ON THE UNIVERSALITY OF 2-DIMENSIONAL DIFFUSION-LIMITED DEPOSITION

A history dependent stick probability is introduced to the diffusion-limited deposition model. The exponents in the scaling laws are calculated. The universality class is also discussed.

Profiling excretory/secretory proteins of Trichinella spiralis muscle larvae by two-dimensional gel electrophoresis and mass spectrometry

Infection of mammalian skeletal muscle with the intracellular parasite Trichinella spiralis results in profound alterations in the host cell and a realignment of host cell gene expression. The role of parasite excretory/secretory (E/S) products in mediating these effects is unknown, largely due to the difficulty in identifying and assigning function to individual proteins. In this study, we have used two-dimensional electrophoresis to analyse the profile of muscle larva excreted/secreted proteins and have coupled this to protein identification using MALDI-TOF mass spectrometry. Interpretation of the peptide mass fingerprint data has relied primarily on the interrogation of a custom-made Trichinella EST database and the NemaGene cluster database for T. spiralis. Our results suggest that this proteomic approach is a useful tool to study protein expression in Trichinella spp. and will contribute to the identification of excreted/secreted proteins.

Proteomic analysis of coronary sinus serum reveals leucine-rich α2-glycoprotein as a novel biomarker of ventricular dysfunction and heart failure

BACKGROUND: Heart failure (HF) prevention strategies require biomarkers that identify disease manifestation. Increases in B-type natriuretic peptide (BNP) correlate with increased risk of cardiovascular events and HF development. We hypothesize that coronary sinus serum from a high BNP hypertensive population reflects an active pathological process and can be used for biomarker exploration. Our aim was to discover differentially expressed disease-associated proteins that identify patients with ventricular dysfunction and HF.

METHODS AND RESULTS: Coronary sinus serum from 11 asymptomatic, hypertensive patients underwent quantitative differential protein expression analysis by 2-dimensional difference gel electrophoresis. Proteins were identified using mass spectrometry and then studied by enzyme-linked immunosorbent assay in sera from 40 asymptomatic, hypertensive patients and 105 patients across the spectrum of ventricular dysfunction (32 asymptomatic left ventricular diastolic dysfunction, 26 diastolic HF, and 47 systolic HF patients). Leucine-rich α2-glycoprotein (LRG) was consistently overexpressed in high BNP serum. LRG levels correlate significantly with BNP in hypertensive, asymptomatic left ventricular diastolic dysfunction, diastolic HF, and systolic HF patient groups (P≤0.05). LRG levels were able to identify HF independent of BNP. LRG correlates with coronary sinus serum levels of tumor necrosis factor-α (P=0.009) and interleukin-6 (P=0.021). LRG is expressed in myocardial tissue and correlates with transforming growth factor-βR1 (P<0.001) and α-smooth muscle actin (P=0.025) expression.

CONCLUSIONS: LRG was identified as a serum biomarker that accurately identifies patients with HF. Multivariable modeling confirmed that LRG is a stronger identifier of HF than BNP and this is independent of age, sex, creatinine, ischemia, β-blocker therapy, and BNP.

Proteomic profiling of human retinal pigment epithelium exposed to an advanced glycation-modified substrate

Purpose The retinal pigment epithelium (RPE) and underlying Bruch’s membrane undergo significant modulation during ageing. Progressive, age-related modifications of lipids and proteins by advanced glycation end products (AGEs) at this cell–substrate interface have been implicated in RPE dysfunction and the progression to age-related macular degeneration (AMD). The pathogenic nature of these adducts in Bruch’s membrane and their influence on the overlying RPE remains unclear. This study aimed to identify alterations in RPE protein expression in cells exposed to AGE-modified basement membrane (AGE-BM), to determine how this “aged” substrate impacts RPE function and to map the localisation of identified proteins in ageing retina. Methods Confluent ARPE-19 monolayers were cultured on AGE-BM and native, non-modified BM (BM). Following 28-day incubation, the proteome was profiled using 2-dimensional gel electrophoresis (2D), densitometry and image analysis was employed to map proteins of interest that were identified by electrospray ionisation mass spectrometry (ESI MS/MS). Immunocytochemistry was employed to localise identified proteins in ARPE-19 monolayers cultured on unmodified and AGE-BM and to analyze aged human retina. Results Image analysis detected altered protein spot densities between treatment groups, and proteins of interest were identified by LC ESI MS/MS which included heat-shock proteins, cytoskeletal and metabolic regulators. Immunocytochemistry revealed deubiquitinating enzyme ubiquitin carboxyterminal hydrolase-1 (UCH-L1), which was upregulated in AGE-exposed RPE and was also localised to RPE in human retinal sections. Conclusions This study has demonstrated that AGE-modification of basement membrane alters the RPE proteome. Many proteins are changed in this ageing model, including UCHL-1, which could impact upon RPE degradative capacity. Accumulation of AGEs at Bruch”s membrane could play a significant role in age-related dysfunction of the RPE.

