Application of genomics and proteomics in Type 1 diabetes pathogenesis research

Type 1 diabetes: entering the proteomic era

During the last decade, a major breakthrough in the field of proteomics has been achieved. This review describes available techniques for proteomic analyses, both gel and non-gel based, particularly concentrating on relative quantification techniques. The principle of the different techniques is discussed, highlighting the advantages and drawbacks of recently available visualization methods in gel-based assays. In addition, recent developments for quantitative analysis in non-gel-based approaches are summarized. This review focuses on applications in Type 1 diabetes. These mainly include proteomic studies on pancreatic islets in animal models and in the human situation. Also discussed are mass spectrometry-based studies on T-cells, and studies on the development of diagnostic markers for diabetic nephropathology by capillary electrophoresis coupled to mass spectrometry.

Proteomics in nutrition: status quo and outlook for biomarkers and bioactives

Food and beverages are the only physical matter we take into our body, if we disregard the air we inhale and the drugs we may have to apply. While traditional nutrition research has aimed at providing nutrients to nourish populations and preventing specific nutrient deficiencies, it more recently explores health-related aspects of individual bioactive components as well as entire diets and this at group rather than population level. The new era of nutrition research translates empirical knowledge to evidence-based molecular science. Modern nutrition research focuses on promoting health, preventing or delaying the onset of disease, optimizing performance, and assessing risk. Personalized nutrition is a conceptual analogue to personalized medicine and means adapting food to individual needs. Nutrigenomics and nutrigenetics build the science foundation for understanding human variability in preferences, requirements, and responses to diet and may become the future tools for consumer assessment motivated by personalized nutritional counseling for health maintenance and disease prevention. The scope of this paper is to review the current and future aspects of nutritional proteomics, focusing on the two main outputs: identification of health biomarkers and analysis of food bioactives.

Advances and challenges in biomarker development for type 1 diabetes prediction and prevention using omic technologies

IMPORTANCE OF THE FIELD: Biomarkers are essential for the identification of high risk children as well as monitoring of prevention outcomes for type 1 diabetes (T1D). AREAS COVERED IN THIS REVIEW: This review discusses progress, opportunities and challenges in biomarker discovery and validation using high throughput genomic, transcriptomic and proteomic technologies. The authors also suggest potential solutions to deal with the current challenges. WHAT THE READER WILL GAIN: Readers will gain an overview of the current status on T1D biomarkers, an integrated review of three omic technologies, their applications and limitations for biomarker discovery and validation, and a critical discussion of the major issues encountered in biomarker development. TAKE HOME MESSAGE: Better biomarkers are still urgently needed for T1D prediction and prevention. The high throughput omic technologies offer great opportunities but also face significant challenges that have to be solved before their potential for biomarker development is fully realized.

Different expression of fibrinopeptide A and related fragments in serum of type 1 diabetic patients with nephropathy

Type 1 diabetes (insulin-dependent diabetes mellitus, IDDM) is an autoimmune disease affecting about 0.12% of the world's population. Diabetic nephropathy (DN) is a major long-term complication of both types of diabetes and retains a high human, social and economic cost. Thus, the identification of markers for the early detection of DN represents a relevant target of diabetic research. The present work is a pilot study focused on proteomic analysis of serum of controls (n=9), IDDM patients (n=10) and DN patients (n=4) by the ClinProt profiling technology based on mass spectrometry. This approach allowed to identify a pattern of peptides able to differentiate the studied populations with sensitivity and specificity close to 100%. Variance of the results allowed to estimate the sample size needed to keep the expected False Discovery Rate low. Moreover, three peptides differentially expressed in the serum of patients as compared to controls were identified by LC-ESI MS/MS as the whole fibrinopeptide A peptide and two of its fragments, respectively. The two fragments were under-expressed in diabetic patients, while Fibrinopeptide A was over-expressed, suggesting that anomalous turnover of Fibrinopeptide A could be involved in the pathogenesis of DN.

