Exploring a targeted approach for public health capacity restrictions during COVID-19 using a new computational model.

This work introduces the Queen's University Agent-Based Outbreak Outcome Model (QUABOOM). This tool is an agent-based Monte Carlo simulation for modelling epidemics and informing public health policy. We illustrate the use of the model by examining capacity restrictions during a lockdown. We find that public health measures should focus on the few locations where many people interact, such as grocery stores, rather than the many locations where few people interact, such as small businesses. We also discuss a case where the results of the simulation can be scaled to larger population sizes, thereby improving computational efficiency.

Spt5 C-terminal repeat domain phosphorylation and length negatively regulate heterochromatin through distinct mechanisms.

Heterochromatin is a condensed chromatin structure that represses transcription of repetitive DNA elements and developmental genes, and is required for genome stability. Paradoxically, transcription of heterochromatic sequences is required for establishment of heterochromatin in diverse eukaryotic species. As such, components of the transcriptional machinery can play important roles in establishing heterochromatin. How these factors coordinate with heterochromatin proteins at nascent heterochromatic transcripts remains poorly understood. In the model eukaryote Schizosaccharomyces pombe (S. pombe), heterochromatin nucleation can be coupled to processing of nascent transcripts by the RNA interference (RNAi) pathway, or to other post-transcriptional mechanisms that are RNAi-independent. Here we show that the RNA polymerase II processivity factor Spt5 negatively regulates heterochromatin in S. pombe through its C-terminal domain (CTD). The Spt5 CTD is analogous to the CTD of the RNA polymerase II large subunit, and is comprised of multiple repeats of an amino acid motif that is phosphorylated by Cdk9. We provide evidence that genetic ablation of Spt5 CTD phosphorylation results in aberrant RNAi-dependent nucleation of heterochromatin at an ectopic location, as well as inappropriate spread of heterochromatin proximal to centromeres. In contrast, truncation of Spt5 CTD repeat number enhanced RNAi-independent heterochromatin formation and bypassed the requirement for RNAi. We relate these phenotypes to the known Spt5 CTD-binding factor Prf1/Rtf1. This separation of function argues that Spt5 CTD phosphorylation and CTD length restrict heterochromatin through unique mechanisms. More broadly, our findings argue that length and phosphorylation of the Spt5 CTD repeat array have distinct regulatory effects on transcription.

Comparing the signaling and transcriptome profiling landscapes of human iPSC-derived and primary rat neonatal cardiomyocytes.

The inaccessibility of human cardiomyocytes significantly hindered years of cardiovascular research efforts. To overcome these limitations, non-human cell sources were used as proxies to study heart function and associated diseases. Rodent models became increasingly acceptable surrogates to model the human heart either in vivo or through in vitro cultures. More recently, due to concerns regarding animal to human translation, including cross-species differences, the use of human iPSC-derived cardiomyocytes presented a renewed opportunity. Here, we conducted a comparative study, assessing cellular signaling through cardiac G protein-coupled receptors (GPCRs) in rat neonatal cardiomyocytes (RNCMs) and human induced pluripotent stem cell-derived cardiomyocytes. Genetically encoded biosensors were used to explore GPCR-mediated nuclear protein kinase A (PKA) and extracellular signal-regulated kinase 1/ 2 (ERK1/2) activities in both cardiomyocyte populations. To increase data granularity, a single-cell analytical approach was conducted. Using automated high content microscopy, our analyses of nuclear PKA and ERK1/2 signaling revealed distinct response clusters in rat and human cardiomyocytes. In line with this, bulk RNA-seq revealed key differences in the expression patterns of GPCRs, G proteins and downstream effector expression levels. Our study demonstrates that human stem cell-derived models of the cardiomyocyte offer distinct advantages for understanding cellular signaling in the heart.

Gßγ subunits colocalize with RNA polymerase II and regulate transcription in cardiac fibroblasts.

