人工智能引导多组学协同探讨木麻黄解磷微生物功能与机制的研究

低磷条件是限制东南沿海主栽防护林树种木麻黄生态功能发挥的主要原因之一。虽然微生物与林木磷吸收的关系被广泛关注，但缓解林木低磷胁迫的功能性微生物依然缺乏，其重要原因是缺乏精准、有效的表型组学手段，能够从复杂林间环境中把解磷微生物对林木的影响剥离出来。申请人前期利用基于人工智能的表型组学和宏基因组测序，发现了一株与木麻黄磷素利用密切相关的根系内生真菌。在此研究基础上，本项目拟采用多组学（表型组学、基因组学、微生物组学）协同，解析关键微生物缓解宿主木麻黄磷素受限的机制，明晰关键微生物在木麻黄环境适应性和连栽障碍中的关键作用，探索该菌株在人工组装菌群的应用前景。本项目的顺利实施，不仅能够获得一种精确降维、快速确定与林木表型相关的关键微生物的新技术体系，还将通过深入分析微生物与宿主木麻黄生物学功能的交互关系，为指导优化林木共生微生物组的开发和利用提供借鉴。

The low phosphorus is one of the main reasons for restricting the ecological function of Casuarina equisetifolia L., a tree planted in the main protection forest in the southeast coast. Although the relationship between microbe and phosphorus absorption has been widely concerned, functional microorganisms that alleviate low phosphorus stress in forests are still lacking. One of the important reason is the lack of precise and effective phenotyping methods that can take out of the effect of phosphate-solubilizing microbes from complex forest environments. Based on artificial intelligence-based phenomics and metagenomic sequencing, we found a root endophytic fungus that is closely related to phosphorus uptake in previous studies. Thus, the project intends to use multi-omics integration(phenomics, genomics, microbiome) to analyze the mechanism of key microorganisms to alleviate the phosphorus limitation of Casuarina equisetifolia L., and to clarify the key role of microbe in environmental adaptability and replant problem of Casuarina equisetifolia L., to explore prospects for utilization of this strain in artificially assembled microbiota. The successful implementation of this project will not only obtain a new technology system for accurate dimensionality reduction and rapid determination of key microorganisms related to forest tree phenotypes, but also optimize the guidance for the development and utilization of symbiotic microbiome through further analysis of the interaction between microorganisms and the biological function of Casuarina equisetifolia L..