Antimicrobial peptides: Application informed by evolution

Abstract

Antimicrobial peptides (AMPs) are essential components of immune defenses of multicellular organisms and are currently in development as anti-infective drugs. AMPs have been classically assumed to have broad-spectrum activity and simple kinetics, but recent evidence suggests an unexpected degree of specificity and a high capacity for synergies. Deeper evaluation of the molecular evolution and population genetics of AMP genes reveals more evidence for adaptive maintenance of polymorphism in AMP genes than has previously been appreciated, as well as adaptive loss of AMP activity. AMPs exhibit pharmacodynamic properties that reduce the evolution of resistance in target microbes, and AMPs may synergize with one another and with conventional antibiotics. Both of these properties make AMPs attractive for translational applications. However, if AMPs are to be used clinically, it is crucial to understand their natural biology in order to lessen the risk of collateral harm and avoid the crisis of resistance now facing conventional antibiotics.

Fig. 1.. Analyzing and depicting synergism.

(A and B) Synergies between Magainin 2 (M) and PGLa (P) visualized with (A) a zone of inhibition assay and (B) a model of the interaction on the membrane. (A) Identical molar amounts of Magainin 2 and PGLa were applied to a freshly inoculated lawn of E. coli and photographed after a 24-hour incubation at 37°C. The sharp zones of bacterial killing reflect the steep concentration dependence of bactericidal activity. Arrows highlight the zones of activity resulting from synergy. (B) The synergistic interaction between PGLa and Magainin 2. Antiparallel PGLa dimers (red) span the membrane. Magainin 2 monomers (blue) lie on each surface of the membrane and contact each PGLa dimer tail to tail. [Redrawn from (19).]

Fig. 2.. Small evolutionary changes matter.

Small evolutionary changes in amino acid composition of AMPs can have major consequences for host survival during infection (30). In D. melanogaster, different alleles of Diptericin (arginine and serine) show pathogen-specific activity here against P. rettgeri. Lines of D. melanogaster with null alleles (black) show higher mortality than do lines homozygous for arginine (red). Lines homozygous for serine (blue) show the highest survival.

Fig. 3.. Resistance evolution against AMPs.

(A) Pharmacodynamics of AMPs differ from those of conventional antibiotics (63). The solid curved line depicts a susceptible bacterial strain, and the dashed line depicts a resistant strain. The respective MICs are shown at the intersections by the solid horizontal line. The Hill coefficient κ, depicting the slope, represents an antibiotic (top, κ = 1), and κ = 4 represents an AMP (bottom) [values are based on (63); typically κ values are higher for AMPs than for antibiotics]. The dose-response curve for the AMP is correspondingly steeper for an AMP, which results in a narrow mutant selection window (light blue) in which genetically resistant mutants are favored. (B) Combining the pharmacodynamical properties of AMPs and comparing them with those of antibiotics, computer simulations predict a lower probability of resistance evolution against AMPs compared with antibiotics. [Adapted from (81).] (C) Experimental resistance evolution of E. coli against 15 AMPs in vitro yields a significantly lower degree of resistance compared with the results for 12 antibiotics, with the exception of two AMPs. [Data are from (80).]

Fig. 4.. Evolution of AMPs and origin of AMPs as drugs.

(A) The number of AMPs currently undergoing clinical trials [data are from (4)] and the organisms from which they are derived. (B) Relative representation of animal taxa in the antimicrobial peptide database (5). This representation is not correlated with the number of species in each of the groups because, for example, insects are by far the most species-rich taxon.