Combining 16S rRNA gene variable regions enables high-resolution microbial community profiling.
Combining 16S rRNA gene variable regions enables high-resolution microbial community profiling.
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结合16S rRNA基因变量区域可以实现高分辨率微生物社区分析。
DOI：
10.1186/s40168-017-0396-x
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发表时间：
2018-01-26
期刊：
影响因子：
15.5
通讯作者：
Shental N
中科院分区：
文献类型：
--
作者：
Fuks G;Elgart M;Amir A;Zeisel A;Turnbaugh PJ;Soen Y;Shental N
我们对地球上显著的微生物多样性的大部分了解来自于对16S rRNA基因的测序。下一代测序方法的使用增加了样本数量和测序深度，但是如今使用最广泛的测序平台的读长相当短，这就要求研究人员选择基因的一个子集进行测序（通常是总长度的16 - 33%）。因此，许多细菌可能共享相同的扩增区域，基因图谱分析的分辨率本身就受到限制。提供超长读长的平台、全基因组鸟枪法测序方法以及我们和其他人之前提出的计算框架都提供了不同的方法来规避这个问题，但都存在各种缺点。我们需要一种简单且低成本的基于16S rRNA基因的图谱分析方法，这种方法能利用短读长来提供对基因更大的覆盖范围，从而实现高分辨率，即使在细菌生物量低和DNA碎片化的恶劣条件下也能如此。
这篇论文提出了短多区域框架（SMURF），这是一种将不同PCR扩增区域的测序结果结合起来以提供一种连贯图谱分析的方法。实际的扩增子长度是所有扩增区域的总长度，因此与当前技术相比，它能提供高得多的分辨率。在计算方面，该方法解决了一个凸优化问题，能够实现极快的重建，并且只需要适中的内存。我们通过计算机模拟以及对两种模拟混合物和实际生物样本进行图谱分析展示了分辨率的提高。对人类微生物组计划中的一种模拟混合物进行重新分析时，当结合两个独立区域时，分辨率提高了约两倍。使用一组定制的六个引物对，其覆盖16S rRNA基因约1200bp（80%），我们能够在一种常见人类肠道细菌分离物的模拟混合物中，相较于单个区域实现约100倍的分辨率提高。最后，使用这组六个引物对对黑腹果蝇微生物组进行图谱分析，分辨率提高了约100倍，从而能够进行有效的下游分析。
SMURF能够识别微生物群落中近乎全长的16S rRNA基因序列，其分辨率优于当前技术。它可以应用于标准的样本制备方案，只需很少的修改。SMURF还为低生物量和碎片化DNA的高分辨率图谱分析铺平了道路，例如在福尔马林固定和石蜡包埋的样本、化石来源的DNA或暴露于其他降解条件下的DNA的情况中。这种方法不限于结合16S rRNA基因的扩增子，还可以应用于任何一组扩增子，例如在多位点序列分型（MLST）中。
本文的网络版（10.1186/s40168 - 017 - 0396 - x）包含补充材料，授权用户可获取。
Most of our knowledge about the remarkable microbial diversity on Earth comes from sequencing the 16S rRNA gene. The use of next-generation sequencing methods has increased sample number and sequencing depth, but the read length of the most widely used sequencing platforms today is quite short, requiring the researcher to choose a subset of the gene to sequence (typically 16–33% of the total length). Thus, many bacteria may share the same amplified region, and the resolution of profiling is inherently limited. Platforms that offer ultra-long read lengths, whole genome shotgun sequencing approaches, and computational frameworks formerly suggested by us and by others all allow different ways to circumvent this problem yet suffer various shortcomings. There is a need for a simple and low-cost 16S rRNA gene-based profiling approach that harnesses the short read length to provide a much larger coverage of the gene to allow for high resolution, even in harsh conditions of low bacterial biomass and fragmented DNA. This manuscript suggests Short MUltiple Regions Framework (SMURF), a method to combine sequencing results from different PCR-amplified regions to provide one coherent profiling. The de facto amplicon length is the total length of all amplified regions, thus providing much higher resolution compared to current techniques. Computationally, the method solves a convex optimization problem that allows extremely fast reconstruction and requires only moderate memory. We demonstrate the increase in resolution by in silico simulations and by profiling two mock mixtures and real-world biological samples. Reanalyzing a mock mixture from the Human Microbiome Project achieved about twofold improvement in resolution when combing two independent regions. Using a custom set of six primer pairs spanning about 1200 bp (80%) of the 16S rRNA gene, we were able to achieve ~ 100-fold improvement in resolution compared to a single region, over a mock mixture of common human gut bacterial isolates. Finally, the profiling of a Drosophila melanogaster microbiome using the set of six primer pairs provided a ~ 100-fold increase in resolution and thus enabling efficient downstream analysis. SMURF enables the identification of near full-length 16S rRNA gene sequences in microbial communities, having resolution superior compared to current techniques. It may be applied to standard sample preparation protocols with very little modifications. SMURF also paves the way to high-resolution profiling of low-biomass and fragmented DNA, e.g., in the case of formalin-fixed and paraffin-embedded samples, fossil-derived DNA, or DNA exposed to other degrading conditions. The approach is not restricted to combining amplicons of the 16S rRNA gene and may be applied to any set of amplicons, e.g., in multilocus sequence typing (MLST). The online version of this article (10.1186/s40168-017-0396-x) contains supplementary material, which is available to authorized users.
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