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Long-read sequencing-based in silico phage typing of vancomycin-resistant Enterococcus faecium
Paola Lisotto1, Erwin C Raangs1, Natacha Couto1,2
1Department of Medical Microbiology and Infection Prevention, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
BMC Genomics
|October 24, 2021
Summary
Phage signatures in long-read sequencing data can rapidly identify related vancomycin-resistant enterococci (VRE) isolates. This method aids in tracking hospital outbreaks caused by VRE, offering faster results than traditional typing.
Area of Science:
- Microbiology
- Genomics
- Infectious Diseases
Background:
- Vancomycin-resistant enterococci (VRE) are significant nosocomial pathogens causing hospital outbreaks.
- Current molecular typing methods like core-genome MLST (cgMLST) rely on short-read sequencing.
- Long-read sequencing offers speed and structural information but lacks precision for SNP-based typing.
Purpose of the Study:
- To compare prophages in 50 complete *E. faecium* genomes across different lineages.
- To explore the utility of phage signatures for typing and identifying VRE outbreaks.
- To assess if long-read sequencing data can identify phage signatures for outbreak detection.
Main Methods:
- Comparative analysis of prophage content in 50 complete *E. faecium* genomes.
- In silico phage typing of twelve isolates using MinION long-read sequencing data.
- Genomic comparison of long-read assemblies to identify isolates based on genome architecture and phage signatures.
Main Results:
- Variation in phage content was observed among different MLST-defined lineages.
- Phages were identified that were present in multiple sequence types (STs) or unique to single lineages.
- Long-read sequencing data allowed for correct identification of isolates belonging to the same complex type based on phage signatures and global genome architecture.
Conclusions:
- Phage content analysis of long-read sequencing data enables rapid identification of related VRE isolates.
- This approach facilitates the development of software for real-time typing analysis, yielding results within hours.
- Further research is needed to evaluate the discriminatory power of this method for investigating ongoing outbreaks over extended periods.
