Laboratory of Genetics, Wageningen University & Research, Wageningen, The Netherlands.
Department of Microbial Population Biology, Max Planck Institute for Evolutionary Biology, Plön, Germany.
mBio. 2023 Jun 27;14(3):e0009823. doi: 10.1128/mbio.00098-23. Epub 2023 Apr 27.
Adaptive evolutionary processes are constrained by the availability of mutations which cause a fitness benefit and together make up the fitness landscape, which maps genotype space onto fitness under specified conditions. Experimentally derived fitness landscapes have demonstrated a predictability to evolution by identifying limited "mutational routes" that evolution by natural selection may take between low and high-fitness genotypes. However, such studies often utilize indirect measures to determine fitness. We estimated the competitive fitness of mutants relative to all single-mutation neighbors to describe the fitness landscape of three mutations in a β-lactamase enzyme. Fitness assays were performed at sublethal concentrations of the antibiotic cefotaxime in a structured and unstructured environment. In the unstructured environment, the antibiotic selected for higher-resistance types-but with an equivalent fitness for a subset of mutants, despite substantial variation in resistance-resulting in a stratified fitness landscape. In contrast, in a structured environment with a low antibiotic concentration, antibiotic-susceptible genotypes had a relative fitness advantage, which was associated with antibiotic-induced filamentation. These results cast doubt that highly resistant genotypes have a unique selective advantage in environments with subinhibitory concentrations of antibiotics and demonstrate that direct fitness measures are required for meaningful predictions of the accessibility of evolutionary routes. The evolution of antibiotic-resistant bacterial populations underpins the ongoing antibiotic resistance crisis. We aim to understand how antibiotic-degrading enzymes can evolve to cause increased resistance, how this process is constrained, and whether it can be predictable. To this end, competition experiments were performed with a combinatorially complete set of mutants of a β-lactamase gene subject to subinhibitory concentrations of the antibiotic cefotaxime. While some mutations confer on their hosts high resistance to cefotaxime, in competition these mutations do not always confer a selective advantage. Specifically, high-resistance mutants had equivalent fitnesses despite different resistance levels and even had selective disadvantages under conditions involving spatial structure. Together, our findings suggest that the relationship between resistance level and fitness at subinhibitory concentrations is complex; predicting the evolution of antibiotic resistance requires knowledge of the conditions that select for resistant genotypes and the selective advantage evolved types have over their predecessors.
适应性进化过程受到突变的可用性的限制,这些突变会导致适应度的提高,并共同构成适应度景观,它将基因型空间映射到特定条件下的适应度上。通过识别自然选择进化可能在低适应度和高适应度基因型之间采取的有限“突变途径”,实验得出的适应度景观证明了进化的可预测性。然而,此类研究通常利用间接措施来确定适应度。我们通过比较突变体与所有单突变体邻居的竞争适应度来描述β-内酰胺酶中三个突变的适应度景观。在抗生素头孢噻肟的亚致死浓度下,在结构化和非结构化环境中进行了适应度测定。在非结构化环境中,抗生素选择了更高抗性的类型,但对一部分突变体具有相当的适应度,尽管抗性存在很大差异,导致适应度景观分层。相比之下,在抗生素浓度较低的结构化环境中,抗生素敏感的基因型具有相对的适应度优势,这与抗生素诱导的丝状生长有关。这些结果使人怀疑在亚抑菌浓度的抗生素环境中,高抗性基因型是否具有独特的选择优势,并表明需要直接的适应度测量才能对进化途径的可及性进行有意义的预测。抗生素耐药细菌种群的进化是抗生素耐药性危机持续存在的基础。我们旨在了解抗生素降解酶如何进化以导致更高的抗性,这一过程受到哪些限制,以及它是否具有可预测性。为此,我们对β-内酰胺酶基因的一组组合完整的突变体进行了竞争实验,这些突变体受到抗生素头孢噻肟的亚抑制浓度的影响。虽然一些突变赋予其宿主对头孢噻肟的高抗性,但在竞争中,这些突变并不总是赋予选择优势。具体来说,尽管具有不同的抗性水平,但高抗性突变体具有相当的适应度,甚至在涉及空间结构的条件下具有选择劣势。总之,我们的研究结果表明,在亚抑制浓度下,抗性水平与适应度之间的关系是复杂的;预测抗生素抗性的进化需要了解选择耐药基因型的条件以及进化后的类型相对于其前代的选择优势。