Reversal of diabetes-evoked changes in mitochondrial protein expression of cardiac left ventricle by treatment with a copper(II)-selective chelator

Cardiac disease is the commonest cause of death amongst diabetic patients. Diabetic cardiomyopathy, which has a poor prognosis, is characterized by left ventricular hypertrophy and impaired cardiac function and mitochondrial damage is said to contribute to its development. We recently showed that treatment with the Cu(II) -selective chelator, triethylenetetramine (TETA), improved cardiac structure, and function in diabetic subjects without modifying hyperglycemia. Thus, TETA has potential utility for the treatment of heart disease. To further understand the molecular mechanism by which it causes these effects, we have conducted the first study of the effect of oral TETA on protein abundance in the cardiac left ventricle of rats with severe streptozotocin-induced diabetes. Proteomic methods showed that of 211 proteins changed in diabetes, 33 recovered after treatment. Through MS, 16 proteins were identified which may constitute major targets of drug action. Remarkably, most of these were mitochondrial proteins with roles in energy metabolism. In addition to components of the mitochondrial respiratory chain and enzymes involved in fatty acid oxidation, TETA treatment normalized both myocardial expression and enzymatic activity of carnitine palmitoyltransferase 2. These findings indicate that mitochondria constitute major targets in the mechanism by which TETA restores cardiac structure and function in diabetes.     

Redox signalling in cardiovascular disease

Oxidative stress has almost universally and unequivocally been implicated in the pathogenesis of all major diseases, including those of the cardiovascular system. Oxidative stress in cells and cardiovascular biology was once considered only in terms of injury, disease and dysfunction. However, it is now appreciated that oxidants are also produced in healthy tissues, and they function as signalling molecules transmitting information throughout the cell. Conversely, when cells move to a more reduced state, as can occur when oxygen is limiting, this can also result in alterations in the function of biomolecules and subsequently cells. At the centre of this 'redox signalling' are oxidoreductive chemical reactions involving oxidants or reductants post translationally modifying proteins. These structural alterations allow changes in cellular redox state to be coupled to alterations in cell function. In this review, we consider aspects of redox signalling in the cardiovascular system, focusing on the molecular basis of redox sensing by proteins and the array of post-translational oxidative modifications that can occur. In addition, we discuss studies utilising proteomic methods to identify redox-sensitive cardiac proteins, as well as those using this technology more broadly to assess redox signalling in cardiovascular disease.     

Characterization of proteomic changes in cardiac mitochondria in streptozotocin-diabetic rats using iTRAQ™ isobaric tags

Diabetes now affects more than 5% of the world's population and heart failure is the most common cause of death amongst diabetic patients. Accumulating evidence supports a view that myocardial mitochondrial structural and functional changes are central to the onset of diabetic heart failure, but the exact nature of these changes at the proteomic level remains unclear.Here we report on proteomic changes in diabetic rat heart mitochondria following 120 days of streptozotocin‐diabetes using the recently developed iTRAQ? labeling method, which permits quantification of proteins directly from complex mixtures, bypassing the limitations associated with gel‐based methods such as 2‐DE. Of 252 unique proteins identified, 144 were represented in at least three of six individual paired experiments. Relative amounts of 65 proteins differed significantly between the groups, confirming that the cardiac mitochondrial proteome is indeed impacted by diabetes. The most significant changes were increased protein levels of enzymes involved in mitochondrial oxidation of long‐chain fatty acids, which was also confirmed by enzyme assays, and decreased levels of multiple enzymes involved in oxidative phosphorylation and catabolism of short‐chain fatty acids and branched‐chain amino acids. We also found significant changes in levels of several enzymes linked to oxidative stress.     

Quantitative proteomic analysis of ovarian cancer cells identified mitochondrial proteins associated with Paclitaxel resistance

Paclitaxel has been widely used as an anti-mitotic agent in chemotherapy for a variety of cancers and adds substantial efficacy as the first-line chemotherapeutic regimen for ovarian cancers. However, the frequent occurrence of paclitaxel resistance limits its function in long-term management. Despite abundant clinical and cellular demonstration of paclitaxel resistant tumors, the molecular mechanisms leading to paclitaxel resistance are poorly understood. Using genomic approaches, we have previously identified an association between a BTB/POZ gene, Nac1, and paclitaxel resistance in ovarian cancer. The experiments presented here have applied multiple quantitative proteomic methods to identify protein changes associated with paclitaxel resistance and Nac1 function. The SKOV-3 ovarian serous carcinoma cell line, which has inducible expression of dominant negative Nac1, was used to determine the paclitaxel treatment associated changes in the presence and absence of functional Nac1. Quantitative proteomic analyses were performed using iTRAQ labeling and mass spectrometry. Two label-free quantitative proteomic methods: LC-MS and spectral count were used to increase confidence of proteomic quantification. A total of 1371 proteins were quantified by at least one of the quantitative proteomic methods. Candidate proteins related to paclitaxel and NAC1 function were identified in this study. Go analysis of the protein changes identified upon paclitaxel resistance revealed that cell component enrichment related to mitochondria. Moreover, tubulin and mitochondrial proteins were the major cellular components with changes associated with paclitaxel treatment. This suggests that mitochondria may play a role in paclitaxel resistance.     

