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How low can we go? The implications of low bacterial load in respiratory microbiota studies

BACKGROUND: Culture-independent sequencing methods are increasingly used to investigate the microbiota associated with human mucosal surfaces, including sites that have low bacterial load in healthy individuals (e.g. the lungs). Standard microbiota methods developed for analysis of high bacterial lo...

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Autores principales: Marsh, Robyn L., Nelson, Maria T., Pope, Chris E., Leach, Amanda J., Hoffman, Lucas R., Chang, Anne B., Smith-Vaughan, Heidi C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6033291/
https://www.ncbi.nlm.nih.gov/pubmed/30003009
http://dx.doi.org/10.1186/s41479-018-0051-8
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author Marsh, Robyn L.
Nelson, Maria T.
Pope, Chris E.
Leach, Amanda J.
Hoffman, Lucas R.
Chang, Anne B.
Smith-Vaughan, Heidi C.
author_facet Marsh, Robyn L.
Nelson, Maria T.
Pope, Chris E.
Leach, Amanda J.
Hoffman, Lucas R.
Chang, Anne B.
Smith-Vaughan, Heidi C.
author_sort Marsh, Robyn L.
collection PubMed
description BACKGROUND: Culture-independent sequencing methods are increasingly used to investigate the microbiota associated with human mucosal surfaces, including sites that have low bacterial load in healthy individuals (e.g. the lungs). Standard microbiota methods developed for analysis of high bacterial load specimens (e.g. stool) may require modification when bacterial load is low, as background contamination derived from sterile laboratory reagents and kits can dominate sequence data when few bacteria are present. MAIN BODY: Bacterial load in respiratory specimens may vary depending on the specimen type, specimen volume, the anatomic site sampled and clinical parameters. This review discusses methodological issues inherent to analysis of low bacterial load specimens and recommends strategies for successful respiratory microbiota studies. The range of methods currently used to process DNA from low bacterial load specimens, and the strategies used to identify and exclude background contamination are also discussed. CONCLUSION: Microbiota studies that include low bacterial load specimens require additional tests to ensure that background contamination does not bias the results or interpretation. Several methods are currently used to analyse the microbiota in low bacterial load respiratory specimens; however, there is scant literature comparing the effectiveness and biases of different methods. Further research is needed to define optimal methods for analysing the microbiota in low bacterial load specimens.
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spelling pubmed-60332912018-07-12 How low can we go? The implications of low bacterial load in respiratory microbiota studies Marsh, Robyn L. Nelson, Maria T. Pope, Chris E. Leach, Amanda J. Hoffman, Lucas R. Chang, Anne B. Smith-Vaughan, Heidi C. Pneumonia (Nathan) Review BACKGROUND: Culture-independent sequencing methods are increasingly used to investigate the microbiota associated with human mucosal surfaces, including sites that have low bacterial load in healthy individuals (e.g. the lungs). Standard microbiota methods developed for analysis of high bacterial load specimens (e.g. stool) may require modification when bacterial load is low, as background contamination derived from sterile laboratory reagents and kits can dominate sequence data when few bacteria are present. MAIN BODY: Bacterial load in respiratory specimens may vary depending on the specimen type, specimen volume, the anatomic site sampled and clinical parameters. This review discusses methodological issues inherent to analysis of low bacterial load specimens and recommends strategies for successful respiratory microbiota studies. The range of methods currently used to process DNA from low bacterial load specimens, and the strategies used to identify and exclude background contamination are also discussed. CONCLUSION: Microbiota studies that include low bacterial load specimens require additional tests to ensure that background contamination does not bias the results or interpretation. Several methods are currently used to analyse the microbiota in low bacterial load respiratory specimens; however, there is scant literature comparing the effectiveness and biases of different methods. Further research is needed to define optimal methods for analysing the microbiota in low bacterial load specimens. BioMed Central 2018-07-05 /pmc/articles/PMC6033291/ /pubmed/30003009 http://dx.doi.org/10.1186/s41479-018-0051-8 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Review
Marsh, Robyn L.
Nelson, Maria T.
Pope, Chris E.
Leach, Amanda J.
Hoffman, Lucas R.
Chang, Anne B.
Smith-Vaughan, Heidi C.
How low can we go? The implications of low bacterial load in respiratory microbiota studies
title How low can we go? The implications of low bacterial load in respiratory microbiota studies
title_full How low can we go? The implications of low bacterial load in respiratory microbiota studies
title_fullStr How low can we go? The implications of low bacterial load in respiratory microbiota studies
title_full_unstemmed How low can we go? The implications of low bacterial load in respiratory microbiota studies
title_short How low can we go? The implications of low bacterial load in respiratory microbiota studies
title_sort how low can we go? the implications of low bacterial load in respiratory microbiota studies
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6033291/
https://www.ncbi.nlm.nih.gov/pubmed/30003009
http://dx.doi.org/10.1186/s41479-018-0051-8
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