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A Hydroponic Co-cultivation System for Simultaneous and Systematic Analysis of Plant/Microbe Molecular Interactions and Signaling
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AlphaFold-Multimer预测了植物-病原体界面上的跨王国相互作用.

Felix Homma1, Jie Huang1, Renier A L van der Hoorn2

  • 1The Plant Chemetics Laboratory, Department of Biology, University of Oxford, OX1 3RB, Oxford, UK.

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概括

人工智能从番茄病原体中发现了新型的小分泌蛋白 (SSP),这些蛋白抑制了植物防御酶. 这揭示了微生物王国中针对植物免疫系统的保存策略.

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科学领域:

  • 植物病理学 植物病理学
  • 微生物遗传学微生物遗传学
  • 生物信息学是一种生物信息学.

背景情况:

  • 植物病原体分泌出许多具有未知的功能的小分泌蛋白 (SSP).
  • 了解这些SSP对于植物防御策略至关重要.

研究的目的:

  • 使用人工智能,选番茄病原体SSP与番茄防御水解酶的相互作用.
  • 为了确定抑制植物免疫反应的新型SSP.

主要方法:

  • 利用AlphaFold-Multimer (AFM) 预测1879个SSP和6个番茄水溶酶之间的相互作用.
  • 经过实验验证,预测了与病变发生相关的亚酶P69B.的抑制剂.

主要成果:

  • 确定了15个未注释的SSP,预计可以抑制酸酶和蛋白酶.
  • 包括Ecp36和Six15在内的四个SSP被证实是P69B抑制剂.
  • P69B 作为一个被各种微生物病原体准的效应器枢纽.

结论:

  • 人工智能,特别是AFM,对于预测植物-病原体界面的跨王国相互作用来说非常强大.
  • 针对P69B的病原体SSP代表了在真菌,细菌和菌菌病原体之间保存的战略.
  • 这项研究增强了我们对植物病原体分子相互作用和潜在控制策略的理解.