Jensen Christian S, Norsigian Charles J, Fang Xin, Nielsen Xiaohui C, Christensen Jens Jørgen, Palsson Bernhard O, Monk Jonathan M
The Regional Department of Clinical Microbiology, Region Zealand, Slagelse, Denmark.
Department of Bioengineering, University of California, San Diego, San Diego, CA, United States.
Front Genet. 2020 Mar 3;11:116. doi: 10.3389/fgene.2020.00116. eCollection 2020.
The mitis group of streptococci (MGS) is a member of the healthy human microbiome in the oral cavity and upper respiratory tract. Troublingly, some MGS are able to escape this niche and cause infective endocarditis, a severe and devastating disease. Genome-scale models have been shown to be valuable in investigating metabolism of bacteria. Here we present the first genome-scale model, iCJ415, for SK141. We validated the model using gene essentiality and amino acid auxotrophy data from closely related species. iCJ415 has 71-76% accuracy in predicting gene essentiality and 85% accuracy in predicting amino acid auxotrophy. Further, the phenotype of was tested using the Biolog Phenotype microarrays, giving iCJ415 a 82% accuracy in predicting carbon sources. iCJ415 can be used to explore the metabolic differences within the MGS, and to explore the complicated metabolic interactions between different species in the human oral cavity.
轻链链球菌组（MGS）是人类口腔和上呼吸道健康微生物群的成员。令人担忧的是，一些MGS能够脱离这个生态位并导致感染性心内膜炎，这是一种严重且具有破坏性的疾病。基因组规模模型已被证明在研究细菌代谢方面具有价值。在此，我们展示了首个针对SK141的基因组规模模型iCJ415。我们使用来自密切相关物种的基因必需性和氨基酸营养缺陷型数据对该模型进行了验证。iCJ415在预测基因必需性方面具有71 - 76%的准确率，在预测氨基酸营养缺陷型方面具有85%的准确率。此外，使用Biolog表型微阵列对其表型进行了测试，iCJ415在预测碳源方面的准确率为82%。iCJ415可用于探索MGS内的代谢差异，以及探索人类口腔中不同物种之间复杂的代谢相互作用。
