Two-hit mouse model of heart failure with preserved ejection fraction combining diet-induced obesity and renin-mediated hypertension.

Heart failure with preserved ejection fraction (HFpEF) is increasingly common but its pathogenesis is poorly understood. The ability to assess genetic and pharmacologic interventions is hampered by the lack of robust preclinical mouse models of HFpEF. We have developed a novel "2-hit" model, which combines obesity and insulin resistance with chronic pressure overload to recapitulate clinical features of HFpEF. C57BL6/NJ mice fed a high fat diet for >10 weeks were administered an AAV8-driven vector resulting in constitutive overexpression of mouse Renin1d . Control mice, HFD only, Renin only and HFD-Renin (aka "HFpEF") littermates underwent a battery of cardiac and extracardiac phenotyping. HFD-Renin mice demonstrated obesity and insulin resistance, a 2-3-fold increase in circulating renin levels that resulted in 30-40% increase in left ventricular hypertrophy, preserved systolic function, and diastolic dysfunction indicated by altered E/e', IVRT, and strain measurements; increased left atrial mass; elevated natriuretic peptides; and exercise intolerance. Transcriptomic and metabolomic profiling of HFD-Renin myocardium demonstrated upregulation of pro-fibrotic pathways and downregulation of metabolic pathways, in particular branched chain amino acid catabolism, similar to findings in human HFpEF. Treatment of these mice with the sodium-glucose cotransporter 2 inhibitor empagliflozin, an effective but incompletely understood HFpEF therapy, improved exercise tolerance, left heart enlargement, and insulin homeostasis. The HFD-Renin mouse model recapitulates key features of human HFpEF and will enable studies dissecting the contribution of individual pathogenic drivers to this complex syndrome. Addition of HFD-Renin mice to the preclinical HFpEF model platform allows for orthogonal studies to increase validity in assessment of interventions. NEW & NOTEWORTHY: Heart failure with preserved ejection fraction (HFpEF) is a complex disease to study due to limited preclinical models. We rigorously characterize a new two-hit HFpEF mouse model, which allows for dissecting individual contributions and synergy of major pathogenic drivers, hypertension and diet-induced obesity. The results are consistent and reproducible in two independent laboratories. This high-fidelity pre-clinical model increases the available, orthogonal models needed to improve our understanding of the causes and assessment treatments for HFpEF.

Nuclear receptor corepressors non-canonically drive glucocorticoid receptor-dependent activation of hepatic gluconeogenesis.

Nuclear receptor corepressors (NCoRs) function in multiprotein complexes containing histone deacetylase 3 (HDAC3) to alter transcriptional output primarily through repressive chromatin remodelling at target loci1-5. In the liver, loss of HDAC3 causes a marked hepatosteatosis largely because of de-repression of genes involved in lipid metabolism6,7; however, the individual roles and contribution of other complex members to hepatic and systemic metabolic regulation are unclear. Here we show that adult loss of both NCoR1 and NCoR2 (double knockout (KO)) in hepatocytes phenocopied the hepatomegalic fatty liver phenotype of HDAC3 KO. In addition, double KO livers exhibited a dramatic reduction in glycogen storage and gluconeogenic gene expression that was not observed with hepatic KO of individual NCoRs or HDAC3, resulting in profound fasting hypoglycaemia. This surprising HDAC3-independent activation function of NCoR1 and NCoR2 is due to an unexpected loss of chromatin accessibility on deletion of NCoRs that prevented glucocorticoid receptor binding and stimulatory effect on gluconeogenic genes. These studies reveal an unanticipated, non-canonical activation function of NCoRs that is required for metabolic health.

Control of murine brown adipocyte development by GATA6.

