Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.747618
Title: The population response of hematopoietic stem cells differentiating into granulocytes
Author: Sri Raja, Lourdes Omesha
ISNI:       0000 0004 7231 8472
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2018
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Abstract:
The stepwise transition of a myeloid progenitor cell to a functional neutrophil requires cytokines and their cognate receptors to provide signalling input during each stage of differentiation. The aim of this project was to experimentally characterize the changing signalling events that occur during this process over a period of 17 days by obtaining dynamic time course data on intracellular signalling protein activation states. The steady state expression of phosphorylated and total levels of Erk1/2, PKB/Akt, STAT3 and STAT5 was measured at various time points throughout the differentiation process. Each of these reporter proteins characterises the signalling status of four distinct collateral signalling pathways activated by the GCSF receptor, a major regulator of the differentiation process. Once a data set had been obtained varied statistical inference methods were used to derive causal inferences between the activation states of these "beacon protein" signalling markers in order to identify possible novel mechanisms of direct or indirect crosstalk, between the signalling pathways. Interestingly some of the newly identified crosstalk interactions validated observations made in other experimental systems, and also suggested potential future experiments to follow up and validate further the inferred network. Understanding how to manipulate these signalling networks could have therapeutic value and these newly identified cross talk events could contribute to a deeper understanding of the cytokine-driven differentiation of stem cells required to achieve successful and useful interventions. In conclusion, the application of mathematical models and statistical inference algorithms to existing and novel experimental data sets has enabled novel conclusions to be drawn about signalling and protein interaction dynamics in the regulation of protein cellular decisions in a heterogeneous population of cells.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.747618  DOI: Not available
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