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Unravelling SWI/SNF ARID1A/B paralogs function at sequence resolution

Unravelling SWI/SNF ARID1A/B paralogs function at sequence resolution
在序列分辨率下揭示 SWI/SNF ARID1A/B 旁系同源物功能
批准号:
BB/Y004477/1
负责人:
Jyoti Choudhary
金额:
$113.67万
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2024
资助国家:
英国
项目状态:
未结题
起止时间:
2024 至 --

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中文摘要
翻译
同源蛋白是通过基因复制事件产生的,它们在序列和结构上非常相似,并具有相关的功能,但它们序列的微小差异可导致其作用的特异性调节。超过60%的人类蛋白质有类似物,它们普遍存在于染色质蛋白复合物中。需要系统的序列到功能映射方法来解开平行对的特定生物学作用和行为,缺乏可扩展的方法,这限制了我们对发散平行功能的分子基础的理解。本项目的总体目标是了解平行蛋白对ARID1A/1B的差异序列-功能关系。这些蛋白质是DNA结合多蛋白组合的亚基,被称为SWI/SNF复合物,对许多基本功能至关重要,包括细胞增殖、细胞周期控制、对DNA损伤的反应和生物体发育。大多数蛋白质通过与其他蛋白质结合而起作用,因此描述蛋白质如何相互作用对于充分理解它们如何发挥作用非常重要。在这个项目中,我们将鉴定与ARID1A和1B相互作用的蛋白质,绘制介导相互作用的结构域或基序,研究其序列突变对细胞生长的影响,最后,整合所有数据构建有助于理解ARID1A和1B功能机制的模型。为了鉴定ARID1A和1B相关蛋白,我们将在保持ARID1A/B与特异性识别它们的抗体的天然相互作用的条件下纯化ARID1A/B,并使用一种称为质谱的技术来鉴定与它们共纯化的蛋白。我们还将使用质谱法来识别翻译后修饰,可以调节蛋白质功能不同方面的小化学“标志”,如蛋白质活性,相互作用或定位等。为了确定结合域,我们将使用肽或短蛋白片段,覆盖ARID1A和1B的整个长度,排列在纸膜上。加入细胞提取物后,可以与肽相互作用的蛋白质仍然与膜结合。然后,每个肽点将通过质谱分析来识别结合的蛋白质。这种策略对于检测依赖于短基序的结合是最优的。为了绘制依赖ARID1A/B三维结构的结合域,我们将使用一种“分子胶”来固定细胞内的相互作用,这种“分子胶”可以结合彼此非常接近的蛋白质。我们将使用质谱法来确定连接在一起的蛋白质区域。为了确定ARID1A/B中在平行体缺失时对细胞生长重要的氨基酸,我们将按顺序将每个aa突变为丙氨酸并监测细胞增殖。最后,我们将合并所有的数据来生成一个表示所获得知识的集成视图的图。这将有助于产生关于ARID1A/B如何不同地执行其特定角色的假设。
英文摘要
Paralog proteins emerged through gene duplication events, they are very similar in sequence and structure and have related functions, but small and subtle differences in their sequences can lead to specific modulation of their roles. More than 60% of human proteins have paralogs and they are prevalent in chromatin protein complexes. Systematic approaches for sequence to function mapping are required to disentangle the specific biological roles and behaviours of the paralog pairs, and lack of scalable methods for this has limited our understanding of the molecular basis of diverging paralog functions. The overarching aim of this project is to understand differential sequence-function relationships of paralog protein pair ARID1A/1B. These proteins are subunits of DNA-binding multiprotein assemblies called SWI/SNF complexes that are important for many essential functions, including cell proliferation, cell cycle control, response to DNA damage and organism development. Most proteins work by associating with other proteins, so characterising how proteins interact is important for fully understanding how they perform their roles. In this project we will identify the proteins that ARID1A and 1B interact with, mapping the domains or motifs that mediate the interactions, investigating the effect of mutations in their sequence on cell growth and finally, integrating all the data to construct models that can be helpful for understanding the mechanisms of ARID1A and 1B function.To identify ARID1A and 1B associated proteins we will purify ARID1A/B in conditions that maintain the native interactions with antibodies that specifically recognise them and use a technique called mass spectrometry to identify proteins that co-purify with them. We will also use mass spectrometry to identify post-translational modifications, small chemical "flags" that can regulated different aspects of protein function, like protein activity, interactions or locatlisation amongst others. To identify binding domains we will use peptides, or short protein fragments, covering the entire length of ARID1A and 1B arrayed on a paper membrane. A cell extract is added, and proteins that can interact with the peptides remain bound to the membrane. Each peptide spot will then be analysed by mass spectrometry to identify the bound proteins. This strategy is optimal to detect binding dependent on short motifs. To map binding domains that depend on the 3D structure of ARID1A/B we will fix the interactions inside the cell using a "molecular glue" that binds proteins that are very close to each other. We will use mass spectrometry to identify the regions of the proteins that were linked together. To identify aminoacids in ARID1A/B that are important for cell growth when the paralog is absent, we will mutate each aa sequentially to alanine and monitor cell proliferation. Finally, we will consolidate all the data to produce a graph that represents an integrated view of the knowledge acquired. This will be useful to generate hypothesis on how ARID1A/B differentially perform their specific roles.
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