Dynamic dysregulation of transcriptomic networks in brainstem autonomic nuclei during hypertension development in the female spontaneously hypertensive rat.

Neurogenic hypertension stems from an imbalance in autonomic function that shifts the central cardiovascular control circuits toward a state of dysfunction. Using the female spontaneously hypertensive rat and the normotensive Wistar-Kyoto rat model, we compared the transcriptomic changes in three autonomic nuclei in the brainstem, nucleus of the solitary tract (NTS), caudal ventrolateral medulla, and rostral ventrolateral medulla (RVLM) in a time series at 8, 10, 12, 16, and 24 wk of age, spanning the prehypertensive stage through extended chronic hypertension. RNA-sequencing data were analyzed using an unbiased, dynamic pattern-based approach that uncovered dominant and several subtle differential gene regulatory signatures. Our results showed a persistent dysregulation across all three autonomic nuclei regardless of the stage of hypertension development as well as a cascade of transient dysregulation beginning in the RVLM at the prehypertensive stage that shifts toward the NTS at the hypertension onset. Genes that were persistently dysregulated were heavily enriched for immunological processes such as antigen processing and presentation, the adaptive immune response, and the complement system. Genes with transient dysregulation were also largely region-specific and were annotated for processes that influence neuronal excitability such as synaptic vesicle release, neurotransmitter transport, and an array of neuropeptides and ion channels. Our results demonstrate that neurogenic hypertension is characterized by brainstem region-specific transcriptomic changes that are highly dynamic with significant gene regulatory changes occurring at the hypertension onset as a key time window for dysregulation of homeostatic processes across the autonomic control circuits.NEW & NOTEWORTHY Hypertension is a major disease and is the primary risk factor for cardiovascular complications and stroke. The gene expression changes in the central nervous system circuits driving hypertension are understudied. Here, we show that coordinated and region-specific gene expression changes occur in the brainstem autonomic circuits over time during the development of a high blood pressure phenotype in a rat model of human essential hypertension.

Integrated transcriptomics and histopathology approach identifies a subset of rejected donor livers with potential suitability for transplantation.

BACKGROUND: Liver transplantation is an effective treatment for liver failure. There is a large unmet demand, even as not all donated livers are transplanted. The clinical selection criteria for donor livers based on histopathological evaluation and liver function tests are variable. We integrated transcriptomics and histopathology to characterize donor liver biopsies obtained at the time of organ recovery. We performed RNA sequencing as well as manual and artificial intelligence-based histopathology (10 accepted and 21 rejected for transplantation). RESULTS: We identified two transcriptomically distinct rejected subsets (termed rejected-1 and rejected-2), where rejected-2 exhibited a near-complete transcriptomic overlap with the accepted livers, suggesting acceptability from a molecular standpoint. Liver metabolic functional genes were similarly upregulated, and extracellular matrix genes were similarly downregulated in the accepted and rejected-2 groups compared to rejected-1. The transcriptomic pattern of the rejected-2 subset was enriched for a gene expression signature of graft success post-transplantation. Serum AST, ALT, and total bilirubin levels showed similar overlapping patterns. Additional histopathological filtering identified cases with borderline scores and extensive molecular overlap with accepted donor livers. CONCLUSIONS: Our integrated approach identified a subset of rejected donor livers that are likely suitable for transplantation, demonstrating the potential to expand the pool of transplantable livers.

Unpacking the multimodal, multi-scale data of the fast and slow lanes of the cardiac vagus through computational modelling.

