Ligand-specific c-Fos expression emerges from the spatiotemporal control of ErbB network dynamics.

Activation of ErbB receptors by epidermal growth factor (EGF) or heregulin (HRG) determines distinct cell-fate decisions, although signals propagate through shared pathways. Using mathematical modeling and experimental approaches, we unravel how HRG and EGF generate distinct, all-or-none responses of the phosphorylated transcription factor c-Fos. In the cytosol, EGF induces transient and HRG induces sustained ERK activation. In the nucleus, however, ERK activity and c-fos mRNA expression are transient for both ligands. Knockdown of dual-specificity phosphatases extends HRG-stimulated nuclear ERK activation, but not c-fos mRNA expression, implying the existence of a HRG-induced repressor of c-fos transcription. Further experiments confirmed that this repressor is mainly induced by HRG, but not EGF, and requires new protein synthesis. We show how a spatially distributed, signaling-transcription cascade robustly discriminates between transient and sustained ERK activities at the c-Fos system level. The proposed control mechanisms are general and operate in different cell types, stimulated by various ligands.

Identification of manipulated variables for a glycosylation control strategy.

N-linked glycan distribution affects important end-use characteristics such as the bioactivity and efficacy of many therapeutic proteins, (including monoclonal antibodies), in vivo. Yet, obtaining desired glycan distributions consistently during batch-to-batch production can be challenging for biopharmaceutical manufacturers. While an appropriately implemented on-line glycosylation control strategy during production can help to ensure a consistent glycan distribution, to date no such strategies have been reported. Our goal is to develop and validate a comprehensive strategy for effective on-line control of glycosylation, the successful achievement of which requires first identifying appropriate manipulated variables that can be used to direct the glycan distribution to a desired state. While various culture conditions such as bioreactor process variables, media type, and media supplements have been shown to affect the glycan distribution, in this study we focus on the latter. Specifically, we implemented a statistically designed series of experiments to determine the significant main effects (as well as interaction effects) of media supplementation with manganese, galactose, ammonia and found that each had significant effects on certain glycans. We also include data indicating the glycosylation enzyme gene transcript levels as well as the intracellular nucleotide sugar concentrations in the presence of the media supplements to provide insight into the intracellular conditions that may be contributing to the changes in glycan distribution. The acquired experimental data sets were then used to identify which glycans can be controlled by the media supplements and to what degree. We determined that MnCl2 can be used as a manipulated variable to increase the relative abundance of M51 and decrease FA2 simultaneously, and galactose can be used as a manipulated variable to increase the relative abundance of FA2G1 and decrease FA2 and A2 simultaneously.

Coordinated dynamic gene expression changes in the central nucleus of the amygdala during alcohol withdrawal.

BACKGROUND: Chronic alcohol use causes widespread changes in the cellular biology of the amygdala's central nucleus (CeA), a GABAergic center that integrates autonomic physiology with the emotional aspects of motivation and learning. While alcohol-induced neurochemical changes play a role in dependence and drinking behavior, little is known about the CeA's dynamic changes during withdrawal, a period of emotional and physiologic disturbance. METHODS: We used a qRT-PCR platform to measure 139 transcripts in 92 rat CeA samples from control (N = 33), chronically alcohol exposed (N = 26), and withdrawn rats (t = 4, 8, 18, 32, and 48 hours; N = 5, 10, 7, 6, 5). This focused transcript set allowed us to identify significant dynamic expression patterns during the first 48 hours of withdrawal and propose potential regulatory mechanisms. RESULTS: Chronic alcohol exposure causes a limited number of small magnitude expression changes. In contrast, withdrawal results in a greater number of large changes within 4 hours of removal of the alcohol diet. Sixty-five of the 139 measured transcripts (47%) showed differential regulation during withdrawal. Over the 48-hour period, dynamic changes in the expression of γ-aminobutyric acid type A (GABA(A) ), ionotropic glutamate and neuropeptide system-related G-protein-coupled receptor subunits, and the Ras/Raf signaling pathway were seen as well as downstream transcription factors (TFs) and epigenetic regulators. Four temporally correlated gene clusters were identified with shared functional roles including NMDA receptors, MAPKKK and chemokine signaling cascades, and mediators of long-term potentiation, among others. Cluster promoter regions shared overrepresented binding sites for multiple TFs including Cebp, Usf-1, Smad3, Ap-2, and c-Ets, suggesting a potential regulatory role. CONCLUSIONS: During alcohol withdrawal, the CeA experiences rapid changes in mRNA expression of these functionally related transcripts that were not predicted by measurement during chronic exposure. This study provides new insight into dynamic expression changes during alcohol withdrawal and suggests novel regulatory relationships that potentially impact the aspects of emotional modulation.

