Simulation Study for Transfer of Antibiotic Resistance via Mutator Subpopulation

Evolution of antibiotic resistance in bacterial populations is an increasing problem having fatal consequences for treatment of diseases. Therefore it is very important to understand this evolution. Traditionally evolution is considered to happen by single point mutations, where each mutant must have a growth advantage over the parent strain and grow to a sufficient number before a second mutation can occur. However, when multiple mutations are necessary for development of resistance, single mutations occurring with a normal mutation rate can not always explain the observed resistance. We introduce an alternative hypothesis by which a subpopulation of mutators drives the evolution process. Resistance is acquired by a subpoplution of mutators, for which the mutation rate is much higher than the wild-type. If the resistance is located on a transferable plasmid it can subsequently be transferred to the wild-type population by conjugation. To examine whether this pathway will in fact speed up evolution, we perform a simulation study, where bacteria are simulated to grow in a chemostat environment, such as the intestine of a human. Since mutation events are stochastic processes, we model the system by a discrete Markov process with the possibility of changes in each state given by a Poisson distribution. Parameters for growth, mutation and conjugation rates used in the simulation study resemble those of E.coli with a mutator obtained with the XL1-red mutator strain having a 5000 times higher mutation rate than the wild-type. We simulate the process for 24 hours and perform 1000 repetitions, which correspond to considering 1000 people with the same initial bacterial population in the intestine. In none of the repetitions a double mutation occurs in the wild-type population, but in almost 300 cases a double mutated strain has been conjugated to the wild-type bacterial population. To confirm these results future work should include an experimental study of the hypothesis.