Nonviral Platform for Expression of Recombinant Protein in Insect Cells.

Nonviral transfection has been used to express various recombinant proteins, therapeutics, and virus-like particles (VLP) in mammalian and insect cells. Virus-free methods for protein expression require fewer steps for obtaining protein expression by eliminating virus amplification and measuring the infectivity of the virus. The nonviral method uses a nonlytic plasmid to transfect the gene of interest into the insect cells instead of using baculovirus, a lytic system. In this chapter, we describe one of the transfection methods, which uses polyethyleneimine (PEI) as a DNA delivery material into the insect cells to express the recombinant protein in both adherent and suspension cells.

Interaction-Based Perspective for Designing Polymer Biomaterial: A Strategic Approach to the Chitosan-Glycerophosphate System.

The conventional approach for developing any polymeric biomaterial is to follow protocols available in the literature and/or perform trial-and-error runs without a scientific basis. Here, we propose an analysis of a complex overlay of molecular interactions between drugs and polymers that provides a strategic pathway for biomaterial development. First, this work provides an innovative interaction-based method for developing an ocular formulation involving in situ gelling chitosan, gelatin, and glycerophosphate systems. A systematic interaction study is conducted based on the measurement of hydrodynamic radius, zeta potential, and viscosity with the sequential addition of formulation components. The increase in the hydrodynamic radius of the polymer with the addition of drugs can be interpreted as better diffusion of the drug inside the charged polymer chains and vice versa. Based on the knowledge of these interactions, a formulation has been designed that shows better drug release results with extended and sustained release compared to literature protocols, hence accentuating the importance of this study. An in-depth analysis of interactions can lead to a better understanding of the system. Second, we demonstrate the development of two dual-drug biomaterial systems, i.e., an in situ gelling and a liquid formulation at ocular surface temperature from the same polymers, which can be used as an ocular antiglaucoma formulation. Prior knowledge of the interactions between the drug polymers can be used to design a better formulation. The demonstrated application of this interaction-based protocol development can be extended universally to any biomaterial. This would provide a comprehensive idea about the properties and interactions of polymers and drugs, which can also serve as a base/starting point for a new formulation/biomaterial development.

A Pipeline for Dynamic Analysis of Mitochondrial Content in Developing T Cells: Bridging the Gap Between High-Throughput Flow Cytometry and Single-Cell Microscopy Analysis.

Analyzing the dynamics of mitochondrial content in developing T cells is crucial for understanding the metabolic state during T cell development. However, monitoring mitochondrial content in real-time needs a balance of cell viability and image resolution. In this chapter, we present experimental protocols for measuring mitochondrial content in developing T cells using three modalities: bulk analysis via flow cytometry, volumetric imaging in laser scanning confocal microscopy, and dynamic live-cell monitoring in spinning disc confocal microscopy. Next, we provide an image segmentation and centroid tracking-based analysis pipeline for automated quantification of a large number of microscopy images. These protocols together offer comprehensive approaches to investigate mitochondrial dynamics in developing T cells, enabling a deeper understanding of their metabolic processes.

Mitochondrial fusion and altered beta-oxidation drive muscle wasting in a Drosophila cachexia model.

Cancer cachexia is a tumour-induced wasting syndrome, characterised by extreme loss of skeletal muscle. Defective mitochondria can contribute to muscle wasting; however, the underlying mechanisms remain unclear. Using a Drosophila larval model of cancer cachexia, we observed enlarged and dysfunctional muscle mitochondria. Morphological changes were accompanied by upregulation of beta-oxidation proteins and depletion of muscle glycogen and lipid stores. Muscle lipid stores were also decreased in Colon-26 adenocarcinoma mouse muscle samples, and expression of the beta-oxidation gene CPT1A was negatively associated with muscle quality in cachectic patients. Mechanistically, mitochondrial defects result from reduced muscle insulin signalling, downstream of tumour-secreted insulin growth factor binding protein (IGFBP) homologue ImpL2. Strikingly, muscle-specific inhibition of Forkhead box O (FOXO), mitochondrial fusion, or beta-oxidation in tumour-bearing animals preserved muscle integrity. Finally, dietary supplementation with nicotinamide or lipids, improved muscle health in tumour-bearing animals. Overall, our work demonstrates that muscle FOXO, mitochondria dynamics/beta-oxidation and lipid utilisation are key regulators of muscle wasting in cancer cachexia.

