Predicting dominant mutations in genetic disorders associated with the misassembly of cytoskeletal proteins

微管蛋白是微管的组成部分，它执行一系列不同的功能，包括有丝分裂和分子运输过程中的染色体对齐。因此，微管蛋白突变与许多表型有关，例如神经元紊乱和对化疗的抵抗。该项目的第一部分涉及在细胞水平上从空间和数量上确定不同微管蛋白亚型的性质。每种同工型都可以用荧光显微镜观察，提供关于其特定定位的信息，以及细胞周期特定阶段的持续时间和强度。此外，还将开发利用神经细胞作为系统来进一步研究微管蛋白亚型的技术。为了确定微管蛋白突变导致致病的机制，我将重点放在微管蛋白βIII和βIV上。然后，该项目将继续进行体外重组和纯化单个微管蛋白亚型，其中可以替代不同的亚型，从而分析微管功能的差异。为了实现这一点，微管蛋白将在真核细胞Sf9中重组表达，并通过亲和纯化进行纯化。然后，这种微管蛋白将被用于使用TIRF显微镜对单个微管进行体外重建分析，以确定不同的同种类型是否影响微管动力学。微管蛋白突变体也将与之一起表达和纯化。为了测试微管蛋白亚型是否也调节微管运动和在微管上的停留时间，将使用实验室现有的马达进行定量分析来测量分子马达运输，并通过生化分析来检测与其他非运动型微管相关蛋白(MAP)的相互作用。通过这项工作，我预计将确定与微管蛋白βIII和βIV突变相关的致病性潜在的分子机制。下一阶段涉及使用生物信息学方法对先前实验工作强调的相关亚型的突变进行计算分析。映射到最近可用的微管结构上的广泛的人类变异将用于这一点，优先考虑以前没有通过这种方法预测的致病突变。为此目的，也可以采用患者基因组数据、多序列比对和分子建模技术等工具，其中这些方法所指出的最具致病性的突变将被纳入实验工作。这包括直接将含有优先致病突变的神经细胞与野生型进行比较，在野生型中，微管功能如前所述进行检查。将生物信息学方法所强调的突变应用于这项实验工作，将使大多数致病突变得以确定，因为它们也将在生物模型中得到验证。最后，使用生物信息学和实验方法在整个项目中收集的数据可以整合到机器学习方法中。这将导致设计一种算法，能够预测哪些微管蛋白突变最有可能导致神经元紊乱或对紫杉醇产生耐药性。

Tubulin is the building block of microtubules, which carry out a diverse set of functions including chromosomal alignment during mitosis and molecular trafficking. Therefore tubulin mutations are linked to a number of phenotypes such as neuronal disorders and resistance to chemotherapy. The first part of the project involves defining the properties of different tubulin isotypes at the cellular level spatially and quantitatively. Each isotype can be visualised using fluorescence microscopy, giving information about its particular localisation as well as the duration and intensity during specific phases of the cell cycle. Alongside this, techniques will be developed to use neuronal cells as a system to study tubulin isotypes further. To define the mechanism of tubulin mutations that results in pathogenicity, I will focus on tubulin beta III and beta IV.The project will then move on to reconstituting and purifying single tubulin isoforms in vitro, where different isoforms can be substituted allowing differences in microtubule function to be analysed. To achieve this, tubulin will be recombinantly expressed in eukaryotic Sf9 cells and purified using affinity purification. This tubulin will then be used in reconstitution assays to be performed in vitro on individual microtubules using TIRF microscopy to define whether different isotypes influence microtubule dynamics. Tubulin mutants will also be expressed and purified alongside. To test whether tubulin isotype also regulates microtubule motor motility and residency time on microtubule, quantitative analysis will be performed to measure molecular motor transport using available motors in the lab and biochemical assays to detect interactions with other non-motor microtubule-associated proteins (MAPs). From this work, I anticipate to define the molecular mechanism underlying the pathogenicity associated with tubulin beta III and beta IV mutations.The next phase involves the use of bioinformatics approaches to computationally analyse mutations in relevant isoforms highlighted by the previous experimental work. A wide array of human variants mapped onto the recently available microtubule structures will be used for this, prioritising pathogenic mutations that have not been predicted by such methods previously. Tools such as patient genome data, multiple sequence alignments and molecular modelling techniques can also be incorporated for this purpose, where mutations indicated to be the most pathogenic by these methods will be taken into experimental work. This comprises directly comparing neuronal cells containing the prioritised pathogenic mutations to wild type where microtubule function is examined as previously described. Applying the mutations highlighted by the bioinformatics approaches into this experimental work will allow the most pathogenic mutations to be determined as they would also be validated within a biological model. Finally, data gathered throughout the project using both bioinformatics and experimental approaches can be integrated into machine learning methods. This will lead to the design of an algorithm that is able to predict which tubulin mutations are most likely to cause neuronal disorders or confer resistance to taxol.