Modeling the function and evolution of metabolic networks across hypersaline-adapted Archaea

该奖项旨在从根本上了解微生物如何在面对地球上最极端的条件时收集营养并保持生存能力。这些生物中的许多生活在盐分饱和的湖泊和池塘中，这些湖泊和池塘营养物质含量低，氧气有限。这些“嗜盐生物”是古生界的成员，他们可以告诉我们能量新陈代谢的起源，因为他们利用广泛的代谢策略来依靠相同的稀缺资源池生存。这些嗜盐者自然地合成独特的化学物质，例如那些类似喷气燃料和可生物降解塑料的化学物质。在有关嗜盐代谢功能的知识方面存在很大差距，这阻碍了将嗜盐微生物用作替代能源解决方案。该项目将通过生成和比较80种嗜盐微生物的能量产生途径的计算模型来填补这些空白。来自两个测试物种的新陈代谢产物的经验测量将被用来完善模型预测。每年，PI的研究小组将教授两个为期一周的科学沉浸研讨会，一个为高中生，另一个为波多黎各大学的本科生。在这两个工作坊中，学生将测量嗜盐微生物在极端压力下的生存能力并对其进行建模。这项研究将提供关于能源生产演变的基础知识，使未来的替代能源战略成为可能，并让不同群体的学生在STEM领域的职业生涯早期参与进来。该项目的长期目标是增加关于古生菌代谢途径如何随着环境中不同营养物质的变化而调节的基础知识。高盐适应的古生菌，或嗜盐菌，为研究转录调控和代谢网络的共同进化提供了一个独特的模型。成员物种共享共同的高盐度栖息地，但在如何产生能量方面表现出广泛的多样性。在季节变化期间，高盐度湖泊间歇性地可获得营养物质。作为回应，嗜盐微生物获得了一系列可能的代谢解决方案，以利用相同的稀缺资源生存。最近来自PI实验室的转录学和代谢组学证据表明，嗜盐生物利用转录调控作为一种主要机制来动态调整代谢网络，以响应营养波动。基于这一证据，工作假说是，在营养波动期间，调节网络与代谢网络以不同的方式共同进化。然而，到目前为止，由于缺乏可驯化的模式生物，古生菌的代谢多样性在很大程度上还没有被探索。最近，已经有了80个嗜盐微生物的基因组序列，这在古生代是前所未有的。利用这些基因组序列数据，将实现以下目标来检验中心假设：(A)利用自动计算方法构建和比较80种嗜盐生物的代谢网络模型；(B)测试关于两个密切相关且遗传上容易控制的嗜盐生物模型物种的营养和遗传扰动的模型预测；(C)使用转录组和代谢组数据作为额外限制条件来完善代谢模型。

This award, seeks fundamental understanding of how microorganisms gather nutrients and remain viable while facing the most extreme conditions on Earth. Many of these organisms reside in salt saturated lakes and ponds that are low in nutrients and limited for oxygen. These "halophiles", members of the domain Archaea, can teach us about the origins of energy metabolism since they exploit a wide array of metabolic strategies to survive on the same pool of scarce resources. These halophiles naturally synthesize unique chemicals, such as those resembling jet fuel and biodegradable plastic. Large gaps in knowledge regarding halophile metabolic functions have prevented the use of halophiles for alternative energy solutions. This project will fill these gaps by generating and comparing computational models of energy production pathways across 80 species of halophiles. Empirical measurements of metabolic products from two test species will be used to refine the model predictions. Each year, the PI's research group will teach two weeklong science immersion workshops, one for high school students and the other for undergraduates at University of Puerto Rico. In both workshops, students will measure and model halophile viability during extreme stress. This research will provide fundamental knowledge regarding the evolution of energy production, enable future alternative energy strategies, and engage a diverse population of students in STEM fields early in their careers.The long-term goal of this project is to increase fundamental knowledge regarding how metabolic pathways of archaeal microorganisms are regulated in response to varying nutrients in the environment. Hypersaline-adapted Archaea, or halophiles, provide a unique model for investigating the co-evolution of the transcription regulatory and metabolic networks. Member species share a common hypersaline habitat, but exhibit extensive diversity in how they generate energy. Nutrients are intermittently available in hypersaline lakes during seasonal variations. In response, halophiles have acquired a wide array of possible metabolic solutions to survive on the same pool of scarce resources. Recent transcriptomic and metabolomics evidence from the PI's lab suggest that halophiles use transcriptional regulation as a primary mechanism to tune the metabolic network dynamically in response to nutrient fluctuations. Based on this evidence, the working hypothesis is that the regulatory network co-evolves with the metabolic network in diverse ways during nutrient fluctuation. However, to date, archaeal metabolic diversity has been largely unexplored due to the scarcity of tractable model organisms. Recently, 80 genome sequences of halophiles have become available, a scale that is unprecedented among Archaea. Using these genomic sequence data, the following objectives will be carried out to test the central hypothesis: (a) Construct and compare metabolic network models for 80 species of halophiles using automated computational methods; (b) Test model predictions regarding nutrient and genetic perturbations in two closely related, genetically tractable halophile model species; (c) Refine metabolic models using transcriptome and metabolome data as additional constraints.