title: Failure of antibiotic treatment in microbial populations.
abstract: The tolerance of bacterial populations to biocidal or antibiotic treatment has been well documented in both biofilm and planktonic settings. However, there is still very little known about the mechanisms that produce this tolerance. Evidence that small, non-mutant subpopulations of bacteria are not affected by an antibiotic challenge has been accumulating and provides an attractive explanation for the failure of typical dosing protocols. Although a dosing challenge can kill the susceptible bacteria, the remaining persister cells can serve as a source of population regrowth. We give a condition for the failure of a periodic dosing protocol for a general chemostat model, which supports the simulations of an earlier, more specialized batch model. Our condition implies that the treatment protocol fails globally, in the sense that a mixed bacterial population will ultimately persist above a level that is independent of the initial composition of the population. We also give a sufficient condition for treatment success, at least for initial population compositions near the steady state of interest, corresponding to bacterial washout. Finally, we investigate how the speed at which the bacteria are wiped out depends on the duration of administration of the antibiotic. We find that this dependence is not necessarily monotone, implying that optimal dosing does not necessarily correspond to continuous administration of the antibiotic. Thus, genuine periodic protocols can be more advantageous in treating a wide variety of bacterial infections.
authors.affiliation: Department of Mathematics, University of Florida, Gainesville, USA. deleenhe@math.ufl.edu
authors.forename: Patrick
authors.initials: P
authors.lastname: De Leenheer
authors.forename: N G
authors.initials: NG
authors.lastname: Cogan
mesh_terms: D000465:Algorithms; D000900:Anti-Bacterial Agents / Q000008:administration & dosage / Q000494:pharmacology*; D001419:Bacteria / Q000187:drug effects* / Q000254:growth & development; D019149:Bioreactors; D049109:Cell Proliferation / Q000187:drug effects; D003198:Computer Simulation; D024881:Drug Resistance, Bacterial; D050296:Microbial Viability / Q000187:drug effects; D008954:Models, Biological
chemical_list: D000900:Anti-Bacterial Agents