A comprehensive benchmarking study of protocols and sequencing platforms for 16S rRNA community profiling.
A comprehensive benchmarking study of protocols and sequencing platforms for 16S rRNA community profiling.
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DOI：
10.1186/s12864-015-2194-9
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发表时间：
2016-01-14
期刊：
影响因子：
4.4
通讯作者：
Hall N
中科院分区：
文献类型：
--
作者：
D'Amore R;Ijaz UZ;Schirmer M;Kenny JG;Gregory R;Darby AC;Shakya M;Podar M;Quince C;Hall N
在过去的5年里，测序技术的快速创新和改进已经完全改变了宏基因组学和宏基因组学实验的格局。因此，对各种方法进行基准测试以询问微生物群落的组成是至关重要的，这样我们就可以评估它们的优势和局限性。微生物群落多样性研究中最常见的系统发育标记是16 S核糖体RNA基因，在过去的10年中，该领域已经从对少量扩增子和样品进行测序转向更复杂的研究，其中询问了数千个样品和多个不同的基因区域。我们组装了2个合成的社区，均匀（EM）和不均匀（UM）分布的古细菌和细菌菌株和物种，作为宏基因组对照材料，以评估不同的实验策略的性能。本研究中使用了2个合成社区，以突出领先测序平台的局限性和优势：MiSeq（Illumina），The Pacific Biosciences RSII，454 GS-FLX/+（Roche）和IonTorrent（Life Technologies）。我们描述了一个广泛的调查的基础上合成社区使用3个实验设计（融合引物，通用尾标签，连接接头）在9个高变16 S rDNA区域。我们证明，库制备方法可以影响数据的解释，由于不同的错误和嵌合率在程序中产生的。观察到的社区组成总是有偏见的，在一定程度上取决于平台，测序区域和引物选择。然而，至关重要的是，我们的分析表明，16 S rRNA测序仍然是定量的，因为样品之间的类群丰度的相对变化可以恢复，尽管这些偏见。我们已经评估了使用最新配置的几个下一代测序平台的一系列实验条件。我们建议，测序平台和实验设计的选择需要考虑在项目的早期阶段，通过运行由几个高变区组成的小型试验来量化每个区域的区分能力。我们还建议使用合成社区作为阳性对照，这将有利于识别可能导致数据误解的潜在偏倚和程序缺陷。本研究的结果将作为指导方针，用于决定考虑哪种实验条件和测序平台以实现最佳微生物谱分析。本文的在线版本（doi：10.1186/s12864-015-2194-9）包含补充材料，可供授权用户使用。
In the last 5 years, the rapid pace of innovations and improvements in sequencing technologies has completely changed the landscape of metagenomic and metagenetic experiments. Therefore, it is critical to benchmark the various methodologies for interrogating the composition of microbial communities, so that we can assess their strengths and limitations. The most common phylogenetic marker for microbial community diversity studies is the 16S ribosomal RNA gene and in the last 10 years the field has moved from sequencing a small number of amplicons and samples to more complex studies where thousands of samples and multiple different gene regions are interrogated. We assembled 2 synthetic communities with an even (EM) and uneven (UM) distribution of archaeal and bacterial strains and species, as metagenomic control material, to assess performance of different experimental strategies. The 2 synthetic communities were used in this study, to highlight the limitations and the advantages of the leading sequencing platforms: MiSeq (Illumina), The Pacific Biosciences RSII, 454 GS-FLX/+ (Roche), and IonTorrent (Life Technologies). We describe an extensive survey based on synthetic communities using 3 experimental designs (fusion primers, universal tailed tag, ligated adaptors) across the 9 hypervariable 16S rDNA regions. We demonstrate that library preparation methodology can affect data interpretation due to different error and chimera rates generated during the procedure. The observed community composition was always biased, to a degree that depended on the platform, sequenced region and primer choice. However, crucially, our analysis suggests that 16S rRNA sequencing is still quantitative, in that relative changes in abundance of taxa between samples can be recovered, despite these biases. We have assessed a range of experimental conditions across several next generation sequencing platforms using the most up-to-date configurations. We propose that the choice of sequencing platform and experimental design needs to be taken into consideration in the early stage of a project by running a small trial consisting of several hypervariable regions to quantify the discriminatory power of each region. We also suggest that the use of a synthetic community as a positive control would be beneficial to identify the potential biases and procedural drawbacks that may lead to data misinterpretation. The results of this study will serve as a guideline for making decisions on which experimental condition and sequencing platform to consider to achieve the best microbial profiling. The online version of this article (doi:10.1186/s12864-015-2194-9) contains supplementary material, which is available to authorized users.