An algorithm for automated detection, localization and measurement of local calcium signals from camera-based imaging

Abstract

Local Ca2+ transients such as puffs and sparks form the building blocks of cellular Ca2+ signaling in numerous cell types. They have traditionally been studied by linescan confocal microscopy, but advances in TIRF microscopy together with improved electron-multiplied CCD (EMCCD) cameras now enable rapid (>500framess−1) imaging of subcellular Ca2+ signals with high spatial resolution in two dimensions. This approach yields vastly more information (ca. 1Gbmin−1) than linescan imaging, rendering visual identification and analysis of local events imaged both laborious and subject to user bias. Here we describe a routine to rapidly automate identification and analysis of local Ca2+ events. This features an intuitive graphical user-interfaces and runs under Matlab and the open-source Python software. The underlying algorithm features spatial and temporal noise filtering to reliably detect even small events in the presence of noisy and fluctuating baselines; localizes sites of Ca2+ release with sub-pixel resolution; facilitates user review and editing of data; and outputs time-sequences of fluorescence ratio signals for identified event sites along with Excel-compatible tables listing amplitudes and kinetics of events.