In vitro laser scanning confocal microscopy and unsupervised segmentation: Quantification of cytosolic calcium and RNA distribution in hypoxic neurons.

The mimicry of neurodegenerative diseases in vitro can be observed through the induction of chronic hypoxia, and the impact of this stress is monitored using multiplexed imaging techniques. While laser scanning confocal microscopy (LSCM) is a valuable tool for observing single neurons under degenerative conditions, accurately quantifying RNA distribution and cell size by deep learning tools remains challenging due to the lack of annotated training datasets. To address this, we propose a framework that combines 3D tracking of RNA distribution and cell size identification using unsupervised image segmentation. Additionally, we quantified the calcium level in neurons using fluorescent microscopy using unsupervised image segmentation. First, we performed imaging of neuronal morphology using differential interference contrast (DIC) optics and RNA/calcium level imaging using fluorescent microscopy. Next, we performed k-means clustering-based cell segmentation. The results show that our framework can distinguish between distinct neuronal states under control and chronic hypoxic conditions. The analysis reveals that hypoxia induces a significant increase in cytosolic calcium level, reduction in neuron diameter, and alterations in RNA distribution.Clinical Relevance- The proposed framework is crucial to study the neurodegeneration process and evaluating the efficacy of neuroprotective drugs through image analysis.

A deep learning approach for automation in neurite tracing and cell size estimation from differential contrast images under healthy and hypoxic condition.

Chronic hypoxia is known to be a major cause of neurite length retraction followed be degeneration. Specifically, laser scanning confocal microscopy (LSCM) based-contrast imaging is used for monitoring neuronal morphology under hypoxic condition. Although imaging of neurons using LSCM via differential contrast imaging (DIC) is a powerful tool to identify the neuronal states under degenerative condition, fully automated quantification of neurite length and cell shape remains challenging. In this context, we propose an integrated framework that combines panorama imaging of neuronal morphology using LSCM, and deep learning model that allows automated tracing of neurites and cell shape. First, we establish an in vitro hypoxic model using cobalt chloride treatment of N2A cells and perform the large-scale imaging using DIC optics. Next, we tested the performance of U-Net, U-Net++ and FCN architecture using DIC images, where U-Net and U-Net++ demonstrates robustness and accuracy in tracing neurite length and segmentation of cell shape. The result shows that the U-Net++ is able to depict the difference in cell size and neurite length for control and chronic hypoxic condition. The proposed method was also validated and compared with other CNN models including FCN and U-Net. Moreover, the analysis indicates a significant alteration of cell shape and neurite length under hypoxic condition via deep-learning based automated cell segmentation.Clinical Relevance-The proposed framework assumes importance where quantification of neurite length and cell shape from a large dataset remains challenging due to time-consuming manual segmentation by experts. Specially, the framework based on labeling of a small dataset (15-20 images) can be used to identify the neuronal state under neurodegeneration and image-based assessment of neuroprotective drugs.

A computational model to uncover the biophysical underpinnings of neural firing heterogeneity in dissociated hippocampal cultures.

