How cells regulate protein levels (and fail to do so in cancer)
How cells regulate protein levels (and fail to do so in cancer)
批准号:
MR/T03050X/1
负责人:
Georg Kustatscher
金额:
$163.91万
依托单位:
依托单位国家:
英国
项目类别:
Fellowship
财政年份:
2020
资助国家:
英国
项目状态:
未结题
起止时间:
2020 至 --
中文摘要
60年前,弗朗西斯·克里克(Francis Crick)对分子生物学的“中心教条”做出了著名的描述。它解释说,遗传信息通过mRNA从DNA流向蛋白质,蛋白质是基因发挥其功能的生物活性分子。然而,这三层基因表达之间的定量关系仍然知之甚少。例如,如果一个细胞需要增加特定蛋白质的数量,它会增加转录(mRNA合成)的速度还是增加翻译(蛋白质合成)的速度?或者它会降低mRNA或蛋白质的降解速度吗?最终,为了回答这些和许多相关的问题,有必要建立一个定量的、完整的整个基因表达过程的视角。为了理解基因型如何导致表型,我们需要量化中心教条。我的工作将是朝着这个方向迈出的重要一步。我的目标是系统地量化DNA、mRNA和蛋白质水平如何相互关联,更重要的是,了解控制和调节这些关系的机制。使用下一代测序和质谱法,我将量化一系列人类细胞中的DNA、mRNA和蛋白质水平,并评估它们在不同条件下的变化。使用高性能计算和机器学习,我将了解哪些因素控制mrna和蛋白质的水平。这个话题对癌症生物学尤为重要。大多数类型的癌症表现为广泛的染色体异常。正常细胞中每个基因有两个副本,但在癌细胞中,这些基因副本中的一些可以被删除或繁殖。最近的研究表明,这对这些基因产生的mRNA水平有直接影响,而蛋白质水平通常被缓冲到正常水平。然而,这并不是对所有的蛋白质都有效:一些致癌基因的扩增会导致蛋白质水平的增加,这可能会推动或维持癌细胞的生长。因此,了解蛋白质水平如何缓冲DNA和mRNA水平的变化将有助于我们了解导致癌症的细胞过程,并可能提供新的治疗策略。中心法则的另一个有趣的方面是,不是所有的人类DNA都产生mrna,也不是所有的mrna都产生蛋白质。事实上,传统上认为98%的人类基因组不编码蛋白质。现代基因组学方法挑战了这一观点。例如,最近的证据表明,癌细胞(以及一般的应激细胞)可能会从mRNA区域产生数千种小蛋白质,这些小蛋白质迄今为止被认为是非编码的。我建议的工作将确定其中的许多并预测它们的潜在功能。同样,这可能对癌症治疗有重要意义,因为这种不寻常的蛋白质可能对癌细胞有特异性,因此提供了有希望的治疗靶点,特别是免疫治疗。总之,我希望我的研究将回答长期存在的关于蛋白质水平是如何调节的生物学问题,并对了解癌症和如何对抗癌症做出直接贡献。
英文摘要
60 years ago, Francis Crick famously described the "central dogma" of molecular biology. It explains that genetic information flows from DNA over mRNA to proteins, which are the bioactive molecules through which genes exert their function. However, the quantitative relationship between these three layers of gene expression remains poorly understood. For example, if a cell needs to increase the amount of a particular protein, will it increase the rate of transcription (mRNA synthesis) or that of translation (protein synthesis)? Or will it reduce the rate at which either mRNA or protein are degraded? Ultimately, to answer these and many related questions, it is necessary to establish a quantitative, integrated perspective of the entire gene expression process. To understand how genotypes lead to phenotypes, we need to quantify the central dogma.My work will be an important step in this direction. My goal is to systematically quantify how DNA, mRNA and protein levels relate to each other and, importantly, to understand which mechanisms control and regulate these relationships. Using next-generation sequencing and mass spectrometry I will quantify DNA, mRNA and protein levels in a range of human cells and assess how they change between different conditions. Using high-performance computing and machine-learning I will look to understand which factors control the levels of mRNAs and proteins. This topic is particularly important for cancer biology. Most types of cancer show wide-spread chromosome abnormalities. Normal cells have two copies of each gene, but in cancer cells some of these gene copies can be deleted or multiplied. Recent research has shown that this has a direct impact on mRNA levels produced by such genes, whereas protein levels are generally buffered towards normal levels. However, this does not work for all proteins: amplification of some oncogenes leads to increased protein levels and this could drive or sustain the growth of cancer cells. Therefore, understanding how protein levels are buffered against changes at the DNA and mRNA level will help us to understand cellular processes that lead to cancer and may offer new therapeutic strategies.Another intriguing aspect of the central dogma is that not all human DNA produces mRNAs, and not all mRNAs produce proteins. In fact, traditionally it is assumed that 98% of the human genome does not encode for proteins. Modern genomics methods have challenged this view. For example, recent evidence suggests that cancer cells (and stressed cells in general) may produce thousands of small proteins from mRNA regions that were so far thought not to be non-coding. My proposed work will identify many of these and predict their potential functions. Again, this could have important implications for cancer therapy, because such unusual proteins may be specific for cancer cells and therefore present promising therapeutic targets, especially for immunotherapy.In summary, I expect that my research will answer long-standing biological questions about how protein levels are regulated, and make a direct contribution towards understanding cancer and how to fight it.
期刊论文(9)
专著(0)
科研奖励(0)
会议论文
Low Cell Number Proteomic Analysis Using In-Cell Protease Digests Reveals a Robust Signature for Cell Cycle State Classification.
使用细胞内蛋白酶消化进行的低细胞数蛋白质组学分析揭示了细胞周期状态分类的稳健特征。
DOI:
10.1016/j.mcpro.2021.100169
发表时间:
2022-01
期刊:
Molecular & cellular proteomics : MCP
影响因子:
--
作者:
[Kelly V, Al-Rawi A, Lewis D, Kustatscher G, Ly T]
通讯作者:
Ly T
Mapping the invisible chromatin transactions of prophase chromosome remodelling
绘制前期染色体重塑的不可见染色质变化图
DOI:
10.1101/2021.06.21.449273
发表时间:
2021
期刊:
影响因子:
--
作者:
[Samejima I]
通讯作者:
Samejima I
2021BBSRC-NSF/BIO UniPlex - Genome-Wide Protein Complex Prediction and Validation
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批准号:BB/X002683/1
-
项目类别:Research Grant
-
资助金额:$38.18万
-
财政年份:2023
-
负责人:Georg Kustatscher
-
依托单位:
国内基金
海外基金
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