Optimizing methods and dodging pitfalls in microbiome research.
Optimizing methods and dodging pitfalls in microbiome research.
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DOI：
10.1186/s40168-017-0267-5
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发表时间：
2017-05-05
期刊：
影响因子：
15.5
通讯作者：
Bittinger K
中科院分区：
文献类型：
--
作者：
Kim D;Hofstaedter CE;Zhao C;Mattei L;Tanes C;Clarke E;Lauder A;Sherrill-Mix S;Chehoud C;Kelsen J;Conrad M;Collman RG;Baldassano R;Bushman FD;Bittinger K
对人类微生物组的研究已经产生了许多关于健康和疾病的见解，但也产生了丰富的实验人工制品。在这里，我们提出了优化实验设计和避免已知陷阱的建议，并按照进行研究的典型顺序进行组织。我们首先回顾了实验设计中的最佳实践，并介绍了动物研究中常见的混杂因素，如年龄、饮食、抗生素使用、宠物所有权、纵向不稳定性和共住期间的微生物共享。通常，需要存储样本，因此我们提供了关于几种样本类型的最佳实践的数据。然后我们讨论了阳性和阴性对照的设计和分析，这应该总是与实验样品一起运行。我们介绍了一套方便的非生物DNA序列，可以作为高容量分析的阳性对照。在研究微生物量低的样品时，对阴性对照和阳性对照进行仔细分析尤为重要，因为污染可能包括大部分或全部样品。最后，我们总结了通过仔细控制多重比较以及比较发现和验证队列来增强实验稳健性的方法。我们希望这里总结的实验策略能够帮助这个激动人心的领域的研究人员有效地推进他们的研究，同时避免错误。本文的在线版本（doi:10.1186/s40168-017-0267-5）包含补充材料，可供授权用户使用。
Research on the human microbiome has yielded numerous insights into health and disease, but also has resulted in a wealth of experimental artifacts. Here, we present suggestions for optimizing experimental design and avoiding known pitfalls, organized in the typical order in which studies are carried out. We first review best practices in experimental design and introduce common confounders such as age, diet, antibiotic use, pet ownership, longitudinal instability, and microbial sharing during cohousing in animal studies. Typically, samples will need to be stored, so we provide data on best practices for several sample types. We then discuss design and analysis of positive and negative controls, which should always be run with experimental samples. We introduce a convenient set of non-biological DNA sequences that can be useful as positive controls for high-volume analysis. Careful analysis of negative and positive controls is particularly important in studies of samples with low microbial biomass, where contamination can comprise most or all of a sample. Lastly, we summarize approaches to enhancing experimental robustness by careful control of multiple comparisons and to comparing discovery and validation cohorts. We hope the experimental tactics summarized here will help researchers in this exciting field advance their studies efficiently while avoiding errors. The online version of this article (doi:10.1186/s40168-017-0267-5) contains supplementary material, which is available to authorized users.