Calcium (Ca2+ ) imaging reveals a variety of correlated firing in cultures of dissociated hippocampal neurons, pinpointing the non-synaptic paracrine release of glutamate as a possible mediator for such firing patterns, although the biophysical underpinnings remain unknown. An intriguing possibility is that extracellular glutamate could bind metabotropic receptors linked with inositol trisphosphate (IP3 ) mediated release of Ca2+ from the endoplasmic reticulum of individual neurons, thereby modulating neural activity in combination with sarco/endoplasmic reticulum Ca2+ transport ATPase (SERCA) and voltage-gated Ca2+ channels (VGCC). However, the possibility that such release may occur in different neuronal compartments and can be inherently stochastic poses challenges in the characterization of such interplay between various Ca2+ channels. Here we deploy biophysical modeling in association with Monte Carlo parameter sampling to characterize such interplay and successfully predict experimentally observed Ca2+ patterns. The results show that the neurotransmitter level at the plasma membrane is the extrinsic source of heterogeneity in somatic Ca2+ transients. Our analysis, in particular, identifies the origin of such heterogeneity to an intrinsic differentiation of hippocampal neurons in terms of multiple cellular properties pertaining to intracellular Ca2+ signaling, such as VGCC, IP3 receptor, and SERCA expression. In the future, the biophysical model and parameter estimation approach used in this study can be upgraded to predict the response of a system of interconnected neurons.

Identification of optimal flow rate for culture media, cell density, and oxygen toward maximization of virus production in a fed-batch baculovirus-insect cell system.

In recent times, it has been realized that novel vaccines are required to combat emerging disease outbreaks, and faster optimization is required to respond to global vaccine demands. Although, fed-batch operations offer better productivity, experiment-based optimization of a new fed-batch process remains expensive and time-consuming. In this context, we propose a novel computational framework that can be used for process optimization and control of a fed-batch baculovirus-insect cell system. Since the baculovirus expression vector system (BEVS) is known to be widely used platforms for recombinant protein/vaccine production, we chose this system to demonstrate the identification of optimal profile. Toward this, first, we constructed a mathematical model that captures the time course of cell and virus growth in a baculovirus-insect cell system. Second, the proposed model was used for numerical analysis to determine the optimal operating profiles of control variables such as culture media, cell density, and oxygen based on a multiobjective optimal control formulation. Third, a detailed comparison between batch and fed-batch culture was perfromed along with a comparison between various alternatives of fed-batch operation. Finally, we demonstrate that a model-based quantification of controlled feed addition in fed-batch culture is capable of providing better productivity as compared to a batch culture. The proposed framework can be utilized for the estimation of optimal operating regions of different control variables to achieve maximum infected cell density and virus yield while minimizing the substrate/media, uninfected cell, and oxygen consumption.

Three-Dimensional Tracking of Intracellular Calcium and Redox State during Real-Time Control in a Hypoxic Gradient in Microglia Culture: Comparison of the Channel Blocker and Reoxygenation under Ischemic Shock.

Real-time three-dimensional (3-D) imaging is crucial for quantifying correlations among various molecules under acute ischemic stroke. Insights into such correlations may be decisive in selecting molecules capable of providing a protective effect within a shorter period. The major bottleneck is maintaining the cultures under severely hypoxic conditions while simultaneously 3-D imaging intracellular organelles with a microscope. Moreover, comparing the protective effect of drugs and reoxygenation remains challenging. To address this, we propose a novel workflow for the induction of gas-environment-based hypoxia in the HMC-3 cells along with 3-D imaging using laser-scanning-confocal microscopy. The imaging framework is complemented with a pipeline for quantifying time-lapse videos and cell-state classification. First, we show an imaging-based assessment of the in vitro model for hypoxia using a steep gradient in O2 with time. Second, we demonstrate the correlation between mitochondrial superoxide production and cytosolic calcium under acute hypoxia. We then test the efficacy of an L-type calcium channel blocker, compare the results with reoxygenation, and show that the blocker alleviates hypoxic conditions in terms of cytosolic calcium and viability within an acute window of one hour. Furthermore, we show that the drug reduces the expression of oxidative stress markers (HIF1A and OXR1) within the same time window. In the future, this model can also be used to investigate drug toxicity and efficacy under ischemic conditions.

