Ashley J. Waardenberg

Phosphoinositide 3-Kinase (PI3K(p110α)) Directly Regulates Key Components of the Z-disc and Cardiac Structure

Maintenance of cardiac structure and Z-disc signaling are key factors responsible for protecting the heart in a setting of stress, but how these processes are regulated is not well defined. We recently demonstrated that PI3K(p110α) protects the heart against myocardial infarction. The aim of this study was to determine whether PI3K(p110α) directly regulates components of the Z-disc and cardiac structure. To address this question, a unique three-dimensional virtual muscle model was applied to gene expression data from transgenic mice with increased or decreased PI3K(p110α) activity under basal conditions (sham) and in a setting of myocardial infarction to display the location of structural proteins. Key findings from this analysis were then validated experimentally. The three-dimensional virtual muscle model visually highlighted reciprocally regulated transcripts associated with PI3K activation that encoded key components of the Z-disc and costamere, including melusin. Studies were performed to assess whether PI3K and melusin interact in the heart. Here, we identify a novel melusin-PI3K interaction that generates lipid kinase activity. The direct impact of PI3K(p110α) on myocyte structure was assessed by treating neonatal rat ventricular myocytes with PI3K(p110α) inhibitors and examining the myofiber morphology of hearts from PI3K transgenic mice. Results demonstrate that PI3K is critical for myofiber maturation and Z-disc alignment. In summary, PI3K regulates the expression of genes essential for cardiac structure and Z-disc signaling, interacts with melusin, and is critical for Z-disc alignment.

ROS-activated ATM-dependent phosphorylation of cytoplasmic substrates identified by large scale phosphoproteomics screen

Ataxia-telangiectasia, mutated (ATM) protein plays a central role in phosphorylating a network of proteins in response to DNA damage. These proteins function in signaling pathways designed to maintain the stability of the genome and minimize the risk of disease by controlling cell cycle checkpoints, initiating DNA repair, and regulating gene expression. ATM kinase can be activated by a variety of stimuli, including oxidative stress. Here, we confirmed activation of cytoplasmic ATM by autophosphorylation at multiple sites. Then we employed a global quantitative phosphoproteomics approach to identify cytoplasmic proteins altered in their phosphorylation state in control and ataxia-telangiectasia (A-T) cells in response to oxidative damage. We demonstrated that ATM was activated by oxidative damage in the cytoplasm as well as in the nucleus and identified a total of 9,833 phosphorylation sites, including 6,686 high-confidence sites mapping to 2,536 unique proteins. A total of 62 differentially phosphorylated peptides were identified; of these, 43 were phosphorylated in control but not in A-T cells, and 19 varied in their level of phosphorylation. Motif enrichment analysis of phosphopeptides revealed that consensus ATM serine glutamine sites were overrepresented. When considering phosphorylation events, only observed in control cells (not observed in A-T cells), with predicted ATM sites phosphoSerine/phosphoThreonine glutamine, we narrowed this list to 11 candidate ATM-dependent cytoplasmic proteins. Two of these 11 were previously described as ATM substrates (HMGA1 and UIMCI/RAP80), another five were identified in a whole cell extract phosphoproteomic screens, and the remaining four proteins had not been identified previously in DNA damage response screens. We validated the phosphorylation of three of these proteins (oxidative stress responsive 1 (OSR1), HDGF, and ccdc82) as ATM dependent after H2O2 exposure, and another protein (S100A11) demonstrated ATM-dependence for translocation from the cytoplasm to the nucleus. These data provide new insights into the activation of ATM by oxidative stress through identification of novel substrates for ATM in the cytoplasm.

Irreversible Triggers for Hypertrophic Cardiomyopathy Are Established in the Early Postnatal Period

BACKGROUND Hypertrophic cardiomyopathy (HCM) is caused by mutations in sarcomere protein genes, and left ventricular hypertrophy (LVH) develops as an adaptive response to sarcomere dysfunction. It remains unclear whether persistent expression of the mutant gene is required for LVH or whether early gene expression acts as an immutable inductive trigger. OBJECTIVES The aim of this study was to use a regulatable murine model of HCM to study the reversibility of pathological LVH. METHODS The authors generated a double-transgenic mouse model, tTAxαMHCR403Q, in which expression of the HCM-causing Arg403Gln mutation in the α-myosin heavy chain (MHC) gene is inhibited by doxycycline administration. Cardiac structure and function were evaluated in groups of mice that received doxycycline for varying periods from 0 to 40 weeks of age. RESULTS Untreated tTAxαMHCR403Q mice showed increased left ventricular (LV) mass, contractile dysfunction, myofibrillar disarray, and fibrosis. In contrast, mice treated with doxycycline from conception to 6 weeks had markedly less LVH and fibrosis at 40 weeks. Transgene inhibition from 6 weeks reduced fibrosis but did not prevent LVH or functional changes. There were no differences in LV parameters at 40 weeks between mice with transgene inhibition from 20 weeks and mice with continuous transgene expression. CONCLUSIONS These findings highlight the critical role of the early postnatal period in HCM pathogenesis and suggest that mutant sarcomeres manifest irreversible cardiomyocyte defects that induce LVH. In HCM, mutation-silencing therapies are likely to be ineffective for hypertrophy regression and would have to be administered very early in life to prevent hypertrophy development.

