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Related Experiment Video

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High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
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Pathovar Transcriptomes.

Amy Platenkamp1, Jay L Mellies1

  • 1Biology Department, Reed College, Portland, Oregon, USA.

Msystems
|August 4, 2017
PubMed
Summary

This study shows that enteropathogenic Escherichia coli (EPEC) isolates with similar genomes have comparable transcriptomes, revealing insights into virulence gene expression across different EPEC lineages and phylogroups.

Area of Science:

  • Microbiology
  • Genomics
  • Molecular Biology

Background:

  • Archetypal bacterial strains are frequently used to understand regulatory networks within a pathovar.
  • Enteropathogenic Escherichia coli (EPEC) serves as a model system for studying bacterial pathogenesis.
  • Pathovars encompass diverse lineages and phylogroups, necessitating comprehensive strain analysis.

Purpose of the Study:

  • To investigate the relationship between genomic similarity and global transcriptome profiles in EPEC isolates.
  • To determine if similar genomic sequences correlate with similar virulence gene expression patterns.
  • To assess the variability in gene expression among different EPEC isolates.

Main Methods:

  • Analysis of 9 EPEC isolates representing 8 lineages and 3 phylogroups.
Keywords:
EPECdiversitygenome analysispathovartranscriptome

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  • Comparison of global transcriptomes under conditions that induce virulence gene expression.
  • Genomic sequence comparison to identify similarities among isolates.

    • Main Results:

    • Isolates with highly similar genomic sequences exhibited similar global transcriptome profiles.
    • Variations in gene expression were observed among individual EPEC isolates.
    • The study identified correlations between genomic relatedness and transcriptional patterns.

    Conclusions:

    • Genomic similarity is a strong predictor of global transcriptome similarity in EPEC.
    • Moving beyond archetypal strains is crucial for a complete understanding of bacterial regulatory networks.
    • Transcriptional pathways across EPEC lineages and phylogroups can potentially be correlated with clinical symptoms.