NEW FINDINGS: What is the topic of this review? The vagus nerve is a crucial regulator of cardiovascular homeostasis, and its activity is linked to heart health. Vagal activity originates from two brainstem nuclei: the nucleus ambiguus (fast lane) and the dorsal motor nucleus of the vagus (slow lane), nicknamed for the time scales that they require to transmit signals. What advances does it highlight? Computational models are powerful tools for organizing multi-scale, multimodal data on the fast and slow lanes in a physiologically meaningful way. A strategy is laid out for how these models can guide experiments aimed at harnessing the cardiovascular health benefits of differential activation of the fast and slow lanes. ABSTRACT: The vagus nerve is a key mediator of brain-heart signaling, and its activity is necessary for cardiovascular health. Vagal outflow stems from the nucleus ambiguus, responsible primarily for fast, beat-to-beat regulation of heart rate and rhythm, and the dorsal motor nucleus of the vagus, responsible primarily for slow regulation of ventricular contractility. Due to the high-dimensional and multimodal nature of the anatomical, molecular and physiological data on neural regulation of cardiac function, data-derived mechanistic insights have proven elusive. Elucidating insights has been complicated further by the broad distribution of the data across heart, brain and peripheral nervous system circuits. Here we lay out an integrative framework based on computational modelling for combining these disparate and multi-scale data on the two vagal control lanes of the cardiovascular system. Newly available molecular-scale data, particularly single-cell transcriptomic analyses, have augmented our understanding of the heterogeneous neuronal states underlying vagally mediated fast and slow regulation of cardiac physiology. Cellular-scale computational models built from these data sets represent building blocks that can be combined using anatomical and neural circuit connectivity, neuronal electrophysiology, and organ/organismal-scale physiology data to create multi-system, multi-scale models that enable in silico exploration of the fast versus slow lane vagal stimulation. The insights from the computational modelling and analyses will guide new experimental questions on the mechanisms regulating the fast and slow lanes of the cardiac vagus toward exploiting targeted vagal neuromodulatory activity to promote cardiovascular health.

Innervation and Neuronal Control of the Mammalian Sinoatrial Node a Comprehensive Atlas.

[Figure: see text].

Integrated Multiomics Reveals Glucose Use Reprogramming and Identifies a Novel Hexokinase in Alcoholic Hepatitis.

BACKGROUND & AIMS: We recently showed that alcoholic hepatitis (AH) is characterized by dedifferentiation of hepatocytes and loss of mature functions. Glucose metabolism is tightly regulated in healthy hepatocytes. We hypothesize that AH may lead to metabolic reprogramming of the liver, including dysregulation of glucose metabolism. METHODS: We performed integrated metabolomic and transcriptomic analyses of liver tissue from patients with AH or alcoholic cirrhosis or normal liver tissue from hepatic resection. Focused analyses of chromatin immunoprecipitation coupled to DNA sequencing was performed. Functional in vitro studies were performed in primary rat and human hepatocytes and HepG2 cells. RESULTS: Patients with AH exhibited specific changes in the levels of intermediates of glycolysis/gluconeogenesis, the tricarboxylic acid cycle, and monosaccharide and disaccharide metabolism. Integrated analysis of the transcriptome and metabolome showed the used of alternate energetic pathways, metabolite sinks and bottlenecks, and dysregulated glucose storage in patients with AH. Among genes involved in glucose metabolism, hexokinase domain containing 1 (HKDC1) was identified as the most up-regulated kinase in patients with AH. Histone active promoter and enhancer markers were increased in the HKDC1 genomic region. High HKDC1 levels were associated with the development of acute kidney injury and decreased survival. Increased HKDC1 activity contributed to the accumulation of glucose-6-P and glycogen in primary rat hepatocytes. CONCLUSIONS: Altered metabolite levels and messenger RNA expression of metabolic enzymes suggest the existence of extensive reprogramming of glucose metabolism in AH. Increased HKDC1 expression may contribute to dysregulated glucose metabolism and represents a novel biomarker and therapeutic target for AH.

Dysregulation of miR-21-associated miRNA regulatory networks by chronic ethanol consumption impairs liver regeneration.