Binary to ternary drug-drug molecular adducts of the antihypertensive drug ketanserin (KTS) with advanced physicochemical properties.

Focusing on a reliable supramolecular synthon approach, novel molecular salts of the antihypertensive medication ketanserin (KTS) with aromatic carboxylic acid derivatives (benzoic acid (BA), 2-hydroxybenzoic acid (2-HBA), and 2,5-dihydroxybenzoic acid (2,5-DHBA)) are reported. Binary salts of KTS with the respective salt former were obtained via solvent-assisted grinding followed by solution crystallization. Salt production was confirmed through crystal structure investigations that revealed proton transfer from the carboxylic acid group of the salt former to the piperidine nitrogen atom of KTS. A rigorous investigation of the crystal packing of novel binary salts of KTS inspired the construction of ternary adducts, and a ternary crystalline product was subsequently identified using milrinone (MLN), another cardiotonic drug. According to our knowledge, this is the first instance of a dual-drug ternary co-crystal combining both antihypertensive drugs. In order to evaluate the impacts of co-crystallization on the in vitro release behaviour of binary and ternary adducts, solubility tests for the cocrystal were carried out under a variety of physiological pH conditions. The results indicate that, in contrast to the parent drug and binary adducts, the solubility rate of the ternary adducts is significantly increased. Finally, the stability of the synthesised adduct was evaluated under a range of conditions, including temperature (40 ± 1 °C), humidity (90% ± 5% RH, 25 °C) and various solvents media, and it was established that they have good stability. We anticipate that the present findings will work with a wide range of medication combinations, providing a potential new approach to create multi-drug systems for cardiovascular disease.

Computational framework to understand the clinical stages of COVID-19 and visualization of time course for various treatment strategies.

Coronavirus disease 2019 is known to be regulated by multiple factors such as delayed immune response, impaired T cell activation, and elevated levels of proinflammatory cytokines. Clinical management of the disease remains challenging due to interplay of various factors as drug candidates may elicit different responses depending on the staging of the disease. In this context, we propose a computational framework which provides insights into the interaction between viral infection and immune response in lung epithelial cells, with an aim of predicting optimal treatment strategies based on infection severity. First, we formulate the model for visualizing the nonlinear dynamics during the disease progression considering the role of T cells, macrophages and proinflammatory cytokines. Here, we show that the model is capable of emulating the dynamic and static data trends of viral load, T cell, macrophage levels, interleukin (IL)-6 and TNF-α levels. Second, we demonstrate the ability of the framework to capture the dynamics corresponding to mild, moderate, severe, and critical condition. Our result shows that, at late phase (>15 days), severity of disease is directly proportional to pro-inflammatory cytokine IL6 and tumor necrosis factor (TNF)-α levels and inversely proportional to the number of T cells. Finally, the simulation framework was used to assess the effect of drug administration time as well as efficacy of single or multiple drugs on patients. The major contribution of the proposed framework is to utilize the infection progression model for clinical management and administration of drugs inhibiting virus replication and cytokine levels as well as immunosuppressant drugs at various stages of the disease.

Non-prophylactic resveratrol-mediated protection of neurite integrity under chronic hypoxia is associated with reduction of Cav1.2 channel expression and calcium overloading.