Gßγ subunits mediate many different signaling processes in various compartments of the cell, including the nucleus. To gain insight into the functions of nuclear Gßγ signaling, we investigated the functional role of Gßγ signaling in the regulation of GPCR-mediated gene expression in primary rat neonatal cardiac fibroblasts. We identified a novel, negative, regulatory role for the Gß1γ dimer in the fibrotic response. Depletion of Gß1 led to derepression of the fibrotic response at the mRNA and protein levels under basal conditions and an enhanced fibrotic response after sustained stimulation of the angiotensin II type I receptor. Our genome-wide chromatin immunoprecipitation experiments revealed that Gß1 colocalized and interacted with RNA polymerase II on fibrotic genes in an angiotensin II-dependent manner. Additionally, blocking transcription with inhibitors of Cdk9 prevented association of Gßγ with transcription complexes. Together, our findings suggest that Gß1γ is a novel transcriptional regulator of the fibrotic response that may act to restrict fibrosis to conditions of sustained fibrotic signaling. Our work expands the role for Gßγ signaling in cardiac fibrosis and may have broad implications for the role of nuclear Gßγ signaling in other cell types.

Performance of a convolutional autoencoder designed to remove electronic noise from p-type point contact germanium detector signals.

We present a convolutional autoencoder to denoise pulses from a p-type point contact high-purity germanium detector similar to those used in several rare event searches. While we focus on training procedures that rely on detailed detector physics simulations, we also present implementations requiring only noisy detector pulses to train the model. We validate our autoencoder on both simulated data and calibration data from an 241 Am source, the latter of which is used to show that the denoised pulses are statistically compatible with data pulses. We demonstrate that our denoising method is able to preserve the underlying shapes of the pulses well, offering improvement over traditional denoising methods. We also show that the shaping time used to calculate energy with a trapezoidal filter can be significantly reduced while maintaining a comparable energy resolution. Under certain circumstances, our denoising method can improve the overall energy resolution. The methods we developed to remove electronic noise are straightforward to extend to other detector technologies. Furthermore, the latent representation from the encoder is also of use in quantifying shape-based characteristics of the signals. Our work has great potential to be used in particle physics experiments and beyond.

Benchmark of Data Processing Methods and Machine Learning Models for Gut Microbiome-Based Diagnosis of Inflammatory Bowel Disease.

Patients with inflammatory bowel disease (IBD) wait months and undergo numerous invasive procedures between the initial appearance of symptoms and receiving a diagnosis. In order to reduce time until diagnosis and improve patient wellbeing, machine learning algorithms capable of diagnosing IBD from the gut microbiome's composition are currently being explored. To date, these models have had limited clinical application due to decreased performance when applied to a new cohort of patient samples. Various methods have been developed to analyze microbiome data which may improve the generalizability of machine learning IBD diagnostic tests. With an abundance of methods, there is a need to benchmark the performance and generalizability of various machine learning pipelines (from data processing to training a machine learning model) for microbiome-based IBD diagnostic tools. We collected fifteen 16S rRNA microbiome datasets (7,707 samples) from North America to benchmark combinations of gut microbiome features, data normalization and transformation methods, batch effect correction methods, and machine learning models. Pipeline generalizability to new cohorts of patients was evaluated with two binary classification metrics following leave-one-dataset-out cross (LODO) validation, where all samples from one study were left out of the training set and tested upon. We demonstrate that taxonomic features processed with a compositional transformation method and batch effect correction with the naive zero-centering method attain the best classification performance. In addition, machine learning models that identify non-linear decision boundaries between labels are more generalizable than those that are linearly constrained. Lastly, we illustrate the importance of generating a curated training dataset to ensure similar performance across patient demographics. These findings will help improve the generalizability of machine learning models as we move towards non-invasive diagnostic and disease management tools for patients with IBD.

A role for BET proteins in regulating basal, dopamine-induced and cAMP/PKA-dependent transcription in rat striatal neurons.

