Bacterial adaptation to sublethal antibiotic gradients can change the ecological properties of multitrophic microbial communities

Abstract

Antibiotics leak constantly into environments due to widespread use in agriculture and human therapy. Although sublethal concentrations are well known to select for antibiotic-resistant bacteria, little is known about how bacterial evolution cascades through food webs, having indirect effect on species not directly affected by antibiotics (e.g. via population dynamics or pleiotropic effects). Here, we used an experimental evolution approach to test how temporal patterns of antibiotic stress, as well as migration within metapopulations, affect the evolution and ecology of microcosms containing one prey bacterium, one phage and two protist predators. We found that environmental variability, autocorrelation and migration had only subtle effects for population and evolutionary dynamics. However, unexpectedly, bacteria evolved greatest fitness increases to both antibiotics and enemies when the sublethal levels of antibiotics were highest, indicating positive pleiotropy. Crucially, bacterial adaptation cascaded through the food web leading to reduced predator-to-prey abundance ratio, lowered predator community diversity and increased instability of populations. Our results show that the presence of natural enemies can modify and even reverse the effects of antibiotics on bacteria, and that antibiotic selection can change the ecological properties of multitrophic microbial communities by having indirect effects on species not directly affected by antibiotics.

Keywords: defence; diversity; eco-evolutionary dynamics; environmental change; parasitism; predation.

Figure 1.

(a) Bacterial and (b) T. pyriformis ciliate abundances in different experimental treatments. The main effects of experimental factors are depicted on the diagonal, and two-way interactions between different factors below the diagonal. Line colours in interaction panels depict ‘column’ factors, and solid and dashed lines the effect of ‘row’ factor. All lines show ±1 s.e.m.

Figure 2.

(a) Chilomonas paramecium flagellate and (b) phage Phi2 abundances in different experimental treatments. The main effects of experimental factors are depicted on the diagonal, and two-way interactions between different factors below the diagonal. Line colours in interaction panels depict ‘column’ factors, and solid and dashed lines the effect of ‘row’ factor. All lines show ±1 s.e.m.

Figure 3.

Bacterial adaptation to antibiotics. The effect of mean antibiotic (a) concentration, (b) migration, (c) variability and (d) autocorrelation structure for the fitness of evolved bacteria relative to ancestral bacterium. All bars show ±1 s.e.m. These assays were performed at high antibiotic concentration.

Figure 4.

Bacterial adaptation to enemies. (a) Defence evolution against different enemies for bacteria evolved in different antibiotic environments during the selection experiment. (b) Defence evolution against different enemies for bacteria evolved in the absence and presence of migration during the selection experiment. (c) Bacterial cell aggregate formation evolution for bacteria evolved in different antibiotic environments during the selection experiment. (d) Pleiotropic growth cost measured in the absence of enemies and antibiotics for bacteria evolved in different antibiotic environments during the selection experiment. All bars show ±1 s.e.m. In (a,b,d), quantities are relative to the ancestral strain.

Figure 5.

Differences in ecological properties of communities. (a) Predator-to-prey abundance ratio, (b) predator community diversity (alpha diversity, Shannon index) and (c–f) instability of (c) bacterial, (d) T. pyriformis, (e) C. paramecium and (f) phage populations evolved in different antibiotic environment during the selection experiment. AB denotes for antibiotic concentration in panels (a,b) and all bars show ±1 s.e.m.