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

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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.