A high throughput machine-learning driven analysis of Ca2+ spatio-temporal maps

A deep learning-based approach for efficient detection and classification of local Ca²⁺ release events in Full-Frame confocal imaging

The release of Ca2+ ions from intracellular stores plays a crucial role in many cellular processes, acting as a secondary messenger in various cell types, including cardiomyocytes, smooth muscle cells, hepatocytes, and many others. Detecting and classifying associated local Ca2+ release events is particularly important, as these events provide insight into the mechanisms, interplay, and interdependencies of local Ca2+release events underlying global intracellular Ca2+signaling. However, time-consuming and labor-intensive procedures often complicate analysis, especially with low signal-to-noise ratio imaging data. Here, we present an innovative deep learning-based approach for automatically detecting and classifying local Ca2+ release events. This approach is exemplified with rapid full-frame confocal imaging data recorded in isolated cardiomyocytes. To demonstrate the robustness and accuracy of our method, we first use conventional evaluation methods by comparing the intersection between manual annotations and the segmentation of Ca2+ release events provided by the deep learning method, as well as the annotated and recognized instances of individual events. In addition to these methods, we compare the performance of the proposed model with the annotation of six experts in the field. Our model can recognize more than 75 % of the annotated Ca2+ release events and correctly classify more than 75 %. A key result was that there were no significant differences between the annotations produced by human experts and the result of the proposed deep learning model. We conclude that the proposed approach is a robust and time-saving alternative to conventional full-frame confocal imaging analysis of local intracellular Ca2+ events.

Ca2+ dynamics in interstitial cells: foundational mechanisms for the motor patterns in the gastrointestinal tract

The gastrointestinal (GI) tract displays multiple motor patterns that move nutrients and wastes through the body. Smooth muscle cells (SMCs) provide the forces necessary for GI motility, but interstitial cells, electrically coupled to SMCs, tune SMC excitability, transduce inputs from enteric motor neurons, and generate pacemaker activity that underlies major motor patterns, such as peristalsis and segmentation. The interstitial cells regulating SMCs are interstitial cells of Cajal (ICC) and PDGF receptor (PDGFR)α+ cells. Together these cells form the SIP syncytium. ICC and PDGFRα+ cells express signature Ca2+-dependent conductances: ICC express Ca2+-activated Cl- channels, encoded by Ano1, that generate inward current, and PDGFRα+ cells express Ca2+-activated K+ channels, encoded by Kcnn3, that generate outward current. The open probabilities of interstitial cell conductances are controlled by Ca2+ release from the endoplasmic reticulum. The resulting Ca2+ transients occur spontaneously in a stochastic manner. Ca2+ transients in ICC induce spontaneous transient inward currents and spontaneous transient depolarizations (STDs). Neurotransmission increases or decreases Ca2+ transients, and the resulting depolarizing or hyperpolarizing responses conduct to other cells in the SIP syncytium. In pacemaker ICC, STDs activate voltage-dependent Ca2+ influx, which initiates a cluster of Ca2+ transients and sustains activation of ANO1 channels and depolarization during slow waves. Regulation of GI motility has traditionally been described as neurogenic and myogenic. Recent advances in understanding Ca2+ handling mechanisms in interstitial cells and how these mechanisms influence motor patterns of the GI tract suggest that the term "myogenic" should be replaced by the term "SIPgenic," as this review discusses.

Tools for Quantitative Analysis of Calcium Signaling Data Using Jupyter-Lab Notebooks

Calcium signaling data analysis has become increasing complex as the size of acquired datasets increases. In this paper we present a Ca2+ signaling data analysis method that employs custom written software scripts deployed in a collection of Jupyter-Lab "notebooks" which were designed to cope with this complexity. The notebook contents are organized to optimize data analysis workflow and efficiency. The method is demonstrated through application to several different Ca2+ signaling experiment types.

An automated method to discover true events and classification of intracellular Ca2+ profiles for endothelium in situ injury assay

