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Au cours de ce travail, nous nous sommes intéressés au rôle de vésicules dérivées des mitochondries dans la maturation des endosomes. Au sein du laboratoire, il a été observé que des protéines de la membrane externe mitochondriale (MEM) étaient recrutées au niveau des endosomes précoces dans des cellules endothéliales en réponse à un traitement au VEGF, un facteur de croissance impliqué de manière majoritaire dans la régulation de l’angiogenèse. Les contacts entre la mitochondrie et des organelles telles que les endosomes, les lysosomes ou la membrane plasmique étant reconnus, nous nous sommes intéressés aux contacts établis entre les endosomes et les mitochondries. Nous avons observé que des contacts pouvaient s’établir via la production de structures semblant dériver des mitochondries (porteuses du marqueur TOM20 typique de la MEM) suite au traitement au VEGF. La caractérisation du contenu protéique de ces structures suite au développement d’un protocole de purification nous a permis d’identifier différents cargos, dont certains se retrouvaient également au niveau des endosomes précoces après un traitement au VEGF. Nous avons essayé de comprendre le rôle de ces vésicules TOM20+ en ciblant des acteurs nécessaires pour leur biogenèse ou leur trafic intracellulaire (les protéines VPS34 ou Syntaxine 17). Leur diminution d’expression nous a permis d’observer une altération du recrutement endosomal des protéines de la MEM dans ces conditions. Par ailleurs, nous avons pu déterminer que ces protéines VPS34 et Syntaxine 17 sont des inhibiteurs de l’angiogenèse in vitro. Finalement, nous avons démontré que ces vésicules TOM20+ permettent le recrutement de la protéine RAB5 dans le compartiment endosomal, ce qui permet la maturation des endosomes précoces en endosomes tardifs.
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This Special Issue of Entropy, titled “Recent Advances in Single-Particle Tracking: Experiment and Analysis”, contains a collection of 13 papers concerning different aspects of single-particle tracking, a popular experimental technique that has deeply penetrated molecular biology and statistical and chemical physics. Presenting original research, yet written in an accessible style, this collection will be useful for both newcomers to the field and more experienced researchers looking for some reference. Several papers are written by authorities in the field, and the topics cover aspects of experimental setups, analytical methods of tracking data analysis, a machine learning approach to data and, finally, some more general issues related to diffusion.
diauxic growth --- replicator equation --- mesoscopic model --- integro-differential equations --- anomalous diffusion --- statistical analysis --- single-particle tracking --- trajectory classification --- fractional Brownian motion --- estimation --- autocovariance function --- neural network --- Monte Carlo simulations --- multifractional Brownian motion --- power of the statistical test --- machine learning classification --- feature engineering --- confinement --- information theory --- Brownian particle --- stochastic thermodynamics --- CTRW --- diffusing-diffusivity --- occupation time statistics --- wound healing dynamics --- single pseudo-particle tracking --- phase contrast image segmentation --- 3D single-particle tracking --- Fisher information --- non-uniform illumination --- SPT --- deep learning --- residual neural networks --- random walk --- heterogeneous --- endosomes --- single particle trajectory --- stochastic processes --- trapping
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This Special Issue of Entropy, titled “Recent Advances in Single-Particle Tracking: Experiment and Analysis”, contains a collection of 13 papers concerning different aspects of single-particle tracking, a popular experimental technique that has deeply penetrated molecular biology and statistical and chemical physics. Presenting original research, yet written in an accessible style, this collection will be useful for both newcomers to the field and more experienced researchers looking for some reference. Several papers are written by authorities in the field, and the topics cover aspects of experimental setups, analytical methods of tracking data analysis, a machine learning approach to data and, finally, some more general issues related to diffusion.
Research & information: general --- Physics --- diauxic growth --- replicator equation --- mesoscopic model --- integro-differential equations --- anomalous diffusion --- statistical analysis --- single-particle tracking --- trajectory classification --- fractional Brownian motion --- estimation --- autocovariance function --- neural network --- Monte Carlo simulations --- multifractional Brownian motion --- power of the statistical test --- machine learning classification --- feature engineering --- confinement --- information theory --- Brownian particle --- stochastic thermodynamics --- CTRW --- diffusing-diffusivity --- occupation time statistics --- wound healing dynamics --- single pseudo-particle tracking --- phase contrast image segmentation --- 3D single-particle tracking --- Fisher information --- non-uniform illumination --- SPT --- deep learning --- residual neural networks --- random walk --- heterogeneous --- endosomes --- single particle trajectory --- stochastic processes --- trapping
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