GSEAplot: A Package for Customizing Gene Set Enrichment Analysis in R.

Gene Set Enrichment Analysis (GSEA) is used to identify differentially expressed gene sets that are enriched for annotated biological functions. The existing GSEA R code is not in the form of a flexible package with analysis and plotting customization options, and the results produced are not generated in the form of R objects. In this study, we introduce the GSEAplot R package with novel functionality for saving relevant information from the analysis to the current R workspace, and we introduce the ability to customize plots and databases. The GSEAplot package provides a novel utility that facilitates the implementation of GSEA R-based in genomics analysis pipelines.

Applying the CiPA approach to evaluate cardiac proarrhythmia risk of some antimalarials used off-label in the first wave of COVID-19.

We applied a set of in silico and in vitro assays, compliant with the Comprehensive In Vitro Proarrhythmia Assay (CiPA) paradigm, to assess the risk of chloroquine (CLQ) or hydroxychloroquine (OH-CLQ)-mediated QT prolongation and Torsades de Pointes (TdP), alone and combined with erythromycin (ERT) and azithromycin (AZI), drugs repurposed during the first wave of coronavirus disease 2019 (COVID-19). Each drug or drug combination was tested in patch clamp assays on seven cardiac ion channels, in in silico models of human ventricular electrophysiology (Virtual Assay) using control (healthy) or high-risk cell populations, and in human-induced pluripotent stem cell (hiPSC)-derived cardiomyocytes. In each assay, concentration-response curves encompassing and exceeding therapeutic free plasma levels were generated. Both CLQ and OH-CLQ showed blocking activity against some potassium, sodium, and calcium currents. CLQ and OH-CLQ inhibited IKr (half-maximal inhibitory concentration [IC50 ]: 1 µM and 3-7 µM, respectively) and IK1 currents (IC50 : 5 and 44 µM, respectively). When combining OH-CLQ with AZI, no synergistic effects were observed. The two macrolides had no or very weak effects on the ion currents (IC50  > 300-1000 µM). Using Virtual Assay, both antimalarials affected several TdP indicators, CLQ being more potent than OH-CLQ. Effects were more pronounced in the high-risk cell population. In hiPSC-derived cardiomyocytes, all drugs showed early after-depolarizations, except AZI. Combining CLQ or OH-CLQ with a macrolide did not aggravate their effects. In conclusion, our integrated nonclinical CiPA dataset confirmed that, at therapeutic plasma concentrations relevant for malaria or off-label use in COVID-19, CLQ and OH-CLQ use is associated with a proarrhythmia risk, which is higher in populations carrying predisposing factors but not worsened with macrolide combination.

Sex differences in human adipose tissue gene expression and genetic regulation involve adipogenesis.

Sex differences in adipose tissue distribution and function are associated with sex differences in cardiometabolic disease. While many studies have revealed sex differences in adipocyte cell signaling and physiology, there is a relative dearth of information regarding sex differences in transcript abundance and regulation. We investigated sex differences in subcutaneous adipose tissue transcriptional regulation using omic-scale data from ∼3000 geographically and ethnically diverse human samples. We identified 162 genes with robust sex differences in expression. Differentially expressed genes were implicated in oxidative phosphorylation and adipogenesis. We further determined that sex differences in gene expression levels could be related to sex differences in the genetics of gene expression regulation. Our analyses revealed sex-specific genetic associations, and this finding was replicated in a study of 98 inbred mouse strains. The genes under genetic regulation in human and mouse were enriched for oxidative phosphorylation and adipogenesis. Enrichment analysis showed that the associated genetic loci resided within binding motifs for adipogenic transcription factors (e.g., PPARG and EGR1). We demonstrated that sex differences in gene expression could be influenced by sex differences in genetic regulation for six genes (e.g., FADS1 and MAP1B). These genes exhibited dynamic expression patterns during adipogenesis and robust expression in mature human adipocytes. Our results support a role for adipogenesis-related genes in subcutaneous adipose tissue sex differences in the genetic and environmental regulation of gene expression.

Defining data-driven primary transcript annotations with primaryTranscriptAnnotation in R.

SUMMARY: Nascent transcript measurements derived from run-on sequencing experiments are critical for the investigation of transcriptional mechanisms and regulatory networks. However, conventional mRNA gene annotations significantly differ from the boundaries of primary transcripts. New primary transcript annotations are needed to accurately interpret run-on data. We developed the primaryTranscriptAnnotation R package to infer the transcriptional start and termination sites of primary transcripts from genomic run-on data. We then used these inferred coordinates to annotate transcriptional units identified de novo. This package provides the novel utility to integrate data-driven primary transcript annotations with transcriptional unit coordinates identified in an unbiased manner. Highlighting the importance of using accurate primary transcript coordinates, we demonstrate that this new methodology increases the detection of differentially expressed transcripts and provides more accurate quantification of RNA polymerase pause indices. AVAILABILITY AND IMPLEMENTATION: https://github.com/WarrenDavidAnderson/genomicsRpackage/tree/master/primaryTranscriptAnnotation. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

An improved auxin-inducible degron system preserves native protein levels and enables rapid and specific protein depletion.

