Transcriptome remodeling in heart disease occurs through the coordinated actions of transcription factors, histone modifications, and other chromatin features at pathology-associated genes. The extent to which genome-wide chromatin reorganization also contributes to the resultant changes in gene expression remains unknown. We examined the roles of two chromatin structural proteins, Ctcf (CCCTC-binding factor) and Hmgb2 (high mobility group protein B2), in regulating pathologic transcription and chromatin remodeling. Our data demonstrate a reciprocal relationship between Hmgb2 and Ctcf in controlling aspects of chromatin structure and gene expression. Both proteins regulate each others' expression as well as transcription in cardiac myocytes; however, only Hmgb2 does so in a manner that involves global reprogramming of chromatin accessibility. We demonstrate that the actions of Hmgb2 on local chromatin accessibility are conserved across genomic loci, whereas the effects on transcription are loci-dependent and emerge in concert with histone modification and other chromatin features. Finally, although both proteins share gene targets, Hmgb2 and Ctcf, neither binds these genes simultaneously nor do they physically colocalize in myocyte nuclei. Our study uncovers a previously unknown relationship between these two ubiquitous chromatin proteins and provides a mechanistic explanation for how Hmgb2 regulates gene expression and cellular phenotype. Furthermore, we provide direct evidence for structural remodeling of chromatin on a genome-wide scale in the setting of cardiac disease.

Cardiac mechanical function is supported by ATP hydrolysis, which provides the chemical free energy to drive the molecular processes underlying cardiac pumping. Physiological rates of myocardial ATP consumption require the heart to resynthesize its entire ATP pool several times per minute. In the failing heart, cardiomyocyte metabolic dysfunction leads to a reduction in the capacity for ATP synthesis and associated free energy to drive cellular processes. Yet it remains unclear if and how metabolic/energetic dysfunction that occurs during heart failure affects mechanical function of the heart. We hypothesize that changes in phosphate metabolite concentrations (ATP, ADP, inorganic phosphate) that are associated with decompensation and failure have direct roles in impeding contractile function of the myocardium in heart failure, contributing to the whole-body phenotype. To test this hypothesis, a transverse aortic constriction (TAC) rat model of pressure overload, hypertrophy, and decompensation was used to assess relationships between metrics of whole-organ pump function and myocardial energetic state. A multi-scale computational model of cardiac mechano-energetic coupling was used to identify and quantify the contribution of metabolic dysfunction to observed mechanical dysfunction. Results show an overall reduction in capacity for oxidative ATP synthesis fueled by either fatty acid or carbohydrate substrates as well as a reduction in total levels of adenine nucleotides and creatine in myocardium from TAC animals compared to sham-operated controls. Changes in phosphate metabolite levels in the TAC rats are correlated with impaired mechanical function, consistent with the overall hypothesis. Furthermore, computational analysis of myocardial metabolism and contractile dynamics predicts that increased levels of inorganic phosphate in TAC compared to control animals kinetically impair the myosin ATPase crossbridge cycle in decompensated hypertrophy/heart failure.

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This paper details a multi-scale model computational model of myocardial energetics---oxidative ATP synthesis, ATP hydrolysis, and phosphate metabolite kinetics---and myocardial mechanics used to analyze data from a rat model of cardiac decompensation and failure. Combined, these two models simulate cardiac mechano-energetics: the coupling between metabolic production of ATP and hydrolysis of ATP to generate mechanical work. The model is used to predict how differences in energetic metabolic state found in failing versus control hearts causally contribute to systolic mechanical dysfunction in heart failure. This Physiome paper describes how to access, run, and manipulate these computer models, how to parameterize the models to match data, and how to compare model predictions to data.

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