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在发育中的果实中模拟蛋白质命运。

Modeling Protein Destiny in Developing Fruit.

机构信息

Unité Mixte de Recherche 1332 Biologie du Fruit et Pathologie, Institut National de la Recherche Agronomique, Université Bordeaux, F33883 Villenave d'Ornon, France.

Institut de Mathématiques de Bordeaux, Ecole Nationale Supérieure de Technologie des Biomolécules de Bordeaux-Institut Polytechnique de Bordeaux, 33400 Talence, France.

出版信息

Plant Physiol. 2019 Jul;180(3):1709-1724. doi: 10.1104/pp.19.00086. Epub 2019 Apr 23.

Abstract

Protein synthesis and degradation are essential processes that regulate cell status. Because labeling in bulky organs, such as fruits, is difficult, we developed a modeling approach to study protein turnover at the global scale in developing tomato () fruit. Quantitative data were collected for transcripts and proteins during fruit development. Clustering analysis showed smaller changes in protein abundance compared to mRNA abundance. Furthermore, protein and transcript abundance were poorly correlated, and the coefficient of correlation decreased during fruit development and ripening, with transcript levels decreasing more than protein levels. A mathematical model with one ordinary differential equation was used to estimate translation ( ) and degradation ( ) rate constants for almost 2,400 detected transcript-protein pairs and was satisfactorily fitted for >1,000 pairs. The model predicted median values of ∼2 min for the translation of a protein, and a protein lifetime of ∼11 d. The constants were validated and inspected for biological relevance. Proteins involved in protein synthesis had higher and values, indicating that the protein machinery is particularly flexible. Our model also predicts that protein concentration is more strongly affected by the rate of translation than that of degradation.

摘要

蛋白质的合成与降解是调控细胞状态的基本过程。由于在果实等大型器官中进行标记较为困难,我们开发了一种建模方法,以在番茄果实的发育过程中从全局尺度研究蛋白质周转。在果实发育过程中收集了关于转录本和蛋白质的定量数据。聚类分析表明,与 mRNA 丰度相比,蛋白质丰度的变化较小。此外,蛋白质丰度和转录本丰度相关性较差,且在果实发育和成熟过程中相关性系数下降,转录本水平的下降超过了蛋白质水平。使用具有一个常微分方程的数学模型来估计近 2400 个检测到的转录本-蛋白质对的翻译( )和降解( )率常数,并对 >1000 对进行了令人满意的拟合。该模型预测了一个蛋白质翻译的中位数约为 2 分钟,而蛋白质的寿命约为 11 天。对常数进行了验证并检查了其生物学相关性。参与蛋白质合成的蛋白质具有更高的 和 值,这表明蛋白质机制特别灵活。我们的模型还预测,蛋白质浓度受翻译速率的影响比降解速率更显著。

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