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Quantitative fluorescence imaging with up to 30 nm resolution to provide 3D data for models of cardiac Ca2+ handling

Presented by: 
C Soeller [Auckland]
Date: 
Monday 20th July 2009 - 10:45 to 11:00
Venue: 
INI Seminar Room 1
Session Title: 
Cellular and sub-cellular Modelling 1
Session Chair: 
Mark Boyett
Abstract: 

Quantitative understanding of the Ca2+ handling in cardiac ventricular myocytes requires accurate knowledge of cardiac ultrastructure and protein distribution. We have therefore developed high-resolution imaging and analysis approaches to measure the three-dimensional distribution of immuno-labelled proteins with optical microscopy methods. Until recently optical imaging was thought to be limited to a resolution of ~250 nm set by the diffraction of light. We have overcome this limitation using a new technique that allows imaging of conventionally labelled fluorescent samples at much higher resolution.

Our technique, called reversible photobleaching microscopy (RPM), allows extension to multi-colour and full 3D localization and provides a new powerful method to study the nanostructure of cardiac muscle. We have used RPM and confocal microscopy to obtain new insight into the distribution of ryanodine receptors and related proteins such as the sodium calcium exchanger and caveolin.

To investigate potential effects of myocyte structure on Ca2+ wave propagation we determined the three-dimensional distribution of RyR clusters within an extended section of a single rat ventricular myocyte to construct a model of stochastic Ca2+ dynamics with a measured Ca2+ release unit (CRU) distribution. The model with a realistic CRU distribution supported Ca2+ waves that spread axially along the cell at velocities of ~50 µm/s. By contrast, in a simplified model with planar CRU distribution axial wave spread was slowed ~two-fold and wave propagation often nearly faltered.

These results demonstrate that features of the CRU distribution on multiple length scales may significantly affect intracellular Ca2+ dynamics and must be captured in detailed mechanistic models to achieve quantitative as well as qualitative insight.

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University of Cambridge Research Councils UK
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