| Popis: |
Neurite outgrowth, one of the underlying cellular processes that defines the development and functionality of the mammalian nervous system, is also a sensitive indicator of neuronal cell health. From screening libraries of putative neurotherapeutic compounds to analyzing the millions of environmental pollutants for which we have inadequate neurotoxicity safety data, the large volume of chemical compounds that require evaluation is a major obstacle for manual imaging and analysis methods. In this context, high-content analysis (HCA) has emerged as a sensitive and accurate method for detecting changes in neuronal cell morphology within a format applicable to screening large chemical libraries. Advances in HCA technologies have enabled the automated imaging and quantitative analysis of neurite outgrowth morphology within a 96-well plate in less than 5 min. Traditionally, neurite outgrowth assessment has been conducted on immortalized cell lines such as pheochromocytoma (PC-12) cells that differentiate into neuron-like cells upon culture with nerve growth factor. Unfortunately, they do not retain all the in vivo characteristics of physiological neuronal tissue, including lack of synapse formation. As researchers refine neurite outgrowth quantitative analysis using HCA, an emerging question is how to quantify this biology in more complex models that more faithfully recapitulate in vivo environments. Primary neurons provide several benefits relative to neuronal cell lines, including the elaboration of axons from secondary dendrites and formation of both pre- and postsynaptic junctions. This chapter reviews techniques for evaluating neurite outgrowth using the ArrayScan HCA platform within a model system of primary cultures of rodent cerebellar granule cells. |