Impaired liver regeneration has been considered as a hallmark of progression of alcohol-associated liver disease. Our previous studies demonstrated that in vivo inhibition of the microRNA (miRNA) miR21 can restore regenerative capacity of the liver in chronic ethanol-fed animals. The present study focuses on the role of microRNA regulatory networks that are likely to mediate the miR-21 action. Rats were chronically fed an ethanol-enriched diet along with pair-fed control animals and treated with AM21 (anti-miR-21), a locked nucleic acid antisense to miR-21. Partial hepatectomy (PHx) was performed and miRNA expression profiling over the course of liver regeneration was assessed. Our results showed dynamic expression changes in several miRNAs after PHx, notably with altered miRNA expression profiles between ethanol and control groups. We found that in vivo inhibition of miR-21 led to correlated differential expression of miR-340-5p and anticorrelated expression of miR-365, let-7a, miR-1224, and miR-146a across all sample groups after PHx. Gene set enrichment analysis identified a miRNA signature significantly associated with hepatic stellate cell activation within whole liver tissue data. We hypothesized that at least part of the PHx-induced miRNA network changes responsive to miR-21 inhibition is localized to hepatic stellate cells. We validated this hypothesis using AM21 and TGF-ß treatments in LX-2 human hepatic stellate cells in culture and measured expression levels of select miRNAs by quantitative RT-PCR. Based on the in vivo and in vitro results, we propose a hepatic stellate cell miRNA regulatory network as contributing to the restoration of liver regenerative capacity by miR-21 inhibition.

Credible practice of modeling and simulation in healthcare: ten rules from a multidisciplinary perspective.

The complexities of modern biomedicine are rapidly increasing. Thus, modeling and simulation have become increasingly important as a strategy to understand and predict the trajectory of pathophysiology, disease genesis, and disease spread in support of clinical and policy decisions. In such cases, inappropriate or ill-placed trust in the model and simulation outcomes may result in negative outcomes, and hence illustrate the need to formalize the execution and communication of modeling and simulation practices. Although verification and validation have been generally accepted as significant components of a model's credibility, they cannot be assumed to equate to a holistic credible practice, which includes activities that can impact comprehension and in-depth examination inherent in the development and reuse of the models. For the past several years, the Committee on Credible Practice of Modeling and Simulation in Healthcare, an interdisciplinary group seeded from a U.S. interagency initiative, has worked to codify best practices. Here, we provide Ten Rules for credible practice of modeling and simulation in healthcare developed from a comparative analysis by the Committee's multidisciplinary membership, followed by a large stakeholder community survey. These rules establish a unified conceptual framework for modeling and simulation design, implementation, evaluation, dissemination and usage across the modeling and simulation life-cycle. While biomedical science and clinical care domains have somewhat different requirements and expectations for credible practice, our study converged on rules that would be useful across a broad swath of model types. In brief, the rules are: (1) Define context clearly. (2) Use contextually appropriate data. (3) Evaluate within context. (4) List limitations explicitly. (5) Use version control. (6) Document appropriately. (7) Disseminate broadly. (8) Get independent reviews. (9) Test competing implementations. (10) Conform to standards. Although some of these are common sense guidelines, we have found that many are often missed or misconstrued, even by seasoned practitioners. Computational models are already widely used in basic science to generate new biomedical knowledge. As they penetrate clinical care and healthcare policy, contributing to personalized and precision medicine, clinical safety will require established guidelines for the credible practice of modeling and simulation in healthcare.

A Novel Mouse Model of Acute-on-Chronic Cholestatic Alcoholic Liver Disease: A Systems Biology Comparison With Human Alcoholic Hepatitis.

BACKGROUND: Alcohol-related liver disease is the main cause of liver-related mortality worldwide. The development of novel targeted therapies for patients with advanced forms (i.e., alcoholic hepatitis, AH) is hampered by the lack of suitable animal models. Here, we developed a novel mouse model of acute-on-chronic alcohol liver injury with cholestasis and fibrosis and performed an extensive molecular comparative analysis with human AH. METHODS: For the mouse model of acute-on-chronic liver injury, we used 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC, 0.05% w/w) diet for 8 weeks to establish cholestatic liver fibrosis. After 1-week washout period, male mice were fed intragastrically for 4 weeks with up to 24 g/kg of ethyl alcohol in a high-fat diet. This animal model was phenotyped using histopathology, clinical chemistry, microbiome, and gene expression approaches. Data were compared to the phenotypes of human alcohol-related liver disease, including AH. RESULTS: Mice with cholestatic liver fibrosis and subsequent alcohol exposure (DDC + EtOH) exhibited exacerbated liver fibrosis with a pericellular pattern, increased neutrophil infiltration, and ductular proliferation, all characteristics of human AH. DDC administration had no effect on urine alcohol concentration or liver steatosis. Importantly, DDC- and alcohol-treated mice showed a transcriptomic signature that resembled that of patients with AH. Finally, we show that mice in the DDC + EtOH group had an increased gut barrier dysfunction, mimicking an important pathophysiological mechanism of human AH. CONCLUSIONS: We developed a novel mouse model of acute-on-chronic cholestatic alcoholic liver injury that has considerable translational potential and can be used to test novel therapeutic modalities for AH.