Brown adipose tissue (BAT) is a thermogenic organ that protects animals against hypothermia and obesity. BAT derives from the multipotent paraxial mesoderm; however, the identity of embryonic brown fat progenitor cells and regulators of adipogenic commitment are unclear. Here, we performed single-cell gene expression analyses of mesenchymal cells during mouse embryogenesis with a focus on BAT development. We identified cell populations associated with the development of BAT, including Dpp4+ cells that emerge at the onset of adipogenic commitment. Immunostaining and lineage-tracing studies show that Dpp4+ cells constitute the BAT fascia and contribute minorly as adipocyte progenitors. Additionally, we identified the transcription factor GATA6 as a marker of brown adipogenic progenitor cells. Deletion of Gata6 in the brown fat lineage resulted in a striking loss of BAT. Together, these results identify progenitor and transitional cells in the brown adipose lineage and define a crucial role for GATA6 in BAT development.

RIP140 deficiency enhances cardiac fuel metabolism and protects mice from heart failure.

During the development of heart failure (HF), the capacity for cardiomyocyte (CM) fatty acid oxidation (FAO) and ATP production is progressively diminished, contributing to pathologic cardiac hypertrophy and contractile dysfunction. Receptor-interacting protein 140 (RIP140, encoded by Nrip1) has been shown to function as a transcriptional corepressor of oxidative metabolism. We found that mice with striated muscle deficiency of RIP140 (strNrip1-/-) exhibited increased expression of a broad array of genes involved in mitochondrial energy metabolism and contractile function in heart and skeletal muscle. strNrip1-/- mice were resistant to the development of pressure overload-induced cardiac hypertrophy, and CM-specific RIP140-deficient (csNrip1-/-) mice were protected against the development of HF caused by pressure overload combined with myocardial infarction. Genomic enhancers activated by RIP140 deficiency in CMs were enriched in binding motifs for transcriptional regulators of mitochondrial function (estrogen-related receptor) and cardiac contractile proteins (myocyte enhancer factor 2). Consistent with a role in the control of cardiac fatty acid oxidation, loss of RIP140 in heart resulted in augmented triacylglyceride turnover and fatty acid utilization. We conclude that RIP140 functions as a suppressor of a transcriptional regulatory network that controls cardiac fuel metabolism and contractile function, representing a potential therapeutic target for the treatment of HF.

Hepatocytes demarcated by EphB2 contribute to the progression of nonalcoholic steatohepatitis.

Current therapeutic strategies for treating nonalcoholic steatohepatitis (NASH) have failed to alleviate liver fibrosis, which is a devastating feature leading to hepatic dysfunction. Here, we integrated single-nucleus transcriptomics and epigenomics to characterize all major liver cell types during NASH development in mice and humans. The bifurcation of hepatocyte trajectory with NASH progression was conserved between mice and humans. At the nonalcoholic fatty liver (NAFL) stage, hepatocytes exhibited metabolic adaptation, whereas at the NASH stage, a subset of hepatocytes was enriched for the signatures of cell adhesion and migration, which were mainly demarcated by receptor tyrosine kinase ephrin type B receptor 2 (EphB2). EphB2, acting as a downstream effector of Notch signaling in hepatocytes, was sufficient to induce cell-autonomous inflammation. Knockdown of Ephb2 in hepatocytes ameliorated inflammation and fibrosis in a mouse model of NASH. Thus, EphB2-expressing hepatocytes contribute to NASH progression and may serve as a potential therapeutic target.

Balanced control of thermogenesis by nuclear receptor corepressors in brown adipose tissue.

