Identification of biochemical adaptations in hyper- or hypocontractile hearts from phospholamban mutant mice by expression proteomics

Global phosphoproteomic profiling reveals perturbed signaling in a mouse model of dilated cardiomyopathy

Phospholamban (PLN) plays a central role in Ca²⁺ homeostasis in cardiac myocytes through regulation of the sarco(endo)plasmic reticulum Ca²⁺-ATPase 2A (SERCA2A) Ca²⁺ pump. An inherited mutation converting arginine residue 9 in PLN to cysteine (R9C) results in dilated cardiomyopathy (DCM) in humans and transgenic mice, but the downstream signaling defects leading to decompensation and heart failure are poorly understood. Here we used precision mass spectrometry to study the global phosphorylation dynamics of 1,887 cardiac phosphoproteins in early affected heart tissue in a transgenic R9C mouse model of DCM compared with wild-type littermates. Dysregulated phosphorylation sites were quantified after affinity capture and identification of 3,908 phosphopeptides from fractionated whole-heart homogenates. Global statistical enrichment analysis of the differential phosphoprotein patterns revealed selective perturbation of signaling pathways regulating cardiovascular activity in early stages of DCM. Strikingly, dysregulated signaling through the Notch-1 receptor, recently linked to cardiomyogenesis and embryonic cardiac stem cell development and differentiation but never directly implicated in DCM before, was a prominently perturbed pathway. We verified alterations in Notch-1 downstream components in early symptomatic R9C transgenic mouse cardiomyocytes compared with wild type by immunoblot analysis and confocal immunofluorescence microscopy. These data reveal unexpected connections between stress-regulated cell signaling networks, specific protein kinases, and downstream effectors essential for proper cardiac function.

Divide and conquer: the application of organelle proteomics to heart failure

Chronic heart failure is a worldwide cause of mortality and morbidity and is the final outcome of a number of different etiologies. This reflects both the complexity of the disease and our incomplete understanding of its underlying molecular mechanisms. One experimental approach to address this is to study subcellular organelles and how their functions are activated and synchronized under physiological and pathological conditions. In this review, we discuss the application of proteomic technologies to organelles and how this has deepened our perception of the cellular proteome and its alterations with heart failure. The use of proteomics to monitor protein quantity and posttranslational modifications has revealed a highly intricate and sophisticated level of protein regulation. Posttranslational modifications have the potential to regulate organelle function and interplay most likely by targeting both structural and signaling proteins throughout the cell, ultimately coordinating their responses. The potentials and limitations of existing proteomic technologies are also discussed emphasizing that the development of novel methods will enhance our ability to further investigate organelles and decode intracellular communication.

Proteome analysis of mouse model systems: A tool to model human disease and for the investigation of tissue-specific biology

The molecular dissections of the mechanistic pathways involved in human disease have always relied on the use of model organisms. Among the higher mammalian organisms, the laboratory mouse (Mus musculus) is the most widely used model. A large number of commercially-available, inbred strains are available to the community, including an ever growing collection of transgenic, knock-out, and disease models. Coupled to availability is the fact that animal colonies can be kept under standardized housing condition at most major universities and research institutes, with relative ease and cost efficiency (compared to larger vertebrates). As such, mouse models to study human biology and disease remains extremely attractive. In the current review we will provide an historic overview of the use of mouse models in proteome research with a focus on general tissue and organelle biology, comparative proteomics of human and mouse and the use of mouse models to study cardiac disease.

Generation and analysis of multidimensional protein identification technology datasets

Systems that couple two dimensional liquid chromatography (LC/LC) with tandem mass spectrometry are widely used in modern proteomics. One such system, multidimensional protein identification technology (MudPIT), couples strong cation exchange chromatography and reversed phase chromatography to tandem mass spectrometry in a single microcapillary column. Using database searching algorithms like SEQUEST and additional computational tools, researchers are able to analyze in great detail complex peptide mixtures generated from biofluids, tissues, cells, organelles, or protein complexes. This chapter describes the use of MudPIT on modern mass spectrometry instrumentation and describes a data analysis pipeline designed to provide low false positive rates and quantitative datasets.