Rapid perturbation of protein function permits the ability to define primary molecular responses while avoiding downstream cumulative effects of protein dysregulation. The auxin-inducible degron (AID) system was developed as a tool to achieve rapid and inducible protein degradation in nonplant systems. However, tagging proteins at their endogenous loci results in chronic auxin-independent degradation by the proteasome. To correct this deficiency, we expressed the auxin response transcription factor (ARF) in an improved inducible degron system. ARF is absent from previously engineered AID systems but is a critical component of native auxin signaling. In plants, ARF directly interacts with AID in the absence of auxin, and we found that expression of the ARF PB1 (Phox and Bem1) domain suppresses constitutive degradation of AID-tagged proteins. Moreover, the rate of auxin-induced AID degradation is substantially faster in the ARF-AID system. To test the ARF-AID system in a quantitative and sensitive manner, we measured genome-wide changes in nascent transcription after rapidly depleting the ZNF143 transcription factor. Transcriptional profiling indicates that ZNF143 activates transcription in cis and regulates promoter-proximal paused RNA polymerase density. Rapidly inducible degradation systems that preserve the target protein's native expression levels and patterns will revolutionize the study of biological systems by enabling specific and temporally defined protein dysregulation.

Universal correction of enzymatic sequence bias reveals molecular signatures of protein/DNA interactions.

Coupling molecular biology to high-throughput sequencing has revolutionized the study of biology. Molecular genomics techniques are continually refined to provide higher resolution mapping of nucleic acid interactions and structure. Sequence preferences of enzymes can interfere with the accurate interpretation of these data. We developed seqOutBias to characterize enzymatic sequence bias from experimental data and scale individual sequence reads to correct intrinsic enzymatic sequence biases. SeqOutBias efficiently corrects DNase-seq, TACh-seq, ATAC-seq, MNase-seq and PRO-seq data. We show that seqOutBias correction facilitates identification of true molecular signatures resulting from transcription factors and RNA polymerase interacting with DNA.

Novel Influences of IL-10 on CNS Inflammation Revealed by Integrated Analyses of Cytokine Networks and Microglial Morphology.

Coordinated interactions between cytokine signaling and morphological dynamics of microglial cells regulate neuroinflammation in CNS injury and disease. We found that pro-inflammatory cytokine gene expression in vivo showed a pronounced recovery following systemic LPS. We performed a novel multivariate analysis of microglial morphology and identified changes in specific morphological properties of microglia that matched the expression dynamics of pro-inflammatory cytokine TNFα. The adaptive recovery kinetics of TNFα expression and microglial soma size showed comparable profiles and dependence on anti-inflammatory cytokine IL-10 expression. The recovery of cytokine variations and microglial morphology responses to inflammation were negatively regulated by IL-10. Our novel morphological analysis of microglia is able to detect subtle changes and can be used widely. We implemented in silico simulations of cytokine network dynamics which showed-counter-intuitively, but in line with our experimental observations-that negative feedback from IL-10 was sufficient to impede the adaptive recovery of TNFα-mediated inflammation. Our integrative approach is a powerful tool to study changes in specific components of microglial morphology for insights into their functional states, in relation to cytokine network dynamics, during CNS injury and disease.

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.

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.

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.

Positive Allosteric Modulation of Kv Channels by Sevoflurane: Insights into the Structural Basis of Inhaled Anesthetic Action.

Inhalational general anesthesia results from the poorly understood interactions of haloethers with multiple protein targets, which prominently includes ion channels in the nervous system. Previously, we reported that the commonly used inhaled anesthetic sevoflurane potentiates the activity of voltage-gated K+ (Kv) channels, specifically, several mammalian Kv1 channels and the Drosophila K-Shaw2 channel. Also, previous work suggested that the S4-S5 linker of K-Shaw2 plays a role in the inhibition of this Kv channel by n-alcohols and inhaled anesthetics. Here, we hypothesized that the S4-S5 linker is also a determinant of the potentiation of Kv1.2 and K-Shaw2 by sevoflurane. Following functional expression of these Kv channels in Xenopus oocytes, we found that converse mutations in Kv1.2 (G329T) and K-Shaw2 (T330G) dramatically enhance and inhibit the potentiation of the corresponding conductances by sevoflurane, respectively. Additionally, Kv1.2-G329T impairs voltage-dependent gating, which suggests that Kv1.2 modulation by sevoflurane is tied to gating in a state-dependent manner. Toward creating a minimal Kv1.2 structural model displaying the putative sevoflurane binding sites, we also found that the positive modulations of Kv1.2 and Kv1.2-G329T by sevoflurane and other general anesthetics are T1-independent. In contrast, the positive sevoflurane modulation of K-Shaw2 is T1-dependent. In silico docking and molecular dynamics-based free-energy calculations suggest that sevoflurane occupies distinct sites near the S4-S5 linker, the pore domain and around the external selectivity filter. We conclude that the positive allosteric modulation of the Kv channels by sevoflurane involves separable processes and multiple sites within regions intimately involved in channel gating.