Brown adipose tissue (BAT) is a key thermogenic organ whose expression of uncoupling protein 1 (UCP1) and ability to maintain body temperature in response to acute cold exposure require histone deacetylase 3 (HDAC3). HDAC3 exists in tight association with nuclear receptor corepressors (NCoRs) NCoR1 and NCoR2 (also known as silencing mediator of retinoid and thyroid receptors [SMRT]), but the functions of NCoR1/2 in BAT have not been established. Here we report that as expected, genetic loss of NCoR1/2 in BAT (NCoR1/2 BAT-dKO) leads to loss of HDAC3 activity. In addition, HDAC3 is no longer bound at its physiological genomic sites in the absence of NCoR1/2, leading to a shared deregulation of BAT lipid metabolism between NCoR1/2 BAT-dKO and HDAC3 BAT-KO mice. Despite these commonalities, loss of NCoR1/2 in BAT does not phenocopy the cold sensitivity observed in HDAC3 BAT-KO, nor does loss of either corepressor alone. Instead, BAT lacking NCoR1/2 is inflamed, particularly with respect to the interleukin-17 axis that increases thermogenic capacity by enhancing innervation. Integration of BAT RNA sequencing and chromatin immunoprecipitation sequencing data revealed that NCoR1/2 directly regulate Mmp9, which integrates extracellular matrix remodeling and inflammation. These findings reveal pleiotropic functions of the NCoR/HDAC3 corepressor complex in BAT, such that HDAC3-independent suppression of BAT inflammation counterbalances stimulation of HDAC3 activity in the control of thermogenesis.

The nuclear receptor ERR cooperates with the cardiogenic factor GATA4 to orchestrate cardiomyocyte maturation.

Estrogen-related receptors (ERR) α and γ were shown recently to serve as regulators of cardiac maturation, yet the underlying mechanisms have not been delineated. Herein, we find that ERR signaling is necessary for induction of genes involved in mitochondrial and cardiac-specific contractile processes during human induced pluripotent stem cell-derived cardiomyocyte (hiPSC-CM) differentiation. Genomic interrogation studies demonstrate that ERRγ occupies many cardiomyocyte enhancers/super-enhancers, often co-localizing with the cardiogenic factor GATA4. ERRγ interacts with GATA4 to cooperatively activate transcription of targets involved in cardiomyocyte-specific processes such as contractile function, whereas ERRγ-mediated control of metabolic genes occurs independent of GATA4. Both mechanisms require the transcriptional coregulator PGC-1α. A disease-causing GATA4 mutation is shown to diminish PGC-1α/ERR/GATA4 cooperativity and expression of ERR target genes are downregulated in human heart failure samples suggesting that dysregulation of this circuitry may contribute to congenital and acquired forms of heart failure.

Defining the lineage of thermogenic perivascular adipose tissue.

Brown adipose tissue can expend large amounts of energy, and therefore increasing its size or activity is a promising therapeutic approach to combat metabolic disease. In humans, major deposits of brown fat cells are found intimately associated with large blood vessels, corresponding to perivascular adipose tissue (PVAT). However, the cellular origins of PVAT are poorly understood. Here, we determine the identity of perivascular adipocyte progenitors in mice and humans. In mice, thoracic PVAT develops from a fibroblastic lineage, consisting of progenitor cells (Pdgfra+, Ly6a+ and Pparg-) and preadipocytes (Pdgfra+, Ly6a+ and Pparg+), which share transcriptional similarity with analogous cell types in white adipose tissue. Interestingly, the aortic adventitia of adult animals contains a population of adipogenic smooth muscle cells (Myh11+, Pdgfra- and Pparg+) that contribute to perivascular adipocyte formation. Similarly, human PVAT contains presumptive fibroblastic and smooth muscle-like adipocyte progenitor cells, as revealed by single-nucleus RNA sequencing. Together, these studies define distinct populations of progenitor cells for thermogenic PVAT, providing a foundation for developing strategies to augment brown fat activity.

A coregulator shift, rather than the canonical switch, underlies thyroid hormone action in the liver.

