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Updated: Apr 22, 2026
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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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Genome-based source attribution using a One Health Escherichia coli isolate collection from 2013 to 2023 in Scotland.
Antonia Chalka1,2, Louise Crozier2, Adriana Vallejo-Trujillo1,2
1The Roslin Institute and Royal (Dick) School of Veterinary Medicine, University of Edinburgh, Easter Bush Estate, Edinburgh, Scotland, EH25 9RG, UK.
Microbial Genomics
|April 20, 2026
Summary
This study used random forest models to trace Escherichia coli (E. coli) contamination sources. A significant livestock E. coli signal was found in 15% of human clinical isolates, highlighting agri-food chain transmission risks.
Area of Science:
- Microbiology
- Genomics
- Epidemiology
Background:
- Escherichia coli (E. coli) is a significant cause of human infections.
- Understanding E. coli transmission routes is crucial for public health.
- Whole-genome sequencing provides high-resolution data for microbial source tracking.
Purpose of the Study:
- To develop and apply random forest-based source attribution models for E. coli.
- To investigate the potential sources of E. coli contamination in food, shellfish, and water samples.
- To assess the contribution of livestock and human sources to E. coli infections.
Main Methods:
- Development of random forest models using 4,230 E. coli whole-genome assemblies.
- Analysis of E. coli isolates from diverse sources including wastewater, livestock, food, and clinical infections.
- Probabilistic assignment of E. coli isolates to potential livestock and human sources.
Main Results:
- A livestock E. coli signal was identified in 15% of human clinical isolates.
- E. coli isolates from food and water frequently showed co-attribution to both livestock and human sources.
- Only 2.3% of food E. coli isolates were linked to human bacteraemia/UTI sequence types.
Conclusions:
- Source attribution models are valuable tools for national E. coli surveillance.
- Findings suggest routine human exposure to specific livestock E. coli strains via the agri-food chain.
- This research supports risk management strategies to protect public health from E. coli transmission.
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