Parks Donovan H, Rigato Fabio, Vera-Wolf Patricia, Krause Lutz, Hugenholtz Philip, Tyson Gene W, Wood David L A
Microba Life Sciences Limited, Brisbane, QLD, Australia.
Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, The University of Queensland, St. Lucia, QLD, Australia.
Front Microbiol. 2021 Apr 20;12:643682. doi: 10.3389/fmicb.2021.643682. eCollection 2021.
A fundamental goal of microbial ecology is to accurately determine the species composition in a given microbial ecosystem. In the context of the human microbiome, this is important for establishing links between microbial species and disease states. Here we benchmark the Microba Community Profiler (MCP) against other metagenomic classifiers using 140 moderate to complex microbial communities and a standardized reference genome database. MCP generated accurate relative abundance estimates and made substantially fewer false positive predictions than other classifiers while retaining a high recall rate. We further demonstrated that the accuracy of species classification was substantially increased using the Microba Genome Database, which is more comprehensive than reference datasets used by other classifiers and illustrates the importance of including genomes of uncultured taxa in reference databases. Consequently, MCP classifies appreciably more reads than other classifiers when using their recommended reference databases. These results establish MCP as best-in-class with the ability to produce comprehensive and accurate species profiles of human gastrointestinal samples.
微生物生态学的一个基本目标是准确确定给定微生物生态系统中的物种组成。在人类微生物组的背景下,这对于建立微生物物种与疾病状态之间的联系很重要。在这里,我们使用140个中度至复杂的微生物群落和一个标准化的参考基因组数据库,将Microba群落分析器(MCP)与其他宏基因组分类器进行了基准测试。MCP生成了准确的相对丰度估计值,与其他分类器相比,误阳性预测大幅减少,同时保持了较高的召回率。我们进一步证明,使用Microba基因组数据库可大幅提高物种分类的准确性,该数据库比其他分类器使用的参考数据集更全面,说明了在参考数据库中纳入未培养分类群基因组的重要性。因此,在使用其他分类器推荐的参考数据库时,MCP比其他分类器能分类更多的读数。这些结果表明MCP是同类最佳,能够生成人类胃肠道样本全面而准确的物种图谱。