The leaf ionome as a multivariable system to detect a plant's physiological status
The leaf ionome as a multivariable system to detect a plant's physiological status
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DOI：
10.1073/pnas.0804175105
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发表时间：
2008-08-19
影响因子：
11.1
通讯作者：
Salt, David E.
中科院分区：
文献类型：
--
作者：
Baxter, Ivan R.;Vitek, Olga;Salt, David E.
生物分子的定量谱包含关于生物体的生理状态的信息的论点已经激发了各种高通量分子谱实验。然而，从这些实验中公正地发现和验证生物分子特征仍然是一个挑战。在这里，我们表明，拟南芥（拟南芥）叶离子组，或元素组成，包含这样的签名，我们建立的统计模型，这些多变量的签名连接到定义的生理反应，如铁（Fe）和磷（P）稳态。铁是植物生长和发育所必需的，但在高水平时可能有毒。正因为如此，拍摄铁浓度受到严格管制，并显示在一个范围内的铁浓度在环境中的变化很小，使他们一个贫穷的探针植物的铁状态。通过评估在不同铁营养条件下生长的植物中的茎离子组，我们已经建立了拟南芥铁响应状态的多变量离子组学特征。该特征已经针对已知的Fe响应蛋白进行了验证，并允许以18%/16%的假阴性/阳性率高通量检测植物的Fe状态。先前收集的来自880个拟南芥突变体和自然加入物的离子组学数据的“元筛选”成功地鉴定了已知的Fe突变体frd 1和frd 3。也已经采取类似的方法来鉴定和使用与P稳态相关的芽离子经济学特征。这项研究建立了与矿质营养稳态相关的生理状态的多变量离子经济学特征确实存在于拟南芥中，并且原则上足够稳健以检测对环境或遗传扰动的特定生理反应。
The contention that quantitative profiles of biomolecules contain information about the physiological state of the organism has motivated a variety of high-throughput molecular profiling experiments. However, unbiased discovery and validation of biomolecular signatures from these experiments remains a challenge. Here we show that the Arabidopsis thaliana (Arabidopsis) leaf ionome, or elemental composition, contains such signatures, and we establish statistical models that connect these multivariable signatures to defined physiological responses, such as iron (Fe) and phosphorus (P) homeostasis. iron is essential for plant growth and development, but potentially toxic at elevated levels. Because of this, shoot Fe concentrations are tightly regulated and show little variation over a range of Fe concentrations in the environment, making them a poor probe of a plant's Fe status. By evaluating the shoot ionome in plants grown under different Fe nutritional conditions, we have established a multivariable ionomic signature for the Fe response status of Arabidopsis. This signature has been validated against known Fe-response proteins and allows the high-throughput detection of the Fe status of plants with a false negative/positive rate of 18%/16%. A "metascreen" of previously collected ionomic data from 880 Arabidopsis mutants and natural accessions for this Fe response signature successfully identified the known Fe mutants frd1 and frd3. A similar approach has also been taken to identify and use a shoot ionomic signature associated with P homeostasis. This study establishes that multivariable ionomic signatures of physiological states associated with mineral nutrient homeostasis do exist in Arabidopsis and are in principle robust enough to detect specific physiological responses to environmental or genetic perturbations.