Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen, The Netherlands.
BU Biointeractions and Plant Health, Wageningen Plant Research, Wageningen University & Research, Wageningen, The Netherlands.
Sci Rep. 2022 Jun 27;12(1):10857. doi: 10.1038/s41598-022-14913-4.
The rhizosphere, the region of soil surrounding roots of plants, is colonized by a unique population of Plant Growth Promoting Rhizobacteria (PGPR). Many important PGPR as well as plant pathogens belong to the genus Pseudomonas. There is, however, uncertainty on the divide between beneficial and pathogenic strains as previously thought to be signifying genomic features have limited power to separate these strains. Here we used the Genome properties (GP) common biological pathways annotation system and Machine Learning (ML) to establish the relationship between the genome wide GP composition and the plant-associated lifestyle of 91 Pseudomonas strains isolated from the rhizosphere and the phyllosphere representing both plant-associated phenotypes. GP enrichment analysis, Random Forest model fitting and feature selection revealed 28 discriminating features. A test set of 75 new strains confirmed the importance of the selected features for classification. The results suggest that GP annotations provide a promising computational tool to better classify the plant-associated lifestyle.
根际是植物根系周围的土壤区域，由独特的植物促生根际细菌（PGPR）种群定植。许多重要的 PGPR 和植物病原体都属于假单胞菌属。然而，先前认为具有区分有益和致病菌株的基因组特征的不确定性，因为这些特征在区分这些菌株方面的能力有限。在这里，我们使用基因组特性（GP）常见生物途径注释系统和机器学习（ML）来建立从根际和叶际分离的 91 株假单胞菌菌株的全基因组 GP 组成与代表植物相关表型的植物相关生活方式之间的关系。GP 富集分析、随机森林模型拟合和特征选择揭示了 28 个有区别的特征。75 株新菌株的测试集证实了所选特征对分类的重要性。结果表明，GP 注释为更好地分类植物相关生活方式提供了有前途的计算工具。