Thyroid hormones (THs) are powerful regulators of metabolism with major effects on body weight, cholesterol, and liver fat that have been exploited pharmacologically for many years. Activation of gene expression by TH action is canonically ascribed to a hormone-dependent "switch" from corepressor to activator binding to thyroid hormone receptors (TRs), while the mechanism of TH-dependent repression is controversial. To address this, we generated a mouse line in which endogenous TRß1 was epitope-tagged to allow precise chromatin immunoprecipitation at the low physiological levels of TR and defined high-confidence binding sites where TRs functioned at enhancers regulated in the same direction as the nearest gene in a TRß-dependent manner. Remarkably, although positive and negative regulation by THs have been ascribed to different mechanisms, TR binding was highly enriched at canonical DR4 motifs irrespective of the transcriptional direction of the enhancer. The canonical NCoR1/HDAC3 corepressor complex was reduced but not completely dismissed by TH and, surprisingly, similar effects were seen at enhancers associated with negatively as well as positively regulated genes. Conversely, coactivator CBP was found at all TH-regulated enhancers, with transcriptional activity correlating with the ratio of CBP to NCoR rather than their presence or absence. These results demonstrate that, in contrast to the canonical "all or none" coregulator switch model, THs regulate gene expression by orchestrating a shift in the relative binding of corepressors and coactivators.

The Nuclear Receptor ESRRA Protects from Kidney Disease by Coupling Metabolism and Differentiation.

Kidney disease is poorly understood because of the organ's cellular diversity. We used single-cell RNA sequencing not only in resolving differences in injured kidney tissue cellular composition but also in cell-type-specific gene expression in mouse models of kidney disease. This analysis highlighted major changes in cellular diversity in kidney disease, which markedly impacted whole-kidney transcriptomics outputs. Cell-type-specific differential expression analysis identified proximal tubule (PT) cells as the key vulnerable cell type. Through unbiased cell trajectory analyses, we show that PT cell differentiation is altered in kidney disease. Metabolism (fatty acid oxidation and oxidative phosphorylation) in PT cells showed the strongest and most reproducible association with PT cell differentiation and disease. Coupling of cell differentiation and the metabolism was established by nuclear receptors (estrogen-related receptor alpha [ESRRA] and peroxisomal proliferation-activated receptor alpha [PPARA]) that directly control metabolic and PT-cell-specific gene expression in mice and patient samples while protecting from kidney disease in the mouse model.

BayesPI-BAR2: A New Python Package for Predicting Functional Non-coding Mutations in Cancer Patient Cohorts.

Most of somatic mutations in cancer occur outside of gene coding regions. These mutations may disrupt the gene regulation by affecting protein-DNA interaction. A study of these disruptions is important in understanding tumorigenesis. However, current computational tools process DNA sequence variants individually, when predicting the effect on protein-DNA binding. Thus, it is a daunting task to identify functional regulatory disturbances among thousands of mutations in a patient. Previously, we have reported and validated a pipeline for identifying functional non-coding somatic mutations in cancer patient cohorts, by integrating diverse information such as gene expression, spatial distribution of the mutations, and a biophysical model for estimating protein binding affinity. Here, we present a new user-friendly Python package BayesPI-BAR2 based on the proposed pipeline for integrative whole-genome sequence analysis. This may be the first prediction package that considers information from both multiple mutations and multiple patients. It is evaluated in follicular lymphoma and skin cancer patients, by focusing on sequence variants in gene promoter regions. BayesPI-BAR2 is a useful tool for predicting functional non-coding mutations in whole genome sequencing data: it allows identification of novel transcription factors (TFs) whose binding is altered by non-coding mutations in cancer. BayesPI-BAR2 program can analyze multiple datasets of genome-wide mutations at once and generate concise, easily interpretable reports for potentially affected gene regulatory sites. The package is freely available at http://folk.uio.no/junbaiw/BayesPI-BAR2/.

Predicting Variation of DNA Shape Preferences in Protein-DNA Interaction in Cancer Cells with a New Biophysical Model.

DNA shape readout is an important mechanism of transcription factor target site recognition, in addition to the sequence readout. Several machine learning-based models of transcription factor-DNA interactions, considering DNA shape features, have been developed in recent years. Here, we present a new biophysical model of protein-DNA interactions by integrating the DNA shape properties. It is based on the neighbor dinucleotide dependency model BayesPI2, where new parameters are restricted to a subspace spanned by the dinucleotide form of DNA shape features. This allows a biophysical interpretation of the new parameters as a position-dependent preference towards specific DNA shape features. Using the new model, we explore the variation of DNA shape preferences in several transcription factors across various cancer cell lines and cellular conditions. The results reveal that there are DNA shape variations at FOXA1 (Forkhead Box Protein A1) binding sites in steroid-treated MCF7 cells. The new biophysical model is useful for elucidating the finer details of transcription factor-DNA interaction, as well as for predicting cancer mutation effects in the future.

