4.7 Article

Toponomics Analysis of Drug-Induced Changes in Arachidonic Acid-Dependent Signaling Pathways during Spinal Nociceptive Processing

Journal

JOURNAL OF PROTEOME RESEARCH
Volume 8, Issue 10, Pages 4851-4859

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/pr900106v

Keywords

Toponome; protein networks; immunohistochemistry; dipyrone; lipoxygenase; arachidonic acid; pain; spinal cord

Funding

  1. DFG [SCHO817-1, SCHO817-2]
  2. LOEWE Lipid Signaling Forschungszentrum Frankfurt (LIFF)
  3. [GE695]

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Multi-Epitope-Ligand-Carthography (MELC) allows consecutive immunohistochemical visualization of up to 100 proteins on the same tissue sample. Subsequent biomathematical analysis of these images allows a quantitative description of changes in protein networks. We used the MELC technology to study the effect of the nonopioid analgesic drug dipyrone on protein network profiles associated with arachidonic acid-dependent signaling pathways. MELC analysis with 31 different fluorescence-labeled tags was used to compare the effect of dipyrone on protein networks in spinal cords of mice with zymosan-induced hyperalgesia, a common model for inflammatory pain. We found that the number of motifs which describe the colocalization of 5-lipoxygenase (5-LO) or 12-LO with other proteins increased disproportionally after dipyrone treatment. Activation of 5-LO and 12-LO induces their translocation to membrane compartments which was also reflected by MELC results. Although no changes in 5-LO or 12-LO expression were seen by Western blot analysis or by immunohistochemistry in spinal cords of dipyrone-treated mice, the activation of both enzymes was verified by determining LO-products. Spinal amounts of 5(S)-hydroxyeicosatetraenoic acid (HETE) and 12(S)-HETE, which are generated by 5-LO and 12-LO, respectively, were significantly increased in spinal cords of dipyrone-treated animals. In primary spinal cord neurons, dipyrone selectively and dose-dependently increased 5(S)-(HETE) and 12(S)-HETE synthesis. Thus, we show for the first time that monitoring protein network profiles by topological proteomic analysis is a useful tool to identify mechanisms of drug actions.

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