Nelson Michael C, Morrison Hilary G, Benjamino Jacquelynn, Grim Sharon L, Graf Joerg
Department of Molecular and Cell Biology, University of Connecticut, Storrs, Connecticut, United States of America.
Josephine Bay Paul Center, Marine Biological Laboratory, Woods Hole, Massachusetts, United States of America.
PLoS One. 2014 Apr 10;9(4):e94249. doi: 10.1371/journal.pone.0094249. eCollection 2014.
The exploration of microbial communities by sequencing 16S rRNA genes has expanded with low-cost, high-throughput sequencing instruments. Illumina-based 16S rRNA gene sequencing has recently gained popularity over 454 pyrosequencing due to its lower costs, higher accuracy and greater throughput. Although recent reports suggest that Illumina and 454 pyrosequencing provide similar beta diversity measures, it remains to be demonstrated that pre-existing 454 pyrosequencing workflows can transfer directly from 454 to Illumina MiSeq sequencing by simply changing the sequencing adapters of the primers. In this study, we modified 454 pyrosequencing primers targeting the V4-V5 hyper-variable regions of the 16S rRNA gene to be compatible with Illumina sequencers. Microbial communities from cows, humans, leeches, mice, sewage, and termites and a mock community were analyzed by 454 and MiSeq sequencing of the V4-V5 region and MiSeq sequencing of the V4 region. Our analysis revealed that reference-based OTU clustering alone introduced biases compared to de novo clustering, preventing certain taxa from being observed in some samples. Based on this we devised and recommend an analysis pipeline that includes read merging, contaminant filtering, and reference-based clustering followed by de novo OTU clustering, which produces diversity measures consistent with de novo OTU clustering analysis. Low levels of dataset contamination with Illumina sequencing were discovered that could affect analyses that require highly sensitive approaches. While moving to Illumina-based sequencing platforms promises to provide deeper insights into the breadth and function of microbial diversity, our results show that care must be taken to ensure that sequencing and processing artifacts do not obscure true microbial diversity.
通过对16S rRNA基因进行测序来探索微生物群落的研究,随着低成本、高通量测序仪器的出现而得到了扩展。基于Illumina的16S rRNA基因测序,由于其成本更低、准确性更高且通量更大,最近已比454焦磷酸测序更受欢迎。尽管最近的报告表明Illumina和454焦磷酸测序提供了相似的β多样性测量结果,但之前的454焦磷酸测序工作流程能否通过简单地更换引物的测序接头,直接从454转移到Illumina MiSeq测序,仍有待证明。在本研究中,我们将靶向16S rRNA基因V4-V5高变区的454焦磷酸测序引物进行了修改,使其与Illumina测序仪兼容。通过对V4-V5区域进行454测序和MiSeq测序以及对V4区域进行MiSeq测序,分析了来自奶牛、人类、水蛭、小鼠、污水和白蚁的微生物群落以及一个模拟群落。我们的分析表明,与从头聚类相比,仅基于参考的OTU聚类会引入偏差,导致某些分类群在一些样本中无法被观察到。基于此,我们设计并推荐了一种分析流程,该流程包括读段合并、污染物过滤、基于参考的聚类,然后是从头OTU聚类,其产生的多样性测量结果与从头OTU聚类分析一致。发现Illumina测序存在低水平的数据集污染,这可能会影响需要高灵敏度方法的分析。虽然转向基于Illumina的测序平台有望更深入地了解微生物多样性的广度和功能,但我们的结果表明,必须谨慎确保测序和处理过程中的人为因素不会掩盖真正的微生物多样性。