Inflammation-associated suppression of metabolic gene networks in acute and chronic liver disease.

Inflammation has been recognized as essential for restorative regeneration. Here, we analyzed the sequential processes during onset of liver injury and subsequent regeneration based on time-resolved transcriptional regulatory networks (TRNs) to understand the relationship between inflammation, mature organ function, and regeneration. Genome-wide expression and TRN analysis were performed time dependently in mouse liver after acute injury by CCl4 (2 h, 8 h, 1, 2, 4, 6, 8, 16 days), as well as lipopolysaccharide (LPS, 24 h) and compared to publicly available data after tunicamycin exposure (mouse, 6 h), hepatocellular carcinoma (HCC, mouse), and human chronic liver disease (non-alcoholic fatty liver, HBV infection and HCC). Spatiotemporal investigation differentiated lobular zones for signaling and transcription factor expression. Acute CCl4 intoxication induced expression of gene clusters enriched for inflammation and stress signaling that peaked between 2 and 24 h, accompanied by a decrease of mature liver functions, particularly metabolic genes. Metabolism decreased not only in pericentral hepatocytes that underwent CCl4-induced necrosis, but extended to the surviving periportal hepatocytes. Proliferation and tissue restorative TRNs occurred only later reaching a maximum at 48 h. The same upstream regulators (e.g. inhibited RXR function) were implicated in increased inflammation and suppressed metabolism. The concomitant inflammation/metabolism TRN occurred similarly after acute LPS and tunicamycin challenges, in chronic mouse models and also in human liver diseases. Downregulation of metabolic genes occurs concomitantly to induce inflammation-associated genes as an early response and appears to be initiated by similar upstream regulators in acute and chronic liver diseases in humans and mice. In the acute setting, proliferation and restorative regeneration associated TRNs peak only later when metabolism is already suppressed.

A data-driven modeling approach to identify disease-specific multi-organ networks driving physiological dysregulation.

Multiple physiological systems interact throughout the development of a complex disease. Knowledge of the dynamics and connectivity of interactions across physiological systems could facilitate the prevention or mitigation of organ damage underlying complex diseases, many of which are currently refractory to available therapeutics (e.g., hypertension). We studied the regulatory interactions operating within and across organs throughout disease development by integrating in vivo analysis of gene expression dynamics with a reverse engineering approach to infer data-driven dynamic network models of multi-organ gene regulatory influences. We obtained experimental data on the expression of 22 genes across five organs, over a time span that encompassed the development of autonomic nervous system dysfunction and hypertension. We pursued a unique approach for identification of continuous-time models that jointly described the dynamics and structure of multi-organ networks by estimating a sparse subset of ∼12,000 possible gene regulatory interactions. Our analyses revealed that an autonomic dysfunction-specific multi-organ sequence of gene expression activation patterns was associated with a distinct gene regulatory network. We analyzed the model structures for adaptation motifs, and identified disease-specific network motifs involving genes that exhibited aberrant temporal dynamics. Bioinformatic analyses identified disease-specific single nucleotide variants within or near transcription factor binding sites upstream of key genes implicated in maintaining physiological homeostasis. Our approach illustrates a novel framework for investigating the pathogenesis through model-based analysis of multi-organ system dynamics and network properties. Our results yielded novel candidate molecular targets driving the development of cardiovascular disease, metabolic syndrome, and immune dysfunction.

