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Updated: Dec 22, 2025
08:03
Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
Published on: December 7, 2021
2.7K
Visualizing variation within Global Pneumococcal Sequence Clusters (GPSCs) and country population snapshots to
Rebecca A Gladstone1, Stephanie W Lo1, Richard Goater2,3
1Parasites and microbes, Wellcome Sanger InstituteHinxton, UK.
Microbial Genomics
|May 8, 2020
Summary
This study provides accessible genomic data visualizations for pneumococcal lineages, geographic distribution, and antibiotic resistance. These interactive tools empower researchers to explore pneumococcal disease insights without specialized bioinformatics training.
Area of Science:
- Microbiology and Bioinformatics
- Genomic Epidemiology
- Public Health
Background:
- Understanding pneumococcal lineages, geographic spread, and antibiotic resistance is crucial for combating pneumococcal disease.
- Genomic data offers valuable insights but often requires specialized bioinformatics expertise for interpretation.
- Disseminating these insights broadly can accelerate research and public health interventions.
Purpose of the Study:
- To develop and present interactive bioinformatic resources for exploring pneumococcal genomic data.
- To increase the accessibility of genomic insights on pneumococcal lineages and antibiotic resistance patterns to a wider community.
- To provide examples demonstrating the utility of these resources for hypothesis generation and testing.
Main Methods:
- Creation of country-specific and international phylogenetic snapshots for 73 Global Pneumococcal Sequence Clusters (GPSCs) using PopPUNK.
- Gene presence/absence analysis with Roary and recombination profiling with Gubbins, visualized in Phandango.
- Temporal phylogenetic signal assessment using BactDating and data visualization in Microreact.
Main Results:
- Identified diverse genetic backgrounds for serotype 14 in South Africa within GPSC9, with sub-clusters emerging in the 1980s.
- Detected a 20kb recombination event in GPSC97 spanning the capsular polysaccharide locus, linked to serotype switching (6A to 19A) in the 1990s.
- Observed antibiotic resistance gene acquisition in GPSC23 between 1953-1975 and contextualized Utah isolates within GPSC31.
Conclusions:
- The provided interactive resources facilitate the exploration of pneumococcal genomic data, aiding in hypothesis generation and testing.
- These tools enable researchers to contextualize their own collections of pneumococcal isolates within broader global and regional patterns.
- Enhanced accessibility of genomic insights promotes a wider understanding of pneumococcal disease dynamics and evolution.
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