Applications of Spatio-temporal Mapping and Particle Analysis Techniques to Quantify Intracellular Ca2+ Signaling In Situ
Overview
Affiliations
Ca imaging of isolated cells or specific types of cells within intact tissues often reveals complex patterns of Ca signaling. This activity requires careful and in-depth analyses and quantification to capture as much information about the underlying events as possible. Spatial, temporal and intensity parameters intrinsic to Ca signals such as frequency, duration, propagation, velocity and amplitude may provide some biological information required for intracellular signalling. High-resolution Ca imaging typically results in the acquisition of large data files that are time consuming to process in terms of translating the imaging information into quantifiable data, and this process can be susceptible to human error and bias. Analysis of Ca signals from cells in situ typically relies on simple intensity measurements from arbitrarily selected regions of interest (ROI) within a field of view (FOV). This approach ignores much of the important signaling information contained in the FOV. Thus, in order to maximize recovery of information from such high-resolution recordings obtained with Cadyes or optogenetic Ca imaging, appropriate spatial and temporal analysis of the Ca signals is required. The protocols outlined in this paper will describe how a high volume of data can be obtained from Ca imaging recordings to facilitate more complete analysis and quantification of Ca signals recorded from cells using a combination of spatiotemporal map (STM)-based analysis and particle-based analysis. The protocols also describe how different patterns of Ca signaling observed in different cell populations in situ can be analyzed appropriately. For illustration, the method will examine Ca signaling in a specialized population of cells in the small intestine, interstitial cells of Cajal (ICC), using GECIs.
Automated denoising software for calcium imaging signals using deep learning.
Kamran S, Moghnieh H, Hossain K, Bartlett A, Tavakkoli A, Drumm B Heliyon. 2024; 10(21):e39574.
PMID: 39524741 PMC: 11546308. DOI: 10.1016/j.heliyon.2024.e39574.
Zawieja S, Pea G, Broyhill S, Patro A, Bromert K, Norton C bioRxiv. 2023; .
PMID: 37662284 PMC: 10473772. DOI: 10.1101/2023.08.24.554619.
Sanders K, Drumm B, Cobine C, Baker S Physiol Rev. 2023; 104(1):329-398.
PMID: 37561138 PMC: 11281822. DOI: 10.1152/physrev.00036.2022.
Algorithm for biological second messenger analysis with dynamic regions of interest.
Knighten J, Aziz T, Pleshinger D, Annamdevula N, Rich T, Taylor M PLoS One. 2023; 18(5):e0284394.
PMID: 37167308 PMC: 10174521. DOI: 10.1371/journal.pone.0284394.
Zheng H, Peri L, Ward G, Sanders K, Ward S FASEB J. 2023; 37(5):e22929.
PMID: 37086093 PMC: 10402933. DOI: 10.1096/fj.202201712R.