Collaborative Research: Linking microbial social interactions within soil aggregate communities to ecosystem C, N, and P cycling

大多数人永远不会想到单细胞细菌可以识别它们的邻居，相互交流，并决定是否合作。奇怪的是，有证据表明，细菌可以被认为具有社会行为和决策能力。尽管越来越多的人接受细菌中的社会行为和交流的想法，但尚不清楚这些小规模行为如何影响自然界中的微生物群落相互作用。这项研究将提供第一个测试是否微生物社会相互作用导致在生态系统水平上的功能的影响，使用微生物群落从天然草地和农业土壤。细菌可以检测到的化学信号形式的通信将影响细胞是否会产生降解植物物质的各种胞外酶。这些细菌群落的社会组织可以允许劳动分工，一些物种提供一组酶，其他物种提供不同的酶，从而提高有机物分解的效率。通过这种方式，细菌之间的社会相互作用可以影响整个生态系统的运作方式。这项研究还将为西班牙裔服务机构的研究生和本科生提供培训机会。学生将获得现场，实验室和计算技术的经验，包括生物信息学和数学建模方法，将博弈论与生态过程联系起来，并将参与到高中科学学生和他们的老师的外联活动中。在土壤中，细菌最有可能与称为聚集体的土壤颗粒团块中的其他细菌相互作用。团聚体赋予土壤结构，有助于水和氧气的流动，保护土壤中的碳，并支持微生物的多样性。这些微生物分解死亡的植物和动物，回收营养物质，并帮助新植物茁壮成长。受到机械扰动的土壤，例如犁耕，会失去许多团聚体和整体结构。这组研究人员假设，土壤团聚体，如在多年未耕种的草原土壤中发现的土壤团聚体，将提供必要的稳定性和空间组织来发展细菌群落，与最近受到干扰的土壤相比，这些细菌群落更多地依赖于不同物种之间的交流和合作。实验将结合联合收割机的分子和生物信息学方法来研究细尺度的细菌，使用低干扰方法分离土壤团聚体和耦合博弈论-生态系统模型，将土壤团聚体中的微生物行为与土壤地球化学循环的变化联系起来。研究人员将在草原生态系统中使用一个特征良好的恢复梯度，包括耕地，不同年龄的恢复地点，以及没有耕作历史的遗迹草原。本研究的总体目标是调查土壤团聚体群落中微生物的社会相互作用及其对生态系统水平上碳、氮和磷循环的影响。具体来说，这项研究将解决两个问题：（1）稳定的，具有生物活性的微聚集体是否能促进具有更高信号和通信潜力的微生物群落，增加代谢相互依赖性和劳动分工？(2)在一个集合群落中的劳动分工如何影响生态系统水平的碳、氮和磷循环？宏基因组和转录组数据将被用来参数化耦合微生物动力学-生态系统模型，用于研究微生物社会相互作用在群落组装和土壤中碳，氮，磷循环中的作用。研究人员还将培训3名研究生和12名本科生。该项目还将加强他们的大学和大自然保护协会之间的研究合作，研究生将通过保护工作的沉浸式体验接受现场采样和骨料筛分技术的培训。一位艺术家将与研究人员合作开发一个虚拟现实程序，将该项目的成果传播给高中生和现场的公众游客。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。

Most people would never imagine that single-celled bacteria could recognize their neighbors, communicate with one another, and make decisions about whether to cooperate. Curiously, evidence suggests that bacteria can be credited with social behavior and decision-making abilities. Despite the increasing acceptance of the idea of social behavior and communication in bacteria, it is not yet known how these small scale behaviors influence microbial community interactions in nature. This study will provide the first test of whether microbial social interactions lead to impacts in function at the ecosystem level using microbial communities from both natural grassland and agricultural soil. Communication in the form of chemical signals that can be detected by bacteria will influence whether cells will make various extracellular enzymes that degrade plant matter. The social organization of these bacterial communities could allow for a division of labor, with some species contributing one set of enzymes and other species contributing different ones, thereby increasing the efficiency of organic matter decomposition. In this way, social interactions among bacteria could influence how well the entire ecosystem works. The research will also provide training opportunities for graduate and undergraduate students at a Hispanic-Serving Institution. Students will gain experience in field, lab, and computational techniques, including bioinformatics and mathematical modeling approaches that link game theory to ecological processes, and will participate in outreach to high school science students and their teacher. In soil, bacteria are most likely to interact with other bacteria within clumps of soil particles known as aggregates. Aggregates give soil a structure, which helps water and oxygen flow, protects carbon in soil, and supports diverse communities of microorganisms. These microbes decompose dead plants and animals, recycle nutrients, and help new plants to thrive. Soil that is mechanically disturbed, for example by plowing, loses many of its aggregates and overall structure. This team of researchers hypothesize that soil aggregates, like those found in prairie soils that have not been farmed for many years, will provide the necessary stability and spatial organization to develop bacterial communities that rely more on communication and cooperation among different species when compared to more recently disturbed soils. Experiments will combine molecular and bioinformatic approaches to study bacteria at fine scales using a low-disturbance method for isolating soil aggregates and a coupled game theory-ecosystem model to connect microbial behavior in soil aggregates to changes in biogeochemical cycling. The researchers will use a well-characterized restoration gradient in a prairie ecosystem, including cultivated sites, restored sites of varying age, and relic prairie with no cultivation history. The overarching goal of this study is to investigate microbial social interactions within soil aggregate communities and their impacts on carbon, nitrogen, and phosphorus cycling at the ecosystem level. Specifically, the study will address two questions: (1) Do stable, biologically active microaggregates foster microbial communities with a higher potential for signaling and communication, with increased metabolic interdependence and division of labor? (2) How does the division of labor within an aggregate community affect ecosystem-level carbon, nitrogen, and phosphorus cycling? Metagenomic and transcriptomic data will be used to parameterize a coupled microbial dynamics-ecosystem model for investigating the roles of microbial social interactions in community assembly and carbon, nitrogen, and phosphorus cycling in soils. The researchers will also train 3 graduate students and 12 undergraduates. This project will also strengthen a research collaboration between their university and The Nature Conservancy, where a graduate student will be trained in field sampling and aggregate sieving techniques through an immersive experience in conservation work. An artist will work with the researchers to develop a virtual reality program to disseminate results of this project to high school students and public visitors to the field site.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.