Pattern analysis uncovers a chronic ethanol-induced disruption of the switch-like dynamics of C/EBP-ß and C/EBP-α genome-wide binding during liver regeneration.

Chronic ethanol intake impairs liver regeneration through a system-wide alteration in the regulatory networks driving the response to injury. Our study focused on the initial phase of response to 2/3rd partial hepatectomy (PHx) to investigate how adaptation to chronic ethanol intake affects the genome-wide binding profiles of the transcription factors C/EBP-ß and C/EBP-α. These factors participate in complementary and often opposing functions for maintaining cellular differentiation, regulating metabolism, and governing cell growth during liver regeneration. We analyzed ChIP-seq data with a comparative pattern count (COMPACT) analysis, which exhaustively enumerates temporal patterns of discretized binding profiles to identify dominant as well as subtle patterns that may not be apparent from conventional clustering analyses. We found that adaptation to chronic ethanol intake significantly alters the genome-wide binding profile of C/EBP-ß and C/EBP-α before and following PHx. A subset of these ethanol-induced changes include C/EBP-ß binding to promoters of genes involved in the profibrogenic transforming growth factor-ß pathway, and both C/EBP-ß and C/EBP-α binding to promoters of genes involved in the cell cycle, apoptosis, homeostasis, and metabolic processes. The shift in C/EBP binding loci, coupled with an ethanol-induced increase in C/EBP-ß binding at 6 h post-resection, indicates that ethanol adaptation may change both the amount and nature of C/EBP binding postresection. Taken together, our results suggest that chronic ethanol consumption leads to a spatially and temporally reorganized activity at many genomic loci, resulting in a shift in the dynamic balance and coordination of cellular processes underlying regenerative response.

Inputs drive cell phenotype variability.

What is the significance of the extensive variability observed in individual members of a single-cell phenotype? This question is particularly relevant to the highly differentiated organization of the brain. In this study, for the first time, we analyze the in vivo variability within a neuronal phenotype in terms of input type. We developed a large-scale gene-expression data set from several hundred single brainstem neurons selected on the basis of their specific synaptic input types. The results show a surprising organizational structure in which neuronal variability aligned with input type along a continuum of sub-phenotypes and corresponding gene regulatory modules. Correlations between these regulatory modules and specific cellular states were stratified by synaptic input type. Moreover, we found that the phenotype gradient and correlated regulatory modules were maintained across subjects. As these specific cellular states are a function of the inputs received, the stability of these states represents "attractor"-like states along a dynamic landscape that is influenced and shaped by inputs, enabling distinct state-dependent functional responses. We interpret the phenotype gradient as arising from analog tuning of underlying regulatory networks driven by distinct inputs to individual cells. Our results change the way we understand how a phenotypic population supports robust biological function by integrating the environmental experience of individual cells. Our results provide an explanation of the functional significance of the pervasive variability observed within a cell type and are broadly applicable to understanding the relationship between cellular input history and cell phenotype within all tissues.

Systemic leukotriene B4 receptor antagonism lowers arterial blood pressure and improves autonomic function in the spontaneously hypertensive rat.

