Abstract
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.
Highlights
Communication between adjacent neurons can be investigated through calcium (Ca) imaging
We 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
SH-SY5Y neuroblastomas were cultured in DMEM/F-12 media (1:1) supplemented with 10% fetal bovine serum (FBS) and 1% pen/strep, and they were grown in an incubator at 37 °C, 5% CO2
Summary
Communication between adjacent neurons can be investigated through calcium (Ca) imaging When this technique is applied, the cells are treated with a Ca-sensitive fluorescent dye. The cell bodies, so-called regions of interest (ROI), need to be determined, the calcium spikes detected, and a network of interacting cells constructed While this can be done manually, it is a resource- and time-consuming task, especially given the large amount of data that is generally involved in computations. Conclusions: We 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
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