Collaborative Research: Linking microbial social interactions within soil aggregate communities to ecosystem C, N, and P cycling
Collaborative Research: Linking microbial social interactions within soil aggregate communities to ecosystem C, N, and P cycling
批准号:
2346371
负责人:
David Lipson
金额:
$98.23万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2024
资助国家:
美国
项目状态:
未结题
起止时间:
2024-04-01 至 2027-03-31
中文摘要
大多数人都无法想象单细胞细菌能够识别它们的邻居,彼此交流,并决定是否合作。奇怪的是,有证据表明,细菌与社会行为和决策能力有关。尽管人们越来越接受细菌的社会行为和交流的观点,但尚不清楚这些小规模行为如何影响自然界微生物群落的相互作用。这项研究将首次利用天然草地和农业土壤中的微生物群落,测试微生物社会相互作用是否会导致生态系统水平上的功能影响。细菌可以检测到的化学信号形式的交流将影响细胞是否会产生各种降解植物物质的细胞外酶。这些细菌群落的社会组织可以允许分工,一些物种提供一套酶,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,细菌之间的社会互动可以影响整个生态系统的运作。该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。学生将获得野外、实验室和计算技术方面的经验,包括生物信息学和将博弈论与生态过程联系起来的数学建模方法,并将参与向高中理科学生和他们的老师的推广。在土壤中,细菌最有可能在称为聚集体的土壤颗粒团块中与其他细菌相互作用。团聚体赋予土壤一种结构,有助于水和氧的流动,保护土壤中的碳,并支持不同的微生物群落。这些微生物分解死去的植物和动物,循环养分,并帮助新植物茁壮成长。土壤受到机械扰动,例如犁地,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,就像在多年未耕种的草原土壤中发现的那样,将提供必要的稳定性和空间组织,以发展细菌群落,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。实验将结合分子和生物信息学方法在精细尺度上研究细菌,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生物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具有良好特征的恢复梯度,包括耕作遗址,不同年龄的恢复遗址和没有耕作历史的遗迹草原。本研究的总体目标是研究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、磷循环的影响。具体来说,该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培养具有更高信号和通信潜力的微生物群落,增加代谢相互依赖和分工?(2)群落内部的分工如何影响生态系统水平的碳、氮、磷循环?宏基因组和转录组数据将用于参数化耦合微生物动力学-生态系统模型,以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。研究人员还将培养3名研究生和12名本科生。该项目还将加强他们的大学与大自然保护协会之间的研究合作,通过身临其境的保护工作体验,一名研究生将接受实地采样和骨料筛分技术的培训。一位艺术家将与研究人员一起开发一个虚拟现实程序,将这个项目的结果传播给高中生和现场的公众游客。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。
英文摘要
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.
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