Bioinformatics for study of autoimmunity

Recent years have witnessed an explosive growth in available biological data pertaining to autoimmunity research. This includes a tremendous quantity of sequence data (biological structures, genetic and physical maps, pathways, etc.) generated by genome and proteome projects plus extensive clinical and epidemiological data. Autoimmunity research stands to greatly benefit from this data so long as appropriate strategies are available to enable full access to and utilization of this data. The quantity and complexity of this biological data necessitates use of advanced bioinformatics strategies for its efficient retrieval, analysis and interpretation. Major progress has been made in development of specialized tools for storage, analysis and modeling of immunological data, and this has led to development of a whole new field know as immunoinformatics. With advances in novel high-throughput immunology technologies immunoinformatics is transforming understanding of how the immune system functions. This paper reviews advances in the field of immunoinformatics pertinent to autoimmunity research including databases, tools in genomics and proteomics, tools for study of B- and T-cell epitopes, integrative approaches, and web servers.

Apolipoprotein M promoter polymorphisms alter promoter activity and confer the susceptibility to the development of type 1 diabetes

OBJECTIVES

Apolipoprotein M plays an important role in the formation of prebeta-HDL and cholesterol efflux to HDL. In the present study, we investigate the potential association between the ApoM promoter polymorphisms and type 1 diabetes.

DESIGN AND METHODS

The study was conducted in Peking Union Medical College, Beijing, China and Karolinska Institutet, Stockholm, Sweden. Two populations, including 493 Han Chinese subjects (177 T1D patients/316 controls) and 225 Swedish (124/101), are enrolled in the present study. Three single nucleotide polymorphisms (SNP) C-1065A, T-855C and T-778C in the promoter region of the ApoM gene are genotyped using a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) protocol. Promoter activity was measured by reporter gene assay.

RESULTS

SNP T-778C was strongly associated with T1D in both Han Chinese (p=0.002, OR=2.188, CI 95%=1.338-3.581) and Swedish (p=0.021, OR=2.865, CI 95%=1.128-7.278) populations. The luciferase activity of -778C promoter was 1.41 times as high as that of -778T promoter (9.90+/-1.92 vs. 7.04+/-0.76, p=0.001).

CONCLUSIONS

Allele C of SNP T-778C may increase promoter activity and confer the risk susceptibility to the development of T1D.

Application of proteomic technology in eye research: a mini review

Proteomics is a rapidly growing research area for the study of the protein cognate of genomic data. This review gives a brief overview of the modern proteomic technology. In addition to general applications of proteomics, we highlight its contribution to studying the physiology of different ocular tissues. We also summarise the published proteomic literature in the broad context of ophthalmic diseases, such as cataract, age-related maculopathy, diabetic retinopathy, glaucoma and myopia. The proteomic technology is a useful research tool and it will continue to advance our understanding of a variety of molecular processes in ocular tissues and diseases.

Application of fluorescence difference gel electrophoresis technology in searching for protein biomarkers in chick myopia

The lens-induced myopia (LIM) in response to concave lens (negative lens) is a well established animal model for studying myopia development. However, the exact visual and neurochemical signaling mechanisms involving myopic eye growth are yet to be elucidated. The feasibility of applying a novel two-dimensional fluorescence difference gel electrophoresis technique for global protein profilings and a search for differential protein expressions in LIM were explored in the present study. Two-dimensional polyacrylamide gel electrophoresis was performed employing a "minimal Lysine labeling" approach and a reverse CyeDye experimental protocol using retinal tissue from chicks. The retinal protein profiles between myopic and control eyes were found to be very similar. More than a thousand protein spots could be detected on a 2D gel. Sixteen and ten protein spots were found to be up-regulated and down-regulated respectively in the myopic eyes according to our preset criteria with the inclusion of an internal pool standard. About 65% of those filtered spots could be successfully identified by peptide mass fingerprinting by matrix-assisted laser desorption ionization-time-of-flight mass spectrometry . Most of the differentially expressed proteins were found to be related to cytoskeletal or oxidative functions. According to the prediction of subcellular locations, most of them (about 84%) were classified as cytoplasmic proteins. The cellular functions for those differentially expressed proteins were reported and their possible involvements in the compensated eye growth were discussed. We have optimized a workable protocol for the study of the differential retinal protein expressions in the LIM using 2D-DIGE approach which was shown to have a number of advantages over the traditional 2D electrophoresis technique.

Protein profiling of pancreatic islets

The insulin-producing beta cell in the islet of Langerhans is central in glucose homeostasis. Its dysfunction is part of the pathogenesis of both Type 1 and 2 diabetes mellitus. In both forms of the disease, there is a cytotoxic component either induced by cytokines, as in Type 1 diabetes, or by elevated levels of glucose and fatty acids, as in Type 2 diabetes. To find the mechanisms responsible for the cytotoxic effects of these compounds proteomic approaches with 2D gel electrophoresis and surface-enhanced laser desorption/ionization time-of-flight mass spectrometry have been undertaken. In this article, we describe these methods, and other methodological aspects of protein profiling of pancreatic islets, and summarize the results obtained with these methods.

