Redondo Miguel A, Jones Christopher M, Legendre Pierre, Guénard Guillaume, Hallin Sara
Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Box 7026, 750 07 Uppsala, Sweden.
Département de sciences biologiques, Université de Montréal, C.P. 6128, succursale Centre-ville, Montréal, Québec H3C 3J7, Canada.
ISME Commun. 2025 May 23;5(1):ycaf087. doi: 10.1093/ismeco/ycaf087. eCollection 2025 Jan.
Phylogenetic conservatism of microbial traits has paved the way for phylogeny-based predictions, allowing us to move from descriptive to predictive functional microbial ecology. Here, we applied phylogenetic eigenvector mapping to predict the presence of genes indicating potential functions of ammonia-oxidizing archaea (AOA), which are important players in nitrogen cycling. Using 160 nearly complete AOA genomes and metagenome assembled genomes from public databases, we predicted the distribution of 18 ecologically relevant genes across an updated gene phylogeny, including a novel variant of an ammonia transporter found in this study. All selected genes displayed a significant phylogenetic signal and gene presence was predicted with an average of >88% accuracy, >85% sensitivity, and >80% specificity. The phylogenetic eigenvector approach performed equally well as ancestral state reconstruction of gene presence. We implemented the predictive models on an sequencing dataset of AOA soil communities and showed key ecological predictions, e.g. that AOA communities in nitrogen-rich soils were predicted to have capacity for ureolytic metabolism while those adapted to low-pH soils were predicted to have the high-affinity ammonia transporter (). Predicting gene presence can shed light on the potential functions that microorganisms perform in the environment, further contributing to a better mechanistic understanding of their community assembly.
微生物性状的系统发育保守性为基于系统发育的预测铺平了道路,使我们能够从描述性的功能微生物生态学转向预测性的功能微生物生态学。在此,我们应用系统发育特征向量映射来预测指示氨氧化古菌(AOA)潜在功能的基因的存在,氨氧化古菌是氮循环中的重要参与者。利用来自公共数据库的160个近乎完整的AOA基因组和宏基因组组装基因组,我们在一个更新的基因系统发育树上预测了18个与生态相关的基因的分布,包括本研究中发现的一种氨转运蛋白的新变体。所有选定的基因都显示出显著的系统发育信号,并且预测基因存在的平均准确率>88%、灵敏度>85%、特异性>80%。系统发育特征向量方法与基因存在的祖先状态重建表现相当。我们在AOA土壤群落的一个测序数据集上实施了预测模型,并展示了关键的生态预测,例如,预测富氮土壤中的AOA群落具有尿素分解代谢能力,而适应低pH土壤的群落则具有高亲和力氨转运蛋白()。预测基因存在可以揭示微生物在环境中执行的潜在功能,进一步有助于更好地从机制上理解它们的群落组装。