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Phage Phenomics: Physiological Approaches to Characterize Novel Viral Proteins
Published on: June 11, 2015
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A computational model for bacteriophage ϕX174 gene expression
Alexis M Hill1, Tanvi A Ingle1, Claus O Wilke1
1Department of Integrative Biology, The University of Texas at Austin, Austin, TX, United States of America.
Plos One
|October 31, 2024
Summary
Computational modeling of bacteriophage phiX174 (ϕX174) reveals that its gene regulation is well explained by standard promoters and terminators. The study addresses challenges in modeling tightly coupled regulatory elements.
Area of Science:
- Molecular Biology
- Computational Biology
- Virology
Background:
- Bacteriophage phiX174 (ϕX174) is a key model organism for molecular biology.
- Understanding ϕX174 gene regulation is crucial but remains incomplete.
- Specific promoter-terminator arrangements in ϕX174 pose modeling challenges.
Purpose of the Study:
- To construct and utilize a computational model for studying ϕX174 gene regulation.
- To estimate the strengths of transcription regulatory elements in ϕX174.
- To investigate the role of putative regulatory elements in ϕX174 gene expression.
Main Methods:
- Development of a computational model for bacteriophage ϕX174.
- Fitting the model to transcriptomics data to estimate regulatory element strengths.
- Simulation of gene expression incorporating canonical and putative regulatory elements.
Main Results:
- Identified a parameter identifiability problem due to the close proximity of promoters and terminators.
- Estimated activities of two putative regulatory elements to be weak.
- Demonstrated that canonical promoters and terminators adequately explain ϕX174 transcript abundances.
Conclusions:
- Bacteriophage ϕX174 gene regulation is sufficiently explained by the established set of promoters and terminators.
- The study highlights challenges and solutions for modeling tightly regulated gene expression.
- Canonical regulatory elements are sufficient to describe observed transcript variations in ϕX174.
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