Heber Kerim, Tian Shuchang, Betancurt-Anzola Daniela, Koo Heejung, Bisanz Jordan E
Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, United States.
One Health Microbiome Center, Huck Life Sciences Institute, University Park, PA 16802, United States.
Bioinformatics. 2025 Aug 2;41(8). doi: 10.1093/bioinformatics/btaf440.
Synthetic microbial communities offer an opportunity to conduct reductionist research in tractable model systems. However, deriving abundances of highly related strains within these communities is currently unreliable. 16S rRNA gene sequencing does not resolve abundance at the strain level and other methods such as quantitative polymerase chain reaction (qPCR) scale poorly and are resource prohibitive for complex communities. We present StrainR2, which utilizes shotgun metagenomic sequencing to provide high accuracy strain-level abundances for all members of a synthetic community, provided their genomes.
Both in silico, and using sequencing data derived from gnotobiotic mice colonized with a synthetic fecal microbiota, StrainR2 resolves strain abundances with greater accuracy and efficiency than other tools utilizing shotgun metagenomic sequencing reads. We demonstrate that StrainR2's accuracy is comparable to that of qPCR on a subset of strains resolved using absolute quantification.
Software is available at GitHub and implemented in C, R, and Bash. Software is supported on Linux and MacOS, with packages available on Bioconda or as a Docker container. The source code at the time of publication is also available on figshare at the doi: 10.6084/m9.figshare.29420780.
合成微生物群落为在易于处理的模型系统中进行简化研究提供了机会。然而，目前在这些群落中推导高度相关菌株的丰度是不可靠的。16S rRNA基因测序无法在菌株水平上解析丰度，而其他方法，如定量聚合酶链反应（qPCR），扩展性较差，并且对于复杂群落来说资源消耗过大。我们提出了StrainR2，它利用鸟枪法宏基因组测序为合成群落的所有成员提供高精度的菌株水平丰度，前提是已知它们的基因组。
无论是在计算机模拟中，还是使用来自定殖有合成粪便微生物群的无菌小鼠的测序数据，与其他利用鸟枪法宏基因组测序读数的工具相比，StrainR2都能以更高的准确性和效率解析菌株丰度。我们证明，在使用绝对定量解析的一部分菌株上，StrainR2的准确性与qPCR相当。
软件可在GitHub上获取，并以C、R和Bash实现。该软件在Linux和MacOS上得到支持，在Bioconda上有软件包，也可作为Docker容器使用。发表时的源代码也可在figshare上获取，doi为：10.6084/m9.figshare.29420780。