The activity of striatal medium-spiny projection neurons is regulated by D1 and D2 dopamine receptors. The D1 receptor (D1R) is a Gαs/olf-coupled GPCR which activates a cAMP/PKA/DARPP-32 signalling cascade that increases excitability and facilitates plasticity, partly through the regulation of transcription. Upon activation via D1R, PKA can translocate to the nucleus to regulate transcription through the phosphorylation of various targets. One candidate effector of PKA-dependent transcriptional regulation is the BET protein Brd4. It is known that when Brd4 is activated by phosphorylation, it binds more readily to acetylated histones at promoters and enhancers; moreover, in non-neuronal cells, PKA signalling has been shown to increase recruitment of Brd4 to chromatin. However, it is unknown whether BET proteins, or Brd4 specifically, are involved in transcriptional activation by cAMP/PKA in neurons. Here, we demonstrate that in adult rats, inhibition of BET proteins with the bromodomain inhibitor JQ1 suppressed the expression of ~25% of D1R-upregulated genes, while also increasing the expression of a subset of immediate-early genes. We further found that cAMP/PKA signalling promotes Brd4 recruitment to dopamine-induced genes in striatal neurons, and that knockdown of Brd4 attenuates D1R-induced gene expression. Finally, we report that JQ1 treatment downregulated expression of many GPCRs and also impaired ERK1/2 signalling in striatal neurons. Our findings identify the BET protein family, and Brd4 in particular, as novel regulators of basal and D1R-dependent transcription in rat striatal neurons, and delineate complex bi-directional effects of bromodomain inhibitors on neuronal transcription.

Measuring hypertrophy in neonatal rat primary cardiomyocytes and human iPSC-derived cardiomyocytes.

In the heart, left ventricular hypertrophy is initially an adaptive mechanism that increases wall thickness to preserve normal cardiac output and function in the face of coronary artery disease or hypertension. Cardiac hypertrophy develops in response to pressure and volume overload but can also be seen in inherited cardiomyopathies. As the wall thickens, it becomes stiffer impairing the distribution of oxygenated blood to the rest of the body. With complex cellular signalling and transcriptional networks involved in the establishment of the hypertrophic state, several model systems have been developed to better understand the molecular drivers of disease. Immortalized cardiomyocyte cell lines, primary rodent and larger animal models have all helped understand the pathological mechanisms underlying cardiac hypertrophy. Induced pluripotent stem cell-derived cardiomyocytes are also used and have the additional benefit of providing access to human samples with direct disease relevance as when generated from patients suffering from hypertrophic cardiomyopathies. Here, we briefly review in vitro and in vivo model systems that have been used to model hypertrophy and provide detailed methods to isolate primary neonatal rat cardiomyocytes as well as to generate cardiomyocytes from human iPSCs. We also describe how to model hypertrophy in a "dish" using gene expression analysis and immunofluorescence combined with automated high-content imaging.

Role of Digital Health and Artificial Intelligence in Inflammatory Bowel Disease: A Scoping Review.

Inflammatory bowel diseases (IBD), subdivided into Crohn's disease (CD) and ulcerative colitis (UC), are chronic diseases that are characterized by relapsing and remitting periods of inflammation in the gastrointestinal tract. In recent years, the amount of research surrounding digital health (DH) and artificial intelligence (AI) has increased. The purpose of this scoping review is to explore this growing field of research to summarize the role of DH and AI in the diagnosis, treatment, monitoring and prognosis of IBD. A review of 21 articles revealed the impact of both AI algorithms and DH technologies; AI algorithms can improve diagnostic accuracy, assess disease activity, and predict treatment response based on data modalities such as endoscopic imaging and genetic data. In terms of DH, patients utilizing DH platforms experienced improvements in quality of life, disease literacy, treatment adherence, and medication management. In addition, DH methods can reduce the need for in-person appointments, decreasing the use of healthcare resources without compromising the standard of care. These articles demonstrate preliminary evidence of the potential of DH and AI for improving the management of IBD. However, the majority of these studies were performed in a regulated clinical environment. Therefore, further validation of these results in a real-world environment is required to assess the efficacy of these methods in the general IBD population.

High-Content Single-Cell Förster Resonance Energy Transfer Imaging of Cultured Striatal Neurons Reveals Novel Cross-Talk in the Regulation of Nuclear Signaling by Protein Kinase A and Extracellular Signal-Regulated Kinase 1/2.

