RESUMO
Heterozygous autosomal dominant mutations in the CXCR4 gene cause WHIM syndrome, a severe combined immunodeficiency disorder. The mutations primarily affect the C-terminal region of the CXCR4 chemokine receptor, specifically several potential phosphorylation sites critical for agonist (CXCL12)-mediated receptor internalization and desensitization. Mutant receptors have a prolonged residence time on the cell surface, leading to hyperactive signaling that is responsible for some of the symptoms of WHIM syndrome. Recent studies have shown that the situation is more complex than originally thought, as mutant WHIM receptors and CXCR4 exhibit different dynamics at the cell membrane, which also influences their respective cellular functions. This review examines the functional mechanisms of CXCR4 and the impact of WHIM mutations in both physiological and pathological conditions.
Assuntos
Mutação , Doenças da Imunodeficiência Primária , Receptores CXCR4 , Transdução de Sinais , Verrugas , Receptores CXCR4/genética , Receptores CXCR4/metabolismo , Humanos , Doenças da Imunodeficiência Primária/genética , Verrugas/genética , Animais , Imunodeficiência Combinada Severa/genética , Imunodeficiência Combinada Severa/imunologia , Trombocitopenia/genética , Quimiocina CXCL12/genética , Quimiocina CXCL12/metabolismoRESUMO
Current live-cell imaging techniques make possible the observation of live events and the acquisition of large datasets to characterize the different parameters of the visualized events. They provide new insights into the dynamics of biological processes with unprecedented spatial and temporal resolutions. Here we describe the implementation and application of a new tool called TrackAnalyzer, accessible from Fiji and ImageJ. Our tool allows running semi-automated single-particle tracking (SPT) and subsequent motion classification, as well as quantitative analysis of diffusion and intensity for selected tracks relying on the graphical user interface (GUI) for large sets of temporal images (X-Y-T or X-Y-C-T dimensions). TrackAnalyzer also allows 3D visualization of the results as overlays of either spots, cells or end-tracks over time, along with corresponding feature extraction and further classification according to user criteria. Our analysis workflow automates the following steps: (1) spot or cell detection and filtering, (2) construction of tracks, (3) track classification and analysis (diffusion and chemotaxis), and (4) detailed analysis and visualization of all the outputs along the pipeline. All these analyses are automated and can be run in batch mode for a set of similar acquisitions.