Integrative whole-genome sequence analysis reveals roles of regulatory mutations in BCL6 and BCL2 in follicular lymphoma.

The contribution of mutations in regulatory regions to tumorigenesis has been the subject of many recent studies. We propose a new framework for integrative analysis of genome-wide sequencing data by considering diverse genetic information. This approach is applied to study follicular lymphoma (FL), a disease for which little is known about the contribution of regulatory gene mutations. Results from a test FL cohort revealed three novel highly recurrent regulatory mutation blocks near important genes implicated in FL, BCL6 and BCL2. Similar findings were detected in a validation FL cohort. We also found transcription factors (TF) whose binding may be disturbed by these mutations in FL: disruption of FOX TF family near the BCL6 promoter may result in reduced BCL6 expression, which then increases BCL2 expression over that caused by BCL2 gene translocation. Knockdown experiments of two TF hits (FOXD2 or FOXD3) were performed in human B lymphocytes verifying that they modulate BCL6/BCL2 according to the computationally predicted effects of the SNVs on TF binding. Overall, our proposed integrative analysis facilitates non-coding driver identification and the new findings may enhance the understanding of FL.

Long-term tracking of budding yeast cells in brightfield microscopy: CellStar and the Evaluation Platform.

With the continuous expansion of single cell biology, the observation of the behaviour of individual cells over extended durations and with high accuracy has become a problem of central importance. Surprisingly, even for yeast cells that have relatively regular shapes, no solution has been proposed that reaches the high quality required for long-term experiments for segmentation and tracking (S&T) based on brightfield images. Here, we present CellStar, a tool chain designed to achieve good performance in long-term experiments. The key features are the use of a new variant of parametrized active rays for segmentation, a neighbourhood-preserving criterion for tracking, and the use of an iterative approach that incrementally improves S&T quality. A graphical user interface enables manual corrections of S&T errors and their use for the automated correction of other, related errors and for parameter learning. We created a benchmark dataset with manually analysed images and compared CellStar with six other tools, showing its high performance, notably in long-term tracking. As a community effort, we set up a website, the Yeast Image Toolkit, with the benchmark and the Evaluation Platform to gather this and additional information provided by others.

BayesPI-BAR: a new biophysical model for characterization of regulatory sequence variations.

Sequence variations in regulatory DNA regions are known to cause functionally important consequences for gene expression. DNA sequence variations may have an essential role in determining phenotypes and may be linked to disease; however, their identification through analysis of massive genome-wide sequencing data is a great challenge. In this work, a new computational pipeline, a Bayesian method for protein-DNA interaction with binding affinity ranking (BayesPI-BAR), is proposed for quantifying the effect of sequence variations on protein binding. BayesPI-BAR uses biophysical modeling of protein-DNA interactions to predict single nucleotide polymorphisms (SNPs) that cause significant changes in the binding affinity of a regulatory region for transcription factors (TFs). The method includes two new parameters (TF chemical potentials or protein concentrations and direct TF binding targets) that are neglected by previous methods. The new method is verified on 67 known human regulatory SNPs, of which 47 (70%) have predicted true TFs ranked in the top 10. Importantly, the performance of BayesPI-BAR, which uses principal component analysis to integrate multiple predictions from various TF chemical potentials, is found to be better than that of existing programs, such as sTRAP and is-rSNP, when evaluated on the same SNPs. BayesPI-BAR is a publicly available tool and is able to carry out parallelized computation, which helps to investigate a large number of TFs or SNPs and to detect disease-associated regulatory sequence variations in the sea of genome-wide noncoding regions.