Mei Ling J. N.
Kuiling, Sjoerd
Groot, James A.
van Logchem, Elske M.
Fuentes, Susana
Franz, Eelco
Bogaert, Debby
Bosch, Thijs
author_sort Hasrat, Raiza
collection PubMed
description The low biomass of respiratory samples makes it difficult to accurately characterise the microbial community composition. PCR conditions and contaminating microbial DNA can alter the biological profile. The objective of this study was to benchmark the currently available laboratory protocols to accurately analyse the microbial community of low biomass samples. To study the effect of PCR conditions on the microbial community profile, we amplified the 16S rRNA gene of respiratory samples using various bacterial loads and different number of PCR cycles. Libraries were purified by gel electrophoresis or AMPure XP and sequenced by V2 or V3 MiSeq reagent kits by Illumina sequencing. The positive control was diluted in different solvents. PCR conditions had no significant influence on the microbial community profile of low biomass samples. Purification methods and MiSeq reagent kits provided nearly similar microbiota profiles (paired Bray–Curtis dissimilarity median: 0.03 and 0.05, respectively). While profiles of positive controls were significantly influenced by the type of dilution solvent, the theoretical profile of the Zymo mock was most accurately analysed when the Zymo mock was diluted in elution buffer (difference compared to the theoretical Zymo mock: 21.6% for elution buffer, 29.2% for Milli-Q, and 79.6% for DNA/RNA shield). Microbiota profiles of DNA blanks formed a distinct cluster compared to low biomass samples, demonstrating that low biomass samples can accurately be distinguished from DNA blanks. In summary, to accurately characterise the microbial community composition we recommend 1. amplification of the obtained microbial DNA with 30 PCR cycles, 2. purifying amplicon pools by two consecutive AMPure XP steps and 3. sequence the pooled amplicons by V3 MiSeq reagent kit. The benchmarked standardized laboratory workflow presented here ensures comparability of results within and between low biomass microbiome studies.
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spelling pubmed-83874762021-09-01 Benchmarking laboratory processes to characterise low-biomass respiratory microbiota Hasrat, Raiza Kool, Jolanda de Steenhuijsen Piters, Wouter A. A. Chu, Mei Ling J. N. Kuiling, Sjoerd Groot, James A. van Logchem, Elske M. Fuentes, Susana Franz, Eelco Bogaert, Debby Bosch, Thijs Sci Rep Article The low biomass of respiratory samples makes it difficult to accurately characterise the microbial community composition. PCR conditions and contaminating microbial DNA can alter the biological profile. The objective of this study was to benchmark the currently available laboratory protocols to accurately analyse the microbial community of low biomass samples. To study the effect of PCR conditions on the microbial community profile, we amplified the 16S rRNA gene of respiratory samples using various bacterial loads and different number of PCR cycles. Libraries were purified by gel electrophoresis or AMPure XP and sequenced by V2 or V3 MiSeq reagent kits by Illumina sequencing. The positive control was diluted in different solvents. PCR conditions had no significant influence on the microbial community profile of low biomass samples. Purification methods and MiSeq reagent kits provided nearly similar microbiota profiles (paired Bray–Curtis dissimilarity median: 0.03 and 0.05, respectively). While profiles of positive controls were significantly influenced by the type of dilution solvent, the theoretical profile of the Zymo mock was most accurately analysed when the Zymo mock was diluted in elution buffer (difference compared to the theoretical Zymo mock: 21.6% for elution buffer, 29.2% for Milli-Q, and 79.6% for DNA/RNA shield). Microbiota profiles of DNA blanks formed a distinct cluster compared to low biomass samples, demonstrating that low biomass samples can accurately be distinguished from DNA blanks. In summary, to accurately characterise the microbial community composition we recommend 1. amplification of the obtained microbial DNA with 30 PCR cycles, 2. purifying amplicon pools by two consecutive AMPure XP steps and 3. sequence the pooled amplicons by V3 MiSeq reagent kit. The benchmarked standardized laboratory workflow presented here ensures comparability of results within and between low biomass microbiome studies. Nature Publishing Group UK 2021-08-25 /pmc/articles/PMC8387476/ /pubmed/34433845 http://dx.doi.org/10.1038/s41598-021-96556-5 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Hasrat, Raiza
Kool, Jolanda
de Steenhuijsen Piters, Wouter A. A.
Chu, Mei Ling J. N.
Kuiling, Sjoerd
Groot, James A.
van Logchem, Elske M.
Fuentes, Susana
Franz, Eelco
Bogaert, Debby
Bosch, Thijs
Benchmarking laboratory processes to characterise low-biomass respiratory microbiota
title Benchmarking laboratory processes to characterise low-biomass respiratory microbiota
title_full Benchmarking laboratory processes to characterise low-biomass respiratory microbiota
title_fullStr Benchmarking laboratory processes to characterise low-biomass respiratory microbiota
title_full_unstemmed Benchmarking laboratory processes to characterise low-biomass respiratory microbiota
title_short Benchmarking laboratory processes to characterise low-biomass respiratory microbiota
title_sort benchmarking laboratory processes to characterise low-biomass respiratory microbiota
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8387476/
https://www.ncbi.nlm.nih.gov/pubmed/34433845
http://dx.doi.org/10.1038/s41598-021-96556-5
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