MnOxGeneTool: A Comprehensive Tool for Identifying and Quantifying Mn(II)-Oxidizing Genes, Revealing Phylogenetic Diversity and Environmental Drivers of Mn(II)-Oxidizers

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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Publication Details

Journal
Environmental Science & Technology
Published
2025-06-03
DOI
https://doi.org/10.1021/acs.est.5c01235
Citations
3
Primary Topic
Geochemistry and Elemental Analysis
Type
article
Field-Weighted Citation Impact
4.01

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article

MnOxGeneTool: A Comprehensive Tool for Identifying and Quantifying Mn(II)-Oxidizing Genes, Revealing Phylogenetic Diversity and Environmental Drivers of Mn(II)-Oxidizers

Yu Shi, Aijie Wang, Jinsong Liang, Yaohui Bai et al.
3 citations
Environmental Science & Technology
Geochemistry and Elemental Analysis
4.01
article

MnOxGeneTool: A Comprehensive Tool for Identifying and Quantifying Mn(II)-Oxidizing Genes, Revealing Phylogenetic Diversity and Environmental Drivers of Mn(II)-Oxidizers

Yu Shi, Aijie Wang, Jinsong Liang, Yaohui Bai, Yuhan Wang, Zhifen Pan, Jiuhui Qu
article en
3 citations

Abstract

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.

Environmental Science & TechnologyVol. 59(23)
Chinese Academy of Sciences (CN), Harbin Institute of Technology (CN), Research Center for Eco-Environmental Sciences (CN), Tsinghua University (CN)
National Natural Science Foundation of China
Life in Land
Openalex Percentile: Top 7%
Geochemistry and Elemental Analysis
4.01
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