Introduction: Endothelial cells (ECs), being located at the interface between flowing blood and vessel wall, maintain cardiovascular homeostasis by virtue of their ability to integrate chemical and physical cues through a spatio-temporally coordinated increase in their intracellular Ca²⁺ concentration ([Ca²⁺]i). Endothelial heterogeneity suggests the existence of spatially distributed functional clusters of ECs that display different patterns of intracellular Ca²⁺ response to extracellular inputs. Characterizing the overall Ca²⁺ activity of the endothelial monolayer in situ requires the meticulous analysis of hundreds of ECs. This complex analysis consists in detecting and quantifying the true Ca²⁺ events associated to extracellular stimulation and classifying their intracellular Ca²⁺ profiles (ICPs). The injury assay technique allows exploring the Ca²⁺-dependent molecular mechanisms involved in angiogenesis and endothelial regeneration. However, there are true Ca²⁺ events of nearly undetectable magnitude that are almost comparable with inherent instrumental noise. Moreover, undesirable artifacts added to the signal by mechanical injury stimulation complicate the analysis of intracellular Ca²⁺ activity. In general, the study of ICPs lacks uniform criteria and reliable approaches for assessing these highly heterogeneous spatial and temporal events. Methods: Herein, we present an approach to classify ICPs that consists in three stages: 1) identification of Ca²⁺ candidate events through thresholding of a feature termed left-prominence; 2) identification of non-true events, known as artifacts; and 3) ICP classification based upon event temporal location. Results: The performance assessment of true-events identification showed competitive sensitivity = [0.9995, 0.9831], specificity = [0.9946, 0.7818] and accuracy = [0.9978, 0.9579] improvements of 2x and 14x, respectively, compared with other methods. The ICP classifier enhanced by artifact detection showed 0.9252 average accuracy with the ground-truth sets provided for validation. Discussion: Results indicate that our approach ensures sturdiness to experimental protocol maneuvers, besides it is effective, simple, and configurable for different studies that use unidimensional time dependent signals as data. Furthermore, our approach would also be effective to analyze the ICPs generated by other cell types, other dyes, chemical stimulation or even signals recorded at higher frequency.

Software for segmenting and quantifying calcium signals using multi-scale generative adversarial networks

Cellular calcium fluorescence imaging utilized to study cellular behaviors typically results in large datasets and a profound need for standardized and accurate analysis methods. Here, we describe open-source software (4SM) to overcome these limitations using an automated machine learning pipeline for subcellular calcium signal segmentation of spatiotemporal maps. The primary use of 4SM is to analyze spatiotemporal maps of calcium activities within cells or across multiple cells. For complete details on the use and execution of this protocol, please refer to Kamran et al. (2022).¹.

Changes in interstitial cells and gastric excitability in a mouse model of sleeve gastrectomy

Obesity is a critical risk factor of several life-threatening diseases and the prevalence in adults has dramatically increased over the past ten years. In the USA the age-adjusted prevalence of obesity in adults was 42.4%, i.e., with a body mass index (BMI, weight (kg)/height (m)²) that exceeds 30 kg/m². Obese individuals are at the higher risk of obesity-related diseases, co-morbid conditions, lower quality of life, and increased mortality more than those in the normal BMI range i.e., 18.5–24.9 kg/m². Surgical treatment continues to be the most efficient and scientifically successful treatment for obese patients. Sleeve gastrectomy or vertical sleeve gastrectomy (VSG) is a relatively new gastric procedure to reduce body weight but is now the most popular bariatric operation. To date there have been few studies examining the changes in the cellular components and pacemaker activity that occur in the gastric wall following VSG and whether normal gastric activity recovers following VSG. In the present study we used a murine model to investigate the chronological changes of gastric excitability including electrophysiological, molecular and morphological changes in the gastric musculature following VSG. There is a significant disruption in specialized interstitial cells of Cajal in the gastric antrum following sleeve gastrectomy. This is associated with a loss of gastric pacemaker activity and post-junctional neuroeffector responses. Over a 4-month recovery period there was a gradual return in interstitial cells of Cajal networks, pacemaker activity and neural responses. These data describe for the first time the changes in gastric interstitial cells of Cajal networks, pacemaker activity and neuroeffector responses and the time-dependent recovery of ICC networks and normalization of motor activity and neural responses following VSG.

Insights on gastrointestinal motility through the use of optogenetic sensors and actuators