Cellular hypoxia is a major cause of oxidative stress, culminating in neuronal damage in neurodegenerative diseases. Numerous ex vivo studies have implicated that hypoxia episodes leading to disruption of Ca2+ homeostasis and redox status contribute to the progression of various neuropathologies and cell death. Isolation and maintenance of primary cell culture being cost-intensive, the details of the time course relationship between Ca2+ overload, L-type Ca2+ channel function, and neurite retraction under chronic and long-term hypoxia remain undefined. In order to explore the effect of oxidative stress and Ca2+ overload on neurite length, first, we developed a 5-day-long neurite outgrowth model using N2a cell line. Second, we propose a chronic hypoxia model to investigate the modulation of the L-type Ca2+ channel (Cav1.2) and oxidative resistance gene (OXR1) expression level during the process of neurite retraction and neuronal damage over 32 h. Thirdly, we developed a framework for quantitative analysis of cytosolic Ca2+, superoxide formation, neurite length, and constriction formation in individual cells using live imaging that provides an understanding of molecular targets. Our findings suggest that an increase in cytosolic Ca2+ is a feature of an early phase of hypoxic stress. Further, we demonstrate that augmentation in the L-type channel leads to amplification in Ca2+ overload, ROS accumulation, and a reduction in neurite length during the late phase of hypoxic stress. Next, we demonstrated that non-prophylactic treatment of resveratrol leads to the reduction of calcium overloading under chronic hypoxia via lowering of L-type channel expression. Finally, we demonstrate that resveratrol-mediated reduction of Cav1.2 channel and STAT3 expression are associated with retention of neurite integrity. The proposed in vitro model assumes significance in the context of drug designing and testing that demands monitoring of neurite length and constriction formations by imaging before animal testing.

Analytics Pipeline for Visualization of Single Cell RNA Sequencing Data from Brochoaveolar Fluid in COVID-19 Patients: Assessment of Neuro Fuzzy-C-Means and HDBSCAN.

Since the mutation in SARS-COV2 poses new challenges in designing vaccines, it is imperative to develop advanced tools for visualizing the genetic information. Specially, it remains challenging to address the patient-to-patient variability and identify the signature for severe/critical conditions. In this endeavor we analyze the large-scale RNA-sequencing data collected from broncho-alveolar fluid. In this work, we have used PCA and tSNE for the dimension-reduction. The novelty of the current work is to depict a detailed comparison of k-means, HDBSAN and neuro-fuzzy method in visualization of high-dimension data on gene expression. Clinical Relevance- The subpopulation profiling can be used to study the patient-to patient variability when infected by SARS-COV-2 and its variants. The distribution of cell types can be relevant in designing new drugs that are targeted to control the distribution of epithelial cells T cells and macrophages.

Hydrogen-Bonded Organic Framework Structure: A Metal-Free Electrocatalyst for the Evolution of Hydrogen.

The hydrogen-bonded organic frameworks (HOFs) have gained significant attention due to their various alluring applications in the fascinating field of supramolecular chemistry. Herein, we report the electrocatalytic activity of HOFs toward the hydrogen evolution reaction (HER) by utilizing the molecular adduct of cyanuric and trithiocyanuric acid with various organic substrates (melamine and 4,4'-bipyridine). Both the experimental and theoretical findings provide insights and validate the electrocatalytic activity toward HER applications. This work contributes significantly to designing novel highly efficient metal-free HOF-based electrocatalysts for the HER.

Imaging Methods for the Assessment of a Complex Hydrogel as an Ocular Drug Delivery System for Glaucoma Treatment: Opportunities and Challenges in Preclinical Evaluation.

Glaucoma is one of the leading causes of loss of vision. The problems associated with the marketed formulations of anti-glaucoma drugs are low bioavailability, unwanted side effects, and low patient compliance. Hydrogels are an important class of soft materials that play a crucial role in developing an ocular drug delivery system. They assume a special significance in addressing the problems associated with the marketed formulations of eyedrops. An appropriate design of the hydrogel system capable of encapsulating single or multiple drugs for glaucoma has emerged in recent times to overcome such challenges. Although various modes of imaging play critical roles in assessing the efficacy of these formulations, evaluating hydrogels for drug permeation and retention remains challenging. Especially, the assessment of dual drugs in the hydrogel system is not straightforward due to the complexity in measuring drug penetration and retention for in vivo or ex vivo systems. There is a need to develop tools for the fabrication and validation of hydrogel-based systems that give insight into precorneal retention, biocompatibility, cellular uptake, and cell permeation. The current review highlights some of the complexities in formulating hydrogel and benchmarking technologies, including confocal laser scanning microscopy, fluorescent microscopy, slit-lamp biomicroscopy, and camera-based imaging. This review also summarizes recent evaluations of various hydrogel formulations using in vitro and in vivo models. Further the article will help researchers from various disciplines, including formulation scientists and biologists, set up preclinical protocols for evaluating polymeric hydrogels.

