MacGregor Heather, Fukai Isis, Ash Kurt, Arkin Adam Paul, Hazen Terry C
University of California, Berkeley, Berkeley, CA, United States.
Bredesen Center, University of Tennessee, Knoxville, TN, United States.
Front Microbiol. 2024 Sep 18;15:1410820. doi: 10.3389/fmicb.2024.1410820. eCollection 2024.
As nuclear technology evolves in response to increased demand for diversification and decarbonization of the energy sector, new and innovative approaches are needed to effectively identify and deter the proliferation of nuclear arms, while ensuring safe development of global nuclear energy resources. Preventing the use of nuclear material and technology for unsanctioned development of nuclear weapons has been a long-standing challenge for the International Atomic Energy Agency and signatories of the Treaty on the Non-Proliferation of Nuclear Weapons. Environmental swipe sampling has proven to be an effective technique for characterizing clandestine proliferation activities within and around known locations of nuclear facilities and sites. However, limited tools and techniques exist for detecting nuclear proliferation in unknown locations beyond the boundaries of declared nuclear fuel cycle facilities, representing a critical gap in non-proliferation safeguards. Microbiomes, defined as "characteristic communities of microorganisms" found in specific habitats with distinct physical and chemical properties, can provide valuable information about the conditions and activities occurring in the surrounding environment. Microorganisms are known to inhabit radionuclide-contaminated sites, spent nuclear fuel storage pools, and cooling systems of water-cooled nuclear reactors, where they can cause radionuclide migration and corrosion of critical structures. Microbial transformation of radionuclides is a well-established process that has been documented in numerous field and laboratory studies. These studies helped to identify key bacterial taxa and microbially-mediated processes that directly and indirectly control the transformation, mobility, and fate of radionuclides in the environment. Expanding on this work, other studies have used microbial genomics integrated with machine learning models to successfully monitor and predict the occurrence of heavy metals, radionuclides, and other process wastes in the environment, indicating the potential role of nuclear activities in shaping microbial community structure and function. Results of this previous body of work suggest fundamental geochemical-microbial interactions occurring at nuclear fuel cycle facilities could give rise to microbiomes that are characteristic of nuclear activities. These microbiomes could provide valuable information for monitoring nuclear fuel cycle facilities, planning environmental sampling campaigns, and developing biosensor technology for the detection of undisclosed fuel cycle activities and proliferation concerns.
随着核技术为满足能源部门对多样化和脱碳不断增长的需求而发展,需要新的创新方法来有效识别和遏制核武器扩散,同时确保全球核能资源的安全开发。防止核材料和技术被用于未经授权的核武器开发,一直是国际原子能机构和《不扩散核武器条约》签署方面临的长期挑战。环境擦拭取样已被证明是一种有效的技术,可用于描述核设施和场地已知位置及其周边的秘密扩散活动。然而,用于检测已申报核燃料循环设施边界之外未知地点核扩散的工具和技术有限,这在防扩散保障方面是一个关键缺口。微生物群落被定义为在具有独特物理和化学性质的特定栖息地中发现的“微生物特征群落”,它可以提供有关周围环境中发生的条件和活动的有价值信息。已知微生物栖息在放射性核素污染场地、乏核燃料储存池和水冷核反应堆的冷却系统中,在这些地方它们会导致放射性核素迁移和关键结构的腐蚀。放射性核素的微生物转化是一个已得到充分证实的过程,在众多野外和实验室研究中都有记录。这些研究有助于识别直接和间接控制环境中放射性核素转化、迁移和归宿的关键细菌类群和微生物介导过程。在此基础上,其他研究将微生物基因组学与机器学习模型相结合,成功地监测和预测了环境中重金属、放射性核素及其他工艺废物的出现,这表明核活动在塑造微生物群落结构和功能方面的潜在作用。此前这一系列工作的结果表明,核燃料循环设施中发生的基本地球化学 - 微生物相互作用可能产生具有核活动特征的微生物群落。这些微生物群落可为监测核燃料循环设施、规划环境取样活动以及开发用于检测未公开的燃料循环活动和扩散问题的生物传感器技术提供有价值的信息。