ArticleMolecular bioSystems2013
A multi-omic systems approach to elucidating Yersinia virulence mechanisms.
Article in Molecular bioSystems, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.
- Multi-omics time-series analysis in microbiome research: a systematic review.Briefings in bioinformatics · 2025Pooled it
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- Unified feature association networks through integration of transcriptomic and proteomic data.PLoS computational biology · 2019Article
- Multiple mechanisms drive phage infection efficiency in nearly identical hosts.The ISME journal · 2018Article
- The MPLEx Protocol for Multi-omic Analyses of Soil Samples.Journal of visualized experiments : JoVE · 2018Article
- Article
- Analysis of differentially expressed proteins in Yersinia enterocolitica-infected HeLa cells.Biochimica et biophysica acta · 2016Article
- Proteomics As a Tool for Studying Bacterial Virulence and Antimicrobial Resistance.Frontiers in microbiology · 2016Review
- Environmental Regulation of Yersinia Pathophysiology.Frontiers in cellular and infection microbiology · 2016Review
- A novel targeted/untargeted GC-Orbitrap metabolomics methodology applied toMetabolomics : Official journal of the Metabolomic Society · 2016Article
- From genome-scale data to models of infectious disease: A Bayesian network-based strategy to drive model development.Mathematical biosciences · 2015Article
- Investigation of Yersinia pestis Laboratory Adaptation through a Combined Genomics and Proteomics Approach.PloS one · 2015Article
- The pyruvate-tricarboxylic acid cycle node: a focal point of virulence control in the enteric pathogen Yersinia pseudotuberculosis.The Journal of biological chemistry · 2014Article
- Coregulation of host-adapted metabolism and virulence by pathogenic yersiniae.Frontiers in cellular and infection microbiology · 2014Review
- GIM3E: condition-specific models of cellular metabolism developed from metabolomics and expression data.Bioinformatics (Oxford, England) · 2013Article
- Drug repurposing: a better approach for infectious disease drug discovery?Current opinion in immunology · 2013Review
- Omics strategies for revealing Yersinia pestis virulence.Frontiers in cellular and infection microbiology · 2012Review
Corrections and comments
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Authors and funding
17 authors at 5 institutions in 1 country.
Funding
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.