Proteomic strategies to elucidate pathogenic mechanisms of spirochetes

Spirochetes are a unique group of bacteria that include several motile and highly invasive pathogens that cause a multitude of acute and chronic disease processes. Nine genomes of spirochetes have been completed, which provide significant insights into pathogenic mechanisms of disease and reflect an often complex lifestyle associated with a wide range of environmental and host factors encountered during disease transmission and infection. Characterization of the outer membrane of spirochetes is of particular interest since it interacts directly with the host and environs during disease and likely contains candidate vaccinogens and diagnostics. In concert with appropriate fractionation techniques, the tools of proteomics have rapidly evolved to characterize the proteome of spirochetes. Of greater significance, studies have confirmed the differential expression of many proteins, including those of the outer membrane, in response to environmental signals encountered during disease transmission and infection. Characterization of the proteome in response to such signals provides novel insights to understand pathogenic mechanisms of spirochetes.     

Analysis of membrane microdomain-associated proteins in the insular cortex of post-mortem human brain

Membrane microdomains (MM) are membrane rafts within the cell membrane enriched in cholesterol and glycosphingolipids that have been implicated in the trafficking and sorting of membrane proteins, secretory and endocytotic pathways, and signal transduction. To date, MM have not been characterised in the human brain. We reason that by identifying MM in the normal human cortex, we may better understand the molecular mechanisms of human brain dysfunction. To characterize the protein composition of MM in the human brain, we have carried out a comprehensive proteomic analysis of detergent resistant membranes (DRMs) associated proteins derived from human postmortem insular cortex using 1-DE separation prior to LC coupled to MS/MS or GeLC-MS/MS. Eighty five proteins were identified including 57 unique to human brain cortex DRMs (by comparison with DRM proteins reported in other cell types). High levels of signal transduction, cell adhesion, cell transport and cell trafficking proteins were identified including synaptic proteins such as synapsin II and synaptic vesicle membrane protein, mitochondrial proteins such as ATPase subunits and metabolic enzymes such as malate dehydrogenase. This data will facilitate our understanding of protein expression changes within membranes in candidate brain regions in human brain diseases such as schizophrenia, bipolar disorder and other psychiatric and neurodegenerative disorders.     

Toward a better understanding of preeclampsia: Comparative proteomic analysis of preeclamptic placentas

Preeclampsia (PE), a pregnancy-specific syndrome of hypertension, proteinuria, and other systemic disturbances, is a state of widespread endothelial dysfunction secondary to defective placentation. Morphologically, the current data displayed degenerative and apoptotic changes in the mitochondria and villous trophoblasts of preeclamptic placenta. To reveal the superimposing alterations in placental proteins that might explain the pathophysiology of PE, we performed 2-DE MALDI-TOF MS/MS proteomics analysis of differentially expressed placental proteins with placenta from eight normal and eight preeclamptic pregnancies. The identified proteins were confirmed by Western blot analysis. We also performed morphologic evaluation of preeclamptic placentas under both electron and light microscopy. The results disclosed the marked overexpression of chaperonin 60, GST, VDAC, ERp29, and cathepsin D in PE. These proteomics findings clearly suggest the possible cellular battle against mitochondria-originated oxidative stress during PE that either end up with recovery or apoptosis. These results provide a better understanding of proteomic alterations and may help in clarification of stress-related changes in preeclamptic placentas.     

One integral characteristic of the set of genetic codes. The property of all known natural codes

Earlier, this author introduced the integral characteristics of the genetic code (“Integral characteristics of the genetic code,” Mathematical Modeling, vol. 22, no. 9, 2010). One of these characteristics that is correlated to the potential of a code for building overlapping genes, when the same piece of DNA encodes two protein sequences, is considered here. This is an investigation of a variety of genetic codes that corresponds to two groups of such codes. First of all, the hypothetical codes were considered and this has allowed the establishment of a range of changes in this characteristic by the use of different numbers of codon permutations in the standard genetic code. The second group of codes is the natural genetic codes. It has turned out that all of the known natural codes today (currently, 15) have one common property. This property is formulated. Note that the first natural standard code was found in the human cell in 1979, in a separate organelle—in mitochondria.     

