Skin Microbiome Surveys Are Strongly Influenced by Experimental Design.
Skin Microbiome Surveys Are Strongly Influenced by Experimental Design.
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DOI：
10.1016/j.jid.2016.01.016
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发表时间：
2016-05
期刊：
影响因子：
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通讯作者：
Grice EA
中科院分区：
文献类型：
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作者：
Meisel JS;Hannigan GD;Tyldsley AS;SanMiguel AJ;Hodkinson BP;Zheng Q;Grice EA
独立于培养物的皮肤微生物群特征研究越来越普遍，部分原因是价格合理且易于获得的测序和分析平台。与基于培养的技术相比，细菌16S核糖体RNA （rRNA）基因的DNA测序或全宏基因组霰弹枪（WMS）测序提供了更精确的微生物群落特征。大多数广泛使用的方案是为了表征其他栖息地（即胃肠道）的微生物群而开发的，并且尚未系统地比较其在皮肤微生物群调查中的效用。在这里，我们为皮肤研究界建立了一个资源，以指导皮肤微生物群特征的实验设计。我们将16S rRNA基因的两个广泛测序区域与WMS测序进行比较，以概括皮肤微生物群落的组成、多样性和遗传功能富集。我们发现WMS测序最准确地概括了微生物群落，但对16S rRNA基因高变区1-3的测序提供了高度相似的结果。高变区4的测序很难捕获皮肤共生微生物群，特别是丙酸杆菌。WMS测序是资源和成本密集型的，它提供了一个群落功能潜力的证据；然而，基于16S rRNA序列标签的宏基因组预测非常接近WMS遗传功能谱。这项工作强调了实验设计对皮肤微生物组调查下游结果的重要性。
Culture-independent studies to characterize skin microbiota are increasingly common, due in part to affordable and accessible sequencing and analysis platforms. Compared to culture-based techniques, DNA sequencing of the bacterial 16S ribosomal RNA (rRNA) gene or whole metagenome shotgun (WMS) sequencing provide more precise microbial community characterizations. Most widely used protocols were developed to characterize microbiota of other habitats (i.e. gastrointestinal), and have not been systematically compared for their utility in skin microbiome surveys. Here we establish a resource for the cutaneous research community to guide experimental design in characterizing skin microbiota. We compare two widely sequenced regions of the 16S rRNA gene to WMS sequencing for recapitulating skin microbiome community composition, diversity, and genetic functional enrichment. We show that WMS sequencing most accurately recapitulates microbial communities, but sequencing of hypervariable regions 1-3 of the 16S rRNA gene provides highly similar results. Sequencing of hypervariable region 4 poorly captures skin commensal microbiota, especially Propionibacterium. WMS sequencing, which is resource- and cost-intensive, provides evidence of a community’s functional potential; however, metagenome predictions based on 16S rRNA sequence tags closely approximate WMS genetic functional profiles. This work highlights the importance of experimental design for downstream results in skin microbiome surveys.