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URoL:EN: A non-parametric framework to understand emergent behaviors of microbial consortia

URoL:EN：理解微生物群落紧急行为的非参数框架

基本信息

批准号：
2222403
负责人：
Yinjie Tang
金额：
$ 294.63万
依托单位：
Washington University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-10-01 至 2027-09-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2222403&HistoricalAwards=false
关键词：
URoL EN non parametric framework

项目摘要

The goal of this project is to develop a new framework to better understand the emergent behaviors of microbial consortia. Emergent behavior is defined as a system’s behavior that arises from the interactions between its individual parts and that cannot easily be predicted by the behavior of these individual parts. For example, researchers found that when subjected to antibiotics, the overall population consisting of both resistant and non-resistant cells grows faster than the individual resistant mutants. Because such behaviors cannot easily be extrapolated from that of individual parts of a system, their study has been based on observation rather than prediction. This project will provide a novel framework to predict emergent survival properties of a synthetic community consisting of individual microbial specialists or generalists that are designed to degrade specific toxic aromatic compounds. This interdisciplinary research is innovative and will advance our knowledge on emergent behaviors of complex living communities. This innovative project will also bring broader impacts to the global synthetic biology community, microbiome scientists, mathematics experts, relevant industry, and future generations. In addition, the team will engage the research community through Synthetic Biology Young Speaker Series, a weekly, virtual, and multi-year forum where a global thought leader gives an opening 5 min talk, followed by a 45 min, rising star’s talk, for 1,000 global audiences. Furthermore, the project will increase K-12 students’ participation in STEM education, focusing on the St. Louis area where most of the K-12 students are underrepresented students. Through these activities, this project will nurture our future leaders in the converging field of research and industry to sustainably meet global chemical and energy demands and address climate crisis issues.This project will use diverse interdisciplinary approaches to develop a non-parametric estimation framework as follows. First, the team will rationally design and create microbial strains that can degrade a specific set of model lignin breakdown products. Second, the team will develop generalizable tools for statistical inferences, including tools for mean function estimation, simultaneous confidence band construction, estimation of joint effects, and breakpoint estimation. Third, the team will perform carefully-designed microbial community assembly and adaptive evolution. From these efforts, the project will generate new quantitative insights into emergent survival properties in synthetic microbial consortia and provide reusable tools for rigorous inferences of emergent properties in various microbial consortia. This project has huge impacts on the scientific community and society thanks to the following reasons. First, the developed framework is generalizable because it does not rely on specific function forms and parameters. Second, the rational and iterative approach of strain design, building, and testing will validate the putative gene functions, filling the critical knowledge gaps. Notably, this work will expand our understanding of the regulatory network controlling aromatic compound catabolism in Rhodococcus opacus, with broad applicability to related organisms. Third, the integrated approach will generate quantitative insights into community assembly and functional redundancy in consortia of rationally constructed organisms. Last, the parallel evolution experiments will also generate insights into evolutionary processes of collective systems and their two forces: robustness and adaptability. Using diverse microbial consortia as model systems, the team will provide the insights into the complex evolution process, enabling quantitative analysis of robustness and adaptability of collective systems. This project will also train graduate students and postdoctoral researchers in an interdisciplinary manner, enabling unique training of the future workforce and educators in chemical engineering, synthetic biology, microbial ecology, and mathematics.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.

该项目的目标是开发一个新的框架，以更好地了解微生物聚生体的涌现行为。涌现行为被定义为一个系统的行为，它产生于其各个部分之间的相互作用，并且不能轻易地通过这些单独部分的行为来预测。例如，研究人员发现，当使用抗生素时，由耐药细胞和非耐药细胞组成的总体群体比单个耐药突变体生长得更快。因为这些行为不能轻易地从系统的各个部分推断出来，所以他们的研究是基于观察而不是预测。该项目将提供一个新的框架来预测由单个微生物专家或通才组成的合成群落的紧急生存特性，这些微生物专家或通才旨在降解特定的有毒芳香族化合物。这种跨学科的研究是创新的，将推进我们对复杂生活社区的涌现行为的认识。这一创新项目还将为全球合成生物学界、微生物组科学家、数学专家、相关行业和子孙后代带来更广泛的影响。此外，该团队将通过合成生物学青年演讲者系列活动与研究界互动，这是一个每周一次的虚拟多年论坛，全球思想领袖将为1,000名全球观众进行5分钟的开场演讲，然后是45分钟的冉冉升起的星星演讲。此外，该项目将增加K-12学生对STEM教育的参与，重点是圣路易斯地区，大多数K-12学生都是代表性不足的学生。通过这些活动，本项目将培养我们未来在研究和工业融合领域的领导者，以可持续地满足全球化学和能源需求，并解决气候危机问题。本项目将使用多种跨学科方法，开发非参数估计框架，如下所示。首先，该团队将合理设计和创建可以降解一组特定模型木质素分解产物的微生物菌株。其次，该团队将开发用于统计推断的通用工具，包括均值函数估计、同时置信带构建、联合效应估计和断点估计工具。第三，该团队将进行精心设计的微生物群落组装和适应性进化。从这些努力中，该项目将产生新的定量见解，在合成微生物财团中的紧急生存特性，并提供可重复使用的工具，严格推断各种微生物财团中的紧急特性。由于以下原因，该项目对科学界和社会产生了巨大影响。首先，开发的框架是可推广的，因为它不依赖于特定的函数形式和参数。其次，菌株设计、构建和测试的合理和迭代方法将验证假定的基因功能，填补关键的知识空白。值得注意的是，这项工作将扩大我们对控制不透明红球菌中芳香族化合物催化剂的调控网络的理解，并广泛适用于相关生物。第三，综合的方法将产生定量的见解，合理构建的生物体的财团中的社区组装和功能冗余。最后，并行进化实验也将产生洞察集体系统的进化过程和他们的两个力量：鲁棒性和适应性。使用不同的微生物财团作为模型系统，该团队将提供对复杂进化过程的见解，从而能够定量分析集体系统的鲁棒性和适应性。该项目还将以跨学科的方式培养研究生和博士后研究人员，为未来的劳动力和教育工作者提供化学工程、合成生物学、微生物生态学和数学方面的独特培训。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。