Result: DARTS: an open-source Python pipeline for Ca 2+ microdomain analysis in live cell imaging data.

Title:
DARTS: an open-source Python pipeline for Ca 2+ microdomain analysis in live cell imaging data.
Authors:
Woelk LM; Department of Applied Medical Informatics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.; Department of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.; Center for Biomedical Artificial Intelligence (bAIome), University Medical Center Hamburg-Eppendorf, Hamburg, Germany., Kovacevic D; The Calcium Signalling Group, Department of Biochemistry and Molecular Cell Biology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany., Husseini H; Department of Applied Medical Informatics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.; Department of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.; Center for Biomedical Artificial Intelligence (bAIome), University Medical Center Hamburg-Eppendorf, Hamburg, Germany., Förster F; Department of Applied Medical Informatics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.; Department of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.; Center for Biomedical Artificial Intelligence (bAIome), University Medical Center Hamburg-Eppendorf, Hamburg, Germany., Gerlach F; The Calcium Signalling Group, Department of Biochemistry and Molecular Cell Biology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany., Möckl F; The Calcium Signalling Group, Department of Biochemistry and Molecular Cell Biology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany., Altfeld M; Institute for Immunology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany., Guse AH; The Calcium Signalling Group, Department of Biochemistry and Molecular Cell Biology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany., Diercks BP; The Calcium Signalling Group, Department of Biochemistry and Molecular Cell Biology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany., Werner R; Department of Applied Medical Informatics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.; Department of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.; Center for Biomedical Artificial Intelligence (bAIome), University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Source:
Frontiers in immunology [Front Immunol] 2024 Jan 11; Vol. 14, pp. 1299435. Date of Electronic Publication: 2024 Jan 11 (Print Publication: 2023).
Publication Type:
Journal Article; Research Support, Non-U.S. Gov't
Language:
English
Journal Info:
Publisher: Frontiers Research Foundation] Country of Publication: Switzerland NLM ID: 101560960 Publication Model: eCollection Cited Medium: Internet ISSN: 1664-3224 (Electronic) Linking ISSN: 16643224 NLM ISO Abbreviation: Front Immunol Subsets: MEDLINE
Imprint Name(s):
Original Publication: [Lausanne : Frontiers Research Foundation]
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Contributed Indexing:
Keywords: Ca2+ microdomains; Python; image analysis; intracellular signaling; live cell imaging; open source; shape normalization
Entry Date(s):
Date Created: 20240126 Date Completed: 20240129 Latest Revision: 20241023
Update Code:
20250114
PubMed Central ID:
PMC10809147
DOI:
10.3389/fimmu.2023.1299435
PMID:
38274810
Database:
MEDLINE

Further Information

Ca <sup>2+</sup> microdomains play a key role in intracellular signaling processes. For instance, they mediate the activation of T cells and, thus, the initial adaptive immune system. They are, however, also of utmost importance for activation of other cells, and a detailed understanding of the dynamics of these spatially localized Ca <sup>2+</sup> signals is crucial for a better understanding of the underlying signaling processes. A typical approach to analyze Ca <sup>2+</sup> microdomain dynamics is live cell fluorescence microscopy imaging. Experiments usually involve imaging a larger number of cells of different groups (for instance, wild type and knockout cells), followed by a time consuming image and data analysis. With DARTS, we present a modular Python pipeline for efficient Ca <sup>2+</sup> microdomain analysis in live cell imaging data. DARTS (Deconvolution, Analysis, Registration, Tracking, and Shape normalization) provides state-of-the-art image postprocessing options like deep learning-based cell detection and tracking, spatio-temporal image deconvolution, and bleaching correction. An integrated automated Ca <sup>2+</sup> microdomain detection offers direct access to global statistics like the number of microdomains for cell groups, corresponding signal intensity levels, and the temporal evolution of the measures. With a focus on bead stimulation experiments, DARTS provides a so-called dartboard projection analysis and visualization approach. A dartboard projection covers spatio-temporal normalization of the bead contact areas and cell shape normalization onto a circular template that enables aggregation of the spatiotemporal information of the microdomain detection results for the individual cells of the cell groups of interest. The dartboard visualization allows intuitive interpretation of the spatio-temporal microdomain dynamics at the group level. The application of DARTS is illustrated by three use cases in the context of the formation of initial Ca <sup>2+</sup> microdomains after cell stimulation. DARTS is provided as an open-source solution and will be continuously extended upon the feedback of the community. Code available at: 10.5281/zenodo.10459243.
(Copyright © 2024 Woelk, Kovacevic, Husseini, Förster, Gerlach, Möckl, Altfeld, Guse, Diercks and Werner.)

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer GD declared a past co-authorship with one of the authors B-PD, AG to the handling editor.