Revised computational metagenomic processing uncovers hidden and biologically meaningful functional variation in the human microbiome.
Revised computational metagenomic processing uncovers hidden and biologically meaningful functional variation in the human microbiome.
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DOI：
10.1186/s40168-017-0231-4
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发表时间：
2017-02-08
期刊：
影响因子：
15.5
通讯作者：
Borenstein E
中科院分区：
文献类型：
--
作者：
Manor O;Borenstein E
最近对人类肠道微生物组的宏基因组分析发现，其分类组成在个体之间具有惊人的可变性。然而，值得注意的是，这些研究通常报告了显著的功能一致性，微生物组的基因组成或总体代谢能力的变化相对较小。在这里，我们解决了分类和功能变异之间的惊人差异，并着手追踪其起源。具体来说，我们证明，在微生物组研究中观察到的功能一致性可以归因于，至少部分归因于共同的计算宏基因组处理程序，这些程序掩盖了微生物组样本之间的真正功能差异。我们确定了几个这样的程序，包括常用的基因丰度归一化、基因家族功能途径的定位和基因家族聚集的实践。我们表明，考虑到这些因素并使用修订的宏基因组处理程序揭示了这种隐藏的功能变异，显著增加了在样品中观察到的功能元件丰度的变异。重要的是，我们发现这种未发现的变异在生物学上是有意义的，它与宿主身份和健康都有关。微生物组功能变异的准确表征对于健康和疾病的比较宏基因组分析至关重要。我们发现宏基因组处理过程掩盖了潜在的和生物学上有意义的功能变异，因此强调了这类研究可能面临的一个重要挑战。揭示这种隐藏的功能变异的元基因组处理的替代方案可以促进改进的宏基因组分析，并有助于查明微生物组功能能力中与疾病和宿主相关的变化。本文的在线版本（doi:10.1186/s40168-017-0231-4）包含补充材料，可供授权用户使用。
Recent metagenomic analyses of the human gut microbiome identified striking variability in its taxonomic composition across individuals. Notably, however, these studies often reported marked functional uniformity, with relatively little variation in the microbiome’s gene composition or in its overall metabolic capacity. Here, we address this surprising discrepancy between taxonomic and functional variations and set out to track its origins. Specifically, we demonstrate that the functional uniformity observed in microbiome studies can be attributed, at least partly, to common computational metagenomic processing procedures that mask true functional variation across microbiome samples. We identify several such procedures, including commonly used practices for gene abundance normalization, mapping of gene families to functional pathways, and gene family aggregation. We show that accounting for these factors and using revised metagenomic processing procedures uncovers such hidden functional variation, significantly increasing observed variation in the abundance of functional elements across samples. Importantly, we find that this uncovered variation is biologically meaningful and that it is associated with both host identity and health. Accurate characterization of functional variation in the microbiome is essential for comparative metagenomic analyses in health and disease. Our finding that metagenomic processing procedures mask underlying and biologically meaningful functional variation therefore highlights an important challenge such studies may face. Alternative schemes for metagenomic processing that uncover this hidden functional variation can facilitate improved metagenomic analysis and help pinpoint disease- and host-associated shifts in the microbiome’s functional capacity. The online version of this article (doi:10.1186/s40168-017-0231-4) contains supplementary material, which is available to authorized users.