Genetically encoded biosensors can be used to track signaling events in living cells by measuring changes in fluorescence emitted by one or more fluorescent proteins. Here, we describe the use of genetically encoded biosensors based on Förster resonance energy transfer (FRET), combined with high-content microscopy, to image dynamic signaling events simultaneously in thousands of neurons in response to drug treatments. We first applied this approach to examine intercellular variation in signaling responses among cultured striatal neurons stimulated with multiple drugs. Using high-content FRET imaging and immunofluorescence, we identified neuronal subpopulations with unique responses to pharmacological manipulation and used nuclear morphology to identify medium spiny neurons within these heterogeneous striatal cultures. Focusing on protein kinase A (PKA) and extracellular signal-regulated kinase 1/2 (ERK1/2) signaling in the cytoplasm and nucleus, we noted pronounced intercellular differences among putative medium spiny neurons, in both the magnitude and kinetics of signaling responses to drug application. Importantly, a conventional "bulk" analysis that pooled all cells in culture yielded a different rank order of drug potency than that revealed by single-cell analysis. Using a single-cell analytical approach, we dissected the relative contributions of PKA and ERK1/2 signaling in striatal neurons and unexpectedly identified a novel role for ERK1/2 in promoting nuclear activation of PKA in striatal neurons. This finding adds a new dimension of signaling crosstalk between PKA and ERK1/2 with relevance to dopamine D1 receptor signaling in striatal neurons. In conclusion, high-content single-cell imaging can complement and extend traditional population-level analyses and provides a novel vantage point from which to study cellular signaling. SIGNIFICANCE STATEMENT: High-content imaging revealed substantial intercellular variation in the magnitude and pattern of intracellular signaling events driven by receptor stimulation. Since individual neurons within the same population can respond differently to a given agonist, interpreting measures of intracellular signaling derived from the averaged response of entire neuronal populations may not always reflect what happened at the single-cell level. This study uses this approach to identify a new form of cross-talk between PKA and ERK1/2 signaling in the nucleus of striatal neurons.

Lipidated peptides derived from intracellular loops 2 and 3 of the urotensin II receptor act as biased allosteric ligands.

Over the last decade, the urotensinergic system, composed of one G protein-coupled receptor and two endogenous ligands, has garnered significant attention as a promising new target for the treatment of various cardiovascular diseases. Indeed, this system is associated with various biomarkers of cardiovascular dysfunctions and is involved in changes in cardiac contractility, fibrosis, and hypertrophy contributing, like the angiotensinergic system, to the pathogenesis and progression of heart failure. Significant investment has been made toward the development of clinically relevant UT ligands for therapeutic intervention, but with little or no success to date. This system therefore remains to be therapeutically exploited. Pepducins and other lipidated peptides have been used as both mechanistic probes and potential therapeutics; therefore, pepducins derived from the human urotensin II receptor might represent unique tools to generate signaling bias and study hUT signaling networks. Two hUT-derived pepducins, derived from the second and the third intracellular loop of the receptor (hUT-Pep2 and [Trp1, Leu2]hUT-Pep3, respectively), were synthesized and pharmacologically characterized. Our results demonstrated that hUT-Pep2 and [Trp1, Leu2]hUT-Pep3 acted as biased ago-allosteric modulators, triggered ERK1/2 phosphorylation and, to a lesser extent, IP1 production, and stimulated cell proliferation yet were devoid of contractile activity. Interestingly, both hUT-derived pepducins were able to modulate human urotensin II (hUII)- and urotensin II-related peptide (URP)-mediated contraction albeit to different extents. These new derivatives represent unique tools to reveal the intricacies of hUT signaling and also a novel avenue for the design of allosteric ligands selectively targeting hUT signaling potentially.

Dopamine D1 receptor signalling in dyskinetic Parkinsonian rats revealed by fiber photometry using FRET-based biosensors.

As with many G protein-coupled receptors (GPCRs), the signalling pathways regulated by the dopamine D1 receptor (D1R) are dynamic, cell type-specific, and can change in the face of disease or drug exposures. In striatal neurons, the D1R activates cAMP/protein kinase A (PKA) signalling. However, in Parkinson's disease (PD), alterations in this pathway lead to functional upregulation of extracellular regulated kinases 1/2 (ERK1/2), contributing to L-DOPA-induced dyskinesia (LID). In order to detect D1R activation in vivo and to study the progressive dysregulation of D1R signalling in PD and LID, we developed ratiometric fiber-photometry with Förster resonance energy transfer (FRET) biosensors and optically detected PKA and ERK1/2 signalling in freely moving rats. We show that in Parkinsonian animals, D1R signalling through PKA and ERK1/2 is sensitized, but that following chronic treatment with L-DOPA, these pathways become partially desensitized while concurrently D1R activation leads to greater induction of dyskinesia.

