Handal Marquez, Paola; (2019) Sampling the Functional Sequence Neighbourhood of Phi29 DNA Polymerase for XNA Synthesis. Masters thesis (M.Phil), UCL (University College London).

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Abstract

Xenobiotic nucleic acids are unnatural analogues of DNA (and RNA) of great biotechnological and pharmaceutical interest. Their chemical synthesis is highly challenging and expensive, rendering the discovery of functional XNAs impractical. Enzymatic synthesis of XNA is a viable alternative but is limited by the low efficiency and low substrate selectivity of the currently available engineered XNA polymerases. A better understanding of the functional space of polymerases is needed to improve their engineering. Directed evolution techniques were implemented to map the sequence-function relationships of phi29 DNA polymerase (phi29 DNAP) in the process of evolving a more efficient HNA polymerase. Phi29 DNAP is a small and well-characterised polymerase with remarkable processivity and limited HNA synthesis activity. Diversity in phi29 DNAP was introduced through insertions and deletions, multiple-site saturation mutagenesis and random mutagenesis, targeting different subdomains of the enzyme. Libraries were partitioned through compartmentalised self-tagging (CST), a functional selection platform for XNA synthetases. A single round of selection did not substantially alter the overall activity of libraries for HNA synthesis, and variants isolated in screening were of comparable activity to the wild-type enzyme. Nevertheless, the results give insight into the functional landscape of phi29 DNAP. Deep sequencing of the libraries used in selection was used to quantify the functional consequence of sequence variation and investigate signs of epistasis for HNA synthesis. Variants that were enriched more than the wild-type, with potentially enhanced HNA synthesis activity, as well as variants that were significantly depleted were identified, both of which contribute to our understanding of the functional sequence space of phi29 DNAP. Altogether, the directed evolution and deep mutational scanning approaches implemented could be used to develop a new generation of more efficient XNA polymerases.

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