The muscularis of the gastrointestinal (GI) tract consists of smooth muscle cells (SMCs) and various populations of interstitial cells of Cajal (ICC), platelet-derived growth factor receptor α⁺ (PDGFRα⁺ ) cells, as well as excitatory and inhibitory enteric motor nerves. SMCs, ICC and PDGFRα⁺ cells form an electrically coupled syncytium, which together with inputs from the enteric nervous system (ENS) regulate GI motility. Early studies evaluating Ca²⁺ signalling behaviours in the GI tract relied upon indiscriminate loading of tissues with Ca²⁺ dyes. These methods lacked the means to study activity in specific cells of interest without encountering contamination from other cells within the preparation. Development of mice expressing optogenetic sensors (GCaMP, RCaMP) has allowed visualization of Ca²⁺ signalling behaviours in a cell specific manner. Additionally, availability of mice expressing optogenetic modulators (channelrhodopsins or halorhodospins) has allowed manipulation of specific signalling pathways using light. GCaMP expressing animals have been used to characterize Ca²⁺ signalling behaviours of distinct classes of ICC and SMCs throughout the GI musculature. These findings illustrate how Ca²⁺ signalling in ICC is fundamental in GI muscles, contributing to tone in sphincters, pacemaker activity in rhythmic muscles and relaying enteric signals to SMCs. Animals that express channelrhodopsin in specific neuronal populations have been used to map neural circuitry and to examine post junctional neural effects on GI motility. Thus, optogenetic approaches provide a novel means to examine the contribution of specific cell types to the regulation of motility patterns within complex multi-cellular systems. Abstract Figure Legends Optogenetic activators and sensors can be used to investigate the complex multi-cellular nature of the gastrointestinal (GI tract). Optogenetic activators that are activated by light such as channelrhodopsins (ChR2), OptoXR and halorhodopsinss (HR) proteins can be genetically encoded into specific cell types. This can be used to directly activate or silence specific GI cells such as various classes of enteric neurons, smooth muscle cells (SMC) or interstitial cells, such as interstitial cells of Cajal (ICC). Optogenetic sensors that are activated by different wavelengths of light such as green calmodulin fusion protein (GCaMP) and red CaMP (RCaMP) make high resolution of sub-cellular Ca²⁺ signalling possible within intact tissues of specific cell types. These tools can provide unparalleled insight into mechanisms underlying GI motility and innervation. This article is protected by copyright. All rights reserved.

PDGFRα+ Interstitial Cells are Effector Cells of PACAP Signaling in Mouse and Human Colon

BACKGROUND & AIMS

Platelet-derived growth factor receptor α (PDGFRα)-positive interstitial cells (PIC) are interposed between enteric nerve fibers and smooth muscle cells (SMCs) in the tunica muscularis of the gastrointestinal tract. PIC have robust expression of small conductance Ca²⁺ activated K⁺ channels 3 (SK3 channels) and transduce inhibitory inputs from purinergic and sympathetic nerves in mouse and human colon. We investigated whether PIC also express pituitary adenylate cyclase-activating polypeptide (PACAP) receptors, PAC1 (PAC₁R), and are involved in mediating inhibitory regulation of colonic contractions by PACAP in mouse and human colons.

METHODS

Gene expression analysis, Ca²⁺ imaging, and contractile experiments were performed on mouse colonic muscles. Ca²⁺ imaging, intracellular electrical recordings, and contractile experiments were performed on human colonic muscles.

RESULTS

Adcyap1r1 (encoding PAC₁R) is highly expressed in mouse PIC. Interstitial cells of Cajal (ICC) and SMCs expressed far lower levels of Adcyap1r. Vipr1 and Vipr2 were expressed at low levels in PIC, ICC, and SMCs. PACAP elicited Ca²⁺ transients in mouse PIC and inhibited spontaneous phasic contractions via SK channels. In human colonic muscles, PAC₁R agonists elicited Ca²⁺ transients in PIC, hyperpolarized SMCs through SK channels and inhibited spontaneous phasic contractions.

CONCLUSIONS

PIC of mouse and human colon utilize PAC₁R-SK channel signal pathway to inhibit colonic contractions in response to PACAP. Effects of PACAP are in addition to the previously described purinergic and sympathetic inputs to PIC. Thus, PIC integrate inhibitory inputs from at least 3 neurotransmitters and utilize several types of receptors to activate SK channels and regulate colonic contractile behaviors.

New open-source software for subcellular segmentation and analysis of spatiotemporal fluorescence signals using deep learning

Cellular imaging instrumentation advancements as well as readily available optogenetic and fluorescence sensors have yielded a profound need for fast, accurate, and standardized analysis. Deep-learning architectures have revolutionized the field of biomedical image analysis and have achieved state-of-the-art accuracy. Despite these advancements, deep learning architectures for the segmentation of subcellular fluorescence signals is lacking. Cellular dynamic fluorescence signals can be plotted and visualized using spatiotemporal maps (STMaps), and currently their segmentation and quantification are hindered by slow workflow speed and lack of accuracy, especially for large datasets. In this study, we provide a software tool that utilizes a deep-learning methodology to fundamentally overcome signal segmentation challenges. The software framework demonstrates highly optimized and accurate calcium signal segmentation and provides a fast analysis pipeline that can accommodate different patterns of signals across multiple cell types. The software allows seamless data accessibility, quantification, and graphical visualization and enables large dataset analysis throughput.

