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Plastid proteomics.

机译:质体蛋白质组学。

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摘要

Plastids are essential organelles present in virtually all cells in plants and in green algae. The proteomes of plastids, and in particular of chloroplasts, have received significant amounts of attention in recent years. Various fractionation and mass spectrometry (MS) techniques have been applied to catalogue the chloroplast proteome and its membrane compartments. Neural network and hidden Markov models, in combination with experimentally derived filters, were used to try to predict the chloroplast subproteomes. Some of the many protein-protein interaction, as well as post-translational modifications have been characterized. Nevertheless, our understanding of the chloroplast proteome and its dynamics is very incomplete. Rapid improvements and wide-scale implementation of MS and new tools for comparative proteomics will undoubtedly accelerate this understanding in the near future. Proteomics studies often generate a large amount of data and these data are only meaningful if they can be easily accessed via the 'world-wide-web' and connected to other types of biological information. The plastid proteome data base (PPDB at http://www.ppdb.tc.cornell.edu/) and other web resources are discussed. This review will briefly summarize recent experimental and theoretical efforts, attempt to translate these data into the functions of the chloroplast and outline expectations and possibilities for (comparative) chloroplast proteomics.
机译:质体是植物和绿藻中几乎所有细胞中存在的必需细胞器。近年来,质体,特别是叶绿体的蛋白质组受到了广泛的关注。各种分馏和质谱(MS)技术已应用于对叶绿体蛋白质组及其膜室进行分类。神经网络和隐马尔可夫模型,结合实验得出的过滤器,被用来预测叶绿体亚蛋白质组。许多蛋白质-蛋白质相互作用以及翻译后修饰中的一些已经被表征。然而,我们对叶绿体蛋白质组及其动力学的了解还很不完整。 MS的快速改进和大规模实施以及用于比较蛋白质组学的新工具无疑将在不久的将来加速这种理解。蛋白质组学研究通常会产生大量数据,这些数据只有在可以通过“万维网”轻松访问并连接到其他类型的生物信息时才有意义。讨论了质体蛋白质组数据库(位于http://www.ppdb.tc.cornell.edu/的PPDB)和其他Web资源。本文将简要总结最近的实验和理论研究成果,试图将这些数据转化为叶绿体的功能,并概述(比较)叶绿体蛋白质组学的期望和可能性。

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