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Updated: Jun 11, 2026

Characterization of a Pathogenic Escherichia coli Strain Derived from Oreochromis spp. Farms Using Whole-Genome Sequencing
Published on: December 23, 2022
EcoliTyper: a species-optimized computational pipeline for comprehensive genotyping and surveillance of Escherichia
Brown Beckley1,2, Amarh Vincent3
1Department of Medical Biochemistry, University of Ghana Medical School, Accra, Ghana. brownbeckley94@gmail.com.
Background:
Escherichia coli is a major bacterial pathogen associated with a high global burden of disease. Effective surveillance requires integrated genomic analysis, but current methods rely on multiple independent tools for sequence typing, serotyping, plasmid screening, and profiling of antimicrobial resistance (AMR) and virulence factors. This fragmented workflow could complicates analysis and hinders standardized reporting.
Results:
We developed EcoliTyper, a computational pipeline that executes a comprehensive set of E. coli genotyping analyses in a single automated workflow. The tool performs species confirmation (via fastANI), assembly quality control, Multi-Locus Sequence Typing (MLST), serotyping (O and H antigens), CH typing (FumC and FimH), Clermont phylogrouping, pathotype classification, and screening for AMR genes, virulence factors, plasmid replicons, biocide and heavy metal resistance markers. It includes cross-genome pattern discovery to summarise gene frequencies and contextualises results using a manually curated lineage database of high-risk clones. All results are compiled into an interactive, gene-centric HTML report, together with TSV, JSON, and plain text files. On a system with 16 CPU cores, EcoliTyper processed 60 E. coli genomes in approximately 129 min.
Availability:
EcoliTyper is freely available under the MIT license at https://github.com/bbeckley-hub/EcoliTyper and is distributed as a self-contained Conda package.
Conclusion:
EcoliTyper addresses workflow fragmentation in E. coli genomics by integrating multiple typing methods into a single, efficient pipeline. By providing structured, multi-format outputs and contextual data, it facilitates rapid isolate characterisation for surveillance and epidemiological studies.
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