16s vs shallowshotgun

Characterization of the bacterial composition and functional repertoires of microbiome samples is the most common application of metagenomics. Although deep whole-metagenome shotgun sequencing (WMS) provides high taxonomic resolution, it is generally cost-prohibitive for large longitudinal investigations. Till now, 16S rRNA gene amplicon sequencing (16S) is the most widely used approach and usually cooperates with WMS to achieve cost-efficiency. However, the accuracy of 16S results and its consistency with WMS data have not been fully elaborated, especially by complicated microbiomes with defined compositional information. Here, we constructed two complex artificial microbiomes, which composed of more than 60 human gut bacterial species with even or varied abundance. Utilizing real fecal samples and mock communities, we provided solid evidence demonstrating that 16S results were of poor consistency with WMS data and its accuracy was not satisfactory. Contrastively, shallow whole-metagenome shotgun sequencing (shallow WMS, S-WMS) with a sequencing depth of 1 Gb provided highly resembled outputs to WMS data at both genus and species levels and presented much higher accurate taxonomic assignments and functional predictions than 16S, thereby representing a better and cost-efficient alternative to 16S for large-scale microbiome studies.

对微生物组样本的细菌组成与功能谱进行表征，是宏基因组学（metagenomics）最常见的应用方向。尽管深度全宏基因组鸟枪法测序（WMS）可提供较高的分类学分辨率，但针对大规模纵向研究而言，其成本通常过高，难以承受。迄今为止，16S rRNA基因扩增子测序（16S）仍是应用最为广泛的技术手段，且常与WMS联用以兼顾成本效益。然而，16S测序结果的准确性及其与WMS数据的一致性尚未得到充分阐释，尤其是在组成信息明确的复杂微生物组样本中。
本研究构建了两套复杂的人工微生物组，每套均由60余种人类肠道细菌菌种组成，丰度分布分别为均匀分布与差异分布。通过利用真实粪便样本与模拟群落，我们提供了确凿证据，证明16S测序结果与WMS数据的一致性较差，且准确性不尽如人意。与之相比，测序深度为1 Gb的浅层全宏基因组鸟枪法测序（shallow WMS, S-WMS）在属、种分类水平上均可输出与WMS高度相似的结果，且其分类注释与功能预测的准确性远高于16S测序，因此可作为大规模微生物组研究中16S测序的更优且更具成本效益的替代方案。