AI Article Synopsis

  • The study compares the closely related pathogens Yersinia pestis (YP) and Yersinia pseudotuberculosis (YPT), both of which have similar genomes but different mortality rates.
  • Through a multi-omic analysis at relevant temperatures, it was found that YP shows higher expression levels of key virulence factors compared to YPT, suggesting that regulatory changes and unique genes contribute to YP's increased pathogenicity.
  • The research also used global transcriptome and proteome data along with computational network analysis to identify potential new virulence factors in Yersinia based on their expression patterns.

Article Abstract

The underlying mechanisms that lead to dramatic differences between closely related pathogens are not always readily apparent. For example, the genomes of Yersinia pestis (YP) the causative agent of plague with a high mortality rate and Yersinia pseudotuberculosis (YPT) an enteric pathogen with a modest mortality rate are highly similar with some species specific differences; however the molecular causes of their distinct clinical outcomes remain poorly understood. In this study, a temporal multi-omic analysis of YP and YPT at physiologically relevant temperatures was performed to gain insights into how an acute and highly lethal bacterial pathogen, YP, differs from its less virulent progenitor, YPT. This analysis revealed higher gene and protein expression levels of conserved major virulence factors in YP relative to YPT, including the Yop virulon and the pH6 antigen. This suggests that adaptation in the regulatory architecture, in addition to the presence of unique genetic material, may contribute to the increased pathogenecity of YP relative to YPT. Additionally, global transcriptome and proteome responses of YP and YPT revealed conserved post-transcriptional control of metabolism and the translational machinery including the modulation of glutamate levels in Yersiniae. Finally, the omics data was coupled with a computational network analysis, allowing an efficient prediction of novel Yersinia virulence factors based on gene and protein expression patterns.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3518462PMC
http://dx.doi.org/10.1039/c2mb25287bDOI Listing

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