Mapping of structural arrangement of cells and collective calcium transients: an integrated framework combining live cell imaging using confocal microscopy and UMAP-assisted HDBSCAN-based approach.

Live cell calcium (Ca2+) imaging is one of the important tools to record cellular activity during in vitro and in vivo preclinical studies. Specially, high-resolution microscopy can provide valuable dynamic information at the single cell level. One of the major challenges in the implementation of such imaging schemes is to extract quantitative information in the presence of significant heterogeneity in Ca2+ responses attained due to variation in structural arrangement and drug distribution. To fill this gap, we propose time-lapse imaging using spinning disk confocal microscopy and machine learning-enabled framework for automated grouping of Ca2+ spiking patterns. Time series analysis is performed to correlate the drug induced cellular responses to self-assembly pattern present in multicellular systems. The framework is designed to reduce the large-scale dynamic responses using uniform manifold approximation and projection (UMAP). In particular, we propose the suitability of hierarchical DBSCAN (HDBSCAN) in view of reduced number of hyperparameters. We find UMAP-assisted HDBSCAN outperforms existing approaches in terms of clustering accuracy in segregation of Ca2+ spiking patterns. One of the novelties includes the application of non-linear dimension reduction in segregation of the Ca2+ transients with statistical similarity. The proposed pipeline for automation was also proved to be a reproducible and fast method with minimal user input. The algorithm was used to quantify the effect of cellular arrangement and stimulus level on collective Ca2+ responses induced by GPCR targeting drug. The analysis revealed a significant increase in subpopulation containing sustained oscillation corresponding to higher packing density. In contrast to traditional measurement of rise time and decay ratio from Ca2+ transients, the proposed pipeline was used to classify the complex patterns with longer duration and cluster-wise model fitting. The two-step process has a potential implication in deciphering biophysical mechanisms underlying the Ca2+ oscillations in context of structural arrangement between cells.

Mathematical modeling of viral infection dynamics and immune response in SARS-CoV-2: A computational framework for testing drug efficacy.

SARS-CoV-2 has emerged to cause the outbreak of COVID-19, which has expanded into a worldwide human pandemic. Although detailed experimental data on animal experiments would provide insight into drug efficacy, the scientists involved in these experiments would be exposed to severe risks. In this context, we propose a computational framework for studying infection dynamics that can be used to capture the growth rate of viral replication and lung epithelial cell in presence of SARS-CoV-2. Specifically, we formulate the model consisting of a system of non-linear ODEs that can be used for visualizing the infection dynamics in a cell population considering the role of T cells and Macrophages. The major contribution of the proposed simulation method is to utilize the infection progression model in testing the efficacy of the drugs having various mechanisms and analyzing the effect of time of drug administration on virus clearance.Clinical Relevance-The proposed computational framework incorporates viral infection dynamics and role of immune response in Covid-19 that can be used to test the impact of drug efficacy and time of drug administration on infection mitigation.

FDA approved L-type channel blocker Nifedipine reduces cell death in hypoxic A549 cells through modulation of mitochondrial calcium and superoxide generation.