Serum, liver, and kidney proteomic analysis for the alloxan-induced type I diabetic mice after insulin gene transfer of naked plasmid through electroporation

Gene therapy has been reported to be effective in treating diabetes mellitus (DM), while little has been found out about the functional protein changes since. The liver and kidney play important roles in glucose absorption, metabolism, and excretion. Changes in the two organs may reflect pathologic alterations during DM, while the serum has a direct connection with most organs and pathological changes. We used alloxan to induce diabetic mice, electrotranferred the insulin gene into their sural muscles, and discovered that their blood glucose decreased to normal level. Consequently, proteomic approaches were applied to evaluate protein changes in the liver, kidney, and serum of normal, diabetic, and gene transferred mice. Forty-three proteins were found either up-regulated or down-reglulated in the liver, kidney, and serum of the alloxan-induced type I diabetic mice. Only five proteins in the liver, five proteins in the kidney, and seven proteins in the serum of diabetic mice were found to be back-regulated to normal levels after gene transfer. These back-regulated proteins are involved in lipid and glucose metabolism, associated with phosphorylation, signal transduction, oxidation, and immune inflammation. Our findings might promote a better understanding for the mechanism of DM, and provide novel targets for estimating the effects of gene therapy.

OMICS-driven biomarker discovery in nutrition and health

While traditional nutrition research has dealt with providing nutrients to nourish populations, it nowadays focuses on improving health of individuals through diet. Modern nutritional research is aiming at health promotion and disease prevention and on performance improvement. As a consequence of these ambitious objectives, the disciplines "nutrigenetics" and "nutrigenomics" have evolved. Nutrigenetics asks the question how individual genetic disposition, manifesting as single nucleotide polymorphisms, copy-number polymorphisms and epigenetic phenomena, affects susceptibility to diet. Nutrigenomics addresses the inverse relationship, that is how diet influences gene transcription, protein expression and metabolism. A major methodological challenge and first pre-requisite of nutrigenomics is integrating genomics (gene analysis), transcriptomics (gene expression analysis), proteomics (protein expression analysis) and metabonomics (metabolite profiling) to define a "healthy" phenotype. The long-term deliverable of nutrigenomics is personalised nutrition for maintenance of individual health and prevention of disease. Transcriptomics serves to put proteomic and metabolomic markers into a larger biological perspective and is suitable for a first "round of discovery" in regulatory networks. Metabonomics is a diagnostic tool for metabolic classification of individuals. The great asset of this platform is the quantitative, non-invasive analysis of easily accessible human body fluids like urine, blood and saliva. This feature also holds true to some extent for proteomics, with the constraint that proteomics is more complex in terms of absolute number, chemical properties and dynamic range of compounds present. Apart from addressing the most complex "-ome", proteomics represents the only platform that delivers not only markers for disposition and efficacy but also targets of intervention. The Omics disciplines applied in the context of nutrition and health have the potential to deliver biomarkers for health and comfort, reveal early indicators for disease disposition, assist in differentiating dietary responders from non-responders, and, last but not least, discover bioactive, beneficial food components. This paper reviews the state-of-the-art of the three Omics platforms, discusses their implication in nutrigenomics and elaborates on applications in nutrition and health such as digestive health, allergy, diabetes and obesity, nutritional intervention and nutrient bioavailability. Proteomic developments, applications and potential in the field of nutrition have been specifically addressed in another review issued by our group.

Proteomics for diabetes research: an update and future perspectives

Diabetes is a common disease worldwide and can cause several complications, leading to systemic derangements and end-organ damage. Despite blood sugar control and adequate therapy with currently available drugs, diabetic complications remain a serious issue in clinical practice, indicating that our knowledge of diabetes and its complications is only at the tip of the iceberg. Better understanding of its pathogenesis and pathophysiology is crucial to achieve better therapeutic outcomes and to prevent its complications. This review provides an overview of proteomics and introduces proteomic technologies commonly used for diabetes research. Recent proteomic studies for the investigation of diabetes and its complications are summarized. Finally, the future perspectives for the field of proteomics in diabetes research are discussed.

