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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
Published on: December 7, 2021
Models of deletion for visualizing bacterial variation: an application to tuberculosis spoligotypes
Josephine F Reyes1, Andrew R Francis, Mark M Tanaka
1School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney 2052, Australia. j.reyes@student.unsw.edu.au
BMC Bioinformatics
|November 28, 2008
Summary
We developed a new method called spoligoforests to visualize relationships among Mycobacterium tuberculosis isolates. This approach uses a deletion model to infer transmission and mutation histories, aiding in understanding tuberculosis evolution.
Area of Science:
- Microbiology
- Genetics
- Evolutionary Biology
Background:
- Molecular typing is crucial for understanding bacterial genetic relationships and pathogen transmission.
- Spoligotyping is a standard method for Mycobacterium tuberculosis (M. tuberculosis) genotyping, analyzing variations in the direct repeat region.
- Graph-based analyses, particularly phylogenies, are popular for visualizing bacterial isolate relationships.
Purpose of the Study:
- To explore various evolutionary models for spoligotypes.
- To develop a novel visualization method for M. tuberculosis isolate relationships.
- To represent likely evolutionary pathways and transmission patterns.
Main Methods:
- Examined multiple models of spoligotype evolution.
- Utilized a second-order variant of Akaike's Information Criterion to select the Zipf model.
- Developed a graph construction method termed 'spoligoforests'.
Main Results:
- Identified that spoligotype mutations commonly involve single or few adjacent spacer losses.
- The Zipf model was selected for resolving ancestral ambiguities.
- Successfully constructed spoligoforests and applied them to a Cuban M. tuberculosis dataset, comparing results with existing methods.
Conclusions:
- Introduced a novel approach, spoligoforests, for analyzing M. tuberculosis isolate relationships.
- The method reconstructs plausible transmission and mutation histories based on a deletion model.
- Spoligoforests can be integrated with clinical data for a comprehensive understanding of M. tuberculosis evolution and transmission.
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