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Biology subjects

Harris, B. N.

Publications and source records attributed to Harris, B. N..

4 recordsLinked to original sources

Systems analysis reveals neuregulin-1 control of cardiomyocyte size and shape mediated by distinct PI3K and p38 pathways

Pathological and physiological stresses induce diverse forms of cardiac hypertrophy, with distinct manifestations in cardiomyocyte size and shape regulated by still poorly understood signaling networks. Here, we combined high-content morphological profiling, phospho-protein arrays, and systems modeling to characterize the diverse forms of hypertrophy induced by angiotensin II, endothelin-1, insulin growth factor-1, and neuregulin-1. Reverse-phase protein array profiling of neonatal rat cardiomyocytes and partial least squares regression modeling revealed that Akt, GSK3, and MAPK signaling are differentially regulated by hypertrophic agonists and are predictive of distinct phenotypic outcomes. Among these agonists, neuregulin-1 uniquely induced cardiomyocyte elongation in both neonatal rat and human iPSC-derived cardiomyocytes, in addition to increasing cell area. Pharmacological perturbations in neonatal rat cardiomyocytes demonstrated that neuregulin1-induced elongation and area expansion both require PI3K activity, whereas p38 selectively mediates cell area. A logic-based network model incorporating dual-specificity phosphatases were sufficient to capture the amplifying PI3K and transient p38 signaling dynamics driving phenotypic changes. Together, these results identify distinct signaling cascades by which neuregulin-1 coordinates cardiomyocyte size and shape, providing mechanistic insight into how hypertrophic remodeling can be differentially regulated. This systems approach provides new insight into the pathways that drive distinct forms of cardiomyocyte hypertrophy, highlighting opportunities to selectively target maladaptive remodeling in heart failure.

systems biology↗

Network Modeling Predicts How DYRK1A Inhibition Promotes Cardiomyocyte Cycling after Ischemic/Reperfusion Injury

The adult mammalian heart has a limited ability to regenerate lost myocardium following myocardial infarction (MI), largely due to the poor proliferative capacity of cardiomyocytes (CMs). Dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) is a known regulator of cell quiescence, though the mechanisms underlying its function remain unclear. Previous studies have shown that pharmacological inhibition of DYRK1A using harmine induces CM cell cycle re-entry after ischemia/reperfusion (I/R) MI. Here, we developed a computational network model of DYRK1A-mediated regulation of the cell cycle, which predicts how DYRK1A inhibition promotes CM re-entry. To validate these predictions, we tested selective DYRK1A inhibitors and observed robust induction of cell cycle activity in neonatal rat cardiomyocytes (NRCMs). Integrating our network model with bulk RNA-sequencing data from DYRK1A inhibitor-treated NRCMs, we identified E2F1 as a key transcriptional driver of cell cycle gene expression. Finally, we demonstrate that both pharmacological and post-developmental inhibition of DYRK1A enhances heart function and increases CM cycling following I/R MI. Our findings suggest that functional recovery induced by small molecule inhibitor of DYRK1A is mediated by the induction of cycling CMs. One Sentence SummaryInhibition of DYRK1A through LCTB-92 induces cardiomyocyte cycling and improved heart function in a mouse model of ischemic/reperfusion injury.

pharmacology and toxicology↗

An accurate and interpretable model to predict antimicrobial resistance in One Health settings

Understanding the microbial genomic contributors to antimicrobial resistance (AMR) is essential for early detection of emerging AMR infections, a pressing global health threat in human and veterinary medicine. Here we used whole genome sequencing and antibiotic susceptibility test data from 980 disease causing Escherichia coli isolated from companion and farm animals to model AMR genotypes and phenotypes for 24 antibiotics. We determined the strength of genotype-to-phenotype relationships for 197 AMR genes with elastic net logistic regression. Model predictors were designed to evaluate different potential modes of AMR genotype translation into resistance phenotypes. Our results show a model that considers the presence of individual AMR genes and total number of AMR genes present from a set of genes known to confer resistance was able to accurately predict isolate resistance on average (mean F1 score = 98.0%, SD = 2.3%, mean accuracy = 98.2%, SD = 2.7%). However, fitted models sometimes varied for antibiotics in the same class and for the same antibiotic across animal hosts, suggesting heterogeneity in the genetic determinants of AMR resistance. We conclude that an interpretable AMR prediction model can be used to accurately predict resistance phenotypes across multiple host species and reveal testable hypotheses about how the mechanism of resistance may vary across antibiotics within the same class and across animal hosts for the same antibiotic.

bioinformatics↗

Dynamic map illuminates Hippo to cMyc module crosstalk driving cardiomyocyte proliferation

Cardiac diseases are characterized by the inability of adult mammalian hearts to overcome the loss of cardiomyocytes (CMs). Current knowledge in cardiac regeneration lacks a clear understanding of the molecular systems determining whether CMs will progress through the cell cycle to proliferate. Here, we developed a computational model of cardiac proliferation signaling that identifies key regulators and provides a systems-level understanding of the cardiomyocyte proliferation regulatory network. This model defines five regulatory networks (DNA replication, mitosis, cytokinesis, growth factor, hippo pathway) of cardiomyocyte proliferation, which integrates 72 nodes and 88 reactions. The model correctly predicts 72 of 76 (94.7%) independent experiments from the literature. Network analysis predicted key signaling regulators of DNA replication (e.g., AKT, CDC25A, Cyclin D/CDK4, E2F), mitosis (e.g., Cyclin B/CDK2, CDC25B/C, PLK1), and cytokinesis, whose functions varied depending on the environmental context. Regulators of DNA replication were found to be highly context-dependent, while regulators of mitosis and cytokinesis were context-independent. We also predicted that in response to the YAP-activating compound TT-10, the Hippo module crosstalks with the growth factor module via PI3K, cMyc, and FoxM1 to drive proliferation. This prediction was validated with inhibitor experiments in primary rat cardiomyocytes and further supported by re-analysis of published data on YAP-stimulated mRNA and open chromatin of Myc from mouse hearts. This study contributes a systems framework for understanding cardiomyocyte proliferation and identifies potential therapeutic regulators that induce cardiomyocyte proliferation.

systems biology↗