| Summary: | The DNA in every cell of the human body is subject to a barrage of exogenous and endogenous mutagens, causing tens of thousands of DNA lesions per cell, per day. To counteract this assault, cells have evolved a network of proteins that work to detect and repair the DNA lesions, collectively known as the DNA damage response (DDR). Despite the actions of the DDR, DNA damage can persist and may lead to changes to the genetic code, in the form of missense, nonsense and silent mutations and chromosomal rearrangements. Mutagenesis in this manner contributes to diseases such as cancer and accelerated ageing. Therefore, preserving genomic integrity is of paramount importance for the health of the organism. In this thesis, I focus on the functional consequences of missense mutations, defined as base pair substitutions altering the amino acid coded for by the codon. The alternative amino acid incorporated into the protein, termed a ‘variant’, may cause disruption to protein activity depending on its location and characteristics. Disruption to protein activity can contribute to carcinogenesis, and is often used to stratify patients forming the basis for specific lines of treatment. Currently, a plethora of methods exist for interpreting the consequences of variants on protein function, but often lack a physiological readout or are limited in their throughput. Here, I describe a new method that provides an efficient, high-throughput means of assessing the impact of variants on protein function. It is based on complementation of a specific human gene knockout cell phenotype, by expression of a series of vertebrate orthologues with increasing evolutionary distance from human. Due to the natural variation of amino acid residues observed in orthologue sequences, full complementation with any given orthologue could reveal variants tolerated by the human protein at certain positions. Here, I test this methodology using proteins from the DDR, due to their extensive cross-species conservation, mutation in diseases such as cancer and relevance to synthetic lethality-based treatments. I show that this method can identify functional variants in DDR genes, as well as determining the importance of previously identified post-translational modification (PTM) sites. Collectively, this method is able to provide insight into impact of amino acid variants on protein function, which offers clinical benefits as well as furthering our understanding of protein regulation.
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