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Unraveling the design principles of endocytosis and signaling using multi‐parametric image analysis.
Author(s) -
Zerial Marino
Publication year - 2007
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.21.5.a150
Subject(s) - endocytosis , endosome , endocytic cycle , microbiology and biotechnology , high content screening , computational biology , biology , computer science , intracellular , cell , genetics
Endocytosis is an essential process serving multiple key cellular functions, such as nutrient uptake, regulation of signal transduction, synaptic transmission and defense against pathogens. To elucidate the molecular design principles underlying endocytosis we developed a pipeline of high‐content and high‐throughput microscopy‐based assays, genome‐wide RNAi screening, automated image analysis and bioinformatics, aimed at identifying new genes required for endocytosis in human cells. Non‐supervised learning algorithms for phenotype definition and recognition were developed for this project. Over 40 measured parameters provide a quantitative description of endosomal compartment morphology and function (e.g. size of endosomes, shape, density of endosomal machinery, cargo content, intracellular distribution, colocalization between cargo and compartment markers, etc). Fast live cell imaging by high‐resolution video‐microscopy and novel image analysis algorithms, including particle detection and tracking algorithms, and a set of statistical procedures revealed novel properties of the endocytic transport machinery. This multi‐parametric analytical platform is used to develop a mathematical model that can quantitatively predict endosome dynamics and signaling properties under various physiological and pathological conditions.