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dc.contributor.authorMarsh, Robyn L
dc.contributor.authorNelson, Maria T
dc.contributor.authorPope, Chris E
dc.contributor.authorLeach, Amanda J
dc.contributor.authorHoffman, Lucas R
dc.contributor.authorChang, Anne B
dc.contributor.authorSmith-Vaughan, Heidi C
dc.date.accessioned2019-09-11T05:36:08Z
dc.date.available2019-09-11T05:36:08Z
dc.date.issued2018
dc.identifier.issn2200-6133en_US
dc.identifier.doi10.1186/s41479-018-0051-8en_US
dc.identifier.urihttp://hdl.handle.net/10072/387219
dc.description.abstractBackground: 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.en_US
dc.description.peerreviewedYesen_US
dc.languageEnglishen_US
dc.publisherBioMed Centralen_US
dc.publisher.placeUnited Kingdom
dc.relation.ispartofpagefrom7:1en_US
dc.relation.ispartofpageto7:9en_US
dc.relation.ispartofissue1en_US
dc.relation.ispartofjournalPneumoniaen_US
dc.relation.ispartofvolume10en_US
dc.subject.fieldofresearchOther Medical and Health Sciencesen_US
dc.subject.fieldofresearchcode1199en_US
dc.subject.keywordsScience & Technologyen_US
dc.subject.keywordsLife Sciences & Biomedicineen_US
dc.subject.keywordsRespiratory Systemen_US
dc.subject.keywordsMicrobiotaen_US
dc.subject.keywords16S rRNA gene sequencingen_US
dc.titleHow low can we go? The implications of low bacterial load in respiratory microbiota studiesen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Articlesen_US
dcterms.bibliographicCitationMarsh, RL; Nelson, MT; Pope, CE; Leach, AJ; Hoffman, LR; Chang, AB; Smith-Vaughan, HC, How low can we go? The implications of low bacterial load in respiratory microbiota studies, Pneumonia, 2018, 10 (1), pp. 7:1-7:9en_US
dcterms.dateAccepted2018-06-21
dcterms.licensehttp://creativecommons.org/licenses/by/4.0/en_US
dc.date.updated2019-09-10T03:28:44Z
dc.description.versionPublisheden_US
gro.rights.copyright© The Author(s). 2018. This 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.en_US
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gro.griffith.authorSmith-Vaughan, Heidi


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