Computational modeling of cytokine signaling in microglia.

Neuroinflammation due to glial activation has been linked to many CNS diseases. We developed a computational model of a microglial cytokine interaction network to study the regulatory mechanisms of microglia-mediated neuroinflammation. We established a literature-based cytokine network, including TNFα, TGFß, and IL-10, and fitted a mathematical model to published data from LPS-treated microglia. The addition of a previously unreported TGFß autoregulation loop to our model was required to account for experimental data. Global sensitivity analysis revealed that TGFß- and IL-10-mediated inhibition of TNFα was critical for regulating network behavior. We assessed the sensitivity of the LPS-induced TNFα response profile to the initial TGFß and IL-10 levels. The analysis showed two relatively shifted TNFα response profiles within separate domains of initial condition space. Further analysis revealed that TNFα exhibited adaptation to sustained LPS stimulation. We simulated the effects of functionally inhibiting TGFß and IL-10 on TNFα adaptation. Our analysis showed that TGFß and IL-10 knockouts (TGFß KO and IL-10 KO) exert divergent effects on adaptation. TFGß KO attenuated TNFα adaptation whereas IL-10 KO enhanced TNFα adaptation. We experimentally tested the hypothesis that IL-10 KO enhances TNFα adaptation in murine macrophages and found supporting evidence. These opposing effects could be explained by differential kinetics of negative feedback. Inhibition of IL-10 reduced early negative feedback that results in enhanced TNFα-mediated TGFß expression. We propose that differential kinetics in parallel negative feedback loops constitute a novel mechanism underlying the complex and non-intuitive pro- versus anti-inflammatory effects of individual cytokine perturbations.

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.

Properties and functional implications of I (h) in hippocampal area CA3 interneurons.

The present study examines the biophysical properties and functional implications of I (h) in hippocampal area CA3 interneurons with somata in strata radiatum and lacunosum-moleculare. Characterization studies showed a small maximum h-conductance (2.6 ± 0.3 nS, n = 11), shallow voltage dependence with a hyperpolarized half-maximal activation (V (1/2) = -91 mV), and kinetics characterized by double-exponential functions. The functional consequences of I (h) were examined with regard to temporal summation and impedance measurements. For temporal summation experiments, 5-pulse mossy fiber input trains were activated. Blocking I (h) with 50 µM ZD7288 resulted in an increase in temporal summation, suggesting that I (h) supports sensitivity of response amplitude to relative input timing. Impedance was assessed by applying sinusoidal current commands. From impedance measurements, we found that I (h) did not confer theta-band resonance, but flattened the impedance-frequency relations instead. Double immunolabeling for hyperpolarization-activated cyclic nucleotide-gated proteins and glutamate decarboxylase 67 suggests that all four subunits are present in GABAergic interneurons from the strata considered for electrophysiological studies. Finally, a model of I (h) was employed in computational analyses to confirm and elaborate upon the contributions of I (h) to impedance and temporal summation.

Outside looking in: Observations on medical education since the Flexner Report.

CONTEXT: This article focuses on the current state of medical education as it relates to the reforms introduced in the wake of the Flexner Report of 1910. The usefulness of outsiders in both understanding and analysing any specialised endeavour, and, specifically, medical education, is carefully considered. No voices call more loudly for change in medical education today than those emanating from within the arena itself. Interestingly, however, the monumental reforms of the Flexner Report were impelled largely from outside the specific discipline of medical education. OBSERVATIONS: Internal tensions exist between the natural and social sciences. These tensions present formidable obstacles to the balance between advances in biomedical knowledge and the humane and socially acceptable application of that knowledge. Medical education's responses to society's pressures for accessibility and humaneness occupy the next discussion point, named here as 're-democratisation' and 're-humanisation'. A final observation questions whether the current proliferation of literature about reforms in medical education can lead to real change, or whether it constitutes a self-referential agitation that, in the aggregate, holds little promise. CONCLUSIONS: It is suggested that not only are outsiders useful, but they may perhaps represent the only channel through which medical education can align its current practice with both its internal ideals and the demands of the public, members of which live and die by its efforts.