KEY POINTS: Evidence indicates an association between hypertension and chronic systemic inflammation in both human hypertension and experimental animal models. Previous studies in the spontaneously hypertensive rat (SHR) support a role for leukotriene B4 (LTB4 ), a potent chemoattractant involved in the inflammatory response, but its mode of action is poorly understood. In the SHR, we observed an increase in T cells and macrophages in the brainstem; in addition, gene expression profiling data showed that LTB4 production, degradation and downstream signalling in the brainstem of the SHR are dynamically regulated during hypertension. When LTB4 receptor 1 (BLT1) receptors were blocked with CP-105,696, arterial pressure was reduced in the SHR compared to the normotensive control and this reduction was associated with a significant decrease in systolic blood pressure (BP) indicators. These data provide new evidence for the role of LTB4 as an important neuro-immune pathway in the development of hypertension and therefore may serve as a novel therapeutic target for the treatment of neurogenic hypertension. ABSTRACT: Accumulating evidence indicates an association between hypertension and chronic systemic inflammation in both human hypertension and experimental animal models. Previous studies in the spontaneously hypertensive rat (SHR) support a role for leukotriene B4 (LTB4 ), a potent chemoattractant involved in the inflammatory response. However, the mechanism for LTB4 -mediated inflammation in hypertension is poorly understood. Here we report in the SHR, increased brainstem infiltration of T cells and macrophages plus gene expression profiling data showing that LTB4 production, degradation and downstream signalling in the brainstem of the SHR are dynamically regulated during hypertension. Chronic blockade of the LTB4 receptor 1 (BLT1) receptor with CP-105,696, reduced arterial pressure in the SHR compared to the normotensive control and this reduction was associated with a significant decrease in low and high frequency spectra of systolic blood pressure, and an increase in spontaneous baroreceptor reflex gain (sBRG). These data provide new evidence for the role of LTB4 as an important neuro-immune pathway in the development of hypertension and therefore may serve as a novel therapeutic target for the treatment of neurogenic hypertension.

A novel comparative pattern analysis approach identifies chronic alcohol mediated dysregulation of transcriptomic dynamics during liver regeneration.

BACKGROUND: Liver regeneration is inhibited by chronic ethanol consumption and this impaired repair response may contribute to the risk for alcoholic liver disease. We developed and applied a novel data analysis approach to assess the effect of chronic ethanol intake in the mechanisms responsible for liver regeneration. We performed a time series transcriptomic profiling study of the regeneration response after 2/3rd partial hepatectomy (PHx) in ethanol-fed and isocaloric control rats. RESULTS: We developed a novel data analysis approach focusing on comparative pattern counts (COMPACT) to exhaustively identify the dominant and subtle differential expression patterns. Approximately 6500 genes were differentially regulated in Ethanol or Control groups within 24 h after PHx. Adaptation to chronic ethanol intake significantly altered the immediate early gene expression patterns and nearly completely abrogated the cell cycle induction in hepatocytes post PHx. The patterns highlighted by COMPACT analysis contained several non-parenchymal cell specific markers indicating their aberrant transcriptional response as a novel mechanism through which chronic ethanol intake deregulates the integrated liver tissue response. CONCLUSIONS: Our novel comparative pattern analysis revealed new insights into ethanol-mediated molecular changes in non-parenchymal liver cells as a possible contribution to the defective liver regeneration phenotype. The results revealed for the first time an ethanol-induced shift of hepatic stellate cells from a pro-regenerative phenotype to that of an anti-regenerative state after PHx. Our results can form the basis for novel interventions targeting the non-parenchymal cells in normalizing the dysfunctional repair response process in alcoholic liver disease. Our approach is illustrated online at http://compact.jefferson.edu .

Inhibition of miR-21 rescues liver regeneration after partial hepatectomy in ethanol-fed rats.

Liver regeneration is a clinically significant tissue repair process that is suppressed by chronic alcohol intake through poorly understood mechanisms. Recently, microRNA-21 (miR-21) has been suggested to serve as a crucial microRNA (miRNA) regulator driving hepatocyte proliferation after partial hepatectomy (PHx) in mice. However, we reported recently that miR-21 is significantly upregulated in ethanol-fed rats 24 h after PHx, despite inhibition of cell proliferation, suggesting a more complex role for this miRNA. Here, we investigate how inhibition of miR-21 in vivo affects the early phase of liver regeneration in ethanol-fed rats. Chronically ethanol-fed rats and pair-fed control animals were treated with AM21, a mixed locked nucleic acid-DNA analog antisense to miR-21 that inhibited miR-21 in vivo to undetectable levels. Liver regeneration after PHx was followed by cell proliferation marker and gene expression analysis, miRNA profiling, and cell signaling pathway analysis. Although liver regeneration was not significantly impaired by AM21 in chow-fed rats, AM21 treatment in ethanol-fed animals completely restored regeneration and enhanced PHx-induced hepatocyte proliferation to levels comparable to those of untreated or chow-fed animals. In addition, a marked deposition of α-smooth muscle actin, a marker of stellate cell activation, which was evident in ethanol-treated animals after PHx, was effectively suppressed by AM21 treatment. Gene expression analysis further indicated that suppression of stellate cell-specific profibrogenic profiles and the Notch signaling contributed to AM21-mediated rescue from deficient hepatocyte proliferation in ethanol-fed animals. Our results indicate that the impact of miR-21 balances proproliferative effects with antiproliferative profibrogenic actions in regulating distinctive regenerative responses in normal vs. disease conditions.

