  Some microbial organisms are known to randomly slip into and out of
hibernation, irrespective of environmental conditions [1]. In a (genetically)
uniform population a typically very small subpopulation becomes metabolically
inactive whereas the majority subpopulation remains active and grows. Bacteria
such as E. coli, Staphylococcus aureus (MRSA-superbug), Mycobacterium
tuberculosis, and Pseudomonas aeruginosa [1-3] show persistence. It can render
bacteria less vulnerable in adverse environments [1, 4, 5] and their effective
eradication through medication more difficult [2, 3, 6]. Here we show that
medication treatment regimes may have to be modified when persistence is taken
into account and characterize optimal approaches assuming that the total
medication dose is constrained. The determining factors are cumulative
toxicity, eradication power of the medication and bacterial response
timescales. Persistent organisms have to be fought using tailored eradication
strategies which display two fundamental characteristics. Ideally, the
treatment time should be significantly longer than in the case of persistence
with the medication uniformly spread out over time; however, if treatment time
has to be limited, then the application of medication has to be concentrated
towards the beginning and end of the treatment. These findings deviate from
current clinical practice, and may therefore help to optimize and simplify
treatments. Our use of multi-objective optimization [7] to map out the optimal
strategies can be generalized to other related problems.
