Proper choice of dose and duration of therapy are maximally important when there are preexisting or de novo emerging point mutations that result in the production of a mutant subpopulation with reduced susceptibility.

Early empirical knowledge derived from the first years of penicillin therapy “Hit strong but short” (KH Spitzy, 1970s) has been ignored in the golden era of antibacterial therapy. Nowadays, these important prinicples of antibacterial therapy have been confirmed by in vitro and in vivo PK/PD experiments.

Critical parameters for selection of subpopulations with reduced susceptibility are

  • Drug exposure
  • Duration of drug exposure
  • Inoculum
  • Mutation frequency
  • Hypermutator status

Drug exposure

Lower degrees of drug intensity allow rapid amplification of the resistant subpopulation, with near complete replacement of the total population by resistant microorganisms by the end of the experiment. In a study by V. Tam the resistant subpopulation was controlled only up to 4 days. Higher drug intensity did not allow the resistant population to fully replace the sensitive population (Tam et al,  2007).


The mutant selective window

The widely used concept of the mutant selective window —the concentration range in which the resistant mutant is enriched—extends between the MIC of the susceptible wild type and the MIC of the resistant mutants. However, the biologically relevant sub-MIC selective window is much wider and needs to include antibiotic concentrations several hundred-fold below MICsusc. Thus, even extremely low antibiotic concentrations that are present in human body compartments during therapeutic use, are relevant for the enrichment and maintenance of pre-existing resistant mutants as well as for the de novo selection of new mutants (E Gullberg et al, 2011).

Selection at subMIC

Duration of drug exposure

As the duration of drug exposure increases, the intensity needed to suppress the antibiotic-resistant subpopulations increases (Tam et al,  2007) highlighting the importance of duration of therapy in patients. The experiments demonstrate that treatment beyond 4-6 days would require higher doses to prevent the selection of resistant subpopulation, especially in patients with reduced function of the immune system.


Bacterial densities in infections are ranging from <104 to 108 CFU/ml. A well-known example is ventilator-associated pneumonia with bacterial densities as high as 108 CFU/ml. Emergence of resistance during therapy has been observed and described. Bacterial densities spanning a range of 104 to 108 CFU/ml are also present in patients with HAP (F. Pirali et al 1994).

Bacterial burden has a significant influence on the ultimate outcome of antibacterial therapy and the choice of antibacterial strategies. Patients with low bacterial burdens (e.g., ∼104 CFU/ml) may potentially be treated with monotherapy, with little chance of driving resistance. In contrast, patients with a higher bacterial density may require additional adjunctive therapies, such as combination chemotherapy, to prevent the emergence of antimicrobial resistance. Future clinical management of patients with HAP and VAP may require patients to be stratified according to the antimicrobial resistance pattern of the bacterial species and pathogen density in order to select the optimal individual regimen (TW. Felton et al 2013).

Mutation frequency

The frequency of mutation measures all the mutants present in a given population. It is a cross section of the bacterial population at a given time and reflects not only the mutation rate but also the history of the population before selection is applied. The probability of the emergence of antibiotic-resistant mutants is a complex phenomenon, in which the physiology, the genetics, the antibiotic-bacterium dynamics, and the historical behavior of bacterial populations, together with the physical structure of the selective medium, play major roles. We must assume that the mutation rate determined under conventional laPatchworkboratory conditions probably differs greatly from that in vivo at the site of infection. (JL Martinez, F Baquero, 2000).

Patchwork structure of bacterial populations selected at different antibiotic concentrations (JL Martinez, F Baquero, 2000):




The presence of antibiotics, even at low concentrations, may constitute an environmental stress that can promote an increase in mutation frequency at subinhibitory concentrations (SK Henderson-Begg et al, 2006).

Subinhibitory concentrations of antibiotics have a strong effect on mutation rates, horizontal gene transfer and biofilm formation, which may all contribute to the emergence and spread of antibiotic resistance (L Laureti et al, 2013)

Hypermutator status

Many bacterial populations harbor a proportion of cells with a mutator phenotype, enabling rapid adaptation to continually changing environments. These cells have a mutation rate that is increased from 10 to 50 up to 10,000 times (JL Martinez, F Baquero, 2000). Mutator bacteria not only complicate the therapy of chronic infections such as lung infections in cystic fibrosis patients but also increase the probability of failures in subsequent treatments after the failure of an initial treatment (A. Giraud et al 2002)

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