Somatic hybrids of higher plants obtained from amiprophosmethyl-resistant mutant Nicotiniana plumbaginifolia

Interspecific and intertribal somatic hybrids were obtained to study the composition and function of microtubules in hybrid plants. The amiprophosmethyl-resistant mutant Nicotiana plumbaginifolia L. was used as donor; canamycin-resistant mutants N. sylvestris L. and Atropa belladonna served as recipients. Cytogenetic analysis confirmed the hybrid nature of the clones selected. Immunoflourescent analysis showed that constitutions of mitotic spindles in regenerating protoplast, isolated from the hybrid NpAb-107 and the mutant N. plunbaginifolia, show no change after a 2-hour treatment with 5 mu M of amiprophosmethyl; in A. belladonna, the division spindle is completely destroyed under these conditions. Tubulin was isolated from the hybrid NpAb-107 and separated by two-dimensional electrophoresis. The results showed that NpAb-107 has the beta-tubulin isoform specific for N. plumbaginifolia in addition to all isoforms of A. belladonna.

Proteomic analysis reveals oxidative stress response as the main adaptative physiological mechanism in cows under different production systems

Three groups of cows representing three ranges of welfare in the production system were included in the study: two groups of Bruna dels Pirineus beef cattle maintained under different management systems (good and semiferal conditions) and a group of Alberes cows, a breed that lives in the mountains (hardest conditions).

In order to identify new stress/welfare biomarkers, serum from Bruna cows living in both environments was subjected to DIGE labelling, two-dimensional electrophoresis and MALDI-MS or ion trap MS. Identification was achieved for 15 proteins, which mainly belonged to three biological functions, the oxidative stress pathway (glutathione peroxidase (GPx) and paraoxonase (PON-1)), the acute phase protein family (Heremans Schmid glycoprotein alpha2 (α2-HSG)) and the complement system.

Biological validation included the Alberes breed. GPx and PON-1 were validated by an enzymatic assay and found to be higher and lower, respectively, in cows living in hard conditions. α2-HSG was validated by ELISA and found to be reduced in hard conditions. Other biomarkers of the redox status were also altered by living conditions: protein carbonyl content, superoxide dismutase (SOD) and glutathione reductase (GR).

Our results show that changes in the redox system are the main adaptation of cows living in challenging environmental conditions. This article is part of a Special Issue entitled: “Farm animal proteomics”.

Proteomic Analysis of Recurrent Joint Inflammation in Juvenile Idiopathic Arthritis

The synovial fluid proteome in juvenile idiopathic arthritis was investigated to isolate joint-specific biomarkers that are expressed in patients displaying recurrent joint inflammation. To identify the synovial specific proteome, matched synovial fluid and plasma samples were subjected to protein separation by 2-dimension electrophoresis (2DE). Forty-three protein spots, overexpressed in the joint, were identified. Synovial fluids from children with single-event knee joint inflammation were then compared with a group with recurrent knee disease. Nine synovial specific proteins were significantly differentially expressed in the recurrent group. Proteolytic fragments of collagen X, fibrin beta-chain, and T-cell receptor alpha-region have been identified among this protein cluster. Putative biomarkers, overexpressed in the joint and differentially expressed in children with recurrent joint inflammation, have been identified. These proteins may play a significant role determining the pathological state within the chronically inflamed joint and influence disease progression in JIA. This is the first study of the synovial proteome in children.

