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Extended Neurite Outgrowth BioApplication Print E-mail
Catalog No. S50-0020-2
Description
The morphology of neuronal cells is modulated by a variety of stimuli such as neurotrophic factors, electrical activity, synaptogenesis, functional maturation and differentiation. The ability to employ a robust, automated method for rapid analysis of morphological changes in such cells is a valuable tool for screening groups. The Extended Neurite Outgrowth (ENO) BioApplication identifies neuronal and neuronal-like cells, quantifies their morphological features and reports a range of measurements to help identify treatments that affect neuronal morphology. Automated measurements include intensity values, overall morphology indicators such as cell shape and area, total and individual neurite length and number, and branch point count. The ENO BioApplication was designed to identify and compare subpopulations of neurons distinguished by the neurotransmitter or other specific protein(s) of interest they express, and report cell level and well level data for each identified subpopulation. Thus, it enables comparison of different cell subpopulations to detect important differences in cellular responses that would otherwise be obscured.

In most applications, cell nuclei are identified in the first channel while neuronal cell bodies and neurites are identified in the second channel. Neuronal cell subpopulations can be identified using markers in the third or fourth channels, as shown in Figure 1. Further adding to its flexibility, the ENO BioApplication performs cell-based measurements in up to six imaging channels, and cells are classified on the basis of average intensities. This BioApplication reports a full set of features for each subpopulation, allowing detailed comparison of different cells in the same assay.

In the figures below, the ENO BioApplication was used to detect and measure neurite outgrowth after stimulation of Thermo Scientific Cellomics NeuroscreenTM-1 cell line with nerve growth factor for 48 hours. The cells were fixed using standard methods and the nuclei were stained with Hoechst dye. Neurons and their neurites were labeled by immunofluorescence using the antibody provided in the Neurite Outgrowth HitKitTM HCS Reagent Kit that is specific for a protein present in both the neuronal cell body and the neurites. Figure 2 (left panel) shows analysis overlays and images from untreated Neuroscreen-1 cells showing basal levels of neurite outgrowth. In contrast, cells that have been treated with a maximal dose (200 ng/mL) of nerve growth factor exhibit process formation, as shown in the right panel.


The ENO BioApplication successfully distinguishes both conditions, and automatically extracts a number of quantitative features. The graph in Figure 3 illustrates the dose dependent increase in both Branch Point Count and Average Neurite Length as detected by the software, demonstrating the power of this BioApplication for detection of complex changes in neuronal morphology.


Features
  • Specifically identifies neuronal cells in a mixed culture and provides objective analysis of neurite outgrowth changes.
  • Reports several quantitative measures of neuronal morphology for single cells, including neurite length, cell body area, and the number of branch and cross points.
  • Analyzes and compares subpopulations of neuronal cells identified with different fluorescent markers.
  • Uses reference wells to automatically determine normal population distributions for a series of measurements and count “responders” to compound treatment.
  • Validated with both Thermo Scientific Cellomics NeuroscreenTM-1 cells and primary neuronal cultures.
  • Highly flexible for user-defined optimization and application across multiple cell types and assays.
Benefits
  • Automates a labor-intensive assay, providing results in hours instead of weeks.
  • Enables thorough analyses of the effects of biological and pharmacological agents on neuronal cells at the cell level.
  • Provides added sophistication to the traditional approach for neuronal analysis.
  • More objective than manual measurements, with improved reproducibility and reliability.

 
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