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1.  Coxsackie and adenovirus receptor (CAR) is a modifier of cardiac conduction and arrhythmia vulnerability in the setting of myocardial ischemia 
To investigate the modulatory effect of the Coxsackie and adenovirus receptor (CAR) on ventricular conduction and arrhythmia vulnerability in the setting of myocardial ischemia.
A heritable component in risk for ventricular fibrillation (VF) during myocardial infarction (MI) has been well established. A recent genome-wide association study (GWAS) for VF during acute MI has led to the identification of a locus on chromosome 21q21 (rs2824292) in the vicinity of the CXADR gene. CXADR encodes the coxsackie and adenovirus receptor (CAR), a cell adhesion molecule predominantly located at intercalated discs of the cardiomyocyte.
The correlation between CAR transcript levels and rs2824292 genotype was investigated in human left ventricular samples. Electrophysiological studies and molecular analyses were performed CAR haploinsufficient mice (CAR+/−).
In human left ventricular samples, the risk allele at the chr21q21 GWAS locus was associated with lower CXADR mRNA levels, suggesting that decreased cardiac levels of CAR predispose to ischemia-induced VF. Hearts from CAR+/− mice displayed ventricular conduction slowing in addition to an earlier onset of ventricular arrhythmias during the early phase of acute myocardial ischemia following LAD ligation. Connexin43 expression and distribution was unaffected, but CAR+/− hearts displayed increased arrhythmia susceptibility upon pharmacological electrical uncoupling. Patch-clamp analysis of isolated CAR+/− myocytes showed reduced sodium current magnitude specifically at the intercalated disc. Moreover, CAR co-precipitated with NaV1.5 in vitro, suggesting that CAR affects sodium channel function through a physical interaction with NaV1.5.
We identify CAR as a novel modifier of ventricular conduction and arrhythmia vulnerability in the setting of myocardial ischemia. Genetic determinants of arrhythmia susceptibility (such as CAR) may constitute future targets for risk stratification of potentially lethal ventricular arrhythmias in patients with coronary artery disease
PMCID: PMC3926969  PMID: 24291282
arrhythmia; ventricular fibrillation; ischemia; single nucleotide polymorphism genetics; ion channels
2.  Adaptations of cytoarchitecture in human dilated cardiomyopathy 
Biophysical Reviews  2014;7:25-32.
Hypertrophic cardiomyopathy is characterised by a histological phenotype of myocyte disarray, but heart tissue samples from patients with dilated cardiomyopathy (DCM) often look comparatively similar to those from healthy individuals apart from conspicuous regions of fibrosis and necrosis. We have previously investigated subcellular alterations in the cytoarchitecture of mouse models of dilated cardiomyopathy and found that both the organisation and composition of the intercalated disc, i.e. the specialised type of cell–cell contact in the heart, is altered. There is also is a change in the composition of the M-band of the sarcomere due to an expression shift towards the more extensible embryonic heart (EH)-myomesin isoform. Analysis of human samples from the Sydney Human Heart Tissue Bank have revealed similar structural findings and also provided evidence for a dramatic change in overall cardiomyocyte size control, which has also been seen in the mouse. Together these changes in cytoarchitecture probably contribute to the decreased functional output that is seen in DCM.
PMCID: PMC4322184
Cytoskeleton; Intercalated disc; Dilated cardiomyopathy; Formin; M-band
3.  Nuclear pore rearrangements and nuclear trafficking in cardiomyocytes from rat and human failing hearts 
Cardiovascular Research  2014;105(1):31-43.
During cardiac hypertrophy, cardiomyocytes (CMs) increase in the size and expression of cytoskeletal proteins while reactivating a foetal gene programme. The process is proposed to be dependent on increased nuclear export and, since nuclear pore trafficking has limited capacity, a linked decrease in import. Our objective was to investigate the role of nuclear import and export in control of hypertrophy in rat and human heart failure (HF).
