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通过宏基因组杂交捕获富集改进16S rRNA的微生物群落特征分析

Improved Microbial Community Characterization of 16S rRNA via Metagenome Hybridization Capture Enrichment.

作者信息

Beaudry Megan S, Wang Jincheng, Kieran Troy J, Thomas Jesse, Bayona-Vásquez Natalia J, Gao Bei, Devault Alison, Brunelle Brian, Lu Kun, Wang Jia-Sheng, Rhodes Olin E, Glenn Travis C

机构信息

Department of Environmental Health Science, University of Georgia, Athens, GA, United States.

Interdisciplinary Toxicology Program, University of Georgia, Athens, GA, United States.

出版信息

Front Microbiol. 2021 Apr 27;12:644662. doi: 10.3389/fmicb.2021.644662. eCollection 2021.

Abstract

Environmental microbial diversity is often investigated from a molecular perspective using 16S ribosomal RNA (rRNA) gene amplicons and shotgun metagenomics. While amplicon methods are fast, low-cost, and have curated reference databases, they can suffer from amplification bias and are limited in genomic scope. In contrast, shotgun metagenomic methods sample more genomic regions with fewer sequence acquisition biases, but are much more expensive (even with moderate sequencing depth) and computationally challenging. Here, we develop a set of 16S rRNA sequence capture baits that offer a potential middle ground with the advantages from both approaches for investigating microbial communities. These baits cover the diversity of all 16S rRNA sequences available in the Greengenes (v. 13.5) database, with no sequence having <78% sequence identity to at least one bait for all segments of 16S. The use of our baits provide comparable results to 16S amplicon libraries and shotgun metagenomic libraries when assigning taxonomic units from 16S sequences within the metagenomic reads. We demonstrate that 16S rRNA capture baits can be used on a range of microbial samples (i.e., mock communities and rodent fecal samples) to increase the proportion of 16S rRNA sequences (average > 400-fold) and decrease analysis time to obtain consistent community assessments. Furthermore, our study reveals that bioinformatic methods used to analyze sequencing data may have a greater influence on estimates of community composition than library preparation method used, likely due in part to the extent and curation of the reference databases considered. Thus, enriching existing aliquots of shotgun metagenomic libraries and obtaining modest numbers of reads from them offers an efficient orthogonal method for assessment of bacterial community composition.

摘要

环境微生物多样性通常从分子角度使用16S核糖体RNA(rRNA)基因扩增子和鸟枪法宏基因组学进行研究。虽然扩增子方法快速、低成本且有经过整理的参考数据库,但它们可能存在扩增偏差,并且在基因组范围上受到限制。相比之下,鸟枪法宏基因组学方法对更多基因组区域进行采样,序列获取偏差较少,但成本要高得多(即使测序深度适中),并且在计算上具有挑战性。在这里,我们开发了一组16S rRNA序列捕获诱饵,它们提供了一种潜在的折衷方案,兼具两种方法的优势,用于研究微生物群落。这些诱饵涵盖了Greengenes(v. 13.5)数据库中所有可用的16S rRNA序列的多样性,对于16S的所有片段,没有任何序列与至少一个诱饵的序列同一性低于78%。当从宏基因组读数中的16S序列分配分类单元时,使用我们的诱饵得到的结果与16S扩增子文库和鸟枪法宏基因组文库相当。我们证明16S rRNA捕获诱饵可用于一系列微生物样本(即模拟群落和啮齿动物粪便样本),以增加16S rRNA序列的比例(平均增加>400倍),并减少分析时间以获得一致的群落评估。此外,我们的研究表明,用于分析测序数据的生物信息学方法可能比所使用的文库制备方法对群落组成估计的影响更大,这可能部分归因于所考虑的参考数据库的范围和整理情况。因此,富集现有的鸟枪法宏基因组文库等分试样并从中获得适量读数,为评估细菌群落组成提供了一种有效的正交方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f83/8110821/331bcec73fba/fmicb-12-644662-g001.jpg

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