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4SM: an automated software solution for cellular dynamic fluorescence signal analysis

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4SM relies on a novel machine-learning pipeline for fluorescence signal segmentation

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4SM is fast and provides a consistent method for high-throughput analysis of datasets

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4SM provides instant signal quantification and graphical representation of the results

Modelling the coupling of the M-clock and C-clock in lymphatic muscle cells

Chronic dysfunction of the lymphatic vascular system results in fluid accumulation between cells: lymphoedema. The condition is commonly acquired secondary to diseases such as cancer or the associated therapies. The primary driving force for fluid return through the lymphatic vasculature is provided by contractions of the muscularized lymphatic collecting vessels, driven by electrochemical oscillations. However, there is an incomplete understanding of the molecular and bioelectric mechanisms involved in lymphatic muscle cell excitation, hampering the development and use of pharmacological therapies. Modelling in silico has contributed greatly to understanding the contributions of specific ion channels to the cardiac action potential, but modelling of these processes in lymphatic muscle remains limited. Here, we propose a model of oscillations in the membrane voltage (M-clock) and intracellular calcium concentrations (C-clock) of lymphatic muscle cells. We modify a model by Imtiaz and colleagues to enable the M-clock to drive the C-clock oscillations. This approach differs from typical models of calcium oscillators in lymphatic and related cell types, but is required to fit recent experimental data. We include an additional voltage dependence in the gating variable control for the L-type calcium channel, enabling the M-clock to oscillate independently of the C-clock. We use phase-plane analysis to show that these M-clock oscillations are qualitatively similar to those of a generalised FitzHugh-Nagumo model. We also provide phase plane analysis to understand the interaction of the M-clock and C-clock oscillations. The model and methods have the potential to help determine mechanisms and find targets for pharmacological treatment of lymphoedema.

Ca2+ transients in ICC-MY define the basis for the dominance of the corpus in gastric pacemaking

Myenteric interstitial cells of Cajal (ICC-MY) generate and actively propagate electrical slow waves in the stomach. Slow wave generation and propagation are altered in gastric motor disorders, such as gastroparesis, and the mechanism for the gradient in slow wave frequency that facilitates proximal to distal propagation of slow waves and normal gastric peristalsis is poorly understood.  Slow waves depend upon Ca2+-activated Cl- channels (encoded by Ano1). We characterized Ca2+ signaling in ICC-MY in situ using mice engineered to have cell-specific expression of GCaMP6f in ICC. Ca2+ signaling differed in ICC-MY in corpus and antrum. Localized Ca2+ transients were generated from multiple firing sites and were organized into Ca2+ transient clusters (CTCs). Ca2+ transient refractory periods occurred upon cessation of CTCs, but a relatively higher frequency of Ca2+ transients persisted during the inter-CTC interval in corpus than in antrum ICC-MY. The onset of Ca2+ transients after the refractory period was associated with initiation of the next CTC. Thus, CTCs were initiated at higher frequencies in corpus than in antrum ICC-MY. Initiation and propagation of CTCs (and electrical slow waves) depends upon T-type Ca2+ channels, and durations of CTCs relied upon L-type Ca2+ channels. The durations of CTCs mirrored the durations of slow waves. CTCs and Ca2+ transients between CTCs resulted from release of Ca2+ from intracellular stores and were maintained, in part, by store-operated Ca2+ entry. Our data suggest that Ca2+ release and activation of Ano1 channels both initiate and contribute to the plateau phase of slow waves.

Ca2+ signaling driving pacemaker activity in submucosal interstitial cells of Cajal in the murine colon

Interstitial cells of Cajal (ICC) generate pacemaker activity responsible for phasic contractions in colonic segmentation and peristalsis. ICC along the submucosal border (ICC-SM) contribute to mixing and more complex patterns of colonic motility. We show the complex patterns of Ca²⁺ signaling in ICC-SM and the relationship between ICC-SM Ca²⁺ transients and activation of smooth muscle cells (SMCs) using optogenetic tools. ICC-SM displayed rhythmic firing of Ca²⁺transients ~ 15 cpm and paced adjacent SMCs. The majority of spontaneous activity occurred in regular Ca²⁺ transients clusters (CTCs) that propagated through the network. CTCs were organized and dependent upon Ca²⁺ entry through voltage-dependent Ca²⁺ conductances, L- and T-type Ca²⁺ channels. Removal of Ca²⁺ from the external solution abolished CTCs. Ca²⁺ release mechanisms reduced the duration and amplitude of Ca²⁺ transients but did not block CTCs. These data reveal how colonic pacemaker ICC-SM exhibit complex Ca^2+-firing patterns and drive smooth muscle activity and overall colonic contractions.