Non-target analysis of maternal and cord blood samples: Advancing computational tools and discovering novel chemicals

项目概要/摘要 非靶向分析（NTA）提供了一种全面的方法来分析环境和生物 几乎所有化学品的样品。尽管NTA最近取得了进展，但确认的人数 与检测到的特征的数量相比，具有分析标准的化学品仍然相当少。那里 因此，需要进一步开发计算工具，以获得更多的化学结构，并充分利用 人力资源管理系统的潜力。提高我们推导出更多化学结构的能力将使我们能够发现新的化学结构。 人类接触的工业化学品，特别是在发展的关键时期， 怀孕它还将使发现内源性产生的代谢物，可能与 重要的生物学结果，如早产。我的建议的目的是开发新的 计算方法，以显着提高我们的能力，分析和解释非目标分析数据 高分辨率质谱（HRMS），并将其应用于研究产前暴露于工业 来自北方加州的一个大的孕妇队列中的化学物质和内源性代谢物。我 该提案基于我在分析和环境化学方面的专业知识，以及我目前的博士后工作经验， 在计算化学和人体暴露应用方面的经验。我寻求额外的培训， 开发和应用创新的计算方法，以更好地描述人类的麻烦， 特别是早产的烦恼。我的提案的贡献有两个方面：（1）发展小说 基于MS数据和物理化学的HRMS数据集的计算结构预测算法 性质（有机溶剂和水之间的平衡分配比，例如，辛醇/水， 氯苯/水、乙醚/水等）(Aim 1）并应用它们来推导潜在的结构， 在来自340名母亲和340名匹配的脐带血样本的HRMS数据集中检测到的化学特征， 补充通过MS/MS和分析标准确定的数量有限的化学品（目标2）;以及 (2)利用分子相互作用研究早产中代谢组和代谢组之间的相互作用 网络可视化和比较工业化学品和内源性之间的分子相互作用 代谢物在早产和足月分娩之间存在差异（目标3）。K99培训将扩展我之前的研究 通过课程工作，研究学徒，和指导阅读的经验，与具体的培训：（1） 先进的分析技能，包括组学数据分析，机器学习和生物统计学;（2）流行病学， 风险评估，人类暴露于化学应激源;（3）人类妊娠和发育。的 在这个奖项获得的技能是至关重要的，我的长期目标，以推进计算方法，以更好地 分析和解释非目标分析数据，以支持更好地表征人类疾病组的工作。 这项工作将产生新的科学知识，大大促进对影响的理解。 环境暴露对健康产生不利影响，特别是早产。

PROJECT SUMMARY/ABSTRACT Non-targeted analysis (NTA) provides a comprehensive approach to analyze environmental and biological samples for nearly all chemicals present. Despite the recent advancements in NTA, the number of confirmed chemicals with analytical standards remains fairly small compared to the number of detected features. There is, thus, a need to further develop computational tools to derive more chemical structures and leverage the full potential of HRMS. Enhancing our ability to derive more chemical structures will enable the discovery of new industrial chemicals that humans are exposed to, especially in critical windows of development, such as pregnancy. It will also enable the discovery of endogenously produced metabolites that may be related to biological outcomes of importance, such as preterm birth. The objective of my proposal is to develop novel computational methods to significantly advance our ability to analyze and interpret non-targeted analysis data from high-resolution mass spectrometry (HRMS) and apply them to study prenatal exposures to industrial chemicals and endogenous metabolites in a large cohort of pregnant women from Northern California. My proposal builds on my expertise in analytical and environmental chemistry and my current postdoctoral experience in computational chemistry and applications in human exposure. I seek additional training to develop and apply innovative computational methods to better characterize the human exposome and in particular the exposome of preterm birth. The contribution of my proposal will be two-fold: (1) developing novel computational structure-prediction algorithms for HRMS datasets based on MS data and physicochemical properties (equilibrium partition ratios between organic solvents and water, e.g., octanol/water, chlorobenzene/water, diethyl ether/water etc.) (Aim 1) and apply them to derive potential structures for chemical features detected in a HRMS dataset from 340 maternal and 340 matched cord blood samples to complement the limited number of chemicals identified through MS/MS and analytical standards (Aim 2); and (2) study the interplay between the exposome and the metabolome in preterm birth using molecular interaction networks to visualize and compare how molecular interactions between industrial chemicals and endogenous metabolites differ between preterm and full-term birth (Aim 3). The K99 training will expand my prior research experience through coursework, research apprenticeship, and mentored reading, with specific training in: (1) advanced analytical skills including -omics data analysis, machine learning, and biostatistics; (2) epidemiology, risk assessment, human exposure to chemical stressors; and (3) human pregnancy and development. The skills acquired during this award are critical to my long-term goal to advance computational methods to better analyze and interpret non-targeted analysis data to support efforts to better characterize the human exposome. This work will produce new scientific knowledge to greatly advance the understanding of the influence of environmental exposures in the development of adverse health outcomes and in particular, preterm birth.