Suppr超能文献

植物-微生物相互作用的分子见解,用于受污染环境的可持续修复。

Molecular insights into plant-microbe interactions for sustainable remediation of contaminated environment.

机构信息

Department of Earth Resources and Environmental Engineering, Hanyang University, Seoul 04763, South Korea.

Department of Biotechnology, Shivaji University, Kolhapur 416004, India.

出版信息

Bioresour Technol. 2022 Jan;344(Pt B):126246. doi: 10.1016/j.biortech.2021.126246. Epub 2021 Oct 29.

Abstract

The widespread distribution of organic and inorganic pollutants in water resources have increased due to rapid industrialization. Rhizospheric zone-associated bacteria along with endophytic bacteria show a significant role in remediation of various pollutants. Metaomics technologies are gaining an advantage over traditional methods because of their capability to obtain detailed information on exclusive microbial communities in rhizosphere of the plant including the unculturable microorganisms. Transcriptomics, proteomics, and metabolomics are functional methodologies that help to reveal the mechanisms of plant-microbe interactions and their synergistic roles in remediation of pollutants. Intensive analysis of metaomics data can be useful to understand the interrelationships of various metabolic activities between plants and microbes. This review comprehensively discusses recent advances in omics applications made hitherto to understand the mechanisms of plant-microbe interactions during phytoremediation. It extends the delivery of the insightful information on plant-microbiomes communications with an emphasis on their genetic, biochemical, physical, metabolic, and environmental interactions.

摘要

由于工业化的快速发展,水资源中的有机和无机污染物广泛分布。根际区相关细菌和内生细菌在各种污染物的修复中起着重要作用。元组学技术因其能够获得有关植物根际中独特微生物群落的详细信息(包括不可培养的微生物)而优于传统方法。转录组学、蛋白质组学和代谢组学是功能方法,有助于揭示植物-微生物相互作用的机制及其在污染物修复中的协同作用。对元组学数据的深入分析有助于了解植物和微生物之间各种代谢活动的相互关系。本综述全面讨论了迄今为止在组学应用方面的最新进展,以了解植物-微生物相互作用在植物修复过程中的机制。它提供了有关植物微生物组通讯的有见地的信息,重点介绍了它们的遗传、生化、物理、代谢和环境相互作用。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验