CompGO: an R package for comparing and visualizing Gene Ontology enrichment differences between DNA binding experiments.

BackgroundGene ontology (GO) enrichment is commonly used for inferring biological meaning from systems biology experiments. However, determining differential GO and pathway enrichment between DNA-binding experiments or using the GO structure to classify experiments has received little attention.ResultsHerein, we present a bioinformatics tool, CompGO, for identifying Differentially Enriched Gene Ontologies, called DiEGOs, and pathways, through the use of a z-score derivation of log odds ratios, and visualizing these differences at GO and pathway level. Through public experimental data focused on the cardiac transcription factor NKX2-5, we illustrate the problems associated with comparing GO enrichments between experiments using a simple overlap approach.ConclusionsWe have developed an R/Bioconductor package, CompGO, which implements a new statistic normally used in epidemiological studies for performing comparative GO analyses and visualizing comparisons from .BED data containing genomic coordinates as well as gene lists as inputs. We justify the statistic through inclusion of experimental data and compare to the commonly used overlap method. CompGO is freely available as a R/Bioconductor package enabling easy integration into existing pipelines and is available at: http://www.bioconductor.org/packages/release/bioc/html/CompGO.html packages/release/bioc/html/CompGO.html

Genetic Networks Governing Heart Development

Animal genomes contain a code for construction of the body plan from a fertilized egg. Understanding how genome information is deciphered to create the complex multilayered regulatory systems that drive organismal development, and which become altered in disease, is one of the greatest challenges in the biological sciences. The development of methods that effectively represent and communicate the complexity inherent in gene regulatory networks remains a major barrier. This review introduces the philosophy of systems biology and discusses recent progress in understanding the development of the heart at a systems biology level.

Progesterone signalling in broiler skeletal muscle is associated with divergent feed efficiency

BackgroundWe contrast the pectoralis muscle transcriptomes of broilers selected from within a single genetic line expressing divergent feed efficiency (FE) in an effort to improve our understanding of the mechanistic basis of FE.ResultsApplication of a virtual muscle model to gene expression data pointed to a coordinated reduction in slow twitch muscle isoforms of the contractile apparatus (MYH15, TPM3, MYOZ2, TNNI1, MYL2, MYOM3, CSRP3, TNNT2), consistent with diminishment in associated slow machinery (myoglobin and phospholamban) in the high FE animals. These data are in line with the repeated transition from red slow to white fast muscle fibres observed in agricultural species selected on mass and FE. Surprisingly, we found that the expression of 699 genes encoding the broiler mitoproteome is modestly–but significantly–biased towards the high FE group, suggesting a slightly elevated mitochondrial content. This is contrary to expectation based on the slow muscle isoform data and theoretical physiological capacity arguments. Reassuringly, the extreme 40 most DE genes can successfully cluster the 12 individuals into the appropriate FE treatment group. Functional groups contained in this DE gene list include metabolic proteins (including opposing patterns of CA3 and CA4), mitochondrial proteins (CKMT1A), oxidative status (SEPP1, HIG2A) and cholesterol homeostasis (APOA1, INSIG1). We applied a differential network method (Regulatory Impact Factors) whose aim is to use patterns of differential co-expression to detect regulatory molecules transcriptionally rewired between the groups. This analysis clearly points to alterations in progesterone signalling (via the receptor PGR) as the major driver. We show the progesterone receptor localises to the mitochondria in a quail muscle cell line.ConclusionsProgesterone is sometimes used in the cattle industry in exogenous hormone mixes that lead to a ~20% increase in FE. Because the progesterone receptor can localise to avian mitochondria, our data continue to point to muscle mitochondrial metabolism as an important component of the phenotypic expression of variation in broiler FE.

Prediction and validation of protein-protein interactors from genome-wide DNA-binding data using a knowledge-based machine-learning approach.

