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Understanding the dynamic regulation of SOCS3

Authors: Kalenderoglou, Nikoletta;

Understanding the dynamic regulation of SOCS3

Abstract

In the past two decades, it has become evident that signal transduction pathways are more than two dimensional pathways consisted of proteins that are just activated or supressed in response to distinct cues. Instead, the dynamic nature of key proteins regulates the strength and quality of the signal. Several key signal transduction pathways are controlled by negative feedback loops that are highly dynamic and demonstrate oscillatory behaviours. Negative feedback regulation of the JAK/STAT pathway by Suppressors of Cytokine Signalling (SOCS) is an example of oscillatory signalling. We sought to investigate the oscillatory capacity of the tumour suppressor protein SOCS3 and its role in important cellular functions using whole-cell population and single-cell analysis. An important aspect of cell biology using experimental cell-population techniques is to produce a synchronized cell culture. Serum starvation and subsequent shock is able to capture the oscillatory behaviour of SOCS3 protein to some extent. However, the average response in whole-cell population systems demonstrated to be ‘noisy’ leading to establishment of a single-cell analysis system. To investigate SOCS3 oscillation at the single cell level, we first attempted to generate cell clones stably expressing SOCS3 C-terminal GFPSpark fusion protein from its respective endogenous promoter to monitor its expression in real time with confocal microscopy. Despite careful optimization of each step of CRISPR/Cas9 strategy, the generation of GFPSpark knockin cell line was not successful. Finally, we utilised the tandem fluorescent protein timer (tFT) strategy to investigate localisation and trafficking of SOCS3 protein and monitor its promoter activity in response to different stimuli. The use of tFT provided us the ability to analyse SOCS3 dynamics across spatial and temporal dimensions under either normal culture conditions or different treatments that are known to influence on SOCS3 half-life and degradation rates.

Keywords

dynamic, CRISPR/Cas-9, synchronisation, Fluorescent timer, pSTAT3, tandem, Ultradian, SOCS3, oscillation, Gaussian process regression

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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