Evolution of drug resistance in Candida glabrata

项目摘要/摘要 慢性或急性感染的发病率和进展反映了进化过程，在这个过程中 病原体与人类宿主进行军备竞赛。虽然疫苗和抗生素使人类 为了扭曲这场竞争的结果，这些抵御传染的堡垒正在被侵蚀。突变与自然 选择，再加上快速的世代时间和巨大的种群规模，似乎给了病原体 在进化竞赛中取得决定性优势。为了重新占据上风，我们必须制定新的治疗策略。 这最好考虑到我们的武器是如何工作的，以及病原体是如何适应性地进化来颠覆它们的。 真菌感染造成了巨大的疾病负担：浅表真菌感染影响多达25%的 全世界每年都会发生200万例侵袭性真菌感染。年的死亡率 侵袭性真菌感染居高不下(20-95%)，其发病率和经济成本都在增加。特别的 令人担忧的是，对抗真菌药物的耐药性正在上升，临床分离株越来越多地显示出 多药耐药。为了合理地改进序贯和联合药物治疗，至关重要的是我们 了解抗真菌药物产生耐药性的方式，以及对其中一种药物的耐药性程度 药物可能会增加或降低对另一种药物的敏感性。 我们提出了三个特定的目标来捕获人类真菌病原体光滑假丝酵母的“抵抗组”。 首先，我们将介绍我们之前开发的基于DNA条形码的血统跟踪的修改版本 系统进入光肩星天牛，然后在四个物种存在的情况下实验性地进化条形码光肩星天牛种群。 代表所有四种主要抗真菌药物类别的不同抗真菌药物。第二，我们将隔离数百人 这些进化实验中的每个适应性谱系，然后在存在的情况下重新测量它们的适合度 以及这些抗真菌药物的缺乏症。这将使我们能够生成一幅精细分辨率的 在特定的抗性选择下产生的突变所产生的权衡和交叉抗性 毒品。最后，我们将对一千多个这些耐药突变体进行全基因组测序， 测量每种药物的最低抑菌浓度(MIC)，生成高分辨率MAP 这描述了基因、健康状况和药物敏感性之间的关系。完成这些目标将 导致有史以来产生的最全面的抗真菌耐药性突变的收集，为此，我们将 知道突变的身份及其在多种药物存在时的适合性后果。我们的数据 将为所有类别的抗真菌药物产生耐药性的机制提供前所未有的洞察力 根据观察到的交叉耐药模式，可用于改进治疗策略的药物 和权衡。我们收集的条形码突变体将打开研究耐药的大门 多药和序贯药物选择，并作为筛选小分子文库的工具 药物发现方面的成就。

Project Summary/Abstract The incidence and progression of chronic or acute infections reflect evolutionary processes, in which pathogens engage in an arms race with their human hosts. While vaccines and antibiotics have enabled mankind to skew the outcome of this contest, these bulwarks against contagion are being eroded. Mutation and natural selection, coupled with rapid generation times and immense population sizes, appear to give pathogens a decisive edge in the evolutionary contest. To regain the upper hand, we must devise new therapeutic strategies that better take into account how our weapons work and how pathogens adaptively evolve to subvert them. Fungal infections impose an enormous disease burden: superficial fungal infections affect as much as 25% of the human population, while each year >2,000,000 invasive fungal infections occur worldwide. Mortality rates for invasive fungal infections are high (20-95%), and their incidence and economic cost are increasing. Of particular concern is the fact that resistance to antifungal drugs is on the rise, with clinical isolates increasingly showing multidrug resistance. To rationally improve upon sequential and combination drug therapies, it is crucial that we understand the ways in which resistance to antifungal drugs arises, and the degree to which resistance to one drug may increase or decrease susceptibility to another. We propose three Specific Aims to capture the “resistome” of the human fungal pathogen, Candida glabrata. First, we will introduce a modified version of our previously developed DNA-barcode based lineage tracking system into C. glabrata, then experimentally evolve barcoded C. glabrata populations in the presence of four different antifungal agents representing all four major antifungal drug classes. Second, we will isolate hundreds of adaptive lineages from each of these evolution experiments then remeasure their fitnesses in the presence and absence of each of these antifungal drugs. This will enable us to generate a finely resolved picture of the trade-offs and cross-resistance conferred by mutations that arise under selection for resistance to a particular drug. Finally, we will whole genome sequence more than a thousand of these drug-resistant mutants, and measure for each the minimum inhibitory concentration (MIC) for each drug, generating a high-resolution map that describes the relationship between genotype, fitness and drug susceptibility. Completion of these Aims will result in the most comprehensive collection of antifungal resistance mutants ever generated, for which we will know the identities of the mutations and their fitness consequences in the presence of multiple drugs. Our data will provide unprecedented insight into the mechanisms by which resistance arises to all classes of antifungal drugs, which can be used to improve therapeutic strategies, based on the observed patterns of cross-resistance and trade-offs. Our collection of barcoded mutants will open the door to investigation of drug resistance under multi-drug and sequential drug selections and serve as a tool to screen small molecule libraries for the purpose of drug discovery.