Application of Stochastic Labeling with Random-Sequence Barcodes for Simultaneous Quantification and Sequencing of Environmental 16S rRNA Genes.
Application of Stochastic Labeling with Random-Sequence Barcodes for Simultaneous Quantification and Sequencing of Environmental 16S rRNA Genes.
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DOI：
10.1371/journal.pone.0169431
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发表时间：
2017
期刊：
影响因子：
3.7
通讯作者：
Inagaki F
中科院分区：
文献类型：
--
作者：
Hoshino T;Inagaki F
新一代测序（NGS）是分析环境DNA的有力工具，提供了微生物群落的全面分子视图。然而，为了获得NGS文库中特定序列的拷贝数，还需要进行定量PCR （qPCR）或数字PCR （dPCR）等额外的定量分析。此外，由于PCR扩增引起的偏差，序列文库中的序列数并不总是反映目标基因的原始拷贝数，这使得使用输入DNA的质量将NGS文库中特定序列的比例转换为拷贝数变得困难。为了解决这个问题，我们应用随机标记方法和随机标记序列，并开发了一种基于ngs的定量方案，该方案可以同时测序和定量目标DNA。这种定量测序（qSeq）是从单引物扩展（SPE）开始的，使用一个与目标特异性序列5 '端相邻的随机标记引物。在SPE过程中，每个DNA分子被随机标记。随后，进行第一轮PCR，专门针对SPE产物，然后进行第二轮PCR以索引NGS。随机标签的数量仅在SPE步骤中确定，因此不受可能引入扩增偏差的两轮PCR的影响。对于16S rRNA基因，经过NGS测序和分类学分类后，通过对序列末端纳入的随机标签计数，通过泊松统计估计出16S rRNA基因靶种型的绝对数量。为了验证该方法的可行性，我们对tokodaisulfolobus 16S rRNA基因进行了qSeq分析，得到了16S rRNA基因5.0 × 103 ~ 5.0 × 104拷贝的准确定量。此外，qSeq应用于模拟微生物群落和环境样本，结果与使用数字PCR获得的结果和基于标准序列库的相对丰度相当。我们证明，这里提出的qSeq协议有利于在一次NGS测序中提供每个目标DNA的较少偏差的绝对拷贝数。通过这种新的微生物生态学实验方案，可以更定量地探索微生物群落组成，从而扩大我们对自然环境中微生物生态系统的认识。
Next-generation sequencing (NGS) is a powerful tool for analyzing environmental DNA and provides the comprehensive molecular view of microbial communities. For obtaining the copy number of particular sequences in the NGS library, however, additional quantitative analysis as quantitative PCR (qPCR) or digital PCR (dPCR) is required. Furthermore, number of sequences in a sequence library does not always reflect the original copy number of a target gene because of biases caused by PCR amplification, making it difficult to convert the proportion of particular sequences in the NGS library to the copy number using the mass of input DNA. To address this issue, we applied stochastic labeling approach with random-tag sequences and developed a NGS-based quantification protocol, which enables simultaneous sequencing and quantification of the targeted DNA. This quantitative sequencing (qSeq) is initiated from single-primer extension (SPE) using a primer with random tag adjacent to the 5’ end of target-specific sequence. During SPE, each DNA molecule is stochastically labeled with the random tag. Subsequently, first-round PCR is conducted, specifically targeting the SPE product, followed by second-round PCR to index for NGS. The number of random tags is only determined during the SPE step and is therefore not affected by the two rounds of PCR that may introduce amplification biases. In the case of 16S rRNA genes, after NGS sequencing and taxonomic classification, the absolute number of target phylotypes 16S rRNA gene can be estimated by Poisson statistics by counting random tags incorporated at the end of sequence. To test the feasibility of this approach, the 16S rRNA gene of Sulfolobus tokodaii was subjected to qSeq, which resulted in accurate quantification of 5.0 × 103 to 5.0 × 104 copies of the 16S rRNA gene. Furthermore, qSeq was applied to mock microbial communities and environmental samples, and the results were comparable to those obtained using digital PCR and relative abundance based on a standard sequence library. We demonstrated that the qSeq protocol proposed here is advantageous for providing less-biased absolute copy numbers of each target DNA with NGS sequencing at one time. By this new experiment scheme in microbial ecology, microbial community compositions can be explored in more quantitative manner, thus expanding our knowledge of microbial ecosystems in natural environments.
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