CAREER: Moving beyond descriptive genomic studies - Applying theoretical ecology principles to predictably intensify anaerobic co-digestion processes

微生物群落共同工作，在工程和自然系统中处理营养物质和有机物。仅根据已知存在的物种来预测复杂的微生物群落的行为是困难的，因为大多数普遍存在的微生物经常随着时间和地点的变化而变化，即使群落行为保持不变。这项工作将制定一个定量标准来描述微生物群落的状态，以评估生物反应器系统的性能。研究小组还将制作以环境工程为重点的漫画，作为推广工作的一部分。这些漫画将针对代表性不足的学龄前儿童和青少年，以提高科学素养，并扩大未来对环境工程的参与。本研究的总体研究目标是应用理论生态学原理来量化驱动微生物群落结构、功能和流动性的基本过程。在这项工作中感兴趣的系统将是厌氧消化器在稳定，不安和恢复期间。这项研究将验证这样一个假设，即对生物处理系统的操作参数进行战略性改变，可以将其微生物群落塑造成可预测的组成，从而实现所需的功能改进。三个研究目标将用于检验这一假设。首先，在两年的时间里，利用从全规模设施收集的序列数据，对在非共消化和共消化条件下运行的全规模厌氧生物反应器中发生的动态微生物群结构和个体微生物相互作用进行量化。将创建正常运行范围基准（norb），以识别在稳定运行条件下预期的自然可变性。其次，将对这些设施的运行参数（包括有机负荷率、挥发性固体破坏、沼气和甲烷生产率、阻力和弹性）的norb进行量化。先进的统计工具将用于确定哪些操作参数对第一个研究目标中观察到的微生物组结构影响最大。最后，将使用实验室规模的厌氧消化器来确定使用操作参数变化来塑造微生物组结构的有效性，以最大限度地提高沼气生产力，阻力和/或弹性。这项工作的结果解决了这些系统中产生的大量序列数据的最大弱点；也就是说，它本质上主要是描述性的，在设计系统和预测未来性能方面效用有限。这项工作的教育和推广阶段将确定使用连续漫画的有效性，以提高K-12学生对复杂环境问题的理解和保留，目标是降低参与环境工程领域的障碍。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。

Microbial communities work together to process nutrients and organic matter in engineered and natural systems. It is difficult to predict how complex microbial communities will behave based on only what species are known to be present, because most prevalent microbes often change over time and from location to location, even as the community behavior stays the same. This work will develop a quantitative standard to describe the state of the microbial community for assessing bioreactor system performance. The research team will also create environmental engineering focused cartoons as part of an outreach effort. The cartoons will target underrepresented preteens and teens to increase scientific literacy and expand future participation in environmental engineering.The overall research objective of this research is to apply the theoretical ecology principles to quantify the fundamental processes that drive microbial community architecture, functionality, and fluidity. The system of interest in this work will be anaerobic digesters during periods of stability, upset, and recovery. This research will test the hypothesis that strategic changes to the operational parameters of biotreatment systems can shape their microbial communities into predictable compositions that achieve the desired functional improvement. Three research objectives will be used to test this hypothesis. First, the dynamic microbiome structures and individual microbial interactions that occur in full-scale anaerobic bioreactors operated under non-co-digesting and co-digesting conditions will be quantified utilizing sequence data collected from full-scale facilities bi-monthly over a two-year period. Normal operational range benchmarks (NORBs) will be created to identify the natural variability that would be expected under stable operating conditions. Second, the NORBs for operational parameters including organic loading rates, volatile solids destruction, biogas and methane productivity, resistance, and resiliency for these same facilities will be quantified. Advanced statistical tools will be used to identify which operational parameters have the largest impact on microbiome structures observed in the first research objective. Finally, laboratory-scale anaerobic digesters will be used to determine the effectiveness of using changes in operational parameters to shape the microbiome structure for maximizing biogas productivity, resistance, and/or resiliency. The results of this work address the greatest weaknesses of the tremendous amount of sequence data generated in these systems; namely that it is largely descriptive in nature with limited utility for designing systems and predicting future performance. The educational and outreach phase of this work will identify the effectiveness of using sequential cartoons to increase the comprehension and retention of complex environmental issues in K-12 students with the goal of lowering barriers to participation in the field of environmental engineering.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.