Antimicrobial Peptides Can Generate Tolerance by Lag and Interfere with Antimicrobial Therapy

Abstract

Antimicrobial peptides (AMPs) are widely distributed molecules secreted mostly by cells of the innate immune system to prevent bacterial proliferation at the site of infection. As with classic antibiotics, continued treatment with AMPs can create resistance in bacteria. However, whether AMPs can generate tolerance as an intermediate stage towards resistance is not known. Here, we show that the treatment of Escherichia coli with different AMPs induces tolerance by lag, particularly for those peptides that have internal targets. This tolerance can be detected as different morphological and physiological changes, which depend on the type of peptide molecule the bacterium has been exposed to. In addition, we show that AMP tolerance can also affect antibiotic treatment. The genomic sequencing of AMP-tolerant strains shows that different mutations alter membrane composition, DNA replication, and translation. Some of these mutations have also been observed in antibiotic-resistant strains, suggesting that AMP tolerance could be a relevant step in the development of antibiotic resistance. Monitoring AMP tolerance is relevant vis-á-vis the eventual therapeutic use of AMPs and because cross-tolerance might favor the emergence of resistance against conventional antibiotic treatments.

Keywords: antimicrobial peptide LL-37; antimicrobial peptides; dermaseptin; pleurocidin; polymyxin B; tolerance.

Figure 1

Periodic incubation of bacteria with AMPs (a) Development of tolerant strains in E. coli against the tested AMPs. Cell cultures were evolved for 10 successive cycles or until resistance was detected (PolB, after 8 cycles) (b) Bacterial survival fraction before and after the assay. Values are shown as the mean ± SEM and individual replicates are displayed. p-values are reported as indicated: *** p < 0.005; **** p < 0.001.

Figure 2

Development of tolerance after AMP treatment. (a) Plate images before and after the first treatment of bacteria with AMPs. (b) Colony area distribution (accumulated in 3 replicates) is shown beside the image plates. Treated and reference means are displayed as dotted lines. (c) Colony appearance times as measured with ScanLag vs. the different AMPs. The vehicle control is displayed for comparison. All experiments were done in triplicate. p-values are reported as indicated: ns: non-significant; **** p < 0.001.

Figure 3

Killing curve assays for evolved strains against all tested AMPs. All combinations for evolved strains and AMPs were tested to detect cross-tolerance. The data are given as the relative surviving bacteria compared to the initial inoculum. Values are shown as the mean ± SEM, and all experiments were performed in triplicates. p-values are reported as indicated: ns: non-significant; * p < 0.05; ** p < 0.01; *** p < 0.005.

Figure 4

Killing curve assays after antibiotic exposure in E. coli strains evolved with Pleu and LL-37. Bacterial viability was measured as the relative number of surviving CFUs compared with the initial inoculum. The concentrations used for each antibiotic were 6.3 µg/mL for ampicillin, 12.5 µg/mL for kanamycin, 0.1 µg/mL for ciprofloxacin, and 20 µg/mL for nalidixic acid. Values are shown as the mean ± SEM, and all experiments were performed in triplicates. p-values are reported as indicated: ns: non-significant; * p < 0.05; ** p < 0.01.