Elucidating the Mechanisms of Dynamic and Robust Control of the Liver Homeostatic Renewal Process: Cell Network Modeling and Analysis.

Recent experimental investigations of liver homeostatic renewal have identified high replication capacity hepatocyte populations as the primary maintainers of liver mass. However, the molecular and cellular processes controlling liver homeostatic renewal remain unknown. To address this problem, we developed and analyzed a mathematical model describing cellular network interactions underlying liver homeostatic renewal. Model simulation results demonstrate that without feedback control, basic homeostatic renewal is not robust to disruptions, leading to tissue loss under persistent/repetitive insults. Consequently, we extended our basic model to incorporate putative regulatory interactions and investigated how such interactions may confer robustness on the homeostatic renewal process. We utilized a Design of Experiments approach to identify the combination of feedback interactions that yields a cell network model of homeostatic renewal capable of maintaining liver mass robustly during persistent/repetitive injury. Simulations of this robust model indicate that repeated injury destabilizes liver homeostasis within several months, which differs from epidemiological observations of a much slower decay of liver function occurring over several years. To address this discrepancy, we extended the model to include feedback control by liver nonparenchymal cells. Simulations and analysis of the final multicellular feedback control network suggest that achieving robust liver homeostatic renewal requires intrinsic stability in a hepatocellular network combined with feedback control by nonparenchymal cells.

Closed-loop modeling of central and intrinsic cardiac nervous system circuits underlying cardiovascular control.

The baroreflex is a multi-input, multi-output control physiological system that regulates blood pressure by modulating nerve activity between the brainstem and the heart. Existing computational models of the baroreflex do not explictly incorporate the intrinsic cardiac nervous system (ICN), which mediates central control of the heart function. We developed a computational model of closed-loop cardiovascular control by integrating a network representation of the ICN within central control reflex circuits. We examined central and local contributions to the control of heart rate, ventricular functions, and respiratory sinus arrhythmia (RSA). Our simulations match the experimentally observed relationship between RSA and lung tidal volume. Our simulations predicted the relative contributions of the sensory and the motor neuron pathways to the experimentally observed changes in the heart rate. Our closed-loop cardiovascular control model is primed for evaluating bioelectronic interventions to treat heart failure and renormalize cardiovascular physiology.

Systems Engineering Approach to Modeling and Analysis of Chronic Obstructive Pulmonary Disease.

Chronic obstructive pulmonary disease (COPD) is a progressive lung disease characterized by airflow limitation. This study develops a systems engineering framework for representing important mechanistic details of COPD in a model of the cardiorespiratory system. In this model, we present the cardiorespiratory system as an integrated biological control system responsible for regulating breathing. Four engineering control system components are considered: sensor, controller, actuator, and the process itself. Knowledge of human anatomy and physiology is used to develop appropriate mechanistic mathematical models for each component. Following a systematic analysis of the computational model, we identify three physiological parameters associated with reproducing clinical manifestations of COPD: changes in the forced expiratory volume, lung volumes, and pulmonary hypertension. We quantify the changes in these parameters (airway resistance, lung elastance, and pulmonary resistance) as the ones that result in a systemic response that is diagnostic of COPD. A multivariate analysis of the simulation results reveals that the changes in airway resistance have a broad impact on the human cardiorespiratory system and that the pulmonary circuit is stressed beyond normal under hypoxic environments in most COPD patients.

A spatial model for integrin clustering as a result of feedback between integrin activation and integrin binding.

Integrins are transmembrane adhesion receptors that bind extracellular matrix (ECM) proteins and signal bidirectionally to regulate cell adhesion and migration. In many cell types, integrins cluster at cell-ECM contacts to create the foundation for adhesion complexes that transfer force between the cell and the ECM. Even though the temporal and spatial regulation of these integrin clusters is essential for cell migration, how cells regulate their formation is currently unknown. It has been shown that integrin cluster formation is independent of actin stress fiber formation, but requires active (high-affinity) integrins, phosphoinositol-4,5-bisphosphate (PIP2), talin, and immobile ECM ligand. Based on these observations, we propose a minimal model for initial formation of integrin clusters, facilitated by localized activation and binding of integrins to ECM ligands as a result of biochemical feedback between integrin binding and integrin activation. By employing a diffusion-reaction framework for modeling these reactions, we show how spatial organization of bound integrins into clusters may be achieved by a local source of active integrins, namely protein complexes formed on the cytoplasmic tails of bound integrins. Further, we show how such a mechanism can turn small local increases in the concentration of active talin or active integrin into integrin clusters via positive feedback. Our results suggest that the formation of integrin clusters by the proposed mechanism depends on the relationships between production and diffusion of integrin-activating species, and that changes to the relative rates of these processes may affect the resulting properties of integrin clusters.

