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Translational Regulation01:29

Translational Regulation

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Translational regulation in prokaryotes ensures efficient protein synthesis by controlling ribosome access to mRNA. This regulation is mediated by secondary RNA structures, including translational riboswitches, RNA thermometers, and small RNAs (sRNAs), which respond to intracellular and environmental signals to modulate gene expression.Translational RiboswitchesRiboswitches in the leader region of mRNAs can regulate translation by altering the accessibility of the Shine-Dalgarno (SD) sequence,...
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High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
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Integrating Transcriptomic and Proteomic Data Using Predictive Regulatory Network Models of Host Response to

Deborah Chasman1, Kevin B Walters2, Tiago J S Lopes2

  • 1Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.

Plos Computational Biology
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Summary

This study integrates host transcriptomes and proteomes to map regulatory networks driving responses to influenza infections. The findings reveal key regulators and pathways involved in differential host responses to varying viral pathogenicities.

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Area of Science:

  • Systems Biology
  • Infectious Disease Research
  • Molecular Biology

Background:

  • Mammalian host response to pathogens involves complex regulatory networks of proteins and genes.
  • Understanding molecular differences in host responses to diverse pathogens is a key challenge in infectious disease research.
  • Systems biology has generated omic data to study host responses to infectious agents like influenza viruses.

Purpose of the Study:

  • To comprehensively understand the regulatory network driving host response to multiple infectious agents.
  • To integrate host transcriptomes and proteomes using a network-based approach.
  • To identify regulatory networks, modules, and subnetworks specific to host responses to influenza infections.

Main Methods:

  • Integrated host transcriptomes and proteomes using a network-based approach.
  • Combined expression-based regulatory network inference, structured-sparsity based regression, and network information flow.
  • Applied the approach to identify regulatory programs for expression modules.

Main Results:

  • Inferred regulatory networks and modules are enriched for immune response pathways.
  • Identified apoptosis, splicing, and interferon signaling in differential host responses to varying viral pathogenicities.
  • Prioritized regulators and identified novel strain and pathogenicity-specific patterns of expression.

Conclusions:

  • The integrated analysis identified novel patterns in host response to influenza infection.
  • Discovered important regulators of host response, including previously unknown ones.
  • RNAi-based knockdown of predicted regulators significantly impacted viral replication.