Max Planck Institute for Plant Breeding Research, Cologne, Germany.
Mol Syst Biol. 2020 Jun;16(6):e9514. doi: 10.15252/msb.20209514.
While classical breeding traits have focussed on above-ground tissues, it is becoming clear that underground aspects of plant life are a hidden treasure of tools applicable for resilient crop production. Plants of the legume family develop specialized organs, called nodules, which serve as hosts for Rhizobium bacteroids. A highly specialized symbiotic relationship exists deep inside the nodules. In exchange for carbohydrates, host-specific rhizobia bacteroids can assimilate nitrogen from the air and fix it into a form that can be used by plants in a process known as biological nitrogen fixation. While we understand certain aspects of how this inter-species relationship is established, the exact biochemistry of this exchange remains dogmatic. In their recent work, Christen and colleagues (Flores-Tinoco et al, 2020) challenge the current model of nitrogen exchange and argue that that an expanded model is needed to fit experimental findings related to nitrogen fixation. The authors perform an elegant set of experiments and highlight that rather than a single-way flow of nitrogen, the N-fixing process is in fact an elaborate metabolic exchange between the nodule-dwelling bacteroids and the host plant. Importantly, this work provides an updated theoretical framework with the "catchy" name CATCH-N which delivers up to 25% higher yields of nitrogen than classical models and is suitable for rational bioengineering and optimization of nitrogen fixation in microorganisms.
虽然经典的育种特性侧重于地上组织,但越来越明显的是,植物地下生活的各个方面都是可应用于弹性作物生产的工具的宝库。豆科植物会形成专门的器官,称为根瘤,作为根瘤菌类细菌的宿主。在根瘤内深处存在一种高度专门化的共生关系。作为宿主特异性根瘤菌类细菌从空气中同化氮并将其固定为植物可利用的形式的交换的回报,宿主会提供碳水化合物,这一过程被称为生物固氮。虽然我们理解了这种种间关系建立的某些方面,但这种交换的确切生物化学仍然是教条式的。在他们最近的工作中,Christen 和同事们(Flores-Tinoco 等人,2020 年)对氮交换的现行模型提出了挑战,并认为需要一个扩展的模型来适应与固氮相关的实验发现。作者进行了一系列优雅的实验,并强调指出,固氮过程实际上是根瘤居住的类细菌和宿主植物之间复杂的代谢交换,而不是氮的单向流动。重要的是,这项工作提供了一个更新的理论框架,名为 CATCH-N,其比经典模型的氮产量高出 25%,适合于微生物中固氮的理性生物工程和优化。