Rapid temporal changes in the expression of a set of neuromodulatory genes during alcohol withdrawal in the dorsal vagal complex: molecular evidence of homeostatic disturbance.

BACKGROUND: Chronic alcohol exposure produces neuroadaptation, which increases the risk of cellular excitotoxicity and autonomic dysfunction during withdrawal. The temporal progression and regulation of the gene expression that contributes to this physiologic and behavioral phenotype is poorly understood early in the withdrawal period. Further, it is unexplored in the dorsal vagal complex (DVC), a brainstem autonomic regulatory structure. METHODS: We use a quantitative polymerase chain reaction platform to precisely and simultaneously measure the expression of 145 neuromodulatory genes in more than 100 rat DVC samples from control, chronically alcohol-exposed, and withdrawn rats. To gain insight into the dynamic progression and regulation of withdrawal, we focus on the expression of a subset of functionally relevant genes during the first 48 hours, when behavioral symptoms are most severe. RESULTS: In the DVC, expression of this gene subset is essentially normal in chronically alcohol-exposed rats. However, withdrawal results in rapid, large-magnitude expression changes in this group. We observed differential regulation in 86 of the 145 genes measured (59%), some as early as 4 hours into withdrawal. Time series measurements (4, 8, 18, 32, and 48 hours after alcohol removal) revealed dynamic expression responses in immediate early genes, γ-aminobutyric acid type A, ionotropic glutamate, and G-protein coupled receptors and the Ras/Raf signaling pathway. Together, these changes elucidate a complex, temporally coordinated response that involves correlated expression of many functionally related groups. In particular, the expression patterns of Gabra1, Grin2a, Grin3a, and Grik3 were tightly correlated. These receptor subunits share overrepresented transcription factor binding sites for Pax-8 and other transcription factors, suggesting a common regulatory mechanism and a role for these transcription factors in the regulation of neurotransmission within the first 48 hours of alcohol withdrawal. CONCLUSIONS: Expression in this gene set is essentially normal in the alcohol-adapted DVC, but withdrawal results in immediate, large-magnitude, and dynamic changes. These data support both increased research focus on the biological ramifications of alcohol withdrawal and enable novel insights into the dynamic withdrawal expression response in this understudied homeostatic control center.

Rational Design of Hydrogel Networks with Dynamic Mechanical Properties to Mimic Matrix Remodeling.

Engineered hydrogels are increasingly used as extracellular matrix (ECM) surrogates for probing cell function in response to ECM remodeling events related to injury or disease (e.g., degradation followed by deposition/crosslinking). Inspired by these events, this work establishes an approach for pseudo-reversible mechanical property modulation in synthetic hydrogels by integrating orthogonal, enzymatically triggered crosslink degradation, and light-triggered photopolymerization stiffening. Hydrogels are formed by a photo-initiated thiol-ene reaction between multiarm polyethylene glycol and a dually enzymatically degradable peptide linker, which incorporates a thrombin-degradable sequence for triggered softening and a matrix metalloproteinase (MMP)-degradable sequence for cell-driven remodeling. Hydrogels are stiffened by photopolymerization using a flexible, MMP-degradable polymer-peptide conjugate and multiarm macromers, increasing the synthetic matrix crosslink density while retaining degradability. Integration of these tools enables sequential softening and stiffening inspired by matrix remodeling events within loose connective tissues (Young's modulus (E) ≈5 to 1.5 to 6 kPa with >3x ΔE). The cytocompatibility and utility of this approach is examined with breast cancer cells, where cell proliferation shows a dependence on the timing of triggered softening. This work provides innovative tools for 3D dynamic property modulation that are synthetically accessible and cell compatible.

A Spatial Model of Hepatic Calcium Signaling and Glucose Metabolism Under Autonomic Control Reveals Functional Consequences of Varying Liver Innervation Patterns Across Species.

