DRAM for distilling microbial metabolism to automate the curation of microbiome function
DRAM for distilling microbial metabolism to automate the curation of microbiome function
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DOI：
10.1093/nar/gkaa621
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发表时间：
2020-09-18
影响因子：
14.9
通讯作者：
Wrighton, Kelly C.
中科院分区：
文献类型：
--
作者：
Shaffer, Michael;Borton, Mikayla A.;Wrighton, Kelly C.
微生物和病毒群落改变了地球生态系统的化学成分，但由于缺乏可扩展的、代谢解析的注释软件，这些生物引擎催化的特定反应很难破译。在这里，我们提出了DRAM(蒸馏和精炼新陈代谢注释)，一个框架，将大量基于微生物组的基因组信息转化为微生物特征目录。为了证明DRAM在新陈代谢不同的基因组中的适用性，我们在硅土社区和以前发表的人类肠道元基因组上评估了DRAM的性能。我们表明，DRAM准确地分配了微生物对地球化学循环的贡献，并在底物水平上自动化了肠道微生物碳水化合物代谢的分配。DRAM的病毒模式DRAM-v建立了识别病毒编码的辅助代谢基因(AMGs)的规则，导致对来自土壤和肠道的数千个假定的AMG进行代谢分类。DRAM和DRAM-v一起提供了关键的代谢谱能力，这些能力破译了支撑微生物组功能的机制。
Microbial and viral communities transform the chemistry of Earth's ecosystems, yet the specific reactions catalyzed by these biological engines are hard to decode due to the absence of a scalable, metabolically resolved, annotation software. Here, we present DRAM (Distilled and Refined Annotation of Metabolism), a framework to translate the deluge of microbiome-based genomic information into a catalog of microbial traits. To demonstrate the applicability of DRAM across metabolically diverse genomes, we evaluated DRAM performance on a defined, in silico soil community and previously published human gut metagenomes. We show that DRAM accurately assigned microbial contributions to geochemical cycles and automated the partitioning of gut microbial carbohydrate metabolism at substrate levels. DRAM-v, the viral mode of DRAM, established rules to identify virally-encoded auxiliary metabolic genes (AMGs), resulting in the metabolic categorization of thousands of putative AMGs from soils and guts. Together DRAM and DRAM-v provide critical metabolic profiling capabilities that decipher mechanisms underpinning microbiome function.