Lysosomal proteomics and disease

A recent trend in proteomic studies has been to analyze macromolecular complexes such as subcellular organelles instead of complete cells or tissues. This "divide and conquer" approach circumvents some of the formidable problems associated with whole proteome analyses and allows focus on a subset of proteins that may be involved in a particular process or disease of interest. One organelle that has been the focus of considerable attention in proteomic studies is the lysosome, an acidic, membrane-delimited compartment that plays an essential role in the degradation and recycling of biological macromolecules. Lysosomal proteomics have been driven in part by the well-established involvement of this organelle in numerous human diseases, but also by the availability of approaches to selectively visualize and/or isolate subsets of lysosomal proteins. In terms of clinical application, proteomic studies of the lysosome have led to the identification of gene defects in three human hereditary diseases. This review summarizes past progress, current limitations and future directions in the field of lysosomal proteomics.     

Degradative proteomics and disease mechanisms

Protein degradation is a fundamental biological process, which is essential for the maintenance and regulation of normal cellular function. In humans and animals, proteins can be degraded by a number of mechanisms: the ubiquitin-proteasome system, autophagy and intracellular proteases. The advances in contemporary protein analysis means that proteomics is increasingly being used to explore these key pathways and as a means of monitoring protein degradation. The dysfunction of protein degradative pathways has been associated with the development of a number of important diseases including cancer, muscle wasting disorders and neurodegenerative diseases. This review will focus on the role of proteomics to study cellular degradative processes and how these strategies are being applied to understand the molecular basis of diseases arising from disturbances in protein degradation.     

Urinary proteomics in cardiovascular disease: Achievements, limits and hopes

Cardiovascular disease (CVD) is the major cause of mortality and morbidity worldwide. Diagnosis of CVD and risk stratification of patients with CVD remains challenging despite the availability of a wealth of non-invasive and invasive tests. Clinical proteomics analyses a large number of peptides and proteins in biofluids. For clinical applications, the urinary proteome appears particularly attractive due to the relative low complexity compared with the plasma proteome and the noninvasive collection of urine. In this article, we review the results from pilot studies into urinary proteomics of coronary artery disease and discuss the potential of urinary proteomics in the context of pathogenesis of CVD.     

Vascular proteomics

The characterization of patients with acute coronary syndromes (ACS) at the molecular and cellular levels provides a novel vision for understanding the pathological and clinical expression of the disease. Recent advances in proteomic technologies permit the evaluation of systematic changes in protein expression in many biological systems and have been extensively applied to cardiovascular diseases (CVD). The cardiovascular system is in permanent intimate contact with blood, making blood-based biomarker discovery a particularly worthwhile approach. Thus, proteomics can potentially yield novel biomarkers reflecting CVD, establish earlier detection strategies, and monitor response to therapy. Here we review the different proteomic strategies used in the study of atherosclerosis and the novel proteins differentially expressed and secreted by atherosclerotic lesions which constitute novel potential biomarkers (HSP-27, Cathepsin D). Special attention is paid to MS-Imaging of atheroma plaque and the generation, for the first time, of 2-D images of lipids, showing the distribution of these molecules in the different areas of the atherosclerotic lesions. In addition new potential biomarkers have been identified in plasma (amyloid A1α, transtherytin), circulating cells (protein profile in monocytes from ACS patients) and individual cells constituents of atheroma plaques (endothelial, VSMC, macrophages) which provide novel insights into vascular pathophysiology.     

Type 2 diabetes: Gaining insight into the disease process using proteomics

The incidence of diabetes mellitus is growing rapidly, with an increasing disease related morbidity and mortality. This is caused by macro- and microvascular complications, as a consequence of the often late diagnosis of type 2 diabetes (T2D), but especially by the difficulties to control glucose homeostasis due to the progressive nature of the disease. T2D is moreover a dual disease, with components of beta-cell failure and components of insulin resistance in peripheral organs, such as liver, fat, and muscle. Understanding the pathogenesis of the disease by gaining insight into the molecular pathways involved in both phenomena is one of the major assets of proteomic approaches. Moreover, proteomics and peptidomics may provide us with robust biomarkers for beta-cell failure, insulin resistance in pheripheral organs, but also for the development of diabetic complications. This review focuses on the knowledge gained by use of proteomic and peptidomic techniques in the study of the pathophysiology of T2D and in the attempts to discover new therapeutic targets.     