Improvements to cardiovascular gene ontology

Gene Ontology (GO) provides a controlled vocabulary to describe the attributes of genes and gene products in any organism. Although one might initially wonder what relevance a ‘controlled vocabulary’ might have for cardiovascular science, such a resource is proving highly useful for researchers investigating complex cardiovascular disease phenotypes as well as those interpreting results from high-throughput methodologies. GO enables the current functional knowledge of individual genes to be used to annotate genomic or proteomic datasets. In this way, the GO data provides a very effective way of linking biological knowledge with the analysis of the large datasets of post-genomics research. Consequently, users of high-throughput methodologies such as expression arrays or proteomics will be the main beneficiaries of such annotation sets. However, as GO annotations increase in quality and quantity, groups using small-scale approaches will gradually begin to benefit too. For example, genome wide association scans for coronary heart disease are identifying novel genes, with previously unknown connections to cardiovascular processes, and the comprehensive annotation of these novel genes might provide clues to their cardiovascular link. At least 4000 genes, to date, have been implicated in cardiovascular processes and an initiative is underway to focus on annotating these genes for the benefit of the cardiovascular community. In this article we review the current uses of Gene Ontology annotation to highlight why Gene Ontology should be of interest to all those involved in cardiovascular research.

Three-layer sandwich gel electrophoresis: a method of salt removal and protein concentration in proteome analysis

Sample preparation plays a critical role in successful proteomic applications. Features of electrospray mass spectrometry impose limits on the types of buffers, detergents and other reagents that can be used in sample preparation. Unfortunately, many of these mass spectrometry incompatible reagents significantly enhance protein recoveries from complex matrices. This problem prompted our search for a better cleanup protocol. Our data suggest that the Three-layer Sandwich Gel Electrophoresis (TSGE) protocol can solve this problem and provide near quantitative recovery of extremely low concentration proteins from harsh solutions, a feature not available from other cleanup protocols. The hallmark of the TSGE protocol is the combination of the properties of agarose gels (that serve as the matrix to immobilize the proteins of interest) with low- and high-percentage polyacrylamide gels (that serve as the concentration and sealing layers, respectively). By electrophoretically driving the proteins of interest from the agarose matrix into the concentration layer, the TSGE protocol simultaneously concentrates the sample in the concentration layer and provides an environment amenable to downstream buffer exchange and proteolytic digestion. In combination with 2D-LC-MS/MS, the TSGE protocol was evaluated in the analysis of a whole cell extract from the protozoan parasite Toxoplasma gondii. Comparison of our experimental proteomic results with in silico predictions from gene data indicated that TSGE did not bias the protein identification.

Characterization of the human skeletal muscle proteome by one-dimensional gel electrophoresis and HPLC-ESI-MS/MS

Changes in protein abundance in skeletal muscle are central to a large number of metabolic and other disorders, including, and perhaps most commonly, insulin resistance. Proteomics analysis of human muscle is an important approach for gaining insight into the biochemical basis for normal and pathophysiological conditions. However, to date, the number of proteins identified by this approach has been limited, with 107 different proteins being the maximum reported so far. Using a combination of one-dimensional gel electrophoresis and high performance liquid chromatography electrospray ionization tandem mass spectrometry, we identified 954 different proteins in human vastus lateralis muscle obtained from three healthy, nonobese subjects. In addition to a large number of isoforms of contractile proteins, we detected all proteins involved in the major pathways of glucose and lipid metabolism in skeletal muscle. Mitochondrial proteins accounted for 22% of all proteins identified, including 55 subunits of the respiratory complexes I-V. Moreover, a number of enzymes involved in endocrine and metabolic signaling pathways as well as calcium homeostasis were identified. These results provide the most comprehensive characterization of the human skeletal muscle proteome to date. These data hold promise for future global assessment of quantitative changes in the muscle proteome of patients affected by disorders involving skeletal muscle.

