Computation, prediction, and experimental tests of fitness for bacteriophage T7 mutants with permuted genomes

We created a simulation based on experimental data from bacteriophage T7 th at computes the developmental cycle of the wildtype phage and also of mutan ts that have an altered genome order. We used the simulation to compute the fitness of more than 10(5) mutants. We tested these computations by constr ucting and experimentally characterizing T7 mutants in which we repositione d gene I, coding for T7 RNA polymerase. Computed protein synthesis rates fo r ectopic gene I strains were in moderate agreement with observed rates. Co mputed phage-doubling rates were close to observations for two of four stra ins, but significantly overestimated those of the other two. Computations i ndicate that the genome organization of wild-type T7 is nearly optimal for growth: only 2.8% of random genome permutations were computed to grow faste r, the highest 31% faster, than wild type. Specific discrepancies between c omputations and observations suggest that a better understanding of the tra nslation efficiency of individual mRNAs and the functions of qualitatively "nonessential" genes will be needed to improve the T7 simulation. In silico representations of biological systems can serve to assess and advance our understanding of the underlying biology. Iteration between computation, pre diction, and observation should increase the rate at which biological hypot heses are formulated and tested.