A bioinformatics strategy for revealing microbial community structures and metabolic pathways by reconstructing multiple genomes from metagenomic sequences.

对临床和环境样品中不可培养的微生物的宏基因组学研究应该允许对在医学和工业应用中有用的基因进行广泛的调查。BLSOM是最适合于宏基因组序列的系统发育分配的方法，因为片段序列可以根据寡核苷酸的组成来聚类，我们为来自物种已知基因组的所有可用序列构建了寡核苷酸-BLSOM，通过在这种大规模BLSOM上定位宏基因组序列，我们可以预测单个宏基因组序列的寡核苷酸类型，揭示了包括病毒在内的未培养微生物的微生物群落结构。该软件将在我们的网站上免费提供。我们还开发了另一种BLSOM策略，用于根据基因组对宏基因组序列进行聚类，并用于从宏基因组分析中获得的表征较差的蛋白质基因的功能预测。

Metagenomics studies of uncultivable microorganisms in clinical and environmental samples should allow extensive surveys of genes useful in medical and industrial applications. BLSOM is the most suitable for phylogenetic assignment of metagenomic sequences because fragmental sequences can be clustered according to phylotypes, solely depending on oligonucleotide composition.We constructed oligonucleotide-BLSOMs for all available sequences from species-known genomes, and by mapping metagenomic sequences on this large-scale BLSOMs, we could predict phylotypes of individual metagenomic sequences, revealing a microbial community structure of uncultured microorganisms including viruses. This software will be freely available at our website. We also developed another BLSOM strategy for clustering metagenomic sequences according to genome, and for function prediction of poorly-characterized protein genes obtained from metagenome analysis.