Methods and results
In myocardial tissue and isolated CMs from patients with dilated cardiomyopathy, nuclear size was increased; Nucleoporin p62, cytoplasmic RanBP1, and nuclear translocation of importins (α and β) were decreased while Exportin-1 was increased. CM from a rat HF model 16 weeks after myocardial infarction (MI) reproduced these nuclear changes. Nuclear import, determined by the rate of uptake of nuclear localization sequence (NLS)-tagged fluorescent substrate, was also decreased and this change was observed from 4 weeks after MI, before HF has developed. Treatment of isolated rat CMs with phenylephrine (PE) for 48 h produced similar cell and nuclear size increases, nuclear import and export protein rearrangement, and NLS substrate uptake decrease through p38 MAPK and HDAC-dependent pathways. The change in NLS substrate uptake occurred within 15 min of PE exposure. Inhibition of nuclear export with leptomycin B reversed established nuclear changes in PE-treated rat CMs and decreased NLS substrate uptake and cell/nuclear size in human CMs.
Nuclear transport changes related to increased export and decreased import are an early event in hypertrophic development. Hypertrophy can be prevented, or even reversed, by targeting import/export, which may open new therapeutic opportunities.
PMCID: PMC4277256  PMID: 25341891
Myocytes; Hypertrophy; Myocardial infarction; Signal transduction; Nuclear transport
4.  GSK3β Phosphorylates Newly Identified Site in the Pro-Ala Rich Region of Cardiac Myosin Binding Protein C and Alters Cross-Bridge Cycling Kinetics in Human 
Circulation research  2012;112(4):633-639.
Cardiac myosin binding protein C (cMyBP-C) regulates cross-bridge cycling kinetics and thereby fine-tunes the rate of cardiac muscle contraction and relaxation. Its effects on cardiac kinetics are modified by phosphorylation. Three phosphorylation sites (Ser275, Ser284, Ser304) have been identified in vivo, all located in the cardiac-specific M-domain of cMyBP-C. However recent work has shown that up to four phosphate groups are present in human cMyBP-C.
To identify and characterize additional phosphorylation sites in human cMyBP-C.
Methods and results
Cardiac MyBP-C was semi-purified from human heart tissue. Tandem mass-spectrometry analysis identified a novel phosphorylation site on serine 133 in the proline-alanine (Pro-Ala) rich linker sequence between the C0 and C1 domains of cMyBP-C. Unlike the known sites, Ser133 was not a target of protein kinase A. In silico kinase prediction revealed glycogen synthase kinase 3β (GSK3β) as the most likely kinase to phosphorylate Ser133. In vitro incubation of the C0C2 fragment of cMyBP-C with GSK3β showed phosphorylation on Ser133. In addition, GSK3β phosphorylated Ser304, although the degree of phosphorylation was less compared to PKA-induced phosphorylation at Ser304. GSK3β treatment of single membrane-permeabilized human cardiomyocytes significantly enhanced the maximal rate of tension redevelopment.
GSK3β phosphorylates cMyBP-C on a novel site, which is positioned in the Pro-Ala rich region and increases kinetics of force development, suggesting a non-canonical role for GSK3β at the sarcomere level. Phosphorylation of Ser133 in the linker domain of cMyBP-C may be a novel mechanism to regulate sarcomere kinetics.
PMCID: PMC3595322  PMID: 23277198
Cardiac myosin binding protein-C; phosphorylation; GSK3β; heart failure; contractile proteins; hypertrophy/remodeling; myocardial contractility
5.  Metabolic Gene Remodeling and Mitochondrial Dysfunction in Failing Right Ventricular Hypertrophy due to Pulmonary Arterial Hypertension 
Circulation. Heart failure  2012;6(1):136-144.
Right ventricular dysfunction (RVD) is the most frequent cause of death in patients with pulmonary arterial hypertension. Whereas abnormal energy substrate utilization has been implicated in the development of chronic left heart failure, data describing such metabolic remodeling in RVD remain incomplete. Thus, we sought to characterize metabolic gene expression changes and mitochondrial dysfunction in functional and dysfunctional RV hypertrophy.
