Analyzing the dynamics of cell cycle processes from fixed samples through ergodic principles
Analyzing the dynamics of cell cycle processes from fixed samples through ergodic principles
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通过遍历原理分析固定样本的细胞周期过程的动态
DOI：
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发表时间：
2015
影响因子：
3.3
通讯作者：
R. Wheeler
中科院分区：
文献类型：
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作者：
R. Wheeler
分析周期性细胞过程的工具，特别是细胞周期，对细胞生物学具有广泛的价值。细胞周期同步和活细胞延时观察被广泛用于分析这些过程，但不适用于许多系统。建立在遍历原理上的简单数学方法是一种成熟的、广泛适用的、强大的替代分析方法，尽管它们的应用不太广泛。这些方法从细胞群体异步地通过周期进展的单个时间点“快照”中提取关于周期过程的动态的数据。在这里，我展示了应用这些简单的数学方法来分析基本的周期性过程周期，包括分裂事件，细胞群体经历单细胞老化，细胞周期与多个裂变（单细胞生殖），以及最近的进展，允许详细的映射细胞周期从不断变化的细胞性质，如大小和DNA含量。这包括使用来自哺乳动物、酵母和单细胞真核寄生虫细胞生物学的现有数据的例子。通过光学显微镜、电子显微镜和流式细胞术在高通量细胞分析方面的不断进步，这些数学方法变得越来越重要，是传统同步化和延时细胞周期分析方法的有力补充。
Tools to analyze cyclical cellular processes, particularly the cell cycle, are of broad value for cell biology. Cell cycle synchronization and live-cell time-lapse observation are widely used to analyze these processes but are not available for many systems. Simple mathematical methods built on the ergodic principle are a well-established, widely applicable, and powerful alternative analysis approach, although they are less widely used. These methods extract data about the dynamics of a cyclical process from a single time-point “snapshot” of a population of cells progressing through the cycle asynchronously. Here, I demonstrate application of these simple mathematical methods to analysis of basic cyclical processes—cycles including a division event, cell populations undergoing unicellular aging, and cell cycles with multiple fission (schizogony)—as well as recent advances that allow detailed mapping of the cell cycle from continuously changing properties of the cell such as size and DNA content. This includes examples using existing data from mammalian, yeast, and unicellular eukaryotic parasite cell biology. Through the ongoing advances in high-throughput cell analysis by light microscopy, electron microscopy, and flow cytometry, these mathematical methods are becoming ever more important and are a powerful complementary method to traditional synchronization and time-lapse cell cycle analysis methods.
影响因子：
7.5
作者：
Pelletier, Laurence;Yamashita, Yukiko M.
通讯作者：
Yamashita, Yukiko M.
影响因子：
7.3
作者：
Wilson NF;Iyer JK;Buchheim JA;Meek W
通讯作者：
Meek W