Therapeutic Targeting of the General RNA Polymerase II Transcription Machinery.

Inhibitors targeting the general RNA polymerase II (RNAPII) transcription machinery are candidate therapeutics in cancer and other complex diseases. Here, we review the molecular targets and mechanisms of action of these compounds, framing them within the steps of RNAPII transcription. We discuss the effects of transcription inhibitors in vitro and in cellular models (with an emphasis on cancer), as well as their efficacy in preclinical and clinical studies. We also discuss the rationale for inhibiting broadly acting transcriptional regulators or RNAPII itself in complex diseases.

Signal profiling of the ß1AR reveals coupling to novel signalling pathways and distinct phenotypic responses mediated by ß1AR and ß2AR.

A comprehensive understanding of signalling downstream of GPCRs requires a broad approach to capture novel signalling modalities in addition to established pathways. Here, using an array of sixteen validated BRET-based biosensors, we analyzed the ability of seven different ß-adrenergic ligands to engage five distinct signalling pathways downstream of the ß1-adrenergic receptor (ß1AR). In addition to generating signalling signatures and capturing functional selectivity for the different ligands toward these pathways, we also revealed coupling to signalling pathways that have not previously been ascribed to the ßAR. These include coupling to Gz and G12 pathways. The signalling cascade linking the ß1AR to calcium mobilization was also characterized using a combination of BRET-based biosensors and CRISPR-engineered HEK 293 cells lacking the Gαs subunit or with pharmacological or genetically engineered pathway inhibitors. We show that both Gs and G12 are required for the full calcium response. Our work highlights the power of combining signal profiling with genome editing approaches to capture the full complement of GPCR signalling activities in a given cell type and to probe their underlying mechanisms.

Differential Activation of P-TEFb Complexes in the Development of Cardiomyocyte Hypertrophy following Activation of Distinct G Protein-Coupled Receptors.

Pathological cardiac hypertrophy is driven by neurohormonal activation of specific G protein-coupled receptors (GPCRs) in cardiomyocytes and is accompanied by large-scale changes in cardiomyocyte gene expression. These transcriptional changes require activity of positive transcription elongation factor b (P-TEFb), which is recruited to target genes by the bromodomain protein Brd4 or the super elongation complex (SEC). Here, we describe GPCR-specific regulation of these P-TEFb complexes and a novel mechanism for activating Brd4 in primary neonatal rat cardiomyocytes. The SEC was required for the hypertrophic response downstream of either the α1-adrenergic receptor (α1-AR) or the endothelin receptor (ETR). In contrast, Brd4 inhibition selectively impaired the α1-AR response. This was corroborated by the finding that the activation of α1-AR, but not ETR, increased Brd4 occupancy at promoters and superenhancers of hypertrophic genes. Transcriptome analysis demonstrated that the activation of both receptors initiated similar gene expression programs, but that Brd4 inhibition attenuated hypertrophic genes more robustly following α1-AR activation. Finally, we show that protein kinase A (PKA) is required for α1-AR stimulation of Brd4 chromatin occupancy. The differential role of the Brd4/P-TEFb complex in response to distinct GPCR pathways has potential clinical implications, as therapies targeting this complex are currently being explored for heart failure.

Histone H2B Ubiquitylation Regulates Histone Gene Expression by Suppressing Antisense Transcription in Fission Yeast.

Histone H2B monoubiquitylation (H2Bub1) is tightly linked to RNA polymerase II transcription elongation, and is also directly implicated in DNA replication and repair. Loss of H2Bub1 is associated with defects in cell cycle progression, but how these are related to its various functions, and the underlying mechanisms involved, is not understood. Here we describe a role for H2Bub1 in the regulation of replication-dependent histone genes in the fission yeast Schizosaccharomyces pombe H2Bub1 activates histone genes indirectly by suppressing antisense transcription of ams2+ -a gene encoding a GATA-type transcription factor that activates histone genes and is required for assembly of centromeric chromatin. Mutants lacking the ubiquitylation site in H2B or the H2B-specific E3 ubiquitin ligase Brl2 had elevated levels of ams2+ antisense transcripts and reduced Ams2 protein levels. These defects were reversed upon inhibition of Cdk9-an ortholog of the kinase component of positive transcription elongation factor b (P-TEFb)-indicating that they likely resulted from aberrant transcription elongation. Reduced Cdk9 activity also partially rescued chromosome segregation phenotypes of H2Bub1 mutants. In a genome-wide analysis, loss of H2Bub1 led to increased antisense transcripts at over 500 protein-coding genes in H2Bub1 mutants; for a subset of these, including several genes involved in chromosome segregation and chromatin assembly, antisense derepression was Cdk9-dependent. Our results highlight antisense suppression as a key feature of cell cycle-dependent gene regulation by H2Bub1, and suggest that aberrant transcription elongation may underlie the effects of H2Bub1 loss on cell cycle progression.

