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通过蛋白质相互作用网络对拟南芥线粒体蛋白质组进行综合鉴定及其功能开发。

Integrative identification of Arabidopsis mitochondrial proteome and its function exploitation through protein interaction network.

机构信息

College of Life Sciences, Center for Bioinformatics and Institute of Biomedical Sciences, East China Normal University, Shanghai, China.

出版信息

PLoS One. 2011 Jan 31;6(1):e16022. doi: 10.1371/journal.pone.0016022.

Abstract

Mitochondria are major players on the production of energy, and host several key reactions involved in basic metabolism and biosynthesis of essential molecules. Currently, the majority of nucleus-encoded mitochondrial proteins are unknown even for model plant Arabidopsis. We reported a computational framework for predicting Arabidopsis mitochondrial proteins based on a probabilistic model, called Naive Bayesian Network, which integrates disparate genomic data generated from eight bioinformatics tools, multiple orthologous mappings, protein domain properties and co-expression patterns using 1,027 microarray profiles. Through this approach, we predicted 2,311 candidate mitochondrial proteins with 84.67% accuracy and 2.53% FPR performances. Together with those experimental confirmed proteins, 2,585 mitochondria proteins (named CoreMitoP) were identified, we explored those proteins with unknown functions based on protein-protein interaction network (PIN) and annotated novel functions for 26.65% CoreMitoP proteins. Moreover, we found newly predicted mitochondrial proteins embedded in particular subnetworks of the PIN, mainly functioning in response to diverse environmental stresses, like salt, draught, cold, and wound etc. Candidate mitochondrial proteins involved in those physiological acitivites provide useful targets for further investigation. Assigned functions also provide comprehensive information for Arabidopsis mitochondrial proteome.

摘要

线粒体是产生能量的主要参与者,并且主持涉及基本代谢和必需分子生物合成的几个关键反应。目前,即使对于模式植物拟南芥,大多数核编码的线粒体蛋白也未知。我们报告了一种基于概率模型(称为朴素贝叶斯网络)的预测拟南芥线粒体蛋白的计算框架,该模型整合了来自八个生物信息学工具的不同基因组数据,多个同源映射,蛋白质结构域特性和使用 1,027 个微阵列图谱的共表达模式。通过这种方法,我们以 84.67%的准确率和 2.53%的 FPR 性能预测了 2,311 个候选线粒体蛋白。与那些经过实验证实的蛋白质一起,鉴定了 2,585 种线粒体蛋白(命名为 CoreMitoP),我们根据蛋白质-蛋白质相互作用网络(PIN)和注释的新功能对具有未知功能的那些蛋白质进行了探索,为 26.65%的 CoreMitoP 蛋白质确定了新的功能。此外,我们发现新预测的线粒体蛋白嵌入了 PIN 的特定子网中,主要作用是响应各种环境胁迫,如盐,干旱,寒冷和伤口等。涉及这些生理活性的候选线粒体蛋白为进一步研究提供了有用的目标。分配的功能还为拟南芥线粒体蛋白质组提供了全面的信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a41/3031521/9817ea39f098/pone.0016022.g001.jpg

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