Rapid breakdown of hepatic glycogen stores into glucose plays an important role during intense physical exercise to maintain systemic euglycemia. Hepatic glycogenolysis is governed by several different liver-intrinsic and systemic factors such as hepatic zonation, circulating catecholamines, hepatocellular calcium signaling, hepatic neuroanatomy, and the central nervous system (CNS). Of the factors regulating hepatic glycogenolysis, the extent of lobular innervation varies significantly between humans and rodents. While rodents display very few autonomic nerve terminals in the liver, nearly every hepatic layer in the human liver receives neural input. In the present study, we developed a multi-scale, multi-organ model of hepatic metabolism incorporating liver zonation, lobular scale calcium signaling, hepatic innervation, and direct and peripheral organ-mediated communication between the liver and the CNS. We evaluated the effect of each of these governing factors on the total hepatic glucose output and zonal glycogenolytic patterns within liver lobules during simulated physical exercise. Our simulations revealed that direct neuronal stimulation of the liver and an increase in circulating catecholamines increases hepatic glucose output mediated by mobilization of intracellular calcium stores and lobular scale calcium waves. Comparing simulated glycogenolysis between human-like and rodent-like hepatic innervation patterns (extensive vs. minimal) suggested that propagation of calcium transients across liver lobules acts as a compensatory mechanism to improve hepatic glucose output in sparsely innervated livers. Interestingly, our simulations suggested that catecholamine-driven glycogenolysis is reduced under portal hypertension. However, increased innervation coupled with strong intercellular communication can improve the total hepatic glucose output under portal hypertension. In summary, our modeling and simulation study reveals a complex interplay of intercellular and multi-organ interactions that can lead to differing calcium dynamics and spatial distributions of glycogenolysis at the lobular scale in the liver.

Modeling the Effect of Amino Acids and Copper on Monoclonal Antibody Productivity and Glycosylation: A Modular Approach.

In manufacturing monoclonal antibodies (mAbs), it is crucial to be able to predict how process conditions and supplements affect productivity and quality attributes, especially glycosylation. Supplemental inputs, such as amino acids and trace metals in the media, are reported to affect cell metabolism and glycosylation; quantifying their effects is essential for effective process development. We aim to present and validate, through a commercially relevant cell culture process, a technique for modeling such effects efficiently. While existing models can predict mAb production or glycosylation dynamics under specific process configurations, adapting them to new processes remains challenging, because it involves modifying the model structure and often requires some mechanistic understanding. Here, a modular modeling technique for adapting an existing model for a fed-batch Chinese hamster ovary (CHO) cell culture process without structural modifications or mechanistic insight is presented. Instead, data is used, obtained from designed experimental perturbations in media supplementation, to train and validate a supplemental input effect model, which is used to "patch" the existing model. The combined model can be used for model-based process development to improve productivity and to meet product quality targets more efficiently. The methodology and analysis are generally applicable to other CHO cell lines and cell types.

Low-dose aspirin for preventing intrauterine growth restriction and pre-eclampsia in sickle cell pregnancy (PIPSICKLE): a randomised controlled trial (study protocol).

INTRODUCTION: Pregnancy in sickle cell disease is fraught with many complications including pre-eclampsia (PE) and intrauterine growth restriction (IUGR). Previously, we found an abnormality in prostacyclin-thromboxane ratio in sickle cell pregnant women, a situation that is also found in non-sickle pregnancies with PE and unexplained IUGR. Low-dose aspirin (LDA) has been shown to reduce the incidence of PE and IUGR in high-risk women by reducing the vasoconstrictor thromboxane while sparing prostacyclin, in effect 'correcting' the ratio. It has been found to be safe for use in pregnancy but has not been tested in sickle cell pregnancy. We hypothesise that LDA will reduce the incidence of IUGR and PE in pregnant haemoglobin SS (HbSS) and haemoglobin SC (HbSC) women. METHODS AND ANALYSIS: This is a multisite, double blind, randomised controlled trial, comparing a daily dose of 100 mg aspirin to placebo, from 12 to 16 weeks' gestation until 36 weeks, in Lagos state, Nigeria. Four hundred and seventy-six eligible pregnant HbSS and HbSC women will be recruited consecutively, randomly assigned to either group and followed from recruitment until delivery. The primary outcome will be the incidence of birth weight below 10th centile for gestational age on INTERGROWTH 21 birth weight charts, or incidence of miscarriage or perinatal death. Secondary outcomes will include PE, maternal death, preterm delivery, perinatal death, number of crises, need for blood transfusion and complications such as infections and placental abruption. Analysis will be by intention to treat and the main treatment effects will be quantified by relative risk with 95% CI, at a 5% significance level. ETHICAL APPROVAL: Ethical approval has been granted by the Health Research and Ethics committees of the recruiting hospitals and the National Health Research and Ethics Committee. Study findings will be presented at conferences and published appropriately. TRAIL REGISTRATION NUMBER: PACTR202001787519553; Pre-results.

