Abstract
Inferring transmission relies on accurately distinguishing between isolates from the same source and those from different sources, and high-quality genomic data are frequently used to model transmission scenarios. The post-enrichment metagenome sequencing (pe-MGS) method uses a sequencing approach to analyse the diversity of a target pathogen enriched by preculturing and has been effectively used to analyse the transmission of nosocomial infections. However, a direct comparison of single nucleotide variant (SNV) call accuracy, cost and feasibility between single-colony whole-genome sequence (sc-WGS) data and pe-MGS for an antimicrobial resistant bacteria of clinical importance, extended-spectrum beta-lactamase producing Escherichia coli (ESBL-EC), is required for implementation in large-scale clinical studies. A spiked stool sample and rectal swabs from six study participants were pre-enriched in buffered peptone water and cultured on MacConkey agar with 1 mg l−1 cefotaxime. Seven single colonies were picked, and the remaining biomass of all colonies was collected from each plate, sequenced and analysed using the mSWEEP/mGEMS pipeline. We created a custom SNV calling workflow that allows heterozygous SNVs in a bacterial population and found that the choice of reference changed the number of measurable SNV distances between the sc-WGS and pe-MGS. Using our custom workflow with a core-gene reference captured 99% of all the SNV calls from multiple sc-WGS data in the pe-MGS data of the same culture. The plate sweep method offers a feasible, cost-effective alternative to multiple single colony picks for describing within-host ESBL-EC diversity. The workflow we developed allows for effective SNV calling from pe-MGS data that were comparable to SNV calls from multiple sc-WGS data from the same sample.
| Original language | English |
|---|---|
| Article number | 001757 |
| Journal | Microbial genomics |
| Volume | 12 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 22 Jun 2026 |
Keywords
- antimicrobial resistance
- bioinformatic methods
- molecular epidemiology
- transmission surveillance
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