Unravelling the proteome of degenerative human mitral valves

Inter-donor variability of extracellular matrix production in long-term cultures of human fibroblasts

Several tissue engineering approaches are based on the ability of mesenchymal cells to endogenously synthesize an extracellular matrix (ECM) in vitro, which can be seen as a form of biomaterial. Accordingly, the inter-donor variability of cell-assembled extracellular matrix (CAM) production is a key parameter to understand in order to progress towards clinical applications, especially for autologous strategies. In this study, CAMs were produced, under good manufacturing process conditions, from skin fibroblasts of 21 patients as part of a clinical trial to evaluate a tissue-engineered vascular graft. The inter-donor variability of CAM strength, thickness, hydroxyproline, and glycosaminoglycan was substantial (coefficient of variability of 33%, 19%, 24%, and 19%, respectively), but a significant correlation was observed between all four properties (Pearson r: 0.43 to 0.70; p-value ≤ 0.05). A CAM matrisome analysis, performed by mass spectrometry, revealed the presence of 70 ECM-related proteins. Our study shows that the relative abundance of 16 proteins (15 non-collagenous) correlated with CAM thickness. These proteins also correlated with CAM hydroxyproline content, as well as 21 other proteins that included fibrillar collagens and non-collagenous proteins. However, data demonstrated that only the relative abundance of type I collagen subunit alpha-1 was correlated to CAM strength. This study is the most extensive evaluation of CAM inter-donor variability to date and will help tissue engineers working with this type of biomaterial to design strategies that take into account this variability, especially for autologous tissue manufacturing.

Several tissue engineering approaches are based on the ability of mesenchymal cells to endogenously synthesize an extracellular matrix (ECM) in vitro, which can be seen as a form of biomaterial.

A modified density gradient proteomic-based method to analyze endolysosomal proteins in cardiac tissue

The importance of lysosomes in cardiac physiology and pathology is well established, and evidence for roles in calcium signaling is emerging. We describe a label-free proteomics method suitable for small cardiac tissue biopsies based on density-separated fractionation, which allows study of endolysosomal (EL) proteins. Density gradient fractions corresponding to tissue lysate; sarcoplasmic reticulum (SR), mitochondria (Mito) (1.3 g/mL); and EL with negligible contamination from SR or Mito (1.04 g/mL) were analyzed using Western blot, enzyme activity assay, and liquid chromatography with tandem mass spectrometry (LC-MS/MS) analysis (adapted discontinuous Percoll and sucrose differential density gradient). Kyoto Encyclopedia of Genes and Genomes, Reactome, Panther, and Gene Ontology pathway analysis showed good coverage of RAB proteins and lysosomal cathepsins (including cardiac-specific cathepsin D) in the purified EL fraction. Significant EL proteins recovered included catalytic activity proteins. We thus present a comprehensive protocol and data set of guinea pig atrial EL organelle proteomics using techniques also applicable for non-cardiac tissue.

Merging microarray studies to identify a common gene expression signature to several structural heart diseases

BACKGROUND

Heart disease is the leading cause of death worldwide. Knowing a gene expression signature in heart disease can lead to the development of more efficient diagnosis and treatments that may prevent premature deaths. A large amount of microarray data is available in public repositories and can be used to identify differentially expressed genes. However, most of the microarray datasets are composed of a reduced number of samples and to obtain more reliable results, several datasets have to be merged, which is a challenging task. The identification of differentially expressed genes is commonly done using statistical methods. Nonetheless, these methods are based on the definition of an arbitrary threshold to select the differentially expressed genes and there is no consensus on the values that should be used.

RESULTS

Nine publicly available microarray datasets from studies of different heart diseases were merged to form a dataset composed of 689 samples and 8354 features. Subsequently, the adjusted p-value and fold change were determined and by combining a set of adjusted p-values cutoffs with a list of different fold change thresholds, 12 sets of differentially expressed genes were obtained. To select the set of differentially expressed genes that has the best accuracy in classifying samples from patients with heart diseases and samples from patients with no heart condition, the random forest algorithm was used. A set of 62 differentially expressed genes having a classification accuracy of approximately 95% was identified.

CONCLUSIONS

We identified a gene expression signature common to different cardiac diseases and supported our findings by showing their involvement in the pathophysiology of the heart. The approach used in this study is suitable for the identification of gene expression signatures, and can be extended to different diseases.