Food vacuole proteome of the malarial parasite Plasmodium falciparum

The Plasmodium falciparum food vacuole (FV) is a lysosome-like organelle where erythrocyte hemoglobin digestion occurs. It is a favorite target in the development of antimalarials. We have used a tandem mass spectrometry approach to investigate the proteome of an FV-enriched fraction and identified 116 proteins. The electron microscopy analysis and the Western blot data showed that the major component of the fraction was the FV and, as expected, the majority of previously known FV markers were recovered. Of particular interest, several proteins involved in vesicle-mediated trafficking were identified, which are likely to play a key role in FV biogenesis and/or FV protein trafficking. Recovery of parasite surface proteins lends support to the cytostomal pathway of hemoglobin ingestion as a FV trafficking route. We have identified 32 proteins described as hypothetical in the databases. This insight into FV protein content provides new clues towards understanding the biological function of this organelle in P. falciparum.     

聚集诱导发光探针对模拟微重力下线粒体膜电位的监测及探针-水凝胶三维成像体系的构建

空间特殊环境会引起宇航员机体损伤，机体生理指标的监测对损伤机制和保护手段的研究至关重要。人体长期处于微重力环境，会引起线粒体功能紊乱。线粒体膜电位是线粒体功能是否正常的重要参考指标，因此，快速、简便地监测模拟微重力环境下线粒体膜电位具有重要意义。该文利用线粒体靶向聚集诱导发光探针 TPE-Ph-In 实现了对细胞的免洗和长周期染色，以及在微重力环境下对线粒体膜电位的成像监测。此外，为克服长时间微重力环境下细胞贴壁不牢固的问题，利用水凝胶 Matrigel 包裹细胞进行培养，用 TPE-Ph-In 进行成像，构建了 AIE 探针-水凝胶 3D 成像体系。该文为探究细胞的微重力效应提供了新的研究方法与思路。     

Computational approaches to predicting essential proteins: A survey

Essential proteins are indispensable to support cellular life. Identifying essential proteins can help us understand the minimal requirements for cell survival, which plays a significant role in the emerging field of synthetic biology. Moreover, essential proteins also serve as candidates of drug targets for developing novel therapy of diseases, such as cancer or infectious disease caused by emerging pathogens. However, it is expensive and time consuming to experimentally identify essential proteins. With accumulation of sequenced genomes, the gap between genome-wide essential protein data and sequence data become increasingly wide. Thus, computational approaches for detecting essential proteins are useful complements to limited experimental methods. There are many features related to protein essentiality. By taking advantage of these features, many computational approaches have been proposed to identify essential proteins. In this paper, we review the state-of-the-art techniques for computational detection of essential proteins, and discuss some challenges for future research in this field.     

HCV inhibits antigen processing and presentation and induces oxidative stress response in gastric mucosa

Productive hepatitis C virus (HCV) infection appears to be primarily confined to the liver. However, a wide variety of extrahepatic disease manifestations are associated with the infection and HCV RNA has been frequently detected in gastric mucosa. The present study aims to determine molecular alterations present in vivo in the stomach where HCV expression does not induce a carcinoma but a lymphoma, thus extending the knowledge of alterations in intracellular pathways consequent to HCV infection. We compared, by 2-D DIGE, the gastric protein expression profile from six HCV positive and six HCV negative samples lacking neoplastic or dysplastic conditions. In HCV positive tissue we observed a down regulation of proteins involved in MHC maturation and assembly, antigen processing and presentation and ER stress, in addition to an up regulation of proteins involved in cellular oxidative stress responses. Ubiquinol-cytochrome-C-reductase (UQCRFS1), part of the mitochondrial respiratory chain complex-III, was identified as the most up regulated protein. Data were confirmed by Western blot and immunohistochemistry. Our results demonstrate a HCV negative influence on the different pathways that determine antigen processing and presentation via MHC-I and the cellular attempts to counteract HCV induced oxidative stress. Both these processes facilitate immune escape and cell survival and probably contribute to HCV chronicization.     

基于模块度优化的蛋白质网络集团探测与分析

探测蛋白质相互作用网络中的功能模块对于理解生物系统的组织和功能具有重要的意义。目前,普遍的做法是将蛋白质相互作用网络表示成一个图,利用各种图聚类算法来挖掘功能模块。本文采用了基于模块度优化的图聚类算法来探测蛋白质相互作用网络中的集团,从具有2617个节点11855个相互作用的酵母蛋白相互作用网络中探测出68个集团。对于得到的集团,首先从拓扑结构的角度验证其的确是内部连接稠密的子图,然后分析了MIPS数据库中ComplexCat提供的已知的蛋白质复合体与这些集团的重叠情况,发现很多蛋白质复合体完全包含在某些集团中,最后使用超几何聚集分布的P值来分析一个集团对某个特定功能的富集程度,并根据最小的P值对应的功能来注释该集团的主要功能,发现集团中大部分的蛋白质具有相同的功能。研究结果表明,该方法探测的集团具有重要的生物学功能意义。     

