Dataset Information

Prediction of Antibiotic Resistance Evolution by Growth Measurement of All Proximal Mutants of Beta-Lactamase.

ABSTRACT: The antibiotic resistance crisis continues to threaten human health. Better predictions of the evolution of antibiotic resistance genes could contribute to the design of more sustainable treatment strategies. However, comprehensive prediction of antibiotic resistance gene evolution via laboratory approaches remains challenging. By combining site-specific integration and high-throughput sequencing, we quantified relative growth under the respective selection of cefotaxime or ceftazidime selection in ∼23,000 Escherichia coli MG1655 strains that each carried a unique, single-copy variant of the extended-spectrum β-lactamase gene blaCTX-M-14 at the chromosomal att HK022 site. Significant synergistic pleiotropy was observed within four subgenic regions, suggesting key regions for the evolution of resistance to both antibiotics. Moreover, we propose PEARP and PEARR, two deep-learning models with strong clinical correlations, for the prospective and retrospective prediction of blaCTX-M-14 evolution, respectively. Single to quintuple mutations of blaCTX-M-14 predicted to confer resistance by PEARP were significantly enriched among the clinical isolates harboring blaCTX-M-14 variants, and the PEARR scores matched the minimal inhibitory concentrations obtained for the 31 intermediates in all hypothetical trajectories. Altogether, we conclude that the measurement of local fitness landscape enables prediction of the evolutionary trajectories of antibiotic resistance genes, which could be useful for a broad range of clinical applications, from resistance prediction to designing novel treatment strategies.

SUBMITTER: Feng S

PROVIDER: S-EPMC9087888 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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Prediction of Antibiotic Resistance Evolution by Growth Measurement of All Proximal Mutants of Beta-Lactamase.

Feng Siyuan S Wu Zhuoxing Z Liang Wanfei W Zhang Xin X Cai Xiujuan X Li Jiachen J Liang Lujie L Lin Daixi D Stoesser Nicole N Doi Yohei Y Zhong Lan-Lan LL Liu Yan Y Xia Yong Y Dai Min M Zhang Liyan L Chen Xiaoshu X Yang Jian-Rong JR Tian Guo-Bao GB

Molecular biology and evolution 20220501 5

The antibiotic resistance crisis continues to threaten human health. Better predictions of the evolution of antibiotic resistance genes could contribute to the design of more sustainable treatment strategies. However, comprehensive prediction of antibiotic resistance gene evolution via laboratory approaches remains challenging. By combining site-specific integration and high-throughput sequencing, we quantified relative growth under the respective selection of cefotaxime or ceftazidime selection ...[more]

PMID: 35485492

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Project description: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. 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, 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.

Project description:Extended-spectrum beta-lactamases (ESBL) constitute a key antibiotic-resistance mechanism affecting Gram-negative bacteria, and also an excellent model for studying evolution in real time. A shift in the epidemiology of ESBLs is being observed, which is characterized by the explosive diversification and increase in frequency of the CTX-M-type beta-lactamases in different settings. This provides a unique opportunity for studying a protein evolutionary radiation by the sequential acquisition of specific mutations enhancing protein efficiency and fitness concomitantly. The existence of driver antibiotic molecules favoring protein divergence has been investigated by combining evolutionary analyses and experimental site-specific mutagenesis. Phylogenetic reconstruction with all the CTX-M variants described so far provided a hypothetical evolutionary scenario showing at least three diversification events. CTX-M-3 was likely the enzyme at the origin of the diversification in the CTX-M-1 cluster, which was coincident with positive selection acting on several amino acid positions. Sixty-three CTX-M-3 derivatives containing all combinations of mutations under positively selected positions were constructed, and their phenotypic efficiency was evaluated. The CTX-M-3 diversification process can only be explained in a complex selective landscape with at least two antibiotics (cefotaxime and ceftazidime), indicating the need to invoke mixtures of selective drivers in order to understand the final evolutionary outcome. Under this hypothesis, we found congruent results between the in silico and in vitro analyses of evolutionary trajectories. Three pathways driving the diversification of CTX-M-3 towards the most complex and efficient variants were identified. Whereas the P167S pathway has limited possibilities of further diversification, the D240G route shows a robust diversification network. In the third route, drift may have played a role in the early stages of CTX-M-3 evolution. Antimicrobial agents should not be considered only as selectors for efficient mechanisms of resistance but also as diversifying agents of the evolutionary trajectories. Different trajectories were identified using a combination of phylogenetic reconstructions and directed mutagenesis analyses, indicating that such an approach might be useful to fulfill the desirable goal of predicting evolutionary trajectories in antimicrobial resistance.

Dataset Information

Prediction of Antibiotic Resistance Evolution by Growth Measurement of All Proximal Mutants of Beta-Lactamase.

Publications

Prediction of Antibiotic Resistance Evolution by Growth Measurement of All Proximal Mutants of Beta-Lactamase.

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