Predicting gene distribution in ammonia-oxidizing archaea using phylogenetic signals.

IF 5.1 Q1 ECOLOGY
ISME communications Pub Date : 2025-05-23 eCollection Date: 2025-01-01 DOI:10.1093/ismeco/ycaf087
Miguel A Redondo, Christopher M Jones, Pierre Legendre, Guillaume Guénard, Sara Hallin
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Abstract

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 amoA 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 amoA 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 (amt2). 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.

利用系统发育信号预测氨氧化古菌基因分布。
微生物特征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转向预测性功能微生物生态学。在此,我们应用系统发育特征向量映射来预测表明氨氧化古菌(AOA)潜在功能的基因的存在,这是氮循环的重要参与者。利用来自公共数据库的160个几乎完整的AOA基因组和宏基因组组装基因组,我们预测了18个生态相关基因在更新的amoA基因系统发育中的分布,包括本研究中发现的氨转运体的新变体。所有选择的基因都显示出显著的系统发育信号,预测基因存在的平均准确性为>88%,>敏感性为85%,>特异性为80%。系统发育特征向量方法的表现与基因存在的祖先状态重建同样好。我们在一个AOA土壤群落的amoA测序数据集上实现了预测模型,并给出了关键的生态预测,例如富氮土壤中的AOA群落预测具有解尿代谢能力,而适应低ph土壤的AOA群落预测具有高亲和力氨转运体(amt2)。预测基因的存在可以揭示微生物在环境中发挥的潜在功能,进一步有助于更好地理解其群落组装的机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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