English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

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

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.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-000E-EC60-5 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-000E-EC61-3
Genre: Journal Article

Files

show Files
hide Files
:
Andres.pdf (Publisher version), 584KB
Name:
Andres.pdf
Description:
-
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
© 2012 Andres et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
License:
-

Locators

show

Creators

show
hide
 Creators:
Andres, Christine1, Author              
Hasenauer, Jan2, Author
Allgower, Frank2, Author
Hucho, Tim1, Author              
Affiliations:
1Signal 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, Berlin, Germany, ou_1479646              
2Institute for Systems Theory and Automatic Control, University of Stuttgart, Stuttgart, Germany, ou_persistent22              

Content

show
hide
Free keywords: -
 Abstract: 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.

Details

show
hide
Language(s): eng - English
 Dates: 2012-03-27
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1371/journal.pone.0034257
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: PLoS One
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: San Francisco, CA : Public Library of Science
Pages: - Volume / Issue: 7 (3) Sequence Number: - Start / End Page: e34257 - e34257 Identifier: ISSN: 1932-6203
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000277850