As hypoxia is a major driver for the pathophysiology of COVID-19, it is crucial to characterize the hypoxic response at the cellular and molecular levels. In order to augment drug repurposing with the identification of appropriate molecular targets, investigations on therapeutics preventing hypoxic cell damage is required. In this work, we propose a hypoxia model based on alveolar lung epithelial cells line using chemical inducer, CoCl2 that can be used for testing calcium channel blockers (CCBs). Since recent studies suggested that CCBs may reduce the infectivity of SARS-Cov-2, we specifically select FDA approved calcium channel blocker, nifedipine for the study. First, we examined hypoxia-induced cell morphology and found a significant increase in cytosolic calcium levels, mitochondrial calcium overload as well as ROS production in hypoxic A549 cells. Secondly, we demonstrate the protective behaviour of nifedipine for cells that are already subjected to hypoxia through measurement of cell viability as well as 4D imaging of cellular morphology and nuclear condensation. Thirdly, we show that the protective effect of nifedipine is achieved through the reduction of cytosolic calcium, mitochondrial calcium, and ROS generation. Overall, we outline a framework for quantitative analysis of mitochondrial calcium and ROS using 3D imaging in laser scanning confocal microscopy and the open-source image analysis platform ImageJ. The proposed pipeline was used to visualize mitochondrial calcium and ROS level in individual cells that provide an understanding of molecular targets. Our findings suggest that the therapeutic value of nifedipine may potentially be evaluated in the context of COVID-19 therapeutic trials.

Quantitative Confocal Microscopy for Grouping of Dose-Response Data: Deciphering Calcium Sequestration and Subsequent Cell Death in the Presence of Excess Norepinephrine.

Fluorescent calcium (Ca2+) imaging is one of the preferred methods to record cellular activity during in vitro preclinical studies, high-content drug screening, and toxicity analysis. Visualization and analysis for dose-response data obtained using high-resolution imaging remain challenging, due to the inherent heterogeneity present in the Ca2+ spiking. To address this challenge, we propose measurement of cytosolic Ca2+ ions using spinning-disk confocal microscopy and machine learning-based analytics that is scalable. First, we implemented uniform manifold approximation and projection (UMAP) for visualizing the multivariate time-series dataset in the two-dimensional (2D) plane using Python. The dataset was obtained through live imaging experiments with norepinephrine-induced Ca2+ oscillation in HeLa cells for a large range of doses. Second, we demonstrate that the proposed framework can be used to depict the grouping of the spiking pattern for lower and higher drug doses. To the best of our knowledge, this is the first attempt at UMAP visualization of the time-series dose response and identification of the Ca2+ signature during lytic death. Such quantitative microscopy can be used as a component of a high-throughput data analysis workflow for toxicity analysis.

Dissociation of the G protein ßγ from the Gq-PLCß complex partially attenuates PIP2 hydrolysis.

Phospholipase C ß (PLCß), which is activated by the Gq family of heterotrimeric G proteins, hydrolyzes the inner membrane lipid phosphatidylinositol 4,5-bisphosphate (PIP2), generating diacylglycerol and inositol 1,4,5-triphosphate (IP3). Because Gq and PLCß regulate many crucial cellular processes and have been identified as major disease drivers, activation and termination of PLCß signaling by the Gαq subunit have been extensively studied. Gq-coupled receptor activation induces intense and transient PIP2 hydrolysis, which subsequently recovers to a low-intensity steady-state equilibrium. However, the molecular underpinnings of this equilibrium remain unclear. Here, we explored the influence of signaling crosstalk between Gq and Gi/o pathways on PIP2 metabolism in living cells using single-cell and optogenetic approaches to spatially and temporally constrain signaling. Our data suggest that the Gßγ complex is a component of the highly efficient lipase GαqGTP-PLCß-Gßγ. We found that over time, Gßγ dissociates from this lipase complex, leaving the less-efficient GαqGTP-PLCß lipase complex and allowing the significant partial recovery of PIP2 levels. Our findings also indicate that the subtype of the Gγ subunit in Gßγ fine-tunes the lipase activity of Gq-PLCß, in which cells expressing Gγ with higher plasma membrane interaction show lower PIP2 recovery. Given that Gγ shows cell- and tissue-specific subtype expression, our findings suggest the existence of tissue-specific distinct Gq-PLCß signaling paradigms. Furthermore, these results also outline a molecular process that likely safeguards cells from excessive Gq signaling.