Molecular variability elicits a tunable switch with discrete neuromodulatory response phenotypes.

Recent single cell studies show extensive molecular variability underlying cellular responses. We evaluated the impact of molecular variability in the expression of cell signaling components and ion channels on electrophysiological excitability and neuromodulation. We employed a computational approach that integrated neuropeptide receptor-mediated signaling with electrophysiology. We simulated a population of neurons in which expression levels of a neuropeptide receptor and multiple ion channels were simultaneously varied within a physiological range. We analyzed the effects of variation on the electrophysiological response to a neuropeptide stimulus. Our results revealed distinct response patterns associated with low versus high receptor levels. Neurons with low receptor levels showed increased excitability and neurons with high receptor levels showed reduced excitability. These response patterns were separated by a narrow receptor level range forming a separatrix. The position of this separatrix was dependent on the expression levels of multiple ion channels. To assess the relative contributions of receptor and ion channel levels to the response profiles, we categorized the responses into six phenotypes based on response kinetics and magnitude. We applied several multivariate statistical approaches and found that receptor and channel expression levels influence the neuromodulation response phenotype through a complex though systematic mapping. Our analyses extended our understanding of how cellular responses to neuromodulation vary as a function of molecular expression. Our study showed that receptor expression and biophysical state interact with distinct relative contributions to neuronal excitability.

Intracellular Information Processing through Encoding and Decoding of Dynamic Signaling Features.

Cell signaling dynamics and transcriptional regulatory activities are variable within specific cell types responding to an identical stimulus. In addition to studying the network interactions, there is much interest in utilizing single cell scale data to elucidate the non-random aspects of the variability involved in cellular decision making. Previous studies have considered the information transfer between the signaling and transcriptional domains based on an instantaneous relationship between the molecular activities. These studies predict a limited binary on/off encoding mechanism which underestimates the complexity of biological information processing, and hence the utility of single cell resolution data. Here we pursue a novel strategy that reformulates the information transfer problem as involving dynamic features of signaling rather than molecular abundances. We pursue a computational approach to test if and how the transcriptional regulatory activity patterns can be informative of the temporal history of signaling. Our analysis reveals (1) the dynamic features of signaling that significantly alter transcriptional regulatory patterns (encoding), and (2) the temporal history of signaling that can be inferred from single cell scale snapshots of transcriptional activity (decoding). Immediate early gene expression patterns were informative of signaling peak retention kinetics, whereas transcription factor activity patterns were informative of activation and deactivation kinetics of signaling. Moreover, the information processing aspects varied across the network, with each component encoding a selective subset of the dynamic signaling features. We developed novel sensitivity and information transfer maps to unravel the dynamic multiplexing of signaling features at each of these network components. Unsupervised clustering of the maps revealed two groups that aligned with network motifs distinguished by transcriptional feedforward vs feedback interactions. Our new computational methodology impacts the single cell scale experiments by identifying downstream snapshot measures required for inferring specific dynamical features of upstream signals involved in the regulation of cellular responses.

Modeling cytokine regulatory network dynamics driving neuroinflammation in central nervous system disorders.

