Introduction

Local Ca2+ Releases (LCRs) are crucial events involved in cardiac pacemaker cell function. However, specific algorithms for automatic LCR detection and analysis have not been developed in live, spontaneously beating pacemaker cells. In the present study we measured LCRs using a high-speed 2D-camera in spontaneously contracting sinoatrial (SA) node cells isolated from rabbit and guinea pig and developed a new algorithm capable of detecting and analyzing the LCRs spatially in two-dimensions, and in time. Our algorithm tracks points along the midline of the contracting cell. It uses these points as a coordinate system for affine transform, producing a transformed image series where the cell does not contract. Action potential-induced Ca2+ transients and LCRs were thereafter isolated from recording noise by applying a series of spatial filters. The LCR birth and death events were detected by a differential (frame-to-frame) sensitivity algorithm applied to each pixel (cell location). An LCR was detected when its signal changes sufficiently quickly within a sufficiently large area. The LCR is considered to have died when its amplitude decays substantially, or when it merges into the rising whole cell Ca2+ transient. Ultimately, our algorithm provides major LCR parameters such as period, signal mass, duration, and propagation path area. As the LCRs propagate within live cells, the algorithm identifies splitting and merging behaviors, indicating the importance of locally propagating Ca2+-induced-Ca2+-release for the fate of LCRs and for generating a powerful ensemble Ca2+ signal. Thus, our new computer algorithms eliminate motion artifacts and detect 2D local spatiotemporal events from recording noise and global signals. While the algorithms were developed to detect LCRs in sinoatrial nodal cells, they have the potential to be used in other applications in biophysics and cell physiology, for example, to detect Ca2+ wavelets (abortive waves), sparks and embers in muscle cells and Ca2+ puffs and syntillas in neurons.

Publications

  1. Computer algorithms for automated detection and analysis of local Ca2+ releases in spontaneously beating cardiac pacemaker cells.
    Cite this
    Maltsev AV, Parsons SP, Kim MS, Tsutsui K, Stern MD, Lakatta EG, Maltsev VA, Monfredi O, 2017-01-01 - PLoS ONE

Credits

  1. Alexander V Maltsev
    Developer

    Laboratory of Cardiovascular Science, NIA/NIH, United States of America

  2. Sean P Parsons
    Developer

    Farncombe Institute, McMaster University, Canada

  3. Mary S Kim
    Developer

    Laboratory of Cardiovascular Science, NIA/NIH, United States of America

  4. Kenta Tsutsui
    Developer

    Laboratory of Cardiovascular Science, NIA/NIH, United States of America

  5. Michael D Stern
    Developer

    Laboratory of Cardiovascular Science, NIA/NIH, United States of America

  6. Edward G Lakatta
    Developer

    Laboratory of Cardiovascular Science, NIA/NIH, United States of America

  7. Victor A Maltsev
    Developer

    Laboratory of Cardiovascular Science, NIA/NIH, United States of America

  8. Oliver Monfredi
    Investigator

    Division of Cardiovascular Sciences, University of Manchester, United Kingdom of Great Britain and Northern Ireland

Community Ratings

UsabilityEfficiencyReliabilityRated By
0 user
Sign in to rate
Summary
AccessionBT006445
Tool TypeApplication
Category
PlatformsWindows
TechnologiesC++
User InterfaceTerminal Command Line
Download Count0
Country/RegionUnited Kingdom of Great Britain and Northern Ireland
Submitted ByOliver Monfredi