| Autor: |
Hwang Eric, Poplawski Gunnar, Dehmelt Leif, Halpain Shelley |
| Jazyk: |
angličtina |
| Rok vydání: |
2011 |
| Předmět: |
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| Zdroj: |
BMC Neuroscience, Vol 12, Iss 1, p 100 (2011) |
| Druh dokumentu: |
article |
| ISSN: |
1471-2202 |
| DOI: |
10.1186/1471-2202-12-100 |
| Popis: |
Abstract Background To date, some of the most useful and physiologically relevant neuronal cell culture systems, such as high density co-cultures of astrocytes and primary hippocampal neurons, or differentiated stem cell-derived cultures, are characterized by high cell density and partially overlapping cellular structures. Efficient analytical strategies are required to enable rapid, reliable, quantitative analysis of neuronal morphology in these valuable model systems. Results Here we present the development and validation of a novel bioinformatics pipeline called NeuriteQuant. This tool enables fully automated morphological analysis of large-scale image data from neuronal cultures or brain sections that display a high degree of complexity and overlap of neuronal outgrowths. It also provides an efficient web-based tool to review and evaluate the analysis process. In addition to its built-in functionality, NeuriteQuant can be readily extended based on the rich toolset offered by ImageJ and its associated community of developers. As proof of concept we performed automated screens for modulators of neuronal development in cultures of primary neurons and neuronally differentiated P19 stem cells, which demonstrated specific dose-dependent effects on neuronal morphology. Conclusions NeuriteQuant is a freely available open-source tool for the automated analysis and effective review of large-scale high-content screens. It is especially well suited to quantify the effect of experimental manipulations on physiologically relevant neuronal cultures or brain sections that display a high degree of complexity and overlap among neurites or other cellular structures. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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