A Numbers Game: Ribosome Densities, Bacterial Growth, and Antibiotic-Mediated Stasis and Death

Abstract

We postulate that the inhibition of growth and low rates of mortality of bacteria exposed to ribosome-binding antibiotics deemed bacteriostatic can be attributed almost uniquely to these drugs reducing the number of ribosomes contributing to protein synthesis, i.e., the number of effective ribosomes. We tested this hypothesis with Escherichia coli K-12 MG1655 and constructs that had been deleted for 1 to 6 of the 7 rRNA (rrn) operons. In the absence of antibiotics, constructs with fewer rrn operons have lower maximum growth rates and longer lag phases than those with more ribosomal operons. In the presence of the ribosome-binding "bacteriostatic" antibiotics tetracycline, chloramphenicol, and azithromycin, E. coli strains with 1 and 2 rrn operons are killed at a substantially higher rate than those with more rrn operons. This increase in the susceptibility of E. coli with fewer rrn operons to killing by ribosome-targeting bacteriostatic antibiotics is not reflected in their greater sensitivity to killing by the bactericidal antibiotic ciprofloxacin, which does not target ribosomes, but also to killing by gentamicin, which does. Finally, when such strains are exposed to these ribosome-targeting bacteriostatic antibiotics, the time before these bacteria start to grow again when the drugs are removed, referred to as the post-antibiotic effect (PAE), is markedly greater for constructs with fewer rrn operons than for those with more rrn operons. We interpret the results of these other experiments reported here as support for the hypothesis that the reduction in the effective number of ribosomes due to binding to these structures provides a sufficient explanation for the action of bacteriostatic antibiotics that target these structures.

Importance: Chemotherapeutic agents, including antibiotics, have been used for more than a century; nevertheless, there are still major gaps in our understanding of how these drugs operate which limit future advances in antibacterial chemotherapy. Although the molecular mechanisms by which antibiotics bind to their target structures are largely known, fundamental questions about how these drugs actually kill and/or inhibit the replication of bacteria remain unanswered and subjects of controversy. We postulate that for the broad class of ribosome-binding bacteriostatic antibiotics, their reducing the number of active (functional) ribosomes per cell provides a sufficient explanation for the abatement of replication and the low rate of decline in densities of viable cells of bacteria exposed to these drugs. Using E. coli K-12 constructs with deletions of from one to six of the seven ribosome-RNA operons and the ribosome-binding bacteriostatic antibiotics tetracycline, chloramphenicol, and azithromycin, we tested this hypothesis. The results of our experiments are consistent with this "numbers game" hypothesis.

FIG 1

A model for the numbers game hypothesis for the action of ribosome-binding bacteriostatic antibiotics. (A) Turnover of ribosome (the green “shmoos”). The dashed circle with an arrow represents degradation and replacement (biogenesis) of ribosomes in a cell. The red diamonds represent antibiotics entering the cells and binding to and being released from the ribosomes. (B) Growth rate and death rate as functions of the number of ribosomes (the black line) (a Hill function; see the text). When the number of ribosomes is in the shaded area, cells die at a low rate. The blue, green, and red lines are normal distributions for the fraction of the population with the corresponding number of functional (not bound to drug) ribosomes. (C) Blow-up, growth, and death when the average number of ribosomes is low.

FIG 2

Rates of growth and lengths of lags for E. coli as a function of numbers of ribosomal (rrn) operons estimated from changes in optical density (600 nm Bioscreen) and CFU data. (A) Means and standard errors of the maximum growth rates (the Malthusian parameter [MP]). (B) Means and standard errors of the length of the lag. (C) Functional relationship between the length of the lag phase and the number of ribosomal operons for MG1655 and constructs with 2 to 6 rrn operons. Data were compiled from separate Bioscreen runs with a minimum of 20 points for each strain.

FIG 3

Susceptibility to killing by ribosome-targeting bacteriostatic antibiotics. (A) Hourly growth/death rates for exponentially growing MG1655 (MG) and constructs with from 0 to 6 ribosomal rrn operon deletions (MG and D1 to D6) exposed to 25, 125, and 40 µg/ml of tetracycline (TET), chloramphenicol (CAM), and azithromycin (AZI), respectively. (B to D) Hourly growth/death rates of E. coli MG1655 and constructs with 7, 6, 3, 2, and 1 rrn operons (respectively, MG, D1, D4, D5, and D6) exposed to different concentrations of tetracycline, chloramphenicol, and azithromycin before the growing cultures were exposed to the drugs and after 24 h of exposure. The results shown in panel A represent the means and standard errors of the estimates of ψ for from 7 to 10 independent experiments of this growth/death rate parameter, and those shown in panel B represent the means and standard errors of the estimates of ψ for from 2 to 4 independent experiments.

FIG 4

Hourly rates of decline in the viable cell density of growing cultures of MG1655 and constructs with 6, 3, 2, and 1 rrn operons (respectively, D1, D4, D5, and D6) exposed to 10 µg/ml gentamicin and 0.75 µg/ml ciprofloxacin. Data represent means and standard errors of the kill rates (ψi) determined for 2 or 3 separate experiments.

FIG 5

Post-antibiotic effect (PAE) for MG1655 (MG) and constructs with 6, 3, 2, and 1 rrn operons (D1, D4, D5, and D6, respectively) exposed to 25, 125, and 40 µg/ml of tetracycline (TET), chloramphenicol (CAM), and azithromycin (AZI), respectively. Data represent differences between the estimated lag values determined following exposure to the antibiotics and those observed in the absence of these drugs. Means and standard errors of PAEs for three separate experiments are shown.