氧化剂
系统发育树
系统发育多样性
系统发育学
多样性(政治)
计算生物学
环境化学
基因
化学
生物
遗传学
政治学
有机化学
法学
作者
Yuhan Wang,Zhifen Pan,Yuyu Shi,Yaohui Bai,Jinsong Liang,Aijie Wang,Jiuhui Qu
标识
DOI:10.1021/acs.est.5c01235
摘要
Manganese (Mn) oxides are crucial for degrading organic pollutants and driving biogeochemical cycles. Microorganisms drive Mn(II) oxidation, but traditional cultivation-dependent identification methods are inefficient and error-prone. To overcome these limitations, we developed MnOxGeneTool, a bioinformatics tool for identifying and quantifying Mn(II)-oxidizing genes from genomic and metagenomic data. MnOxGeneTool consists of three main components: (1) a curated database of known Mn(II)-oxidizing proteins and their homologues, (2) a hidden Markov models (HMMs) database derived from this protein data set, and (3) a computational pipeline that integrates bioinformatics tools (e.g., HMMER and BLASTX) to identify and quantify Mn(II)-oxidizing genes. We assessed the accuracy and sensitivity of these HMMs through cross-validation, demonstrating their effectiveness in identifying Mn(II)-oxidizing genes in bacterial genomes. Using MnOxGeneTool, we explored the phylogenetic diversity of Mn(II)-oxidizers and identified 824 bacterial genera containing Mn(II)-oxidizing genes, significantly expanding previous knowledge in this field. Additionally, we analyzed metagenomic data from various environments to explore environmental drivers of Mn(II)-oxidizing genes, identifying two potential drivers: oligotrophic conditions and alkaline environments. These findings enable targeted discovery of novel Mn(II)-oxidizers and genetic determinants through identification of their ecological niches and expression optima, thereby expanding MnOxGeneTool's predictive coverage of uncatalogued Mn(II)-oxidizing proteins. By providing an innovative bioinformatics tool that enables efficient identification and quantification of Mn(II)-oxidizing genes from both genomic and metagenomic data, this study offers significant advancements in the research of biogenic Mn(II) oxidation. The tool is available at https://github.com/wyh19990121/MnOxGeneTool.
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