Lasek-Nesselquist Erica, Lu Jackson, Schneider Ryan, Ma Zhuo, Russo Vincenzo, Mishra Smruti, Pai Manjunath P, Pata Janice D, McDonough Kathleen A, Malik Meenakshi
Wadsworth Center, New York State Department of Health, Albany, NY, United States.
Albany College of Pharmacy and Health Sciences, Albany, NY, United States.
Front Microbiol. 2019 Feb 28;10:345. doi: 10.3389/fmicb.2019.00345. eCollection 2019.
The extensive use of daptomycin for treating complex methicillin-resistant infections has led to the emergence of daptomycin-resistant strains. Although genomic studies have identified mutations associated with daptomycin resistance, they have not necessarily provided insight into the evolution and hierarchy of genetic changes that confer resistance, particularly as antibiotic concentrations are increased. Additionally, plate-dependent analyses that passage bacteria in the presence of antibiotics can induce selective pressures unrelated to antibiotic exposure. We established a continuous culture bioreactor model that exposes strain N315 to increasing concentrations of daptomycin without the confounding effects of nutritional depletion to further understand the evolution of drug resistance and validate the bioreactor as a method that produces clinically relevant results. Samples were collected every 24 h for a period of 14 days and minimum inhibitory concentrations were determined to monitor the acquisition of daptomycin resistance. The collected samples were then subjected to whole genome sequencing. The development of daptomycin resistance in N315 was associated with previously identified mutations in genes coding for proteins that alter cell membrane charge and composition. Although genes involved in metabolic functions were also targets of mutation, the common route to resistance relied on a combination of mutations at a few key loci. Tracking the frequency of each mutation throughout the experiment revealed that mutations need not arise progressively in response to increasing antibiotic concentrations and that most mutations were present at low levels within populations earlier than would be recorded based on single-nucleotide polymorphism (SNP) filtering criteria. In contrast, a serial-passaged population showed only one mutation in a gene associated with resistance and provided limited detail on the changes that occur upon exposure to higher drug dosages. To conclude, this study demonstrates the successful modeling of antibiotic resistance in a bioreactor and highlights the evolutionary paths associated with the acquisition of daptomycin non-susceptibility.
达托霉素在治疗复杂性耐甲氧西林感染中的广泛使用导致了耐达托霉素菌株的出现。尽管基因组研究已经确定了与达托霉素耐药性相关的突变，但它们不一定能深入了解赋予耐药性的遗传变化的演变和层次结构，尤其是在抗生素浓度增加的情况下。此外，在抗生素存在下传代细菌的平板依赖性分析可能会诱导与抗生素暴露无关的选择压力。我们建立了一个连续培养生物反应器模型，将N315菌株暴露于浓度不断增加的达托霉素中，而不会受到营养耗竭的混杂影响，以进一步了解耐药性的演变，并验证该生物反应器作为一种能产生临床相关结果的方法。在14天的时间里，每24小时收集一次样本，并测定最低抑菌浓度，以监测达托霉素耐药性的获得情况。然后对收集的样本进行全基因组测序。N315中达托霉素耐药性的发展与先前确定的编码改变细胞膜电荷和组成的蛋白质的基因突变有关。虽然参与代谢功能的基因也是突变的靶点，但耐药的常见途径依赖于几个关键位点的突变组合。在整个实验过程中追踪每个突变的频率发现，突变不一定会随着抗生素浓度的增加而逐渐出现，而且大多数突变在群体中的水平在早期就很低，比基于单核苷酸多态性（SNP）筛选标准记录的要早。相比之下，连续传代的群体在与耐药性相关的基因中只显示出一个突变，并且在接触更高剂量药物时发生的变化方面提供的细节有限。总之，这项研究证明了在生物反应器中成功模拟抗生素耐药性，并突出了与获得达托霉素不敏感性相关的进化路径。
