{'fraction_non_alphanumeric': 0.01716581446311176, 'fraction_numerical': 0.0003652300949598247, 'mean_word_length': 5.951776649746193, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
The fitness landscape of TEM-1 β-lactamase is stratified and inverted by sublethal concentrations of cefotaxime

Adaptive evolutionary processes are constrained by the availability of mutations which cause a fitness benefit – a concept that may be illustrated by ‘fitness landscapes’ which map the relationship of genotype space with fitness. Experimentally derived 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 utilise indirect measures to determine fitness. We estimated the competitive fitness of each mutant relative to all of its single-mutation neighbours to describe the fitness landscape of three mutations in a β-lactamase enzyme at sub-lethal concentrations of the antibiotic cefotaxime in a structured and unstructured environment. We found that in the unstructured environment the antibiotic selected for higher-resistance types – but with an equivalent fitness for subsets of mutants, despite substantial variation in resistance – resulting in a stratified fitness landscape. In contrast, in a structured environment with 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 sub-inhibitory concentrations of antibiotics, and demonstrate that direct fitness measures are required for meaningful predictions of the accessibility of evolutionary routes. Importance 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 we performed competition experiments with a combinatorially-complete set of mutants of a β-lactamase gene subject to sub-inhibitory concentrations of the antibiotic cefotaxime. While some mutants confer their hosts with high resistance to cefotaxime, in competition these mutants do not always confer a selective advantage. Similarly, we identified conditions involving spatial structure where mutations causing high resistance result in a selective disadvantage. Together, this work suggests that the relationship between resistance level and fitness at sub-inhibitory 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.