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Rationally designing antisense therapy to keep up with evolving bacterial resistance

Fig 4

Mean Therapy Failure Time for Simulations Made in 100 ml Rich Medium Caption: A. shows summary of 1000 trajectories at each of the 90 combinations of possible independent-delivery-vehicle (5) and different values of ω (18), (or 12500 total) of which Figs, D, E, and F in S1 File show individual examples. It is seen that mean time to failure of the therapy is lengthened at higher ω and larger number of independent delivery mechanisms. In other words, making nonspecific mutations less advantageous and making specific mutations more advantageous elongates therapy efficacy. The simulations were performed as if the experiment were conducted in 100 ml rich medium B. shows mean therapy failure times for up to five-fold combination therapy of conventional antibiotics. Each data point is the mean of 1000 individual simulations. Under therapy the WT is assumed to have 10 percent of maximum growth rate and single mutation renders effectiveness of an antibiotic nil. Mathematically the simulation parameters are equivalent to our earlier simulations except in this case without any specific mutations. Error bars are .

Fig 4

doi: https://doi.org/10.1371/journal.pone.0209894.g004