Σφακιανάκης Αλέξανδρος
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Κυριακή 6 Αυγούστου 2017

High content analysis of phagocytic activity and cell morphology with PuntoMorph

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Publication date: Available online 5 August 2017
Source:Journal of Neuroscience Methods
Author(s): Hassan Al-Ali, Han Gao, Camilla Dalby-Hansen, Vanessa Ann Peters, Yan Shi, Roberta Brambilla
BackgroundPhagocytosis is essential for maintenance of normal homeostasis and healthy tissue. As such, it is a therapeutic target for a wide range of clinical applications. The development of phenotypic screens targeting phagocytosis has lagged behind, however, due to the difficulties associated with image-based quantification of phagocytic activity.New methodWe present a robust algorithm and cell-based assay system for high content analysis of phagocytic activity. The method utilizes fluorescently labeled beads as a phagocytic substrate with defined physical properties. The algorithm employs statistical modeling to determine the mean fluorescence of individual beads within each image, and uses the information to conduct an accurate count of phagocytosed beads. In addition, the algorithm conducts detailed and sophisticated analysis of cellular morphology, making it a standalone tool for high content screening.ResultsWe tested our assay system using microglial cultures. Our results recapitulated previous findings on the effects of microglial stimulation on cell morphology and phagocytic activity. Moreover, our cell-level analysis revealed that the two phenotypes associated with microglial activation, specifically cell body hypertrophy and increased phagocytic activity, are not highly correlated. This novel finding suggests the two phenotypes may be under the control of distinct signaling pathways.Comparison with existing methodsWe demonstrate that our assay system outperforms preexisting methods for quantifying phagocytic activity in multiple dimensions including speed, accuracy, and resolution.ConclusionsWe provide a framework to facilitate the development of high content assays suitable for drug screening. For convenience, we implemented our algorithm in a standalone software package, PuntoMorph.



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