In the absence of the selecting drugs, chromosomal mutations for resistance to antibiotics and other chemotheraputic agents commonly engender a cost in the fitness of microorganisms. Recent in vivo and in vitro experimental studies of the adaptation to these “costs of resistance” in Escherichia coli, HIV, and Salmonella typhimurium found that evolution in the absence of these drugs commonly results in the ascent of mutations that ameliorate these costs, rather than higher-fitness, drug-sensitive revertants. To ascertain the conditions under which this compensatory evolution, rather than reversion, will occur, we did computer simulations, in vitro experiments, and DNA sequencing studies with low-fitness rpsL (streptomycin-resistant) mutants of E. coli with and without mutations that compensate for the fitness costs of these ribosomal protein mutations. The results of our investigation support the hypothesis that in these experiments, the ascent of intermediate-fitness compensatory mutants, rather than high-fitness revertants, can be attributed to higher rates of compensatory mutations relative to that of reversion and to the numerical bottlenecks associated with serial passage. We argue that these bottlenecks are intrinsic to the population dynamics of parasitic and commensal microbes and discuss the implications of these results to the problem of drug resistance and adaptive evolution in parasitic and commmensal microorganisms in general.

In contrast to planktonic cells, bacteria imbedded biofilms are notoriously refractory to treatment by antibiotics or bacteriophage (phage) used alone. Given that the mechanisms of killing differ profoundly between drugs and phages, an obvious question is whether killing is improved by combining antibiotic and phage therapy. However, this question has only recently begun to be explored. Here, in vitro biofilm populations of Pseudomonas aeruginosa PA14 were treated singly and with combinations of two phages and bactericidal antibiotics of five classes. By themselves, phages and drugs commonly had only modest effects in killing the bacteria. However some phage-drug combinations reduced bacterial densities to well below that of the best single treatment; in some cases, bacterial densities were reduced even below the level expected if both agents killed independently of each other (synergy). Furthermore, there was a profound order effect in some cases: treatment with phages before drugs achieved maximum killing. Combined treatment was particularly effective in killing in Pseudomonas biofilms grown on layers of cultured epithelial cells. Phages were also capable of limiting the extent to which minority populations of bacteria resistant to the treating antibiotic ascend. The potential of combined antibiotic and phage treatment of biofilm infections is discussed as a realistic way to evaluate and establish the use of bacteriophage for the treatment of humans.

To determine the functional relationship between the density of bacteria and the pharmacodynamics of antibiotics, and the potential consequences of this inoculum effect on the microbiological course of antibiotic treatment of Staphylococcus aureus infections. In vitro time–kill, MIC estimation and antibiotic bioassay experiments were performed with S. aureus ATCC 25923 to ascertain the functional relationship between rates of kill and the MICs of six classes of antibiotics and the density of bacteria exposed. The potential consequences of the observed inoculum effects on the microbiological course of antibiotic treatment are explored with a mathematical model. Modest or substantial inoculum effects on efficacy were observed for all six antibiotics studied, such as density-dependent declines in the rate and extent of antibiotic-mediated killing and increases in MIC. Although these measures of antibiotic efficacy declined with inoculum, this density effect did not increase monotonically. At higher densities, the rate of kill of ciprofloxacin and oxacillin declined with the antibiotic concentration. For daptomycin and vancomycin, much of this inoculum effect is due to density-dependent reductions in the effective concentration of the antibiotic. For the other four antibiotics, this density effect is primarily associated with a decrease in per-cell antibiotic concentration. With parameters in the range estimated, our mathematical model predicts that the course of antibiotic treatment can be affected by cell density; treatment protocols based on conventional (density-independent) MICs can fail to clear higher density infections. The MICs used for pharmacokinetic/pharmacodynamic indices should be functions of the anticipated densities of the infecting population.