A proteomic chronology of gene expression through the cell cycle in human myeloid leukemia cells.
A proteomic chronology of gene expression through the cell cycle in human myeloid leukemia cells.
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DOI：
10.7554/elife.01630
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发表时间：
2014-01-01
期刊：
影响因子：
7.7
通讯作者：
Lamond AI
中科院分区：
文献类型：
--
作者：
Ly T;Ahmad Y;Shlien A;Soroka D;Mills A;Emanuele MJ;Stratton MR;Lamond AI
技术进步使细胞蛋白和RNA水平的分析具有前所未有的深度和灵敏度，允许在基本生物过程中对基因调控进行公正的重新评估。在这里，我们使用离心洗脱结合基于质谱的蛋白质组学和RNA-Seq记录了人类髓性白血病细胞在最小扰动细胞周期中蛋白质和mRNA表达水平的动态，避免了人工同步过程。我们在不同的细胞周期阶段鉴定了骨髓特异性基因表达和蛋白质丰度、异构体表达和磷酸化的变化。我们剖析了整个细胞周期中大量基因表达和超过6000个基因的蛋白质和mRNA水平之间的关系，揭示了复杂的基因特异性模式。该数据集是迄今为止人类细胞中基因表达的最深入的调查之一，呈现在一个可在线搜索的数据库中，即蛋白质组动力学百科全书（http://www.peptracker.com/epd/）。DOI: http://dx.doi.org/10.7554/eLife.01630.001细胞是复杂的环境：在任何时候，成千上万种不同的基因都充当产生信使RNA （mRNA）分子的分子模板，信使RNA （mRNA）分子本身就是用于产生蛋白质的模板。然而，并不是所有的基因在所有细胞中都是活跃的：作为细胞分裂周期的一部分，当细胞生长和分裂时，基因会定期开启和关闭。同样，在免疫细胞和皮肤细胞中，mRNA和蛋白质的生成模式也是不同的。近年来，用于检测mRNA分子和蛋白质的工具变得更加强大，使研究人员能够超越仅仅测量细胞中mRNA和蛋白质的总量，现在可以测量由特定基因编码的特定mRNA和蛋白质分子的单个数量。然而，在细胞周期的不同阶段进行这些测量一直是一个挑战。大多数用于此的方法都涉及人为地“阻止”细胞周期，这可能导致难以解释的副作用。Ly等人现在已经克服了这些问题，使用三种方法的组合来测量来自髓性白血病的人类癌细胞中与6000多个基因相关的mRNA和蛋白质分子的水平。利用细胞在细胞周期中改变大小的事实，Ly等人使用离心技术根据细胞的大小和细胞周期所处的阶段来分离细胞，从而避免了细胞周期阻滞的需要。一种叫做RNA-Seq的方法被用来测量细胞中不同mRNA分子的水平，一种叫做质谱仪的设备被用来识别和测量许多不同蛋白质的水平。除了能够在整个细胞分裂周期中跟踪大量基因的mRNA和蛋白质生产水平，同时也获得了关于有多少蛋白质被修饰的详细信息外，Ly等人发现——与预期相反——低数量的mRNA分子有时与高数量的相应蛋白质相关，反之亦然。这项工作提供了对mRNA水平与其相应蛋白产物之间复杂关系的更好理解，也证明了如何可能检测细胞类型和疾病状态（包括不同类型的癌症）之间微妙但重要的差异。DOI: http://dx.doi.org/10.7554/eLife.01630.002
Technological advances have enabled the analysis of cellular protein and RNA levels with unprecedented depth and sensitivity, allowing for an unbiased re-evaluation of gene regulation during fundamental biological processes. Here, we have chronicled the dynamics of protein and mRNA expression levels across a minimally perturbed cell cycle in human myeloid leukemia cells using centrifugal elutriation combined with mass spectrometry-based proteomics and RNA-Seq, avoiding artificial synchronization procedures. We identify myeloid-specific gene expression and variations in protein abundance, isoform expression and phosphorylation at different cell cycle stages. We dissect the relationship between protein and mRNA levels for both bulk gene expression and for over ∼6000 genes individually across the cell cycle, revealing complex, gene-specific patterns. This data set, one of the deepest surveys to date of gene expression in human cells, is presented in an online, searchable database, the Encyclopedia of Proteome Dynamics (http://www.peptracker.com/epd/). DOI: http://dx.doi.org/10.7554/eLife.01630.001 Cells are complex environments: at any one time, thousands of different genes act as molecular templates to produce messenger RNA (mRNA) molecules, which themselves are templates used to produce proteins. However, not all genes are active at all times inside all cells: as cells grow and divide as part of the cell division cycle, genes are switched on and off on a regular basis. Similarly, the patterns of mRNA and protein production are different in, say, immune and skin cells. In recent years, the tools available for detecting mRNA molecules and proteins have become more powerful, allowing researchers to move beyond just measuring the total amounts of mRNA and protein in the cell to now measuring individual amounts of specific mRNA and protein molecules encoded by specific genes. However, it has been a challenge to make these measurements at different stages of the cell cycle. Most of the methods used to do this have involved artificially ‘arresting’ the cell cycle, which can lead to side effects that are difficult to account for. Ly et al. have now overcome these problems using a combination of three methods to measure the levels of mRNA and protein molecules associated with over 6000 genes in human cancer cells derived from myeloid leukemia. Exploiting the fact that cells change size during the cell cycle, Ly et al. used a centrifugation technique to separate cells based on their size and, therefore, the stage of the cell cycle they were at, thus avoiding the need to arrest the cell cycle. An approach called RNA-Seq was then employed to measure the levels of the different mRNA molecules in the cells, and a device called a mass spectrometer was used to identify and measure the levels of many different proteins. In addition to being able to follow the level of mRNA and protein production for a large number of genes throughout the cell division cycle, while also obtaining detailed information about how many of the proteins are modified, Ly et al. discovered that—contrary to expectations—low numbers of mRNA molecules were sometimes associated with high numbers of the corresponding protein, and vice versa. This work provides a better understanding of the complex relationship between the levels of an mRNA and its corresponding protein product, and also demonstrates how it may be possible to detect subtle but important differences between cell types and disease states, including different types of cancer. DOI: http://dx.doi.org/10.7554/eLife.01630.002