Comparative proteomics profiling of a phospholamban mutant mouse model of dilated cardiomyopathy reveals progressive intracellular stress responses

Defective mobilization of Ca2+ by cardiomyocytes can lead to cardiac insufficiency, but the causative mechanisms leading to congestive heart failure (HF) remain unclear. In the present study we performed exhaustive global proteomics surveys of cardiac ventricle isolated from a mouse model of cardiomyopathy overexpressing a phospholamban mutant, R9C (PLN-R9C), and exhibiting impaired Ca2+ handling and death at 24 weeks and compared them with normal control littermates. The relative expression patterns of 6190 high confidence proteins were monitored by shotgun tandem mass spectrometry at 8, 16, and 24 weeks of disease progression. Significant differential abundance of 593 proteins was detected. These proteins mapped to select biological pathways such as endoplasmic reticulum stress response, cytoskeletal remodeling, and apoptosis and included known biomarkers of HF (e.g. brain natriuretic peptide/atrial natriuretic factor and angiotensin-converting enzyme) and other indicators of presymptomatic functional impairment. These altered proteomic profiles were concordant with cognate mRNA patterns recorded in parallel using high density mRNA microarrays, and top candidates were validated by RT-PCR and Western blotting. Mapping of our highest ranked proteins against a human diseased explant and to available data sets indicated that many of these proteins could serve as markers of disease. Indeed we showed that several of these proteins are detectable in mouse and human plasma and display differential abundance in the plasma of diseased mice and affected patients. These results offer a systems-wide perspective of the dynamic maladaptions associated with impaired Ca2+ homeostasis that perturb myocyte function and ultimately converge to cause HF.

Lost in translation: five grand challenges for proteomic biomarker discovery

The biomedical community has the imperative to develop reliable, clinically relevant and generalizable bioassays that can be used to accurately recognize those individuals with early-stage disease or those patients who will respond to therapy, with the ultimate aim of achieving individualized medicine. In recent years, increasingly sophisticated proteomic screening technologies have been introduced, providing the biomedical community with a valuable new approach for the systematic discovery and validation of novel diagnostic, prognostic and therapeutic tools. Nevertheless, the complexity of the cellular milieu wherein a variety of macromolecules interact in dynamic fashion, combined with the complex clinical manifestation of chronic pathologies and widespread diversity of patient populations, mean that universal biomarkers will not be easily developed. In this review, the five key challenges that must be surmounted in order to advance the clinical impact of this nascent field are described, and plausible solutions based on the authors' own ongoing proteomic profiling of cardiovascular disease is outlined.

Analyzing the cardiac muscle proteome by liquid chromatography-mass spectrometry-based expression proteomics

Cardiomyopathies are diseases of the heart resulting in impaired cardiac muscle function, which can lead to heart dilation or overt heart failure. These diseases represent a major cause of global morbidity and death. Innovative preventive and therapeutic measures are urgently needed for early detection, categorization, and treatment of patients at risk of cardiomyopathy. These developments will require a more complete understanding of the molecular effects of impaired cardiac function, even prior to overt disease. The use of gel-free expression proteomics in the detailed analysis of cardiac tissues should yield significant insight into the pathophysiology of these diseases.

Multidimensional protein identification technology: current status and future prospects

Protein profiling using high-throughput tandem mass spectrometry has become a powerful method for analyzing changes in global protein expression patterns in cells and tissues as a function of developmental, physiologic and disease processes. This review summarizes the utility and practical application of multidimensional protein identification technology as a platform for comprehensive proteomic profiling of complex biologic samples. The strengths and potential problems and limitations associated with this powerful technology are discussed, with an emphasis placed on one of the biggest challenges currently facing large-scale expression profiling projects -- namely, data analysis. Complementary bioinformatic computational data mining strategies, such as clustering, functional annotation and statistical inference, are also discussed as these are increasingly necessary for interpreting the results of global proteomic profiling studies.

