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从人类胃肠道中鉴定、恢复和优化此前未描述的群体水平基因组。

Identification, Recovery, and Refinement of Hitherto Undescribed Population-Level Genomes from the Human Gastrointestinal Tract.

作者信息

Laczny Cedric C, Muller Emilie E L, Heintz-Buschart Anna, Herold Malte, Lebrun Laura A, Hogan Angela, May Patrick, de Beaufort Carine, Wilmes Paul

机构信息

Luxembourg Centre for Systems Biomedicine, University of Luxembourg Belvaux, Luxembourg.

Integrated Biobank of Luxembourg Luxembourg, Luxembourg.

出版信息

Front Microbiol. 2016 Jun 21;7:884. doi: 10.3389/fmicb.2016.00884. eCollection 2016.

Abstract

Linking taxonomic identity and functional potential at the population-level is important for the study of mixed microbial communities and is greatly facilitated by the availability of microbial reference genomes. While the culture-independent recovery of population-level genomes from environmental samples using the binning of metagenomic data has expanded available reference genome catalogs, several microbial lineages remain underrepresented. Here, we present two reference-independent approaches for the identification, recovery, and refinement of hitherto undescribed population-level genomes. The first approach is aimed at genome recovery of varied taxa and involves multi-sample automated binning using CANOPY CLUSTERING complemented by visualization and human-augmented binning using VIZBIN post hoc. The second approach is particularly well-suited for the study of specific taxa and employs VIZBIN de novo. Using these approaches, we reconstructed a total of six population-level genomes of distinct and divergent representatives of the Alphaproteobacteria class, the Mollicutes class, the Clostridiales order, and the Melainabacteria class from human gastrointestinal tract-derived metagenomic data. Our results demonstrate that, while automated binning approaches provide great potential for large-scale studies of mixed microbial communities, these approaches should be complemented with informative visualizations because expert-driven inspection and refinements are critical for the recovery of high-quality population-level genomes.

摘要

在种群水平上关联分类身份和功能潜力对于混合微生物群落的研究至关重要,而微生物参考基因组的可用性极大地促进了这一研究。虽然使用宏基因组数据分箱从环境样本中独立于培养物恢复种群水平的基因组扩展了可用的参考基因组目录,但仍有几个微生物谱系的代表性不足。在这里,我们提出了两种独立于参考的方法,用于识别、恢复和完善迄今未描述的种群水平的基因组。第一种方法旨在恢复不同分类群的基因组,包括使用CANOPY CLUSTERING进行多样本自动分箱,并辅以可视化以及事后使用VIZBIN进行人工增强分箱。第二种方法特别适合于特定分类群的研究,并从头使用VIZBIN。使用这些方法,我们从人类胃肠道来源的宏基因组数据中总共重建了六个不同且有差异的代表基因组,分别来自α-变形菌纲、柔膜菌纲、梭菌目和黑素杆菌纲。我们的结果表明,虽然自动分箱方法为混合微生物群落的大规模研究提供了巨大潜力,但这些方法应辅以信息丰富的可视化,因为专家驱动的检查和完善对于高质量种群水平基因组的恢复至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/53c0/4914512/815f6e5013de/fmicb-07-00884-g001.jpg

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