Deriving accurate microbiota profiles from human samples with low bacterial content through post-sequencing processing of Illumina MiSeq data.
Deriving accurate microbiota profiles from human samples with low bacterial content through post-sequencing processing of Illumina MiSeq data.
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DOI：
10.1186/s40168-015-0083-8
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发表时间：
2015
期刊：
影响因子：
15.5
通讯作者：
Marsh RL
中科院分区：
文献类型：
--
作者：
Jervis-Bardy J;Leong LE;Marri S;Smith RJ;Choo JM;Smith-Vaughan HC;Nosworthy E;Morris PS;O'Leary S;Rogers GB;Marsh RL
16 S rRNA基因测序在具有挑战性的临床环境中的快速扩展导致了越来越多的质量不一的文献。在很大程度上，这是由于未能解决具有低水平细菌和高水平非细菌DNA的样品的特征的假信号。我们已经开发了一种基于配对末端读取Illumina MiSeq的方法的工作流程，该方法能够显着提高测序后的数据质量。我们证明了这种方法的有效性，通过其应用于儿科上呼吸道样本从几个解剖部位。基于常用工具开发了处理序列数据的工作流程。从不同样品类型生成的数据显示非细菌信号和“污染物”细菌读数的水平存在显著变化。观察到参考数据库准确分配操作分类单位（OTU）身份的能力存在显著差异。三个OTU挑选策略进行了试验如下：从头开始，开放参考和封闭参考，与开放参考表现得更好。被鉴定为潜在试剂污染的OTU的相对丰度显示出与扩增子浓度的强负相关性，从而允许它们的目标去除。去除虚假信号显示，通常含有低水平细菌和高水平人类DNA的样本类型的改善最大。通过主坐标和共现分析证明了预滤波数据和伪信号去除的实质性影响。例如，对腺样体拭子和中耳液样品中的分类群共现的分析表明，未能去除假信号导致11个细菌属中的6个被包括在内，这些细菌属占样品类型之间80%的相似性。将所提出的工作流程应用于一组具有挑战性的临床样本，证明了其在从数据集中去除伪信号方面的实用性，从而可以从否则将是高度误导性的输出中获得临床见解。虽然其他方法可能实现类似的改进，但这里采用的方法代表了一种排除污染和其他伪影信号的可用手段。本文的在线版本（doi：10.1186/s40168-015-0083-8）包含补充材料，可供授权用户使用。
The rapid expansion of 16S rRNA gene sequencing in challenging clinical contexts has resulted in a growing body of literature of variable quality. To a large extent, this is due to a failure to address spurious signal that is characteristic of samples with low levels of bacteria and high levels of non-bacterial DNA. We have developed a workflow based on the paired-end read Illumina MiSeq-based approach, which enables significant improvement in data quality, post-sequencing. We demonstrate the efficacy of this methodology through its application to paediatric upper-respiratory samples from several anatomical sites. A workflow for processing sequence data was developed based on commonly available tools. Data generated from different sample types showed a marked variation in levels of non-bacterial signal and ‘contaminant’ bacterial reads. Significant differences in the ability of reference databases to accurately assign identity to operational taxonomic units (OTU) were observed. Three OTU-picking strategies were trialled as follows: de novo, open-reference and closed-reference, with open-reference performing substantially better. Relative abundance of OTUs identified as potential reagent contamination showed a strong inverse correlation with amplicon concentration allowing their objective removal. The removal of the spurious signal showed the greatest improvement in sample types typically containing low levels of bacteria and high levels of human DNA. A substantial impact of pre-filtering data and spurious signal removal was demonstrated by principal coordinate and co-occurrence analysis. For example, analysis of taxon co-occurrence in adenoid swab and middle ear fluid samples indicated that failure to remove the spurious signal resulted in the inclusion of six out of eleven bacterial genera that accounted for 80% of similarity between the sample types. The application of the presented workflow to a set of challenging clinical samples demonstrates its utility in removing the spurious signal from the dataset, allowing clinical insight to be derived from what would otherwise be highly misleading output. While other approaches could potentially achieve similar improvements, the methodology employed here represents an accessible means to exclude the signal from contamination and other artefacts. The online version of this article (doi:10.1186/s40168-015-0083-8) contains supplementary material, which is available to authorized users.
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影响因子：
12.3
作者：
Weiss S;Amir A;Hyde ER;Metcalf JL;Song SJ;Knight R
通讯作者：
Knight R
DOI：
10.1164/rccm.201304-0775oc
发表时间：
2013-11-15
影响因子：
24.7
作者：
Goleva, Elena;Jackson, Leisa P.;Leung, Donald Y. M.
通讯作者：
Leung, Donald Y. M.
DOI：
10.1093/bioinformatics/btt593
发表时间：
2014-03-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Zhang J;Kobert K;Flouri T;Stamatakis A
通讯作者：
Stamatakis A
影响因子：
3.7
作者：
Willner D;Daly J;Whiley D;Grimwood K;Wainwright CE;Hugenholtz P
通讯作者：
Hugenholtz P
影响因子：
4.4
作者：
Schloss, Patrick D.;Westcott, Sarah L.;Weber, Carolyn F.
通讯作者：
Weber, Carolyn F.