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An open source tool for automatic spatiotemporal assessment of calcium transients and local 'signal-close-to-noise' activity in calcium imaging data.

ABSTRACT: Local and spontaneous calcium signals play important roles in neurons and neuronal networks. Spontaneous or cell-autonomous calcium signals may be difficult to assess because they appear in an unpredictable spatiotemporal pattern and in very small neuronal loci of axons or dendrites. We developed an open source bioinformatics tool for an unbiased assessment of calcium signals in x,y-t imaging series. The tool bases its algorithm on a continuous wavelet transform-guided peak detection to identify calcium signal candidates. The highly sensitive calcium event definition is based on identification of peaks in 1D data through analysis of a 2D wavelet transform surface. For spatial analysis, the tool uses a grid to separate the x,y-image field in independently analyzed grid windows. A document containing a graphical summary of the data is automatically created and displays the loci of activity for a wide range of signal intensities. Furthermore, the number of activity events is summed up to create an estimated total activity value, which can be used to compare different experimental situations, such as calcium activity before or after an experimental treatment. All traces and data of active loci become documented. The tool can also compute the signal variance in a sliding window to visualize activity-dependent signal fluctuations. We applied the calcium signal detector to monitor activity states of cultured mouse neurons. Our data show that both the total activity value and the variance area created by a sliding window can distinguish experimental manipulations of neuronal activity states. Notably, the tool is powerful enough to compute local calcium events and 'signal-close-to-noise' activity in small loci of distal neurites of neurons, which remain during pharmacological blockade of neuronal activity with inhibitors such as tetrodotoxin, to block action potential firing, or inhibitors of ionotropic glutamate receptors. The tool can also offer information about local homeostatic calcium activity events in neurites.

SUBMITTER: Prada J

PROVIDER: S-EPMC5895056 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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An open source tool for automatic spatiotemporal assessment of calcium transients and local 'signal-close-to-noise' activity in calcium imaging data.

Prada Juan J Sasi Manju M Martin Corinna C Jablonka Sibylle S Dandekar Thomas T Blum Robert R

PLoS computational biology 20180330 3

Local and spontaneous calcium signals play important roles in neurons and neuronal networks. Spontaneous or cell-autonomous calcium signals may be difficult to assess because they appear in an unpredictable spatiotemporal pattern and in very small neuronal loci of axons or dendrites. We developed an open source bioinformatics tool for an unbiased assessment of calcium signals in x,y-t imaging series. The tool bases its algorithm on a continuous wavelet transform-guided peak detection to identify ...[more]

PMID: 29601577

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Project description:Background and objectiveEver since its discovery, calcium imaging has proven its worth in discovering new insights into the mechanisms of cellular communication. Yet, the analysis of the data generated by calcium imaging experiments demands a large amount of time from researchers. Tools enabling automated and semi-automated analysis are available, but often they allow automating only a part of the data analysis process. Therefore, we developed CALIMA (https://aethelraed.nl/calima), a free and open-source standalone software tool that provides an opportunity to quickly detect cells, to obtain the calcium spikes, and to determine the underlying network structure of neuronal cell cultures.MethodsOwing to the difference of Gaussians algorithm applied for the cell detection, CALIMA is able to detect regions of interest (ROIs) quickly. The z-scoring algorithm provides a means to set the requirements for spike detection, and the neuronal connections can be reconstructed by analyzing the cross-correlation between the cellular activity. We evaluated CALIMA's reliability, speed, and functionality with a special focus on neuronal cell detection and network reconstruction. The evaluation was performed by using real-life data such as a known example dataset (cultured primary rat cortical neurons, University of Pennsylvania) and by analyzing video graphic footage of in vitro brain cell samples (SH-SY5Y neuroblastoma cultures, one sample with synchronous neuron firing). The obtained results were compared to the corresponding outcomes observed on same datasets for other similar software solutions. Moreover, we compared the results of segmentation and peak detection analysis, the ones obtained using CALIMA and those acquired manually.ResultsCALIMA was able to detect the cells in the cultures within seconds. The average sensitivity was 82% across the datasets checked, comparing favorably with the alternative software solutions. Using the correct parameters, CALIMA's Ca-spikes detection sensitivity reached 96%. Lastly, neuronal networks were reconstructed by combining the data on the ROI's activity and the cell's positions, finding the most likely inter-cell connections.ConclusionsWe found that CALIMA proved to be a robust and fast tool to analyze the data of experiments for the digital reconstruction of the neuronal cellular network while being able to process the analysis steps with minimal user input required and in a time efficient manner.

Dataset Information

An open source tool for automatic spatiotemporal assessment of calcium transients and local 'signal-close-to-noise' activity in calcium imaging data.

Publications

An open source tool for automatic spatiotemporal assessment of calcium transients and local 'signal-close-to-noise' activity in calcium imaging data.

Similar Datasets

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