Understanding and targeting non-genetic mechanisms of drug resistance

项目摘要/摘要 耐药性是感染性疾病治疗失败的关键因素之一。因此，克服 抗药性将显著改善患者的预后，并降低医疗成本。广泛的研究 关于耐药的遗传机制的研究揭示了药物是如何通过改变 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能解释了耐药性是如何频繁而迅速地出现的。理解 驱动耐药性演变的非遗传机制可能为耐药性的发展铺平道路 新的治疗策略来对抗抗药性。研究培训计划将利用系统 人类主要真菌病原菌白色念珠菌剖析其分子基础的生物学方法 副耐药，一种非遗传的耐药机制(目标1和2)，并检查临床 靶向副耐药的相关性和治疗潜力(目标3)。在目标1中，申请者林静博士(Lucy) 谢将在K99阶段进行单细胞RNA测序和ODE建模培训，以确定转录 反应和估计与建立副抗性、发育相关的开关频率 一个定量的框架来理解副抵抗是如何建立的。在目标2中，谢博士将在池塘中进行训练 在K99阶段用CRISPRi进行筛选，在R00阶段完成分析，以确定 并确定如何维持参数抵抗。在目标3中，谢博士将确定 收集约1,000株野生白念珠菌的副耐药性，并鉴定其化学调节剂 ~gt；1000个生物活性小分子库中的副耐药研究临床和治疗 副抗性在R00阶段的意义。职业发展计划旨在为谢博士提供 有机会和支持获得单细胞RNA测序和CRISPRI方面的更多专业知识 技术、统计和建模方法，以及额外的专业发展培训 在教学、写作和实验室管理技能方面。导师Daniel Jarosz教授是酵母蛋白方面的一流专家 和非遗传遗传。补充专业知识由共同导师James Ferrell教授提供(量化 生物学)，以及顾问阿米·巴特教授(临床微生物学)和朱迪思·伯曼教授(抗真菌药物耐受性 以及合作者Michael Hallett教授(单细胞技术)和Rebecca Shapiro教授 (CRISPR技术)。斯坦福大学医学院培养了高度合作和支持的 研究环境，并在一个充满活力的科学界内提供出色的基础设施。总而言之， 谢博士将接受高质量的研究和职业发展培训，并准备创办自己的公司 独立研究计划。拟议的研究将提供对非遗传机制的机械性见解。 并建立一个框架，用于开发新的治疗方法，以规避药物 耐药性，对微生物病原体具有重要影响。

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.