Calumenin, a multiple EF-hands Ca2+-binding protein, interacts with ryanodine receptor-1 in rabbit skeletal sarcoplasmic reticulum

Calumenin is a multiple EF-hand Ca2+-binding protein located in endo/sarcoplasmic reticulum of mammalian tissues. In the present study, we cloned two rabbit calumenin isoforms (rabbit calumenin-1 and -2, GenBank Accession Nos. SY225335 and AY225336, respectively) by RT-PCR. Both isoforms contain a 19 aa N-terminal signal sequence, 6 EF-hand domains, and a C-terminal ER/SR retrieval signal, HDEF. Both calumenin isoforms exist in rabbit cardiac and skeletal muscles, but calumenin-2 is the main isoform in skeletal muscle. Presence of calumenin in rabbit sarcoplasmic reticulum (SR) was identified by Western blot analysis. GST-pull down and co-immunoprecipitation experiments showed that ryanodine receptor 1 (RyR1) interacted with calumenin-2 in millimolar Ca2+ concentration range. Experiments of gradual EF-hand deletions suggest that the second EF-hand domain is essential for calumenin binding to RyR1. Adenovirus-mediated overexpression of calumenin-2 in C2C12 myotubes led to increased caffeine-induced Ca2+ release, but decreased depolarization-induced Ca2+ release. Taken together, we propose that calumenin-2 in the SR lumen can directly regulate the RyR1 activity in Ca2+-dependent manner.

Multidimensional protein identification technology (MudPIT): technical overview of a profiling method optimized for the comprehensive proteomic investigation of normal and diseased heart tissue

An optimized analytical expression profiling strategy based on gel-free multidimensional protein identification technology (MudPIT) is reported for the systematic investigation of biochemical (mal)-adaptations associated with healthy and diseased heart tissue. Enhanced shotgun proteomic detection coverage and improved biological inference is achieved by pre-fractionation of excised mouse cardiac muscle into subcellular components, with each organellar fraction investigated exhaustively using multiple repeat MudPIT analyses. Functional-enrichment, high-confidence identification, and relative quantification of hundreds of organelle- and tissue-specific proteins are achieved readily, including detection of low abundance transcriptional regulators, signaling factors, and proteins linked to cardiac disease. Important technical issues relating to data validation, including minimization of artifacts stemming from biased under-sampling and spurious false discovery, together with suggestions for further fine-tuning of sample preparation, are discussed. A framework for follow-up bioinformatic examination, pattern recognition, and data mining is also presented in the context of a stringent application of MudPIT for probing fundamental aspects of heart muscle physiology as well as the discovery of perturbations associated with heart failure.

The continuing evolution of shotgun proteomics

Shotgun proteomics has emerged as a powerful approach for the analysis of complex protein mixtures, including biofluids, tissues, cells, organelles or protein complexes. Having evolved from the integration of chromatography and mass spectrometry, innovations in sample preparation, multidimensional chromatography, mass spectrometry and proteomic informatics continually facilitate, enable and challenge shotgun proteomics. As a result, shotgun proteomics continues to evolve and enable new areas of biological research, and is beginning to impact human disease diagnosis and therapeutic intervention.

Integrating global proteomic and genomic expression profiles generated from islet alpha cells: opportunities and challenges to deriving reliable biological inferences

Systematic profiling of expressed gene products represents a promising research strategy for elucidating the molecular phenotypes of islet cells. To this end, we have combined complementary genomic and proteomic methods to better assess the molecular composition of murine pancreatic islet glucagon-producing alphaTC-1 cells as a model system, with the expectation of bypassing limitations inherent to either technology alone. Gene expression was measured with an Affymetrix MG_U74Av2 oligonucleotide array, while protein expression was examined by performing high-resolution gel-free shotgun MS/MS on a nuclear-enriched cell extract. Both analyses were carried out in triplicate to control for experimental variability. Using a stringent detection p value cutoff of 0.04, 48% of all potential mRNA transcripts were predicted to be expressed (probes classified as present in at least two of three replicates), while 1,651 proteins were identified with high-confidence using rigorous database searching. Although 762 of 888 cross-referenced cognate mRNA-protein pairs were jointly detected by both platforms, a sizeable number (126) of gene products was detected exclusively by MS alone. Conversely, marginal protein identifications often had convincing microarray support. Based on these findings, we present an operational framework for both interpreting and integrating dual genomic and proteomic datasets so as to obtain a more reliable perspective into islet alpha cell function.

