Automated and sensitive genomic co-profiling for precision pharmacogenomics

项目总结/摘要 基因组学方法，如表达谱分析和表观基因组谱分析具有巨大的潜在优势， 药物的影响并评估患者对临床治疗的反应。然而，缺乏先进的 样品制备方法是将信息性基因组技术应用于 化学生物学和临床医学。即使是先进的单细胞基因组学方法也需要大量的总投入 数量和努力产生一种以上的基因组图谱，这可能不足以 信息性或预测性。强大的计算工具，以整合多层次的`组学信息是 如果可以从正确的样本中获得数据，因此，需要准备多个 序列库类型在同一时间（如共分析表观基因组和转录组）从少数 单一流线型系统中的原代细胞是化学生物学发展中关键的缺失环节 并意识到基因组医学的潜在影响。该项目将解决这个问题。 通过建立同时的表观基因组和表达共分析样品的制备挑战 在自动化微流体装置中从低生物量样品制备方法。共同特征分析样本 制备系统将构成能够接受小的多个原代细胞样品的单个微型装置， 在一次运行中自动产生多种序列库类型。我们将应用这种能力来剖析 组蛋白去乙酰化酶抑制剂（HDACi）是一类重要的新药。HDACi具有 （目前）对基因活性的不可预测的影响，但显示出对增殖， 炎症、自身免疫和神经过程。评价潜在的治疗效果和安全性 为了评估HDACi治疗的免疫性（关于对感染的免疫性），我们将共同分析HDACi处理的人原代细胞。

Project Summary/Abstract Genomics methods like expression profiling and epigenomic profiling hold enormous potential benefit to parse the effects of drugs and assess patient response to therapy in the clinic. However, the lack of advanced sample preparation methods is a blocking issue in translating informative genomic techniques for application in chemical biology and clinical medicine. Even advanced single-cell genomics methods require large total input quantities and struggle to produce more than one type of genomic profile, which may not be sufficiently informative or predictive. Powerful computational tools to integrate multiple layers of `omic information are available and ready to accept data if available from the right samples. Thus, the need to prepare multiple sequence library types at the same time (eg co-profiling epigenome and transcriptome) from small numbers of primary cells in a single streamlined system is a crucial missing link in the advancement of chemical biology and realizing the potential impact of genomic medicine. The proposed project will solve this sample preparation challenge by establishing simultaneous epigenomic and expression co-profiling sample preparation method from low biomass samples in an automated microfluidic device. The co-profiling sample preparation system will constitute a single microdevice able to accept small multiple primary cell samples and automatically produce multiple sequence library types in a single run. We will apply this capability to dissect the pleiotropic effects of an important new drug class, histone deacetylase inhibitors (HDACi). HDACi have (currently) unpredictable effects on gene activity, but show promise for therapeutic modulation of proliferative, inflammatory, autoimmune, and neurological processes. To evaluate potential therapeutic effects and safety (regarding immunity to infection) of HDACi treatment, we will co-profile HDACi-treated human primary cells.