Lekklar Chakkree, Chadchawan Supachitra, Boon-Long Preeda, Pfeiffer Wolfgang, Chaidee Anchalee
Center of Excellence in Environment and Plant Physiology, Department of Botany, Faculty of Science, Chulalongkorn University, Bangkok, 10330, Thailand.
Fachbereich Biowissenschaften, Abteilung Pflanzenphysiologie, Universität Salzburg, 5020, Salzburg, Austria.
Protoplasma. 2019 Mar;256(2):331-347. doi: 10.1007/s00709-018-1293-2. Epub 2018 Aug 10.
How many subcellular targets of the beneficial silicon effect do exist in salt-stressed rice? Here, we investigate the effects of silicon on the different components of salt stress, i.e., osmotic stress, sodium, and chloride toxicity. These components are separated by multivariate analysis of 18 variables measured in rice seedlings (Oryza sativa L.). Multivariate analysis can dissect vectors and extract targets as principal components, given the regressions between all variables are known. Consequently, the exploration of 153 correlations and 306 regression models between all variables is essential, and regression parameters for variables of shoot (silicon, sodium, chloride, carotenoids, chlorophylls a and b, and relative growth rate) and variables of shoot and root (hydrogen peroxide, ascorbate peroxidase (APX), catalase (CAT), fresh weight, dry weight, root-to-shoot ratio) are determined. The regression models [log (y) = y + a × log (x)] are confirmed by variance analysis of global goodness of fits (p < 0.0001). Thereby, logarithmic transformation yields linearization for multivariate analysis by Pearson's correlation. Four principal components are extracted: two targets of osmotic stress, one target of sodium toxicity, and one target of chloride toxicity. Thereby, silicon improves salt tolerance by increasing APX and CAT activities and decreasing hydrogen peroxide, salt ion accumulation, photosynthetic pigment losses, and growth inhibition. Salt stress increases silicon uptake pointing to a physiological regulation of plant salt stress in the presence of silicon. This mechanism and its four components are promising targets for further agricultural application.
在盐胁迫的水稻中,有益硅效应的亚细胞靶点究竟有多少?在此,我们研究了硅对盐胁迫不同组分的影响,即渗透胁迫、钠和氯毒性。通过对水稻幼苗(Oryza sativa L.)中测量的18个变量进行多变量分析来分离这些组分。鉴于所有变量之间的回归关系已知,多变量分析可以剖析向量并提取作为主成分的靶点。因此,探索所有变量之间的153个相关性和306个回归模型至关重要,并确定了地上部分变量(硅、钠、氯、类胡萝卜素、叶绿素a和b以及相对生长率)和地上与地下部分变量(过氧化氢、抗坏血酸过氧化物酶(APX)、过氧化氢酶(CAT)、鲜重、干重、根冠比)的回归参数。通过全局拟合优度的方差分析(p < 0.0001)证实了回归模型[log(y) = y + a × log(x)]。由此,对数变换通过Pearson相关性实现了多变量分析的线性化。提取了四个主成分:两个渗透胁迫靶点、一个钠毒性靶点和一个氯毒性靶点。由此,硅通过增加APX和CAT活性以及减少过氧化氢、盐离子积累、光合色素损失和生长抑制来提高耐盐性。盐胁迫增加了硅的吸收,表明在硅存在的情况下植物盐胁迫存在生理调节。这一机制及其四个组分是进一步农业应用的有前景的靶点。