Aperture-controllable nano-electrospray emitter and its application in cardiac proteome analysis

The emitter clogging is the most common hardware failure of nano-electrospray ionization, to improve the durability and electrospray stability of fused silica emitters, we demonstrate a means of fabricating nano-electrospray emitters with controllable aperture size and gradually-narrowed channel on the tip. We simulated the fluid morphologies in the emitter channels by computational fluid dynamics and found more stable flow on aperture-controllable nano-electrospray emitter. Besides, we found the unstable flow sections of commercial emitters match the actual clogging sections very well, indicating the main cause of emitter clogging is unstable flow. We further tested the emitters by nano-LC-MS based proteome analysis. Compared with the commercial emitter, aperture-controllable nano-electrospray emitters promoted the total ion chromatogram intensity by 25%, the number of identified proteins by 6.58%, and the number of identified peptides by 7.87%. In total, 989 proteins were identified from 1 μg of extracted mouse cardiac proteins. After the optimization by using mouse samples, we analyzed clinical auricular dextral tissues from patients undergoing cardiac surgery and found 16 proteins related to atrial fibrillation. Overall, aperture-controllable nano-electrospray emitter exhibits better sensitivity and reproducibility in the application of nano-LC-MS cardiac proteome analysis.

Conservation and divergence of protein pathways in the vertebrate heart

Heart disease is the leading cause of death in the western world. Attaining a mechanistic understanding of human heart development and homeostasis and the molecular basis of associated disease states relies on the use of animal models. Here, we present the cardiac proteomes of 4 model vertebrates with dual circulatory systems: the pig (Sus scrofa), the mouse (Mus musculus), and 2 frogs (Xenopus laevis and Xenopus tropicalis). Determination of which proteins and protein pathways are conserved and which have diverged within these species will aid in our ability to choose the appropriate models for determining protein function and to model human disease. We uncover mammalian- and amphibian-specific, as well as species-specific, enriched proteins and protein pathways. Among these, we find and validate an enrichment in cell-cycle-associated proteins within Xenopus laevis. To further investigate functional units within cardiac proteomes, we develop a computational approach to profile the abundance of protein complexes across species. Finally, we demonstrate the utility of these data sets for predicting appropriate model systems for studying given cardiac conditions by testing the role of Kielin/chordin-like protein (Kcp), a protein found as enriched in frog hearts compared to mammals. We establish that germ-line mutations in Kcp in Xenopus lead to valve defects and, ultimately, cardiac failure and death. Thus, integrating these findings with data on proteins responsible for cardiac disease should lead to the development of refined, species-specific models for protein function and disease states.

Clinical biomarker discovery by SWATH-MS based label-free quantitative proteomics: impact of criteria for identification of differentiators and data normalization method

BACKGROUND

SWATH-MS has emerged as the strategy of choice for biomarker discovery due to the proteome coverage achieved in acquisition and provision to re-interrogate the data. However, in quantitative analysis using SWATH, each sample from the comparison group is run individually in mass spectrometer and the resulting inter-run variation may influence relative quantification and identification of biomarkers. Normalization of data to diminish this variation thereby becomes an essential step in SWATH data processing. In most reported studies, data normalization methods used are those provided in instrument-based data analysis software or those used for microarray data. This study, for the first time provides an experimental evidence for selection of normalization method optimal for biomarker identification.

METHODS

The efficiency of 12 normalization methods to normalize SWATH-MS data was evaluated based on statistical criteria in 'Normalyzer'-a tool which provides comparative evaluation of normalization by different methods. Further, the suitability of normalized data for biomarker discovery was assessed by evaluating the clustering efficiency of differentiators, identified from the normalized data based on p-value, fold change and both, by hierarchical clustering in Genesis software v.1.8.1.

RESULTS

Conventional statistical criteria identified VSN-G as the optimal method for normalization of SWATH data. However, differentiators identified from VSN-G normalized data failed to segregate test and control groups. We thus assessed data normalized by eleven other methods for their ability to yield differentiators which segregate the study groups. Datasets in our study demonstrated that differentiators identified based on p-value from data normalized with Loess-R stratified the study groups optimally.

CONCLUSION

This is the first report of experimentally tested strategy for SWATH-MS data processing with an emphasis on identification of clinically relevant biomarkers. Normalization of SWATH-MS data by Loess-R method and identification of differentiators based on p-value were found to be optimal for biomarker discovery in this study. The study also demonstrates the need to base the choice of normalization method on the application of the data.

Label-Free Quantitative Phosphoproteomics Reveals Regulation of Vasodilator-Stimulated Phosphoprotein upon Stathmin-1 Silencing in a Pair of Isogenic Colorectal Cancer Cell Lines

In this communication, we present the phosphoproteome changes in an isogenic pair of colorectal cancer cell lines, viz., the poorly metastatic HCT-116 and the highly metastatic derivative E1, upon stathmin-1 (STMN1) knockdown. The aim was to better understand how the alterations of the phosphoproteins in these cells are involved in cancer metastasis. After the phosphopeptides were enriched using the TiO₂ HAMMOC approach, comparative proteomics analysis was carried out using sequential window acquisition of all theoretical mass spectra-MS. Following bioinformatics analysis using MarkerView and OneOmics platforms, we identified a list of regulated phosphoproteins that may play a potential role in signaling, maintenance of cytoskeletal structure, and focal adhesion. Among these phosphoproteins, was the actin cytoskeleton regulator protein, vasodilator-stimulated phosphoprotein (VASP), where its change in phosphorylation status was found to be concomitant with STMN1-associated roles in metastasis. We further showed that silencing of stathmin-1 altered the expression, subcellular localization and phosphorylation status of VASP, which suggested that it might be associated with remodeling of the cell cytoskeleton in colorectal cancer metastasis.

