Banana (Musa spp.) as a model to study the meristem proteome:: Acclimation to osmotic stress
Banana (Musa spp.) as a model to study the meristem proteome:: Acclimation to osmotic stress
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DOI：
10.1002/pmic.200600533
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发表时间：
2007-01-01
期刊：
影响因子：
3.4
通讯作者：
Panis, Bart
中科院分区：
文献类型：
--
作者：
Carpentier, Sebastien C.;Witters, Erwin;Panis, Bart
香蕉（Musa spp.）多茎分生组织是研究分生组织蛋白质组的极好模型。使用2-DE协议开发的少量的组织和MS为基础的跨物种多肽鉴定，我们揭示了分生组织蛋白质组和研究蔗糖介导的渗透胁迫的影响，在耐脱水品种。使用非参数单变量统计对由于高蔗糖处理而显著上调或下调的蛋白质进行分类。我们的研究结果表明，维持一个保护性的细胞内蔗糖浓度，增强表达的特定基因的节能糖酵解和细胞壁的完整性的保护是必不可少的，以维持稳态，适应和生存脱水。通过比较脱水耐受性品种与脱水敏感性品种，我们能够区分几种基因型特异性蛋白质（同种型），并且可以将脱水耐受性品种与参与能量代谢的蛋白质（例如，磷酸甘油酸激酶，磷酸葡萄糖变位酶，UDP-葡萄糖焦磷酸化酶）和与应激适应相关的蛋白质（例如，OSR 40样蛋白、脱落胁迫成熟蛋白样蛋白）。这项工作表明，蛋白质组分析可以成功地用于进行定量差异分析，并在一个柑橘类作物的遗传变异的特点。
Banana (Musa spp.) multiple shoot meristems are an excellent model to study the meristem proteome. Using a 2-DE protocol developed for small amounts of tissue and MS-based cross species polypeptide identification, we have revealed the meristem proteome and investigated the influence of sucrose-mediated osmotic stress in a dehydration-tolerant variety. Proteins that were significantly up- or down-regulated due to the high-sucrose treatment were classified using non-parametric univariate statistics. Our results suggest that the maintenance of an osmoprotective intracellular sucrose concentration, the enhanced expression of particular genes of the energy-conserving glycolysis and the conservation of the cell wall integrity are essential to maintain homeostasis, to acclimate and to survive dehydration. By comparing the dehydration-tolerant variety with a dehydration-sensitive variety, we were able to distinguish several genotype-specific proteins (isoforms), and could associate the dehydration-tolerant variety with proteins involved in energy metabolism (e.g., phosphoglycerate kinase, phosphoglucomutase, UDP-glucose pyrophosphorylase) and proteins that are associated with stress adaptation (e.g., OSR40-like protein, abscisic stress ripening protein-like protein). This work shows that proteome analysis can be used successfully to perform quantitative difference analysis and to characterize genetic variations in a recalcitrant crop.