A central goal of pharmacological efforts to treat central nervous system (CNS) diseases is to develop systemic therapeutics that can restore CNS homeostasis. Achieving this goal requires a fundamental understanding of CNS function within the organismal context so as to leverage the mechanistic insights on the molecular basis of cellular and tissue functions towards novel drug target identification. The immune system constitutes a key link between the periphery and CNS, and many neurological disorders and neurodegenerative diseases are characterized by immune dysfunction. We review the salient opportunities for applying computational models to CNS disease research, and summarize relevant approaches from studies of immune function and neuroinflammation. While the accurate prediction of disease-related phenomena is often considered the central goal of modeling studies, we highlight the utility of computational modeling applications beyond making predictions, particularly for drawing counterintuitive insights from model-based analysis of multi-parametric and time series data sets.

Multiscale model of dynamic neuromodulation integrating neuropeptide-induced signaling pathway activity with membrane electrophysiology.

We developed a multiscale model to bridge neuropeptide receptor-activated signaling pathway activity with membrane electrophysiology. Typically, the neuromodulation of biochemical signaling and biophysics have been investigated separately in modeling studies. We studied the effects of Angiotensin II (AngII) on neuronal excitability changes mediated by signaling dynamics and downstream phosphorylation of ion channels. Experiments have shown that AngII binding to the AngII receptor type-1 elicits baseline-dependent regulation of cytosolic Ca(2+) signaling. Our model simulations revealed a baseline Ca(2+)-dependent response to AngII receptor type-1 activation by AngII. Consistent with experimental observations, AngII evoked a rise in Ca(2+) when starting at a low baseline Ca(2+) level, and a decrease in Ca(2+) when starting at a higher baseline. Our analysis predicted that the kinetics of Ca(2+) transport into the endoplasmic reticulum play a critical role in shaping the Ca(2+) response. The Ca(2+) baseline also influenced the AngII-induced excitability changes such that lower Ca(2+) levels were associated with a larger firing rate increase. We examined the relative contributions of signaling kinases protein kinase C and Ca(2+)/Calmodulin-dependent protein kinase II to AngII-mediated excitability changes by simulating activity blockade individually and in combination. We found that protein kinase C selectively controlled firing rate adaptation whereas Ca(2+)/Calmodulin-dependent protein kinase II induced a delayed effect on the firing rate increase. We tested whether signaling kinetics were necessary for the dynamic effects of AngII on excitability by simulating three scenarios of AngII-mediated KDR channel phosphorylation: (1), an increased steady state; (2), a step-change increase; and (3), dynamic modulation. Our results revealed that the kinetics emerging from neuromodulatory activation of the signaling network were required to account for the dynamical changes in excitability. In summary, our integrated multiscale model provides, to our knowledge, a new approach for quantitative investigation of neuromodulatory effects on signaling and electrophysiology.

MicroRNA network changes in the brain stem underlie the development of hypertension.

Hypertension is a major chronic disease whose molecular mechanisms remain poorly understood. We compared neuroanatomical patterns of microRNAs in the brain stem of the spontaneous hypertensive rat (SHR) to the Wistar Kyoto rat (WKY, control). We quantified 419 well-annotated microRNAs in the nucleus of the solitary tract (NTS) and rostral ventrolateral medulla (RVLM), from SHR and WKY rats, during three main stages of hypertension development. Changes in microRNA expression were stage- and region-dependent, with a majority of SHR vs. WKY differential expression occurring at the hypertension onset stage in NTS versus at the prehypertension stage in RVLM. Our analysis identified 24 microRNAs showing time-dependent differential expression in SHR compared with WKY in at least one brain region. We predicted potential gene regulatory targets corresponding to catecholaminergic processes, neuroinflammation, and neuromodulation using the miRWALK and RNA22 databases, and we tested those bioinformatics predictions using high-throughput quantitative PCR to evaluate correlations of differential expression between the microRNAs and their predicted gene targets. We found a novel regulatory network motif consisting of microRNAs likely downregulating a negative regulator of prohypertensive processes such as angiotensin II signaling and leukotriene-based inflammation. Our results provide new evidence on the dynamics of microRNA expression in the development of hypertension and predictions of microRNA-mediated regulatory networks playing a region-dependent role in potentially altering brain-stem cardiovascular control circuit function leading to the development of hypertension.