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Threshold-free population analysis identifies larger DRG neurons to respond stronger to NGF stimulation

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons50067

Andres,  Christine
Signal Transduction in Mental Retardation and Pain (Tim Hucho), Dept. of Human Molecular Genetics (Head: Hans-Hilger Ropers), Max Planck Institute for Molecular Genetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons50297

Hucho,  Tim
Signal Transduction in Mental Retardation and Pain (Tim Hucho), Dept. of Human Molecular Genetics (Head: Hans-Hilger Ropers), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Andres.pdf
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Zitation

Andres, C., Hasenauer, J., Allgower, F., & Hucho, T. (2012). Threshold-free population analysis identifies larger DRG neurons to respond stronger to NGF stimulation. PLoS One, 7(3), e34257-e34257. doi:10.1371/journal.pone.0034257.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000E-EC60-5
Zusammenfassung
Sensory neurons in dorsal root ganglia (DRG) are highly heterogeneous in terms of cell size, protein expression, and signaling activity. To analyze their heterogeneity, threshold-based methods are commonly used, which often yield highly variable results due to the subjectivity of the individual investigator. In this work, we introduce a threshold-free analysis approach for sparse and highly heterogeneous datasets obtained from cultures of sensory neurons. This approach is based on population estimates and completely free of investigator-set parameters. With a quantitative automated microscope we measured the signaling state of single DRG neurons by immunofluorescently labeling phosphorylated, i.e., activated Erk1/2. The population density of sensory neurons with and without pain-sensitizing nerve growth factor (NGF) treatment was estimated using a kernel density estimator (KDE). By subtraction of both densities and integration of the positive part, a robust estimate for the size of the responsive subpopulations was obtained. To assure sufficiently large datasets, we determined the number of cells required for reliable estimates using a bootstrapping approach. The proposed methods were employed to analyze response kinetics and response amplitude of DRG neurons after NGF stimulation. We thereby determined the portion of NGF responsive cells on a true population basis. The analysis of the dose dependent NGF response unraveled a biphasic behavior, while the study of its time dependence showed a rapid response, which approached a steady state after less than five minutes. Analyzing two parameter correlations, we found that not only the number of responsive small-sized neurons exceeds the number of responsive large-sized neurons--which is commonly reported and could be explained by the excess of small-sized cells--but also the probability that small-sized cells respond to NGF is higher. In contrast, medium-sized and large-sized neurons showed a larger response amplitude in their mean Erk1/2 activity.