Rule extraction for fatty liver detection using neural networks

Neural Computing and Applications - Non-alcoholic fatty liver disease (NAFLD) is one of the most common diseases in the world. Recently the FibroScan device is used as a noninvasive, yet costly...     

Gastrointestinal fluids proteomics

Seventy million people suffer from diseases of the gastrointestinal tract annually in US, translating to US$85.5 billion in direct healthcare costs. The debilitating effects of these gastrointestinal (GI) diseases can be circumvented with good biomarkers for early detection of these disorders, which will greatly increase the success of curative treatments. GI fluids represent a potential reservoir of biomarkers for early diagnosis of various GI and systemic diseases since these fluids are the most proximal fluid bathing diseased cells. They are anticipated to have proteomes that closely reflect the ensemble of proteins secreted from the respective GI tissues. Most importantly, the disease markers present in GI fluids should be present in higher concentrations than in sera, thus offering greater sensitivity in their detection. However, proteome analysis of GI fluids can be complex mainly due to the dynamic range of protein content and the numerous PTMs of proteins in each specialized GI compartment. This review attempts to discuss the physiology of the various GI fluids, the special technical considerations required for proteome analysis of each fluid, as well as to summarize the current state of knowledge of biomarker discoveries and clinical utility of GI fluids such as salivary, gastric, pancreatic, and biliary secretions.     

Contribution of proteomics to the study of the role of cytokeratins in disease and physiopathology

Cytokeratins (CKs), the most abundant group of cytoskeletal intermediate filaments, and proteomics are strongly connected. On the one hand, proteomics has been extremely useful to uncover new features and functions of CKs, on the other, the highly abundant CKs serve as an exceptional tool to test new technological developments in proteomics. As a result, proteomics has contributed to finding valuable associations of CKs with diseases as diverse as cancer, cystic fibrosis, steatohepatitis, viral and bacterial infection, keratoconus, vitreoretinopathy, preeclampsia or the chronic fatigue syndrome, as well as to characterizing their participation in a number of physiopathological processes, including drug resistance, response to toxicants, inflammation, stem cell differentiation, embryo development, and tissue repair. In some cases, like in cystic fibrosis, CKs have been described as potential therapeutic targets. The development of a specific field of proteomics where CKs become the main subject of research aims and hypotheses is suggested.     

Clinical proteomics in neurodegenerative diseases

Investigation of the human specimens is an essential element for understanding the pathogenesis of neurodegenerative disorders, such as Alzheimer's disease, Parkinson's disease, and multiple sclerosis. The studies hold promise for identifying biomarkers for diagnosis and prognosis, elucidating disease mechanisms, and accelerating the development of new strategies for therapeutic intervention. Here, we review proteomics studies of human brain samples in light of recent advances of mass spectrometry, focusing on the general strategies for experimental design and analysis (e.g., sample pooling and replication, selection of proteomics platforms, and false discovery rate in data processing), because quantitative analysis of clinical samples is confounded by a number of variables, including genetic differences, antemortem and postmortem factors, and experimental errors. Diverse proteomics platforms are also discussed with respect to sensitivity, throughput, and accuracy. Regarding the enormous complexity of the human brain and the limitation of current proteomics technologies, it may be more practical to analyze a subset of proteome in a functional context, in order to facilitate the identification of important disease-related proteins in the substantial noise reflecting biological and technical variances.     

