Understanding and targeting non-genetic mechanisms of drug resistance

项目总结/摘要 耐药性是导致感染性疾病治疗失败的关键因素之一。因此，克服 耐药性将显著改善患者的预后并降低医疗保健成本。广泛的研究 关于耐药性的遗传机制的研究揭示了药物是如何通过改变细胞内的 DNA序列然而，新出现的证据表明，非遗传机制，如染色质-和 基于蛋白质的表观遗传状态可以解释耐药性如何频繁和迅速地出现。理解 驱动耐药性进化的非遗传机制可能为开发 新的治疗策略来对抗耐药性。研究培训计划将利用系统 人类主要真菌病原体白色念珠菌的生物学方法来剖析分子基础 副耐药，耐药的非遗传机制（目的1和2），并检查临床 靶向副抵抗的相关性和治疗潜力（目的3）。在目标1中，申请人林静博士（露西） Xie将在K99阶段进行单细胞RNA测序和ODE建模培训，以确定转录 响应和估计开关频率与建立pararesistance，发展 一个量化的框架来理解pararesistance是如何建立的。在目标2中，谢博士将在 在K99阶段用CRISPRi进行筛选，并在R 00阶段完成分析，以确定 pararesistance并确定pararesistance是如何维持的。在目标3中，谢博士将确定 1,000株野生C.白色念珠菌的分离和鉴定的化学调节剂 在> 1，000个生物活性小分子的文库中进行副抵抗，以研究临床和治疗 在R 00阶段的副抵抗的影响。职业发展计划旨在为谢博士提供 有机会和支持，以获得更多的专业知识，在单细胞RNA测序和CRISPRi 技术、统计和建模方法，以及额外的专业发展培训 教学写作和实验室管理技能导师教授丹尼尔Jarosz是一个领先的专家在酵母朊病毒 和非基因遗传。互补的专业知识由共同导师James Ferrell教授（定量 Ami Bhatt教授（临床微生物学）和Judith Berman教授（抗真菌药物耐受性 和阻力），以及合作者教授迈克尔Hallett（单细胞技术）和教授丽贝卡夏皮罗 （CRISPR技术）。斯坦福大学医学院培养了一个高度协作和支持的 研究环境，并在充满活力的科学界提供优良的基础设施。总的来说， 博士谢将接受高质量的研究和职业发展培训，并准备推出自己的 独立研究计划。拟议中的研究将提供对非遗传机制的机械见解 并建立一个框架来开发新的治疗方法， 耐药性，对微生物病原体具有重要意义。

PROJECT SUMMARY/ABSTRACT Drug resistance is one of the key contributing factors to treatment failure in infectious disease. Thus, overcoming drug resistance would significantly improve patient outcome and reduce healthcare costs. Extensive research on genetic mechanisms of drug resistance have revealed how drugs are rendered ineffective via changes in the DNA sequence. However, emerging evidence suggest that non-genetic mechanisms such as chromatin- and protein-based epigenetic states may explain how drug resistance arises frequently and rapidly. Understanding the non-genetic mechanisms that drive the evolution of drug resistance could pave the way for the development of novel therapeutic strategies to combat drug resistance. The Research Training Plan will leverage systems biology approaches in a leading human fungal pathogen Candida albicans to dissect the molecular underpinning of pararesistance, a non-genetic mechanism of drug resistance (Aims 1 and 2) and examine the clinical relevance and therapeutic potential of targeting pararesistance (Aim 3). In Aim 1, the applicant Dr. Jing Lin (Lucy) Xie will train in single-cell RNA sequencing and ODE modeling in the K99 phase to identify the transcriptional response and estimate the switching frequency associated with the establishment of pararesistance, developing a quantitative framework to understand how pararesistance is established. In Aim 2, Dr. Xie will train in pooled screen with CRISPRi in the K99 phase and complete the analysis in R00 phase to identify regulators of pararesistance and determine how pararesistance is maintained. In Aim 3, Dr. Xie will establish the prevalence of pararesistance in a collection of ~1,000 wild C. albicans isolates and identify chemical modulators of pararesistance in a library of >1,000 bioactive small molecules to investigate the clinical and therapeutic implications of pararesistance in the R00 phase. The Career Development Plan is designed to provide Dr. Xie with the opportunity and support to acquire additional expertise in single-cell RNA-sequencing and CRISPRi technologies and statistical and modeling methodologies, as well as additional professional development training in teaching, writing, and lab management skills. Mentor Prof. Daniel Jarosz is a leading expert in yeast prions and non-genetic inheritance. Complementary expertise is offered by co-mentor Prof. James Ferrell (quantitative biology), and advisors Prof. Ami Bhatt (clinical microbiology) and Prof. Judith Berman (antifungal drug tolerance and resistance), and collaborators Prof. Michael Hallett (single-cell technologies) and Prof. Rebecca Shapiro (CRISPR technologies). The Stanford University School of Medicine fosters a highly collaborative and supportive research environment and provides excellent infrastructures within a vibrant scientific community. In summary, Dr. Xie will receive high-quality training in research and career development, and is poised to launch her own independent research program. The proposed studies will offer mechanistic insight into non-genetic mechanisms of drug resistance and establish a framework for developing novel therapeutics that would circumvent drug resistance, with important implications for microbial pathogens.