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MOBHunter: a data integration platform for identification and classification of mobile genetic elements in microbial
Camila Rojas-Villalobos1,2, Francisco J Ossandon1, Camila Castillo-Vilcahuaman1,3
1Centro Científico y Tecnológico de Excelencia Ciencia & Vida, Santiago 8580704, Chile.
MOBHunter is a new bioinformatic pipeline for identifying and classifying mobile genetic elements (MGEs) in microbial genomes. This tool provides a unified framework for robust MGE analysis, reducing research time.
Area of Science:
- Genomics
- Bioinformatics
- Microbial Evolution
Background:
- Horizontal gene transfer (HGT) drives microbial genome evolution and adaptation.
- Mobile genetic elements (MGEs) are key components of HGT, conferring traits like antibiotic resistance.
- Existing bioinformatic tools lack a unified framework for comprehensive MGE identification and classification.
Purpose of the Study:
- To develop an advanced bioinformatic pipeline, MOBHunter, for unified MGE identification and classification.
- To consolidate diverse bioinformatic tools and algorithms into a single, efficient workflow.
- To provide robust, evidence-based classifications and visualizations of MGEs in microbial genomes.
Main Methods:
- Development of MOBHunter, a pipeline integrating standalone tools and in-house algorithms.
- Consolidation of data collection, processing, and interpretation into a unified workflow.
- Implementation of consensus identification and score-supported classification for MGEs.
Main Results:
- MOBHunter offers a unified framework for comprehensive MGE analysis.
- The pipeline provides consensus identifications, score-supported classifications, and enhanced web visualizations.
- MOBHunter significantly reduces analysis time by streamlining the MGE identification and interpretation process.
Conclusions:
- MOBHunter represents a significant advancement in the identification and classification of MGEs.
- The platform enhances the understanding of flexible genome regions in microbial populations.
- MOBHunter facilitates robust genomic analysis for researchers studying microbial evolution and adaptation.
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