The ability to accurately predict the DNA targets and interacting cofactors of transcriptional regulators from genome-wide data can significantly advance our understanding of gene regulatory networks. NKX2-5 is a homeodomain transcription factor that sits high in the cardiac gene regulatory network and is essential for normal heart development. We previously identified genomic targets for NKX2-5 in mouse HL-1 atrial cardiomyocytes using DNA-adenine methyltransferase identification (DamID). Here, we apply machine learning algorithms and propose a knowledge-based feature selection method for predicting NKX2-5 protein : protein interactions based on motif grammar in genome-wide DNA-binding data. We assessed model performance using leave-one-out cross-validation and a completely independent DamID experiment performed with replicates. In addition to identifying previously described NKX2-5-interacting proteins, including GATA, HAND and TBX family members, a number of novel interactors were identified, with direct protein : protein interactions between NKX2-5 and retinoid X receptor (RXR), paired-related homeobox (PRRX) and Ikaros zinc fingers (IKZF) validated using the yeast two-hybrid assay. We also found that the interaction of RXRα with NKX2-5 mutations found in congenital heart disease (Q187H, R189G and R190H) was altered. These findings highlight an intuitive approach to accessing protein–protein interaction information of transcription factors in DNA-binding experiments.

An Always Correlated gene expression landscape for ovine skeletal muscle, lessons learnt from comparison with an "equivalent" bovine landscape

BackgroundWe have recently described a method for the construction of an informative gene expression correlation landscape for a single tissue, longissimus muscle (LM) of cattle, using a small number (less than a hundred) of diverse samples. Does this approach facilitate interspecies comparison of networks?FindingsUsing gene expression datasets from LM samples from a single postnatal time point for high and low muscling sheep, and from a developmental time course (prenatal to postnatal) for normal sheep and sheep exhibiting the Callipyge muscling phenotype gene expression correlations were calculated across subsets of the data comparable to the bovine analysis. An “Always Correlated” gene expression landscape was constructed by integrating the correlations from the subsets of data and was compared to the equivalent landscape for bovine LM muscle. Whilst at the high level apparently equivalent modules were identified in the two species, at the detailed level overlap between genes in the equivalent modules was limited and generally not significant. Indeed, only 395 genes and 18 edges were in common between the two landscapes.ConclusionsSince it is unlikely that the equivalent muscles of two closely related species are as different as this analysis suggests, within tissue gene expression correlations appear to be very sensitive to the samples chosen for their construction, compounded by the different platforms used. Thus users need to be very cautious in interpretation of the differences. In future experiments, attention will be required to ensure equivalent experimental designs and use cross-species gene expression platform to enable the identification of true differences between different species.

Analysis of steric effects in DamID profiling of transcription factor target genes.

DNA adenine methyltransferase identification (DamID) is an enzymatic technology for detecting DNA regions targeted by chromatin-associated proteins. Proteins are fused to bacterial DNA adenine methyltransferase (Dam) and expressed in cultured cells or whole organisms. Here, we used DamID to detect DNA regions bound by the cardiac-restricted transcription factors (TFs) NKX2-5 and SRF, and ubiquitously-expressed co-factors ELK1 and ELK4. We compared targets bound by these TFs as N- and C-terminal fusions with Dam, for both wild type (WT) NKX2-5 and mutant proteins mimicking those found in congenital heart disease. Overall, DamID is highly robust: while the orientation of WT Dam fusions can affect the size of the target sets, their signatures remained largely reproducible. Furthermore, a severe NKX2-5 mutant lacking the homeodomain showed strong steric effects negatively impacting target discovery. The extent of steric effect is likely to be dependent on the protein in question and the orientation of Dam fusion.

PDGFRα signaling in cardiac stem and stromal cells modulates quiescence, metabolism and self-renewal, and promotes anatomical and functional repair

The interstitial and perivascular spaces of the mammalian heart contain a highly interactive tissue community essential for cardiac homeostasis, repair and regeneration. Mesenchymal cells (fibroblasts) are one of the most abundant cell types and make up the organ superstructure. They play key roles as sentinels, tissue architects, paracrine signaling hubs and lineage precursors, and are linked to heart disease through their roles in inflammation and fibrosis. Platelet-derived growth factors (PFGFs) are secreted by several cell types involved in cardiac injury and repair. Here we explore in detail how PDGF receptor α (PDGFRα) signaling in cardiac fibroblasts affects their activation, differentiation and self-renewal. Short-term systemic delivery of PDGF-AB to mice from the time of myocardial infarction (MI) led to activation, proliferation and increased self-renewal of fibroblasts, and subsequent expansion of myofibroblasts. Underpinning this, as evidenced in uninjured mice, was a cell cycle priming effect, in which PDGF-AB induced exit of fibroblasts from quiescence without stimulating proliferation. Despite fibrogenesis, however, treated MI hearts showed enhanced anatomical and functional repair that was associated with pro-regenerative effects on endothelial cells, immune cells and cardiomyocytes. Our study provides a rationale for a novel therapeutic approach to cardiac injury involving stimulating fibroblast activation and endogenous repair mechanisms.