RoL: FELS: EAGER Rules of lifespan determination and buffering from lifelong spatiotemporal activity of key aging pathways.

RoL：FELS：EAGER 寿命确定规则和关键衰老途径的终生时空活动的缓冲。

• 批准号: 1838314
• 负责人: Adriana San Miguel
• 金额: $ 30万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-15 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1838314&HistoricalAwards=false
• 关键词: RoL; FELS; EAGER; Rules; lifespan

This project will develop tools and data necessary to accurately predict lifespan from the activity of genes that respond to environmental conditions such as food intake or stress exposure. It is not fully understood how genes and the environment determine an individual's specific longevity outcome. For example, it is known that calorie reduction or reduction in oxidative stress can lead to increased longevity, but precisely predicting longevity from this information alone is not possible. Given the difficulties of studying aging in humans, the roundworm, Caenorhabditis elegans, will be used as a model to link the activity of specific genes known to affect aging. A mathematical model of the relationship between environment, genes, and longevity will be generated to reveal which genes and environments are most important in determining aging and longevity and to enable the prediction of lifespan. This information will be used in future work that focuses on whether these predictions can be extended to other organisms, and ultimately to humans. Through this work, two graduate students and one postdoctoral researcher will receive interdisciplinary training. In addition, this project will support a Latinx-directed STEM initiative for high-school students.The project's main goal is to develop an experimental and analytical pipeline that will enable the establishment of rules of lifespan determination in the model organism Caenorhabditis elegans. Mathematical and statistical models that can predict lifespan of an individual based on lifelong activity of key aging pathways will be developed. The research tests whether variability in activity of key genes (due to biological noise or environmental or genetic perturbations) is propagated to variability in lifespan. To address this question, a microfluidic platform that enables monitoring of multiple individuals throughout their lifespan, while quantifying the activity of key aging pathways through endogenous fluorescent reporters, will be developed. The proposed platform will allow data pairing, where gene activity at the single individual level can be paired with its lifespan. Experimental tools that enable simultaneous quantitative analysis of in vivo gene activity and combinatorial environmental perturbations will be developed. These tools hinge on microfluidics, computer vision, automation, and new reporter strains engineered by CRISPR to track gene activity under endogenous regulatory control. The acquired data sets will be used to derive data-driven mathematical models that describe the stochastic dynamics of gene activity and its downstream phenotypic outcome: lifespan. Novel statistical techniques will be combined with mathematical models to infer phenotypic heterogeneity and robustness within populations. Interdisciplinary training will be provided to two graduate students and one postdoctoral researcher, and the award will support an educational program directed at broaden participation of Latinx high-school students in science.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目将开发必要的工具和数据，以便根据对食物摄入或压力暴露等环境条件作出反应的基因活动准确预测寿命。基因和环境如何决定一个人的具体寿命结果还没有完全了解。例如，已知卡路里减少或氧化应激减少可导致寿命延长，但仅从该信息精确预测寿命是不可能的。考虑到研究人类衰老的困难，蛔虫，秀丽隐杆线虫，将被用作模型，以联系已知影响衰老的特定基因的活性。将生成环境、基因和寿命之间关系的数学模型，以揭示哪些基因和环境在决定衰老和寿命方面最重要，并能够预测寿命。这些信息将用于未来的工作，重点是这些预测是否可以扩展到其他生物，并最终扩展到人类。通过这项工作，两名研究生和一名博士后研究员将接受跨学科的培训。此外，该项目还将支持一项针对高中生的拉丁语指导的STEM倡议，该项目的主要目标是开发一个实验和分析管道，以便能够建立模式生物秀丽隐杆线虫的寿命确定规则。将开发数学和统计模型，根据关键衰老途径的终身活动预测个人的寿命。该研究测试了关键基因活性的变异性（由于生物噪音或环境或遗传干扰）是否会传播到寿命的变异性。为了解决这个问题，将开发一种微流体平台，该平台能够在其整个生命周期中监测多个个体，同时通过内源性荧光报告分子量化关键衰老途径的活性。拟议的平台将允许数据配对，其中单个个体水平的基因活性可以与其寿命配对。将开发能够同时定量分析体内基因活性和组合环境扰动的实验工具。这些工具依赖于微流体、计算机视觉、自动化和由CRISPR工程化的新报告菌株，以跟踪内源性调控控制下的基因活性。所获得的数据集将用于推导数据驱动的数学模型，该模型描述基因活性的随机动态及其下游表型结果：寿命。新的统计技术将与数学模型相结合，以推断群体内的表型异质性和稳健性。该奖项将为两名研究生和一名博士后研究员提供跨学科培训，并将支持一项旨在扩大拉丁裔高中学生参与科学的教育计划。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Numerical Approaches to Division and Label Structured Population Models

划分和标记结构化总体模型的数值方法

• 发表时间: 2020
• 期刊: Letters in biomathematics
• 作者: Santiago, Fabian;Flores, Kevin B.;Sindi, Suzanne S.
• 通讯作者: Sindi, Suzanne S.

Learning partial differential equations for biological transport models from noisy spatio-temporal data

• DOI: 10.1098/rspa.2019.0800
• 发表时间: 2020-02-26
• 期刊: PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
• 影响因子: 3.5
• 作者: Lagergren, John H.;Nardini, John T.;Flores, Kevin B.
• 通讯作者: Flores, Kevin B.