A probabilistic framework for microarray data analysis: fundamental probability models and statistical inference.

Gene expression studies generate large quantities of data with the defining characteristic that the number of genes (whose expression profiles are to be determined) exceed the number of available replicates by several orders of magnitude. Standard spot-by-spot analysis still seeks to extract useful information for each gene on the basis of the number of available replicates, and thus plays to the weakness of microarrays. On the other hand, because of the data volume, treating the entire data set as an ensemble, and developing theoretical distributions for these ensembles provides a framework that plays instead to the strength of microarrays. We present theoretical results that under reasonable assumptions, the distribution of microarray intensities follows the Gamma model, with the biological interpretations of the model parameters emerging naturally. We subsequently establish that for each microarray data set, the fractional intensities can be represented as a mixture of Beta densities, and develop a procedure for using these results to draw statistical inference regarding differential gene expression. We illustrate the results with experimental data from gene expression studies on Deinococcus radiodurans following DNA damage using cDNA microarrays.

An Exceedingly Rare Presentation of Severe Folate Deficiency-Induced Non-Immune Hemolytic Anemia.

Macrocytic anemia is usually associated with vitamin B12 or folate deficiency. However, folate deficiency was rarely reported as a cause of hemolytic anemia. We present a case of a young man with a history of alcohol abuse who initially presented with an acute on chronic abdominal pain and was found to have jaundice and scleral icterus. His liver enzymes were unremarkable, and his abdominal imaging did not reveal any acute pathology. However, he was found to have a severe non-immune hemolytic anemia secondary to folate deficiency.

The growth of methylammonium lead iodide perovskites by close space vapor transport.

Vapor deposition processes have shown promise for high-quality perovskite solar cells with potential pathways for scale-up to large area manufacturing. Here, we present a sequential close space vapor transport process to deposit CH3NH3PbI3 (MAPI) perovskite thin films by depositing a layer of PbI2 then reacting it with CH3NH3I (MAI) vapor. We find that, at T = 100 °C and pressure = 9 torr, a ∼225 nm-thick PbI2 film requires ≥125 minutes in MAI vapor to form a fully-reacted MAPI film. Raising the temperature to 160 °C increases the rate of reaction, such that MAPI forms within 15 minutes, but with reduced surface coverage. The reaction kinetics can be approximated as roughly first-order with respect to PbI2, though there is evidence for a more complicated functional relation. Perovskite films reacted at 100 °C for 150 minutes were fabricated into solar cells with an SLG/ITO/CdS/MAPI/Spiro-OMeTAD/Au structure, and a device efficiency of 12.1% was achieved. These results validate the close space vapor transport process and serve as an advance toward scaled-up, vapor-phase perovskite manufacturing through continuous vapor transport deposition.

Diurnal Patterns of Gene Expression in the Dorsal Vagal Complex and the Central Nucleus of the Amygdala - Non-rhythm-generating Brain Regions.

Genes that establish the circadian clock have differential expression with respect to solar time in central and peripheral tissues. Here, we find circadian-time-induced differential expression in a large number of genes not associated with circadian rhythms in two brain regions lacking overt circadian function: the dorsal vagal complex (DVC) and the central nucleus of the amygdala (CeA). These regions primarily engage in autonomic, homeostatic, and emotional regulation. However, we find striking diurnal shifts in gene expression in these regions of male Sprague Dawley rats with no obvious patterns that could be attributed to function or region. These findings have implications for the design of gene expression studies as well as for the potential effects of xenobiotics on these regions that regulate autonomic and emotional states.

Quantitative modeling and analysis of the transforming growth factor beta signaling pathway.

