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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
Paralog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,但它们序列上的微小和细微差异可以导致它们作用的特定调节。超过60%的人类蛋白质有并列关系,它们普遍存在于染色质蛋白复合体中。需要系统的序列到功能映射的方法来解开并列对数对的特定生物学角色和行为,而缺乏可扩展的方法限制了我们对不同并列对数函数的分子基础的理解。本项目的主要目的是了解Paralog蛋白对ARID1A/1B的差异序列-功能关系。这些蛋白质是DNA结合的多蛋白组合的亚基,称为SWI/SNF复合体,对许多基本功能非常重要,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来发挥作用,因此,表征蛋白质如何相互作用对于充分了解它们如何发挥作用很重要。在这个项目中,我们将识别与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,研究它们序列突变对细胞生长的影响,最后,整合所有数据来构建有助于理解ARID1A和1B功能机制的模型。为了鉴定ARID1A和1B相关蛋白质,我们将在保持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学的技术来鉴定与它们共同纯化的蛋白质。我们还将使用质谱学来识别翻译后修饰,即可以调节蛋白质功能的不同方面的小化学“标记”,如蛋白质活性、相互作用或定位等。为了确定结合区域,我们将使用覆盖在纸膜上的ARID1A和1B的整个长度的多肽或短蛋白质片段。加入细胞提取物,能够与多肽相互作用的蛋白质仍然与膜结合。然后对每个多肽斑点进行质谱分析,以确定结合的蛋白质。这一策略对于检测依赖于短基序的结合是最佳的。为了绘制依赖于ARID1A/B的3D结构的结合结构域,我们将使用一种结合彼此非常接近的蛋白质的“分子胶”来固定细胞内的相互作用。我们将使用质谱学来识别连接在一起的蛋白质区域。为了在没有paralog的情况下确定ARID1A/B中对细胞生长重要的氨基酸,我们将按顺序突变每个AA以产生丙氨酸并监测细胞增殖。最后,我们将合并所有数据,以生成表示所获得知识的综合视图的图表。这将有助于产生关于ARID1A/B如何以不同方式发挥其特定作用的假说。
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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