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MicroRNA-based Regulation of Picornavirus Tropism
Published on: February 6, 2017
Competing pathways control host resistance to virus via tRNA modification and programmed ribosomal frameshifting
Nathaniel D Maynard1, Derek N Macklin, Karla Kirkegaard
1Department of Bioengineering, Stanford University, Stanford, CA, USA.
Molecular Systems Biology
|February 2, 2012
Summary
Host sulfur metabolism and tRNA modification impact viral infection. Specific pathways offer protection or enhance infection by influencing viral protein production through programmed ribosomal frameshifting.
Area of Science:
- Microbiology
- Molecular Biology
- Biochemistry
Background:
- Viral infection involves complex host-pathogen interactions.
- Host cellular machinery, including metabolism and translation, can influence viral replication.
Purpose of the Study:
- To investigate the link between host sulfur metabolism, tRNA modification, and viral infection susceptibility.
- To elucidate the mechanisms by which these host factors affect viral protein synthesis and replication.
Main Methods:
- Utilized Escherichia coli and lambda phage as a model system.
- Employed genetic manipulation of host pathways (iron-sulfur cluster biosynthesis, tRNA thiolation).
- Combined experimental assays with computational modeling to analyze viral protein ratios and competitive binding.
Main Results:
- The iron-sulfur cluster biosynthesis pathway conferred protection against lambda phage infection.
- A tRNA thiolation pathway was found to enhance viral infection.
- tRNA(Lys) uridine 34 modification inhibited programmed ribosomal frameshifting (PRF), altering the ratio of lambda phage proteins gpG and gpGT.
- The protective effect of iron-sulfur cluster biosynthesis was indirect, mediated by competitive binding of the sulfur donor IscS.
Conclusions:
- Host sulfur metabolism and tRNA modification are critical determinants of viral infection susceptibility.
- These host factors modulate viral replication through mechanisms like PRF and competitive binding.
- The identified network has potential broad implications for understanding human viral infections due to conserved components.
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