Rapid and easy semi-quantitative evaluation method for diacylglycerol and inositol-1,4,5-trisphosphate generation in orexin receptor signalling

Authors

  • M. E. Ekholm,

    1.  Unit of Physiology, Department of Neuroscience, Uppsala University, Uppsala, Sweden
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  • L. Johansson,

    1.  Unit of Physiology, Department of Neuroscience, Uppsala University, Uppsala, Sweden
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  • J. P. Kukkonen

    1.  Unit of Physiology, Department of Neuroscience, Uppsala University, Uppsala, Sweden
    2.  Department of Basic Veterinary Sciences, University of Helsinki, Helsinki, Finland
    3.  Department of Biology, Åbo Akademi University, Turku, Finland
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J. Kukkonen, Department of Basic Veterinary Sciences, University of Helsinki, POB 66, 00014 Helsinki, Finland. E-mail: jyrki.kukkonen@helsinki.fi

Abstract

Aim:  Fluorescent protein-based indicators have enabled measurement of intracellular signals previously nearly inaccessible for studies. However, indicators showing intracellular translocation upon response suffer from serious limitations, especially the very time-consuming data collection. We therefore set out in this study to evaluate whether fixing and counting cells showing translocation could mend this issue.

Methods:  Altogether three different genetically encoded indicators for diacylglycerol and inositol-1,4,5-trisphosphate were transiently expressed in Chinese hamster ovary cells stably expressing human OX1 orexin receptors. Upon stimulation with orexin-A, the cells were fixed with six different protocols.

Results:  Different protocols showed clear differences in their ability to preserve the indicator’s localization (i.e. translocation after stimulus) and its fluorescence, and the best results for each indicator were obtained with a different protocol. The concentration–response data obtained with cell counting are mostly comparable to the real-time translocation and biochemical data.

Conclusion:  The counting method, as used here, works at single time point and looses the single-cell-quantitative aspect. However, it also has some useful properties. First, it easily allows processing of a 100- to 1000-fold higher cell numbers than real-time imaging producing statistically consistent population-quantitative data much faster. Secondly, it does not require expensive real-time imaging equipment. Fluorescence in fixed cells can also be quantitated, though this analysis would be more time-consuming than cell counting. Thirdly, in addition to the quantitative data collection, the method could be applied for identifying responsive cells. This might be very useful in identification of e.g. orexin-responding neurones in a large population of non-responsive cells in primary cultures.

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