Combining Optical Approaches with Human Inducible Pluripotent Stem Cells in G Protein-Coupled Receptor Drug Screening and Development.

Drug discovery for G protein-coupled receptors (GPCRs) stands at an interesting juncture. Screening programs are slowly moving away from model heterologous cell systems such as human embryonic kidney (HEK) 293 cells to more relevant cellular, tissue and whole animal platforms. Investigators are now developing analytical approaches as means to undertake different aspects of drug discovery by scaling into increasingly more relevant models all the way down to the single cell level. Such approaches include cellular, tissue slice and whole animal models where biosensors that track signaling events and receptor conformational profiles can be used. Here, we review aspects of biosensor-based imaging approaches that might be used in inducible pluripotent stem cell (iPSC) and organoid models, and focus on how such models must be characterized in order to apply them in drug screening.

Receptor- and cellular compartment-specific activation of the cAMP/PKA pathway by α1-adrenergic and ETA endothelin receptors.

The signalling functions of many G protein-coupled receptors (GPCRs) expressed in the myocardium are incompletely understood. Among these are the endothelin receptor (ETR) family and α1-adrenergic receptor (α1-AR), which are thought to couple to the G protein Gαq. In this study, we used transcriptome analysis to compare the signalling networks downstream of these receptors in primary neonatal rat cardiomyocytes. This analysis indicated increased expression of target genes of cAMP responsive element modulator (CREM) after 24 h treatment with the α1-AR agonist phenylephrine, but not the ETR agonist endothelin-1, suggesting a specific role for the α1-AR in promoting cAMP production in cardiomyocytes. To validate the difference observed between these two GPCRs, we used heterologous expression of the receptors and genetically encoded biosensors in HEK 293 cell lines. We validated that both α1A- and α1B-AR subtypes were able to lead to the accumulation of cAMP in response to phenylephrine in both the nucleus and cytoplasm in a Gαs-dependent manner. However, the ETR subtype ETA did not affect cAMP levels in either compartment. All three receptors were coupled to Gαq signalling as expected. Further, we showed that activation of PKA in different compartments was α1-AR subtype specific, with α1B-AR able to activate PKA in the cytoplasm and nucleus and α1A-AR only able to in the nucleus. We provide evidence for a pathway downstream of the α1-AR, and show that distinct pools of a receptor lead to differential activation of downstream effector proteins dependent on their cellular compartment.

Spatiotemporal expression and transcriptional perturbations by long noncoding RNAs in the mouse brain.

Long noncoding RNAs (lncRNAs) have been implicated in numerous cellular processes including brain development. However, the in vivo expression dynamics and molecular pathways regulated by these loci are not well understood. Here, we leveraged a cohort of 13 lncRNAnull mutant mouse models to investigate the spatiotemporal expression of lncRNAs in the developing and adult brain and the transcriptome alterations resulting from the loss of these lncRNA loci. We show that several lncRNAs are differentially expressed both in time and space, with some presenting highly restricted expression in only selected brain regions. We further demonstrate altered regulation of genes for a large variety of cellular pathways and processes upon deletion of the lncRNA loci. Finally, we found that 4 of the 13 lncRNAs significantly affect the expression of several neighboring proteincoding genes in a cis-like manner. By providing insight into the endogenous expression patterns and the transcriptional perturbations caused by deletion of the lncRNA locus in the developing and postnatal mammalian brain, these data provide a resource to facilitate future examination of the specific functional relevance of these genes in neural development, brain function, and disease.