Application of semiquantitative proteomics techniques to the maillard reaction

Proteomic tools-in particular, mass spectrometry (MS)-have advanced significantly in recent years, and the identification of proteins within complex mixtures is now a routine procedure. Quantitative methods of analysis are less well advanced and continue to develop. These include the use of stable isotope ratio approaches, isotopically labeled peptide standards, and nonlabeling methods. This paper summarizes the use of MS as a proteomics tool to identify and semiquantify proteins and their modified forms by using examples of relevance to the Maillard reaction. Finally, some challenges for the future are presented.

Unraveling the Pathogenesis of Type 1 Diabetes with Proteomics: Present And Future Directions

Type 1 diabetes (T1D) is the result of selective destruction of the insulin-producing beta-cells in the pancreatic islets of Langerhans. T1D is due to a complex interplay between the beta-cell, the immune system, and the environment in genetically susceptible individuals. The initiating mechanism(s) behind the development of T1D are largely unknown, and no genes or proteins are specific for most T1D cases. Different pro-apoptotic cytokines, IL-1 beta in particular, are present in the islets during beta-cell destruction and are able to modulate beta-cell function and induce beta-cell death. In beta-cells exposed to IL-1 beta, a race between destructive and protective events are initiated and in susceptible individuals the deleterious events prevail. Proteins are involved in most cellular processes, and it is thus expected that their cumulative expression profile reflects the specific activity of cells. Proteomics may be useful in describing the protein expression profile and thus the diabetic phenotype. Relatively few studies using proteomics technologies to investigate the T1D pathogenesis have been published to date despite the defined target organ, the beta-cell. Proteomics has been applied in studies of differentiating beta-cells, cytokine exposed islets, dietary manipulated islets, and in transplanted islets. Although that the studies have revealed a complex and detailed picture of the protein expression profiles many functional implications remain to be answered. In conclusion, a rather detailed picture of protein expression in beta-cell lines, islets, and transplanted islets both in vitro and in vivo have been described. The data indicate that the beta-cell is an active participant in its own destruction during diabetes development. No single protein alone seems to be responsible for the development of diabetes. Rather the cumulative pattern of changes seems to be what favors a transition from dynamic stability in the unperturbed beta-cell to dynamic instability and eventually to beta-cell destruction.

L-gamma-Glutamyl-L-cysteinyl-glycine (glutathione; GSH) and GSH-related enzymes in the regulation of pro- and anti-inflammatory cytokines: a signaling transcriptional scenario for redox(y) immunologic sensor(s)?

Of the antioxidant/prooxidant mechanisms mediating the regulation of inflammatory mediators, particularly cytokines, oxidative stress-related pathways remain a cornerstone. It is conspicuous that there is a strong association between free radical accumulation (ROS/RNS; oxidative stress) and the evolution of inflammation and inflammatory-related responses. The scenario that upholds a consensus on the aforementioned is still evolving to unravel, from an immunologic perspective, the molecular mechanisms associated with ROS/RNS-dependent inflammation. Cytokines are keynote players when it comes to defining an intimate relationship among reduction-oxidation (redox) signals, oxidative stress and inflammation. How close we are to identifying the molecular basis of this intricate association should be weighed against the involvement of specific signaling molecules and, potentially, transcription factors. L-gamma-Glutamyl-L-cysteinyl-glycine, or glutathione (GSH), an antioxidant thiol, has shaped, and still is refining, the face of oxidative signaling in terms of regulating the milieu of inflammatory mediators, ostensibly via the modulation (expression/repression) of oxygen- and redox-responsive transcription factors, hence termed redox(y)-sensitive cofactors. When it comes to the arena of oxygen sensing, oxidative stress and inflammation, nuclear factor-kappaB (NF-kappaB) and hypoxia-inducible factor-1alpha (HIF-1alpha) are key players that determine antioxidant/prooxidant responses with oxidative challenge. It is the theme therein to underlie current understanding of the molecular association hanging between oxidative stress and the evolution of inflammation, walked through an elaborate discussion on the role of transcription factors and cofactors. Would that classify glutathione and other redox signaling cofactors as potential anti-inflammatory molecules emphatically remains of particular interest, especially in the light of identifying upstream and downstream molecular pathways for conceiving therapeutic, alleviating strategy for oxidant-mediated, inflammatory-related disease conditions.