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Biology subjects

George, G.

Publications and source records attributed to George, G..

2 recordsLinked to original sources

A Fyn - specific biosensor reveals localized, pulsatile kinase activity and spatially regulated signaling crosstalk

Cell behavior is controlled through spatio-temporally localized protein activity. Despite unique and often contradictory roles played by Src-family-kinases (SFKs) in regulating cell physiology, activity patterns of individual SFKs have remained elusive. Here, we report a biosensor for specifically visualizing active conformation of SFK-Fyn in live cells. We deployed combinatorial library screening to isolate a binding-protein (F29) targeting activated Fyn. Nuclear-magnetic-resonance (NMR) analysis provides the structural basis of F29 specificity for Fyn over homologous SFKs. Using F29, we engineered a sensitive, minimally-perturbing fluorescence-resonance-energy-transfer (FRET) biosensor (FynSensor) that reveals cellular Fyn activity to be spatially localized, pulsatile and sensitive to adhesion/integrin signaling. Strikingly, growth factor stimulation further enhanced Fyn activity in pre-activated intracellular zones. However, inhibition of focal-adhesion-kinase activity not only attenuates Fyn activity, but abolishes growth-factor modulation. FynSensor imaging uncovers spatially-organized, sensitized signaling clusters, direct crosstalk between integrin and growth-factor-signaling, and clarifies how compartmentalized Src-kinase activity may drive cell fate.

cell biology

PheGWAS: A new dimension to visualize GWAS across multiple phenotypes

MotivationPheGWAS was developed to enhance exploration of phenome-wide pleiotropy at the genome-wide level through the efficient generation of a dynamic visualization combining Manhattan plots from GWAS with PheWAS to create a three-dimensional "landscape". Pleiotropy in sub-surface GWAS significance strata can be explored in a sectional view plotted within user defined levels. Further complexity reduction is achieved by confining to a single chromosomal section. Comprehensive genomic and phenomic coordinates can be displayed. ResultsPheGWAS is demonstrated using summary data from Global Lipids Genetics Consortium (GLGC) GWAS across multiple lipid traits. For single and multiple traits PheGWAS highlighted all eight-eight and sixty-nine loci respectively. Further, the genes and SNPs reported in GLGC were identified using additional functions implemented within PheGWAS. Not only is PheGWAS capable of identifying independent signals but also provide insights to local genetic correlation (verified using HESS) and in identifying the potential regions that share causal variants across phenotypes (verified using colocalization tests). Availability and ImplementationThe PheGWAS software and code are freely available at (https://github.com/georgeg0/PheGWAS). Contacta.doney@dundee.ac.uk, g.z.george@dundee.ac.uk

bioinformatics