Methods and Results
Two different rat models of RV hypertrophy were studied. The model of RVD (SU5416/hypoxia) exhibited a significantly decreased gene expression of PPAR-gamma coactivator-1 alpha (PGC-1α), PPAR-α and ERR-α. The expression of multiple PCG-1α target genes required for fatty acid oxidation (FAO) was similarly decreased. Decreased PGC-1α expression was also associated with a net loss of mitochondrial protein and oxidative capacity. Reduced mitochondrial number was associated with a downregulation of TFAM and other genes required for mitochondrial biogenesis. Electron microscopy demonstrated that in RVD tissue, mitochondria had abnormal shape and size. Lastly, respirometric analysis demonstrated that mitochondria isolated from RVD-tissue had a significantly reduced ADP-stimulated (state 3) rate for complex I. Conversely, functional RV hypertrophy in the pulmonary artery banding (PAB) model showed normal expression of PGC-1α, whereas the expression of FAO genes was either preserved or unregulated. Moreover, PAB-RV tissue exhibited preserved TFAM expression and mitochondrial respiration despite elevated RV pressure-overload.
Right ventricular dysfunction, but not functional RV hypertrophy in rats, demonstrates a gene expression profile compatible with a multilevel impairment of fatty acid metabolism and significant mitochondrial dysfunction, partially independent of chronic pressure-overload.
PMCID: PMC3790960  PMID: 23152488
pulmonary heart disease; metabolism; pressure; fatty acids; mitochondria
6.  Multiple Reaction Monitoring to Identify Site-Specific Troponin I Phosphorylated Residues in the Failing Human Heart 
Circulation  2012;126(15):1828-1837.
Human cardiac troponin I is known to be phosphorylated at multiple amino acid residues by several kinases. Advances in mass spectrometry allow sensitive detection of known and novel phosphorylation sites and measurement of the level of phosphorylation simultaneously at each site in myocardial samples.
Methods and Results
On the basis of in silico prediction and liquid chromatography/mass spectrometry data, 14 phosphorylation sites on cardiac troponin I, including 6 novel residues (S4, S5, Y25, T50, T180, S198), were assessed in explanted hearts from end-stage heart failure transplantation patients with ischemic heart disease or idiopathic dilated cardiomyopathy and compared with samples obtained from nonfailing donor hearts (n=10 per group). Thirty mass spectrometry–based multiple reaction monitoring quantitative tryptic peptide assays were developed for each phosphorylatable and corresponding nonphosphorylated site. The results show that in heart failure there is a decrease in the extent of phosphorylation of the known protein kinase A sites (S22, S23) and other newly discovered phosphorylation sites located in the N-terminal extension of cardiac troponin I (S4, S5, Y25), an increase in phosphorylation of the protein kinase C sites (S41, S43, T142), and an increase in phosphorylation of the IT-arm domain residues (S76, T77) and C-terminal domain novel phosphorylation sites of cardiac troponin I (S165, T180, S198). In a canine dyssynchronous heart failure model, enhanced phosphorylation at 3 novel sites was found to decline toward control after resynchronization therapy.
Selective, functionally significant phosphorylation alterations occurred on individual residues of cardiac troponin I in heart failure, likely reflecting an imbalance in kinase/phosphatase activity. Such changes can be reversed by cardiac resynchronization.
PMCID: PMC3733556  PMID: 22972900
heart failure; mass spectrometry; phosphorylation; troponin
7.  Computational opportunities for remote collaboration and capacity building afforded by Web 2.0 and cloud computing 
Biophysical reviews  2012;4(3):153-160.
In this paper, we state our aims and aspirations for building a global network of likeminded people interested in developing and encouraging students in the field of computational biophysics (CB). Global capacity building efforts have uncovered local computational talent in virtually every community regardless of where the students reside. Our vision is to discover and encourage these aspiring investigators by suggesting ways that they and other “garage scientists” can participate in new science even if they have no access to sophisticated research infrastructure. We argue that participatory computing in the “cloud” is particularly suitable for CB and available to any budding computational biophysicist if he or she is provided with open-minded mentors who have the necessary skills and generosity. We recognize that there are barriers to the development of such remote collaborations, and we discuss possible pathways to overcome these barriers. We point out that this Special Issue of Biophysical Reviews provides a much-needed forum for the development of several specific applications of CB.