Sarcolipin retention in the endoplasmic reticulum depends on its C-terminal RSYQY sequence and its interaction with sarco(endo)plasmic Ca(2+)-ATPases

Sarcolipin (SLN) and phospholamban (PLN) are effective inhibitors of the sarco(endo)plasmic reticulum Ca(2+)-ATPase (SERCA). These homologous proteins differ at their N and C termini: the C-terminal Met-Leu-Leu in PLN is replaced by Arg-Ser-Tyr-Gln-Tyr in SLN. The role of the C-terminal sequence of SLN tagged N-terminally with the FLAG epitope (NF-SLN) in endoplasmic reticulum (ER) retention was investigated by transfecting human embryonic kidney-293 cells with cDNAs encoding NF-SLN or a series of NF-SLN mutants in which C-terminal amino acids were deleted progressively. Immunofluorescence and immunoblotting of transfected cells by using anti-FLAG antibodies indicated that NF-SLN and PLN tagged at its N terminus with the FLAG epitope, even when overexpressed, were restricted to the ER. However, C-terminal truncation deletions of SLN, which lacked RSYQY, were not localized to ER and did not inhibit Ca(2+)-dependent Ca2+ uptake by SERCA. The shortest deletion constructs, NF-SLN 1-22 and NF-SLN 1-23, did not express stable protein products. However, all NF-SLN cDNA constructs, including NF-SLN 1-22 and NF-SLN 1-23, were expressed stably and localized to the ER when they were coexpressed with SERCA2a. These results show that NF-SLN subcellular distribution depends on SERCA coexpression and on its luminal, C-terminal RSYQY sequence. By using immunoprecipitation and MS, glucose-regulated protein 78/BiP and glucose-regulated protein 94 were identified as proteins that interact with NF-SLN through the RSYQY sequence. Thus, in the absence of SERCA, retention of NF-SLN in the ER is mediated through its association with other components through the C-terminal RSYQY sequence.

Cardiac-specific overexpression of sarcolipin inhibits sarco(endo)plasmic reticulum Ca2+ ATPase (SERCA2a) activity and impairs cardiac function in mice

Sarcolipin (SLN) inhibits the cardiac sarco(endo)plasmic reticulum Ca(2+) ATPase (SERCA2a) by direct binding and is superinhibitory if it binds through phospholamban (PLN). To determine whether overexpression of SLN in the heart might impair cardiac function, transgenic (TG) mice were generated with cardiac-specific overexpression of NF-SLN (SLN tagged at its N terminus with the FLAG epitope). The level of NF-SLN expression (the NF-SLN/PLN expression ratio) was equivalent to that which induces profound superinhibition when coexpressed with PLN and SERCA2a in HEK-293 cells. In TG hearts, the apparent affinity of SERCA2a for Ca(2+) was decreased compared with non-TG littermate control hearts. Invasive hemodynamic and echocardiographic analyses revealed impaired cardiac contractility and ventricular hypertrophy in TG mice. Basal PLN phosphorylation was reduced. In isolated papillary muscle subjected to isometric tension, peak amplitudes of Ca(2+) transients and peak tensions were reduced, whereas decay times of Ca(2+) transients and relaxation times of tension were increased in TG mice. Isoproterenol largely restored contractility in papillary muscle and stimulated PLN phosphorylation to wild-type levels in intact hearts. No compensatory changes in expression of SERCA2a, PLN, ryanodine receptor, and calsequestrin were observed in TG hearts. Coimmunoprecipitation indicated that overexpressed NF-SLN was bound to both SERCA2a and PLN, forming a ternary complex. These data suggest that NF-SLN overexpression inhibits SERCA2a through stabilization of SERCA2a-PLN interaction in the absence of PLN phosphorylation and through the inhibition of PLN phosphorylation. Inhibition of SERCA2a impairs contractility and calcium cycling, but responsiveness to beta-adrenergic agonists may prevent progression to heart failure.