Transitions: Modeling microbial community metabolic interactions under extreme conditions

这项研究的目的是确定生活在极端条件下的微生物如何进行代谢交流。极端微生物是生命恢复力的杰出例子，它们在沸腾的温泉、饱和盐的盐水湖和曾经被认为是无菌的沙漠中茁壮成长。该项目使用生活在高盐环境中的极端微生物作为测试系统，绘制和模拟营养物质如何在微生物群落中流动，从而在粮食短缺时期实现弹性。人们对适应盐的微生物的代谢知之甚少，但它产生生物技术感兴趣的化学物质和酶。因此，该研究有望揭示生物弹性的一般原理，并为极端微生物代谢产物的未来工业应用提供新的方法。这些活动将使PI的研究方向从纯实验室培养的分子实验过渡到野外生态学和代谢模型。教育计划的目标是促进跨学科的包容性学习体验。PI将与她所在团队的学生和博士后一起组成“共同学习团队”，团队负责人将与该领域的学生一起学习如何取样和收集数据。在这些垂直整合的团队中，每个人都在一起学习的观点有望减少权力动态，促进积极的研究文化，让所有团队成员都感到受欢迎和重视。提出的研究验证了高盐微生物群落相互作用以维持稳定性的假设，尽管盐度和养分可用性发生了变化。高盐适应古细菌，或嗜盐菌，为研究微生物群落中的代谢相互作用提供了独特的模型。成员物种共享一个共同的高盐栖息地，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，高盐湖中的营养物质是间歇性的，导致严重的能量压力。作为回应，嗜盐菌已经进化出一系列可能的代谢解决方案，以在同一稀缺资源池中生存。高盐微生物群落有很大的潜力揭示群落对环境扰动的恢复力的一般原理。然而，关于社区互动机制的知识在很大程度上仍然是未知的。在拟议的工作中，PI和合作者通过追求以下目标来解决这些问题：(a)为高盐群落构建基于约束的模型，以解释和预测代谢相互作用；(b)对大盐湖微生物群落进行时空梯度采样，以检验模型预测结果；(c)在生态相关条件下在实验室生长的合成群落中测试模型预测。为了实现这些目标，我们提出了一个全面的专业发展计划，包括深入研究代谢模型和在大盐湖旅行期间进行野外生态学培训。所提出的模型有望对微生物群落的通量分布进行高度准确的预测。这项研究使PI能够在先前发现古细菌极端微生物代谢网络转录调节机制的基础上，启动一个新的和令人兴奋的研究方向。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This goal of this research is to determine how microbes living in extreme conditions communicate metabolically. Microbial extremophiles are remarkable examples of life’s resilience, thriving in hot springs at boiling temperatures, in brine lakes saturated with salt, and in deserts once thought to be sterile. This project uses extremophiles that live in high salt as a test system to map and model how nutrients flow through microbial communities, enabling resilience during times of food scarcity. The metabolism of salt-adapted microbes is poorly understood but produces chemicals and enzymes of interest to biotechnology. The proposed research is therefore expected to reveal general principles of biological resilience and present novel approaches for future industrial applications of extremophile metabolic products. These activities will enable a transition in the PI's research direction from molecular experiments in pure laboratory cultures to field ecology and metabolic modeling. The goal of the education plan is to foster inclusive learning experiences that span disciplinary lines. Together with students and postdocs from her group, the PI will form “co-learning teams" in which the team leader learns, alongside students in the field, how to sample and collect data. In these vertically integrated teams, the perspective that everyone is learning together is expected to lessen power dynamics and promote a positive research culture where all team members feel welcome and valued. The proposed research tests the hypothesis that hypersaline microbial communities interact to maintain stability despite changes in salinity and nutrient availability. Hypersaline-adapted archaea, or halophiles, provide a unique model for investigating the metabolic interactions in microbial communities. 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 variation, resulting in severe energy stress. In response, halophiles have evolved a wide array of possible metabolic solutions to survive on the same pool of scarce resources. Hypersaline microbial communities have great potential to reveal general principles of community resilience to environmental perturbation. However, knowledge regarding the mechanisms of community interactions remain largely uncharacterized. In the proposed work, the PI and collaborators address these questions by pursuing the following objectives: (a) constructing constraint-based models for hypersaline communities to explain and predict metabolic interactions; (b) sampling the Great Salt Lake microbial communities over temporal and spatial gradients to test model predictions; (c) testing model predictions in synthetic communities grown in the lab under ecologically relevant conditions. To accomplish these aims, a comprehensive Professional Development Plan is proposed, including intensive study in metabolic modeling and training in field ecology during trips to the Great Salt Lake. The proposed models are expected to enable highly accurate predictions of flux distributions in microbial communities. This research enables the PI to launch a new and exciting research direction, building on prior work that discovered mechanisms of transcriptional regulation of metabolic networks in archaeal extremophiles.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.