Recent progress in urinary proteomics

Urinary proteomics has become one of the most attractive subdisciplines in clinical proteomics as the urine is an ideal source for the discovery of noninvasive biomarkers for kidney and nonkidney diseases. This field has been growing rapidly as indicated by >80 original research articles on urinary proteome analyses appearing since 2001, of which 28 (approximately 1/3) had been published within the year 2006. The most common technologies used in recent urinary proteome studies remain gel-based methods (1-DE, 2-DE and 2-D DIGE), whereas LC-MS/MS, SELDI-TOF MS, and CE-MS are other commonly used techniques. In addition, mass spectrometric immunoassay (MSIA) and array technology have also been applied. This review provides an extensive but concise summary of recent applications of urinary proteomics. Proteomic analyses of dialysate and ultrafiltrate fluids derived from renal replacement therapy (or artificial kidney) are also discussed.     

Computational proteomics on the grid

The large number of protein sequences, provided by genomic projects at an increasing pace, constitutes a challenge for large scale computational studies of protein structure and thermodynamics. Grid technology is very suitable to face this challenge, since it provides a way to access the resources needed in compute and data intensive applications. In this work, we concentrate on the grid-aware implementation of a protein structure prediction algorithm.     

Quantitative proteomics for investigating psychiatric disorders

The underlying pathophysiology of psychiatric disorders remains elusive. The use of quantitative proteomics to investigate disease-specific protein signatures holds great promise to improve the understanding of psychiatric disorders and identify relevant biomarkers. In this review, we discuss quantitative proteomic approaches for elucidating molecular mechanisms of psychiatric disorders, i.e. anxiety, schizophrenia, bipolar disorder and depression, by studying specimens from animal models and patients. We present gel-based, label-free and stable isotope-labeling methodologies and evaluate their strengths and limitations in the context of psychiatric research, with a focus on (15)N metabolic labeling of live animals due to its increased accuracy and potential for future applications. We also review biomarker candidate validation methods and present quantitative proteomic studies from the literature that aim to disentangle the molecular pathobiology of psychiatric disorders and identify candidate biomarkers. Finally, we explore the applicability of implementing proteomic methods as a routine diagnostic tool in the clinical laboratory.     

Semi-automated sample preparation for plasma proteomics

The discovery of new biomarkers will be an essential step to enhance our ability to better diagnose and treat human disease. The proteomics research community has recently increased its use of human blood (plasma/serum) as a sample source for these discoveries. However, while blood is fairly non-invasive and readily available as a specimen, it is not easily analyzed by liquid chromatography (LC)/mass spectrometry (MS), because of its complexity. Therefore, sample preparation is a crucial step prior to the analysis of blood. This sample preparation must also be standardized in order to gain the most information from these valuable samples and to ensure reproducibility. We have designed a semi-automated and highly parallel procedure for the preparation of human plasma samples. Our process takes the samples through eight successive steps before analysis by LC/MS: (1) receipt, (2) reformatting, (3) filtration, (4) depletion, (5) concentration determination and normalization, (6) digestion, (7) extraction, and (8) randomization, triplication, and lyophilization. These steps utilize a number of different liquid handlers and liquid chromatography (LC) systems. This process enhances our ability to discover new biomarkers from human plasma.     

Protein microarray platforms for clinical proteomics

Proteomics for clinical applications is presently in a state of transition. It has become clear that the classical approaches based on 2-DE and/or MS need to be complemented by different kinds of technologies. The well-known problems include sample complexity, sensitivity, quantitation, reproducibility, and analysis time. We suggest that the new technologies for clinical proteomics can be supported by antibody-centric protein microarray platforms. These platforms presently include antibody microarrays and lysate, or reverse capture/reverse phase protein microarrays. Other forms of these arrays are in less mature developmental stages, including ORF and self assembling protein microarrays. Bioinformatic support for interpreting these arrays is becoming more available as the whole field of systems biology begins to mature. The present set of applications for these platforms is profoundly focused on certain common cancers, immunology, and cystic fibrosis. However, we predict that many more disease entities will become studied as knowledge of the power and availability of these platforms becomes more widely established. We anticipate that these platforms will eventually evolve to accommodate label-free detection technologies, human genome-scale numbers of analytes, and increases in analytic and bioinformatic speeds.