Parallel Evolution of Tobramycin Resistance across Species and Environments

Abstract

Different species exposed to a common stress may adapt by mutations in shared pathways or in unique systems, depending on how past environments have molded their genomes. Understanding how diverse bacterial pathogens evolve in response to an antimicrobial treatment is a pressing example of this problem, where discovery of molecular parallelism could lead to clinically useful predictions. Evolution experiments with pathogens in environments containing antibiotics, combined with periodic whole-population genome sequencing, can be used to identify many contending routes to antimicrobial resistance. We separately propagated two clinically relevant Gram-negative pathogens, Pseudomonas aeruginosa and Acinetobacter baumannii, in increasing concentrations of tobramycin in two different environments each: planktonic and biofilm. Independently of the pathogen, the populations adapted to tobramycin selection by parallel evolution of mutations in fusA1, encoding elongation factor G, and ptsP, encoding phosphoenolpyruvate phosphotransferase. As neither gene is a direct target of this aminoglycoside, mutations to either are unexpected and underreported causes of resistance. Additionally, both species acquired antibiotic resistance-associated mutations that were more prevalent in the biofilm lifestyle than in the planktonic lifestyle; these mutations were in electron transport chain components in A. baumannii and lipopolysaccharide biosynthesis enzymes in P. aeruginosa populations. Using existing databases, we discovered site-specific parallelism of fusA1 mutations that extends across bacterial phyla and clinical isolates. This study suggests that strong selective pressures, such as antibiotic treatment, may result in high levels of predictability in molecular targets of evolution, despite differences between organisms’ genetic backgrounds and environments. IMPORTANCE The rise of antimicrobial resistance is a leading medical threat, motivating efforts to forecast both its evolutionary dynamics and its genetic causes. Aminoglycosides are a major class of antibiotics that disrupt translation, but resistance may occur by a number of mechanisms. Here, we show the repeated evolution of resistance to the aminoglycoside tobramycin in both P. aeruginosa and A. baumannii via mutations in fusA1, encoding elongation factor G, and ptsP, encoding the nitrogen-specific phosphotransferase system. Laboratory evolution and whole-population genome sequencing were used to identify these targets, but mutations at identical amino acid positions were also found in published genomes of diverse bacterial species and clinical isolates. We also identified other resistance mechanisms associated with growth in biofilms that likely interfere with drug binding or uptake. Characterizing the evolution of multiple species in the presence of antibiotics can identify new, repeatable causes of resistance that may be predicted and counteracted by alternative treatment.

Comparative Evolutionary Patterns of Burkholderia cenocepacia and B. multivorans During Chronic Co-infection of a Cystic Fibrosis Patient Lung

“…It remains important to understand why LPS is under selection in B. cenocepacia or B. multivorans. While the most common explanation invokes selection for immune evasion, it is also possible that LPS modifications are adaptations to biofilm growth (Traverse et al, 2013) or antibiotic resistance (Scribner et al, 2020). Another explanation for loss of OAg is that it increases Bcc survival in phagocytic eukaryotic cells such as amoebae, epithelial cells and human macrophages Kotrange et al, 2011;Maldonado et al, 2016).…”

Adaptation and phenotypic diversification ofBacillus thuringiensis407 biofilm are accompanied by a fuzzy spreader morphotype

“…Since the first report introducing the bead-based experiment evolution setup 24 , which primarily focused on the ecological mechanisms that sustained biofilm diversity, numerous follow-up studies have validated the robustness of this model by describing the mutational patterns 59 , genetic properties 53,[60][61][62][63] , niche complementarity 64,65 , and antibiotic resistance 66,67 . Unlike other laboratory-based experimental evolution systems, this simple method is useful for modelling the complex biofilm cycle, including initial attachment, biofilm maturation, dispersal and recolonization 68,69 .…”

The roles of history, chance, and natural selection in the evolution of antibiotic resistance

“…In contrast, P lines became cross-resistant to CAZ by adeN mutations that regulate the adeIJK complex or pgpB mutations that are also regulated by adeN ( Figure 1D Figure 4B); this gene encodes penicillin binding-protein 2, one of the most common causes of de novo resistance to IMI in clinical isolates (35). Therefore, evolution in b-lactam antibiotics generated parallel evolution regardless of the genetic background (14,15).…”

“…As any other evolved trait, antimicrobial resistance (AMR) is subject to these three evolutionary forces (Box 1). Antibiotics can impose strong selection pressure on microbial populations, leading to highly repeatable evolutionary outcomes (14,15), with the level of parallelism predicted to depend on the strength of antibiotic pressure (16). However, evolutionary history can also alter the distribution of fitness effects of AMR mutations, their mechanisms of action, or their degree of conferred resistance (17).…”