PMCID: PMC3467109  PMID: 23066431
Computational biophysics; White paper; Cloud computing; Capacity building; Garage science; Global network
8.  Current Status of Biomarkers for Prostate Cancer 
Prostate cancer (PCa) is a leading cause of cancer-related death of men globally. Since its introduction, there has been intense debate as to the effectiveness of the prostate specific antigen (PSA) test as a screening tool for PCa. It is now evident that the PSA test produces unacceptably high rates of false positive results and is not prognostic. Here we review the current status of molecular biomarkers that promise to be prognostic and that might inform individual patient management. It highlights current efforts to identify biomarkers obtained by minimally invasive methods and discusses current knowledge with regard to gene fusions, mRNA and microRNAs, immunology, and cancer-associated microparticles.
PMCID: PMC3709717  PMID: 23708103
PSA; genomics; antibody microarrays; diagnostic biomarkers; genomics; prostate cancer; proteomics
9.  An Antibody-Based Leukocyte-Capture Microarray for the Diagnosis of Systemic Lupus Erythematosus 
PLoS ONE  2013;8(3):e58199.
The diagnosis of Systemic Lupus Erythematosus (SLE) is challenging due to its heterogeneous clinical presentation and the lack of robust biomarkers to distinguish it from other autoimmune diseases. Further, currently used laboratory tests do not readily distinguish active and inactive disease. Several groups have attempted to apply emerging high throughput profiling technologies to diagnose and monitor SLE. Despite showing promise, many are expensive and technically challenging for routine clinical use. The goal of this work is to develop a better diagnostic and monitoring tool for SLE. We report a highly customisable antibody microarray that consists of a duplicate arrangement of 82 antibodies directed against surface antigens on peripheral blood mononuclear cells (PMBCs). This high-throughput array was used to profile SLE patients (n = 60) with varying disease activity, compared to healthy controls (n = 24), patients with rheumatoid arthritis (n = 25), and other autoimmune diseases (n = 28). We used a computational algorithm to calculate a score from the entire microarray profile and correlated it with SLE disease activity. Our results demonstrate that leukocyte-capture microarray profiles can readily distinguish active SLE patients from healthy controls (AUROC = 0.84). When combined with the standard laboratory tests (serum anti-dsDNA, complements C3 and C4), the microarrays provide significantly increased discrimination. The antibody microarrays can be enhanced by the addition of other markers for potential application to the diagnosis and stratification of SLE, paving the way for the customised and accurate diagnosis and monitoring of SLE.
PMCID: PMC3596412  PMID: 23516448
10.  Normal passive viscoelasticity but abnormal myofibrillar force generation in human hypertrophic cardiomyopathy 
Hypertrophic cardiomyopathy (HCM) is characterized by left ventricular hypertrophy, increased ventricular stiffness and impaired diastolic filling. We investigated to what extent myocardial functional defects can be explained by alterations in the passive and active properties of human cardiac myofibrils. Skinned ventricular myocytes were prepared from patients with obstructive HCM (two patients with MYBPC3 mutations, one with a MYH7 mutation, and three with no mutation in either gene) and from four donors. Passive stiffness, viscous properties, and titin isoform expression were similar in HCM myocytes and donor myocytes. Maximal Ca2+-activated force was much lower in HCM myocytes (14 ± 1 kN/m2) than in donor myocytes (23 ± 3 kN/m2; P < 0.01), though cross-bridge kinetics (ktr) during maximal Ca2+ activation were 10% faster in HCM myocytes. Myofibrillar Ca2+ sensitivity in HCM myocytes (pCa50 = 6.40 ± 0.05) was higher than for donor myocytes (pCa50 = 6.09 ± 0.02; P < 0.001) and was associated with reduced phosphorylation of troponin-I (ser-23/24) and MyBP-C (ser-282) in HCM myocytes. These characteristics were common to all six HCM patients and may therefore represent a secondary consequence of the known and unknown underlying genetic variants. Some HCM patients did however exhibit an altered relationship between force and cross-bridge kinetics at submaximal Ca2+ concentrations, which may reflect the primary mutation. We conclude that the passive viscoelastic properties of the myocytes are unlikely to account for the increased stiffness of the HCM ventricle. However, the low maximum Ca2+-activated force and high Ca2+ sensitivity of the myofilaments are likely to contribute substantially to any systolic and diastolic dysfunction, respectively, in hearts of HCM patients.
