(BfH) How do signalling networks control host-pathogen interactions?

Lead Research Organisation: University of Edinburgh
Department Name: Sch of Biological Sciences

Abstract

Protein phosphorylation is a key regulatory process that controls many aspects of eukaryotic life. Both free living and pathogenic organisms employ phosphorylation regulated signalling networks to adapt and respond to their environment. Apicomplexan parasites, including Plasmodium, which is the causative agent of malaria, Toxoplasma and Eimeria have complex life cycles involving differentiation between asexual stages causing disease and the sexual stages necessary for transmisssion (Philip et al, 2012; Philip and Haystead, 2007). Signalling networks are critical for these steps and, although the biology of the asexual and sexual stages is remarkably different, several signalling master regulators are expressed and appear to function in both stages. Due to inadequate genetic tools, it was difficult to examine the precise function of phosphorylation-modulating enzymes essential for both asexual and sexual stages of the parasite. However, we have recently established a tool for conditional regulation of protein levels of phosphorylation regulators in in vivo laboratory models of malaria (Philip and Waters, 2015). This tool revealed crucial roles for a parasite calcium-dependent protein phosphatase, Calcineurin, in regulating parasite colonization of both the host and vector. However the identities of the phosphatase's associated regulators and substrates remain elusive. Mapping the identity and function of Calcineurin effectors will reveal how these signalling networks are rewired in the two diverse life-cycle stages of the parasite.
In this PhD project you will engage in innovative chemical-genetic and proteomic strategies to uncover signalling enzymes required for different lifecycle stages of the malaria parasite and, in turn discover identities of their substrates and regulators. You will integrate the data generated and use bioinformatics approaches to construct and model signalling networks to gain better understanding of pathways essential for malaria parasite infection and transmission.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
BB/M010996/1 01/10/2015 31/03/2024
2672483 Studentship BB/M010996/1 01/10/2019 31/12/2023