Transforming growth factor beta (TGF-beta) signaling, which regulates multiple cellular processes including proliferation, apoptosis, and differentiation, plays an important but incompletely understood role in normal and cancerous tissues. For instance, although TGF-beta functions as a tumor suppressor in the premalignant stages of tumorigenesis, paradoxically, it also seems to act as a tumor promoter in advanced cancer leading to metastasis. The mechanisms by which TGF-beta elicits such diverse responses during cancer progression are still not entirely clear. As a first step toward understanding TGF-beta signaling quantitatively, we have developed a comprehensive, dynamic model of the canonical TGF-beta pathway via Smad transcription factors. By describing how an extracellular signal of the TGF-beta ligand is sensed by receptors and transmitted into the nucleus through intracellular Smad proteins, the model provides quantitative insight into how TGF-beta-induced responses are modulated and regulated. Subsequent model analysis shows that mechanisms associated with Smad activation by ligand-activated receptor, nuclear complex formation among Smad proteins, and inactivation of ligand-activated Smad (e.g., degradation, dephosphorylation) may be critical for regulating TGF-beta-targeted functional responses. The model was also used to predict dynamic characteristics of the Smad-mediated pathway in abnormal cells, from which we generated four testable hypotheses regarding potential mechanisms by which TGF-beta's tumor-suppressive roles may appear to morph into tumor-promotion during cancer progression.

Reliable preparation of agarose phantoms for use in quantitative magnetic resonance elastography.

Agarose phantoms are one type of phantom commonly used in developing in vivo brain magnetic resonance elastography (MRE) sequences because they are inexpensive and easy to work with, store, and dispose of; however, protocols for creating agarose phantoms are non-standardized and often result in inconsistent phantoms with significant variability in mechanical properties. Many magnetic resonance imaging (MRI) and ultrasound studies use phantoms, but often these phantoms are not tailored for desired mechanical properties and as such are too stiff or not mechanically consistent enough to be used in MRE. In this work, we conducted a systematic study of agarose phantom creation parameters to identify those factors that are most conducive to producing mechanically consistent agarose phantoms for MRE research. We found that cooling rate and liquid temperature affected phantom homogeneity. Phantom stiffness is affected by agar concentration (quadratically), by final liquid temperature and salt content in phantoms, and by the interaction of these two metrics each with stir rate. We captured and quantified the implied relationships with a regression model that can be used to estimate stiffness of resulting phantoms. Additionally, we characterized repeatability, stability over time, impact on MR signal parameters, and differences in agar gel microstructure. This protocol and regression model should prove beneficial in future MRE development studies that use phantoms to determine stiffness measurement accuracy.

Ligand-dependent responses of the ErbB signaling network: experimental and modeling analyses.

Deregulation of ErbB signaling plays a key role in the progression of multiple human cancers. To help understand ErbB signaling quantitatively, in this work we combine traditional experiments with computational modeling, building a model that describes how stimulation of all four ErbB receptors with epidermal growth factor (EGF) and heregulin (HRG) leads to activation of two critical downstream proteins, extracellular-signal-regulated kinase (ERK) and Akt. Model analysis and experimental validation show that (i) ErbB2 overexpression, which occurs in approximately 25% of all breast cancers, transforms transient EGF-induced signaling into sustained signaling, (ii) HRG-induced ERK activity is much more robust to the ERK cascade inhibitor U0126 than EGF-induced ERK activity, and (iii) phosphoinositol-3 kinase is a major regulator of post-peak but not pre-peak EGF-induced ERK activity. Sensitivity analysis leads to the hypothesis that ERK activation is robust to parameter perturbation at high ligand doses, while Akt activation is not.

Causality Analysis and Cell Network Modeling of Spatial Calcium Signaling Patterns in Liver Lobules.

Dynamics as well as localization of Ca2+ transients plays a vital role in liver function under homeostatic conditions, repair, and disease. In response to circulating hormonal stimuli, hepatocytes exhibit intracellular Ca2+ responses that propagate through liver lobules in a wave-like fashion. Although intracellular processes that control cell autonomous Ca2+ spiking behavior have been studied extensively, the intra- and inter-cellular signaling factors that regulate lobular scale spatial patterns and wave-like propagation of Ca2+ remain to be determined. To address this need, we acquired images of cytosolic Ca2+ transients in 1300 hepatocytes situated across several mouse liver lobules over a period of 1600 s. We analyzed this time series data using correlation network analysis, causal network analysis, and computational modeling, to characterize the spatial distribution of heterogeneity in intracellular Ca2+ signaling components as well as intercellular interactions that control lobular scale Ca2+ waves. Our causal network analysis revealed that hepatocytes are causally linked to multiple other co-localized hepatocytes, but these influences are not necessarily aligned uni-directionally along the sinusoids. Our computational model-based analysis showed that spatial gradients of intracellular Ca2+ signaling components as well as intercellular molecular exchange are required for lobular scale propagation of Ca2+ waves. Additionally, our analysis suggested that causal influences of hepatocytes on Ca2+ responses of multiple neighbors lead to robustness of Ca2+ wave propagation through liver lobules.