Detection of cardiac wall motion asynchrony by computer analysis techniques

Digital image processing is emerging as an increasingly important modality in the evolution of different types of image acquisition and analysis in cardiology. It has become an integral element in the technologies that are being developped and explored. New mathematical concepts in the assessment of cardiac function have been applied to digital images of the heart. Among them, the measurement of temporal changes in regional wall motion of the heart using Fourier analysis led to a significant improvement in the detection of regional alterations of ventricular function. Several imaging modalities can benefit from this approach for the assessment of the temporal sequence of cardiac wall motion.     

K-Means Clustering Versus Validation Measures: A Data-Distribution Perspective

K-means is a well-known and widely used partitional clustering method. While there are considerable research efforts to characterize the key features of the K-means clustering algorithm, further investigation is needed to understand how data distributions can have impact on the performance of K-means clustering. To that end, in this paper, we provide a formal and organized study of the effect of skewed data distributions on K-means clustering. Along this line, we first formally illustrate that K-means tends to produce clusters of relatively uniform size, even if input data have varied “true” cluster sizes. In addition, we show that some clustering validation measures, such as the entropy measure, may not capture this uniform effect and provide misleading information on the clustering performance. Viewed in this light, we provide the coefficient of variation (CV) as a necessary criterion to validate the clustering results. Our findings reveal that K-means tends to produce clusters in which the variations of cluster sizes, as measured by CV, are in a range of about 0.3–1.0. Specifically, for data sets with large variation in “true” cluster sizes (e.g., $ hbox{CV} ≫ 1.0$), K-means reduces variation in resultant cluster sizes to less than 1.0. In contrast, for data sets with small variation in “true” cluster sizes (e.g., $hbox{CV} ≪ 0.3$), K-means increases variation in resultant cluster sizes to greater than 0.3. In other words, for the earlier two cases, K-means produces the clustering results which are away from the “true” cluster distributions.      

Profiling the potential biomarkers for cell differentiation of pancreatic cancer using iTRAQ and 2-D LC-MS/MS

Pancreatic cancer is a highly lethal disease that is difficult to diagnose at early stage and even more difficult to cure. SW1990 and PANC-1 represent the two cancer cell lines, which are both derived from pancreatic duct, but at different cell differentiation stages. In this study, we applied the iTRAQ-labeling technology and 2-D strong cation exchange/reversed phase liquid chromatography – LC-MS/MS) to profile the secreted proteins of SW1990 and PANC-1 cells in a conditioned cell culture medium. A total of 401 proteins were identified by MS/MS and protein database searching, the percentages of these proteins predicted in the categories of plasma membrane, intracellular and secreted proteins were 29.2, 32.7 and 38.2%, respectively. Fifty six proteins were identified with unknown functions and 19 proteins were quantified with significant level changes between the two cancer cell lines under the specific cell condition with 12 proteins being up-regulated (>1.3-fold change) in PANC-1 (e.g. FLJ31222 protein, 97 kDa protein, type IV collagenase precursor, 38 kDa protein and centaurin) and seven proteins being up-regulated in SW1990 (e.g. fibroblast growth factor receptor substrate 2, putative p150, hypothetical protein LOC 654463 and LOC 55701). The proteins with significant level changes may provide a baseline to investigate mechanisms underlying the differentiation of two cell lines and can be further screened for better protein biomarkers in pancreatic cancer.     

Biomarkers for cardiovascular risk assessment in autoimmune diseases

Autoimmune diseases, such as antiphospholipid syndrome, systemic lupus erythematosus, and rheumatoid arthritis, are characterized by a high prevalence of cardiovascular (CV) disease (CVD), which constitutes the leading causes of morbidity and mortality among such patients. Although such effects are partly explained by a higher prevalence of traditional CV risk factors, many studies indicate that such factors do not fully explain the enhanced CV risk in these patients. In addition, risk stratification algorithms based upon traditional CV risk factors are not as predictive in autoimmune diseases as in the general population. For these reasons, the timely and accurate assessment of CV risk in these high-risk populations still remains an unmet clinical need. An enhanced contribution of different inflammatory components of the immune response, as well as autoimmune elements (e.g. autoantibodies, autoantigens, and cellular response), has been proposed to underlie the incremental CV risk observed in these populations. Recent advances in proteomic tools have contributed to the discovery of proteins involved in CVDs, including some that may be suitable to be used as biological markers. In this review we summarize the main markers in the field of CVDs associated with autoimmunity, as well as the recent advances in proteomic technology and their application for biomarker discovery in autoimmune disease.     

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.