Kikuchi Jun, Yamada Shunji
Environmental Metabolic Analysis Research Team, RIKEN Center for Sustainable Resource Science 1-7-22 Suehiro-cho, Tsurumi-ku Yokohama 230-0045 Japan
Graduate School of Bioagricultural Sciences, Nagoya University Furo-cho, Chikusa-ku Nagoya 464-8601 Japan.
RSC Adv. 2021 Sep 13;11(48):30426-30447. doi: 10.1039/d1ra03008f. eCollection 2021 Sep 6.
The environment, from microbial ecosystems to recycled resources, fluctuates dynamically due to many physical, chemical and biological factors, the profile of which reflects changes in overall state, such as environmental illness caused by a collapse of homeostasis. To evaluate and predict environmental health in terms of systemic homeostasis and resource balance, a comprehensive understanding of these factors requires an approach based on the "exposome paradigm", namely the totality of exposure to all substances. Furthermore, in considering sustainable development to meet global population growth, it is important to gain an understanding of both the circulation of biological resources and waste recycling in human society. From this perspective, natural environment, agriculture, aquaculture, wastewater treatment in industry, biomass degradation and biodegradable materials design are at the forefront of current research. In this respect, nuclear magnetic resonance (NMR) offers tremendous advantages in the analysis of samples of molecular complexity, such as crude bio-extracts, intact cells and tissues, fibres, foods, feeds, fertilizers and environmental samples. Here we outline examples to promote an understanding of recent applications of solution-state, solid-state, time-domain NMR and magnetic resonance imaging (MRI) to the complex evaluation of organisms, materials and the environment. We also describe useful databases and informatics tools, as well as machine learning techniques for NMR analysis, demonstrating that NMR data science can be used to evaluate the exposome in both the natural environment and human society towards a sustainable future.
从微生物生态系统到循环资源，环境会因许多物理、化学和生物因素而动态波动，这些因素的特征反映了整体状态的变化，例如内稳态崩溃导致的环境疾病。为了从系统内稳态和资源平衡的角度评估和预测环境健康，全面了解这些因素需要一种基于“暴露组范式”的方法，即对所有物质暴露的总和。此外，在考虑可持续发展以满足全球人口增长时，了解人类社会中生物资源的循环和废物回收非常重要。从这个角度来看，自然环境、农业、水产养殖、工业废水处理、生物质降解和可生物降解材料设计是当前研究的前沿领域。在这方面，核磁共振（NMR）在分析分子复杂性样品方面具有巨大优势，例如粗生物提取物、完整细胞和组织、纤维、食品、饲料、肥料和环境样品。在这里，我们概述一些例子，以促进对溶液态、固态、时域核磁共振和磁共振成像（MRI）在生物、材料和环境复杂评估中的最新应用的理解。我们还描述了有用的数据库和信息学工具，以及用于核磁共振分析的机器学习技术，证明核磁共振数据科学可用于评估自然环境和人类社会中的暴露组，以实现可持续的未来。
