Begonia—A Two-Photon Imaging Analysis Pipeline for Astrocytic Ca2+ Signals

Abstract

Imaging the intact brain of awake behaving mice without the dampening effects of anesthesia, has revealed an exceedingly rich repertoire of astrocytic Ca2+ signals. Analyzing and interpreting such complex signals pose many challenges. Traditional analyses of fluorescent changes typically rely on manually outlined static region-of-interests, but such analyses fail to capture the intricate spatiotemporal patterns of astrocytic Ca2+ dynamics. Moreover, all astrocytic Ca2+ imaging data obtained from awake behaving mice need to be interpreted in light of the complex behavioral patterns of the animal. Hence processing multimodal data, including animal behavior metrics, stimulation timings, and electrophysiological signals is needed to interpret astrocytic Ca2+ signals. Managing and incorporating these data types into a coherent analysis pipeline is challenging and time-consuming, especially if research protocols change or new data types are added. Here, we introduce Begonia, a MATLAB-based data management and analysis toolbox tailored for the analyses of astrocytic Ca2+ signals in conjunction with behavioral data. The analysis suite includes an automatic, event-based algorithm with few input parameters that can capture a high level of spatiotemporal complexity of astrocytic Ca2+ signals. The toolbox enables the experimentalist to quantify astrocytic Ca2+ signals in a precise and unbiased way and combine them with other types of time series data.

Astrocytic IP3Rs: Beyond IP3R2

“…To accurately capture Ca 2+ dynamics in sub-cellular compartments, there is a need to adopt imaging techniques with improved resolution and to develop tools for efficient analysis in three-dimensional (Bindocci et al, 2017;Romanos et al, 2019). Because of our poor understanding of functional compartments, analysis of astrocytic Ca 2+ dynamics has been moving toward state-of-the-art event-based analysis (Romanos et al, 2019;Wang et al, 2019;Bjørnstad et al, 2021), nevertheless ROI (regionof-interest) based analysis, informed by cellular anatomy (functional compartments) and molecular architecture, has been critical for understanding neuron physiology (e.g., spines and boutons). To this end, the identification of morphologically distinct subcellular compartments are promising targets for classical ROI based analysis, i.e., "glial microdomains" on Bergmann glial processes (Grosche et al, 1999) and "astrocytic compartments" on major branches (Panatier et al, 2011), both revealed using confocal microscopy, and astrocytic nodes and shafts within the spongiform structure visualized using live STED microscopy (Arizono et al, 2020).…”

Advocating For Interdisciplinary Collaborations To Unravel The Astrocyte "Calcium Code"

“…Recently, several image analysis algorithms have been developed to quantify astrocyte calcium signals in 2D+time microscopy images. Among them, we can cite GECIquant [43], CaSCaDe [18], FASP [44], AQuA [45] and, more recently, Begonia [46] and Astral [47]. Most of these methods are ROI-based approaches (ROI: region of interest), meaning that calcium signals are analyzed through fixed spatial boundaries in the image.…”

Photonics tools begin to clarify astrocyte calcium transients

“…Contrary to AQuA, however, Begonia allows for easy integration of other time-series data and is optimized for handling large, high-frame-rate ( ) datasets, thereby avoiding significantly long processing times. 124 …”

“…Contrary to AQuA, however, Begonia allows for easy integration of other time-series data and is optimized for handling large, high-frame-rate (∼30 Hz) datasets, thereby avoiding significantly long processing times. 124 Majority of the aforementioned analysis packages are targeted to single cell analysis. Software package Astral is designed to analyze astrocyte-astrocyte or astrocyte-neuron interactions at a network level.…”