Research Highlights
► The passive stiffness of skinned HCM cardiac myocytes was similar to that of normal (donor) myocytes. ► Maximum Ca-activated force production was reduced by 40% in HCM vs donor myocytes. ► This loss of force could contribute to systolic dysfunction in HCM hearts. ► Myofibrillar Ca sensitivity was higher in HCM than in donor myocytes. ► The enhanced Ca sensitivity could compensate for the smaller maximum force but would tend to cause diastolic dysfunction. ► These characteristics were common to all HCM patients studied, suggesting the changes were secondary consequence of the underlying genetic variants.
PMCID: PMC2954357  PMID: 20615414
Hypertrophic cardiomyopathy; Skinned cardiac myocytes; Viscoelasticity; Ca2+ sensitivity; Cross-bridge kinetics
11.  A model selection approach to discover age-dependent gene expression patterns using quantile regression models 
BMC Genomics  2009;10(Suppl 3):S16.
It has been a long-standing biological challenge to understand the molecular regulatory mechanisms behind mammalian ageing. Harnessing the availability of many ageing microarray datasets, a number of studies have shown that it is possible to identify genes that have age-dependent differential expression (DE) or differential variability (DV) patterns. The majority of the studies identify "interesting" genes using a linear regression approach, which is known to perform poorly in the presence of outliers or if the underlying age-dependent pattern is non-linear. Clearly a more robust and flexible approach is needed to identify genes with various age-dependent gene expression patterns.
Here we present a novel model selection approach to discover genes with linear or non-linear age-dependent gene expression patterns from microarray data. To identify DE genes, our method fits three quantile regression models (constant, linear and piecewise linear models) to the expression profile of each gene, and selects the least complex model that best fits the available data. Similarly, DV genes are identified by fitting and comparing two quantile regression models (non-DV and the DV models) to the expression profile of each gene. We show that our approach is much more robust than the standard linear regression approach in discovering age-dependent patterns. We also applied our approach to analyze two human brain ageing datasets and found many biologically interesting gene expression patterns, including some very interesting DV patterns, that have been overlooked in the original studies. Furthermore, we propose that our model selection approach can be extended to discover DE and DV genes from microarray datasets with discrete class labels, by considering different quantile regression models.
In this paper, we present a novel application of quantile regression models to identify genes that have interesting linear or non-linear age-dependent expression patterns. One important contribution of this paper is to introduce a model selection approach to DE and DV gene identification, which is most commonly tackled by null hypothesis testing approaches. We show that our approach is robust in analyzing real and simulated datasets. We believe that our approach is applicable in many ageing or time-series data analysis tasks.
PMCID: PMC2788368  PMID: 19958479
12.  Differential variability analysis of gene expression and its application to human diseases 
Bioinformatics  2008;24(13):i390-i398.
Motivation: Current microarray analyses focus on identifying sets of genes that are differentially expressed (DE) or differentially coexpressed (DC) in different biological states (e.g. diseased versus non-diseased). We observed that in many human diseases, some genes have a significantincrease or decrease in expression variability (variance). Asthese observed changes in expression variability may be caused by alteration of the underlying expression dynamics, such differential variability (DV) patterns are also biologically interesting.
Results: Here we propose a novel analysis for changes in gene expression variability between groups of amples, which we call differential variability analysis. We introduce the concept of differential variability (DV), and present a simple procedure for identifying DV genes from microarray data. Our procedure is evaluated with simulated and real microarray datasets. The effect of data preprocessing methods on identification of DV gene is investigated. The biological significance of DV analysis is demonstrated with four human disease datasets. The relationships among DV, DE and DC genes are investigated. The results suggest that changes in expression variability are associated with changes in coexpression pattern, which imply that DV is not merely stochastic noise, but informative signal.
Availability: The R source code for differential variability analysis is available from the contact authors upon request.
PMCID: PMC2718620  PMID: 18586739

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