植物と微生物のマッチングでより良いバイオエネルギー作物を目指す(Plant, microbe matchmaking for better bioenergy crops)

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2023-03-20 オークリッジ国立研究所(ORNL)

米国の研究所、Oak Ridge National Laboratoryの研究者たちは、バイオエネルギー植物が有益な微生物を認識し、植物の成長や土壌中の炭素の貯蔵を促進することができると特定された特定のタンパク質とアミノ酸を発見しました。
研究は、LysM受容体キナーゼと呼ばれるタンパク質が、植物と微生物のシグナリングを調節し、バイオマス生産、根の性能、および炭素貯蔵に影響を与えることを示しています。これにより、科学者たちは、植物と微生物の共生を促進するバイオエンジニアリングの努力をより正確にターゲット化し、未来の気候においてポプラの成長と持続可能性を向上させることができます。この研究には、計算構造生物学を使用した新しい方法が用いられ、様々な植物での遺伝子機能の同定を加速することができます。

<関連情報>

バイオエネルギー作物ポピュラスにおける植物-微生物相互作用の制御における植物リシンモチーフ受容体様キナーゼの役割を探求する Exploring the role of plant lysin motif receptor-like kinases in regulating plant-microbe interactions in the bioenergy crop Populus

Kevin R. Cope, Erica T. Prates, John I. Miller, Omar N.A. Demerdash, Manesh Shah, David Kainer, Ashley Cliff, Kyle A. Sullivan, Mikaela Cashman, Matthew Lane, Anna Matthiadis, Jesse Labbé, Timothy J. Tschaplinski, Daniel A. Jacobson, Udaya C. Kalluri
Computational and Structural Biotechnology Journal  Available online: 31 December 2022
DOI:https://doi.org/10.1016/j.csbj.2022.12.052

植物と微生物のマッチングでより良いバイオエネルギー作物を目指す(Plant, microbe matchmaking for better bioenergy crops)

Abstract

For plants, distinguishing between mutualistic and pathogenic microbes is a matter of survival. All microbes contain microbe-associated molecular patterns (MAMPs) that are perceived by plant pattern recognition receptors (PRRs). Lysin motif receptor-like kinases (LysM-RLKs) are PRRs attuned for binding and triggering a response to specific MAMPs, including chitin oligomers (COs) in fungi, lipo-chitooligosaccharides (LCOs), which are produced by mycorrhizal fungi and nitrogen-fixing rhizobial bacteria, and peptidoglycan in bacteria. The identification and characterization of LysM-RLKs in candidate bioenergy crops including Populus are limited compared to other model plant species, thus inhibiting our ability to both understand and engineer microbe-mediated gains in plant productivity. As such, we performed a sequence analysis of LysM-RLKs in the Populus genome and predicted their function based on phylogenetic analysis with known LysM-RLKs. Then, using predictive models, molecular dynamics simulations, and comparative structural analysis with previously characterized CO and LCO plant receptors, we identified probable ligand-binding sites in Populus LysM-RLKs. Using several machine learning models, we predicted remarkably consistent binding affinity rankings of Populus proteins to CO. In addition, we used a modified Random Walk with Restart network-topology based approach to identify a subset of Populus LysM-RLKs that are functionally related and propose a corresponding signal transduction cascade. Our findings provide the first look into the role of LysM-RLKs in Populus-microbe interactions and establish a crucial jumping-off point for future research efforts to understand specificity and redundancy in microbial perception mechanisms.

生物化学工学
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