Region and cell-type resolved quantitative proteomic map of the human heart

The heart is a central human organ and its diseases are the leading cause of death worldwide, but an in-depth knowledge of the identity and quantity of its constituent proteins is still lacking. Here, we determine the healthy human heart proteome by measuring 16 anatomical regions and three major cardiac cell types by high-resolution mass spectrometry-based proteomics. From low microgram sample amounts, we quantify over 10,700 proteins in this high dynamic range tissue. We combine copy numbers per cell with protein organellar assignments to build a model of the heart proteome at the subcellular level. Analysis of cardiac fibroblasts identifies cellular receptors as potential cell surface markers. Application of our heart map to atrial fibrillation reveals individually distinct mitochondrial dysfunctions. The heart map is available at maxqb.biochem.mpg.de as a resource for future analyses of normal heart function and disease.

The human heart is composed of distinct regions and cell types, but relatively little is known about their specific protein composition. Here, the authors present a region- and cell type-specific proteomic map of the healthy human heart, revealing functional differences and potential cell type markers.

Comparative Transcriptomic Profiling and Gene Expression for Myxomatous Mitral Valve Disease in the Dog and Human

Myxomatous mitral valve disease is the single most important mitral valve disease in both dogs and humans. In the case of the dog it is ubiquitous, such that all aged dogs will have some evidence of the disease, and for humans it is known as Barlow's disease and affects up to 3% of the population, with an expected increase in prevalence as the population ages. Disease in the two species show many similarities and while both have the classic myxomatous degeneration only in humans is there extensive fibrosis. This dual pathology of the human disease markedly affects the valve transcriptome and the difference between the dog and human is dominated by changes in genes associated with fibrosis. This review will briefly examine the comparative valve pathology and then, in more detail, the transcriptomic profiling and gene expression reported so far for both species.

Optimized Protocol for the Extraction of Proteins from the Human Mitral Valve

Analysis of the cellular proteome can help to elucidate the molecular mechanisms underlying diseases due to the development of technologies that permit the large-scale identification and quantification of the proteins present in complex biological systems.The knowledge gained from a proteomic approach can potentially lead to a better understanding of the pathogenic mechanisms underlying diseases, allowing for the identification of novel diagnostic and prognostic disease markers, and, hopefully, of therapeutic targets. However, the cardiac mitral valve represents a very challenging sample for proteomic analysis because of the low cellularity in proteoglycan and collagen-enriched extracellular matrix. This makes it challenging to extract proteins for a global proteomic analysis. This work describes a protocol that is compatible with subsequent protein analysis, such as quantitative proteomics and immunoblotting. This can allow for the correlation of data concerning protein expression with data on quantitative mRNA expression and non-quantitative immunohistochemical analysis. Indeed, these approaches, when performed together, will lead to a more comprehensive understanding of the molecular mechanisms underlying diseases, from mRNA to post-translational protein modification. Thus, this method can be relevant to researchers interested in the study of cardiac valve physiopathology.

Normal human mitral valve proteome: A preliminary investigation by gel-based and gel-free proteomic approaches

The mitral valve is a highly complex structure which regulates blood flow from the left atrium to the left ventricle (LV) avoiding a significant forward gradient during diastole or regurgitation during systole. The integrity of the mitral valve is also essential for the maintenance of normal LV size, geometry, and function. Significant advances in the comprehension of the biological, functional, and mechanical behavior of the mitral valve have recently been made. However, current knowledge of protein components in the normal human mitral valve is still limited and complicated by the low cellularity of this tissue and the presence of high abundant proteins from the extracellular matrix. We employed here an integrated proteomic approach to analyse the protein composition of the normal human mitral valve and reported confident identification of 422 proteins, some of which have not been previously described in this tissue. In particular, we described the ability of pre-MS separation technique based on liquid-phase IEF and SDS-PAGE to identify the largest number of proteins. We also demonstrated that some of these proteins, e.g. αB-Crystallin, septin-11, four-and-a-half LIM domains protein 1, and dermatopontin, are synthesised by interstitial cells isolated from human mitral valves. These initial results provide a valuable basis for future studies aimed at analysing in depth the mitral valve protein composition and at investigating potential pathogenetic molecular mechanisms. Data are available via ProteomeXchange with identifier PXD004397.