This study will use the genome network as a framework for predicting evolution in a virus. The viral genome will be modified in simple ways by deleting or replacing a single gene, and the modified virus will be adapted to observe how it evolves in response to the modification. The general prediction is that changes which evolve in the modified virus will occur in the parts of the genome known to interact with the modified gene. The study will provide a direct test of this framework with experimental data. The virus used is the harmless bacteriophage T7, which offers a good model system for other viruses because much is already known about T7 molecular biology, a genome network can be assembled, and T7 grows only on a few strains of bacteria. The work will give useful insight to several questions and goals in public health and molecular epidemiology, as well as in basic biology: (i) the feasibility of engineering new genomes and creating recombinant vaccines safely;(ii) how well we can predict molecular evolution;(iii) whether genome interactions are conserved across related species;(iv) how to detect genetic signatures of evolution in engineered versus natural genomes.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM057756-12
Application #
7674690
Study Section
Special Emphasis Panel (ZRG1-GGG-J (02))
Program Officer
Eckstrand, Irene A
Project Start
1998-01-01
Project End
2010-08-31
Budget Start
2009-09-01
Budget End
2010-08-31
Support Year
12
Fiscal Year
2009
Total Cost
$185,138
Indirect Cost
Name
University of Texas Austin
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
170230239
City
Austin
State
TX
Country
United States
Zip Code
78712
Paff, Matthew L; Nuismer, Scott L; Ellington, Andrew et al. (2016) Virus wars: using one virus to block the spread of another. PeerJ 4:e2166
Bull, James J (2016) Lethal gene drive selects inbreeding. Evol Med Public Health 2017:1-16
Paff, Matthew L; Nuismer, Scott L; Ellington, Andrew D et al. (2016) Design and engineering of a transmissible antiviral defense. J Biol Eng 10:12
Bull, J J (2015) Evolutionary decay and the prospects for long-term disease intervention using engineered insect vectors. Evol Med Public Health 2015:152-66
Bull, J J (2015) Evolutionary reversion of live viral vaccines: Can genetic engineering subdue it? Virus Evol 1:
Bull, James J; Crandall, Cameron; Rodriguez, Anna et al. (2015) Models for the directed evolution of bacterial allelopathy: bacteriophage lysins. PeerJ 3:e879
Paff, Matthew L; Stolte, Steven P; Bull, James J (2014) Lethal mutagenesis failure may augment viral adaptation. Mol Biol Evol 31:96-105
Schmerer, Matthew; Molineux, Ian J; Bull, James J (2014) Synergy as a rationale for phage therapy using phage cocktails. PeerJ 2:e590
Bull, James J; Lauring, Adam S (2014) Theory and empiricism in virulence evolution. PLoS Pathog 10:e1004387
Schmerer, Matthew; Molineux, Ian J; Ally, Dilara et al. (2014) Challenges in predicting the evolutionary maintenance of a phage transgene. J Biol Eng 8:21

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