ConStrains可识别宏基因组数据集中的微生物菌株。
ConStrains identifies microbial strains in metagenomic datasets.
作者信息
Luo Chengwei, Knight Rob, Siljander Heli, Knip Mikael, Xavier Ramnik J, Gevers Dirk
机构信息
Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, Massachusetts, USA.
Gastrointestinal Unit and Center for the Study of Inflammatory Bowel Disease, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.
出版信息
Nat Biotechnol. 2015 Oct;33(10):1045-52. doi: 10.1038/nbt.3319. Epub 2015 Sep 7.
An important fraction of microbial diversity is harbored in strain individuality, so identification of conspecific bacterial strains is imperative for improved understanding of microbial community functions. Limitations in bioinformatics and sequencing technologies have to date precluded strain identification owing to difficulties in phasing short reads to faithfully recover the original strain-level genotypes, which have highly similar sequences. We present ConStrains, an open-source algorithm that identifies conspecific strains from metagenomic sequence data and reconstructs the phylogeny of these strains in microbial communities. The algorithm uses single-nucleotide polymorphism (SNP) patterns in a set of universal genes to infer within-species structures that represent strains. Applying ConStrains to simulated and host-derived datasets provides insights into microbial community dynamics.
微生物多样性的一个重要部分蕴藏在菌株个体性中,因此鉴定同种细菌菌株对于更好地理解微生物群落功能至关重要。由于难以对短读段进行定相以忠实地恢复具有高度相似序列的原始菌株水平基因型,生物信息学和测序技术的局限性迄今为止妨碍了菌株鉴定。我们提出了ConStrains,这是一种开源算法,可从宏基因组序列数据中鉴定同种菌株,并重建这些菌株在微生物群落中的系统发育。该算法使用一组通用基因中的单核苷酸多态性(SNP)模式来推断代表菌株的种内结构。将ConStrains应用于模拟数据集和宿主来源的数据集,可以深入了解微生物群落动态。
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