Quantum-information processing for a coherent superposition state via a mixed entangled coherent channel

An entangled two-mode coherent state is studied within the framework of 2 x 2-dimensional Hilbert space. An entanglement concentration scheme based on joint Bell-state measurements is worked out. When the entangled coherent state is embedded in vacuum environment, its entanglement is degraded but not totally lost. It is found that the larger the initial coherent amplitude, the faster entanglement decreases. We investigate a scheme to teleport a coherent superposition state while considering a mixed quantum channel. We find that the decohered entangled coherent state may be useless for quantum teleportation as it gives the optimal fidelity of teleportation less than the classical limit 2/3.

Phase and space resolved optical emission spectroscopic investigations of an inductively coupled RF plasma using an imaging acousto-optic spectrometer

A novel acousto-optic spectrometer (IfU Diagnostic Systems GmbH) for 2-dimensional (2D) optical emission spectroscopy with high spectral resolution has been developed. The spectrometer is based on acousto-optic tuneable filter technology with fast random wavelength access. Measurements for characterisation of the imaging quality, the spatial resolution, and the spectral resolution are presented. The applicability for 2D-space and phase resolved optical emission spectroscopy (2D-PROES) is shown. 2D-PROES has been applied to an inductively coupled plasma with radio frequency excitation at 13.56 MHz.

Stratification and Monitoring of Juvenile Idiopathic Arthritis Patients by Synovial Proteome Analysis

Juvenile idiopathic arthritis (JIA) comprises a poorly understood group of chronic, childhood onset, autoimmune diseases with variable clinical outcomes. We investigated whether profiling of the synovial fluid (SF) proteome by a fluorescent dye based, two-dimensional gel (DIGE) approach could distinguish patients in whom inflammation extends to affect a large number of joints, early in the disease process. SF samples from 22 JIA patients were analyzed: 10 with oligoarticular arthritis, 5 extended oligoarticular and 7 polyarticular disease. SF samples were labeled with Cy dyes and separated by two-dimensional electrophoresis. Multivariate analyses were used to isolate a panel of proteins which distinguish patient subgroups. Proteins were identified using MALDI-TOF mass spectrometry with expression further verified by Western immunoblotting and immunohistochemistry. Hierarchical clustering based on the expression levels of a set of 40 proteins segregated the extended oligoarticular from the oligoarticular patients (p <0.05). Expression patterns of the isolated protein panel have also been observed over time, as disease spreads to multiple joints. The data indicates that synovial fluid proteome profiles could be used to stratify patients based on risk of disease extension. These protein profiles may also assist in monitoring therapeutic responses over time and help predict joint damage. © 2009 American Chemical Society.

Novel breast cancer biomarkers identified by integrative proteomic and gene expression mapping

Proteomic and transcriptomic platforms both play important roles in cancer research, with differing strengths and limitations. Here, we describe a proteo-transcriptomic integrative strategy for discovering novel cancer biomarkers, combining the direct visualization of differentially expressed proteins with the high-throughput scale of gene expression profiling. Using breast cancer as a case example, we generated comprehensive two-dimensional electrophoresis (2DE)/mass spectrometry (MS) proteomic maps of cancer (MCF-7 and HCC-38) and control (CCD-1059Sk) cell lines, identifying 1724 expressed protein spots representing 484 different protein species. The differentially expressed cell-line proteins were then mapped to mRNA transcript databases of cancer cell lines and primary breast tumors to identify candidate biomarkers that were concordantly expressed at the gene expression level. Of the top nine selected biomarker candidates, we reidentified ANX1, a protein previously reported to be differentially expressed in breast cancers and normal tissues, and validated three other novel candidates, CRAB, 6PGL, and CAZ2, as differentially expressed proteins by immunohistochemistry on breast tissue microarrays. In total, close to half (4/9) of our protein biomarker candidates were successfully validated. Our study thus illustrates how the systematic integration of proteomic and transcriptomic data from both cell line and primary tissue samples can prove advantageous for accelerating cancer biomarker discovery.

Hierarchical Bayesian models in ecology: Reconstructing species interaction networks from non-homogeneous species abundance data

The relationships among organisms and their surroundings can be of immense complexity. To describe and understand an ecosystem as a tangled bank, multiple ways of interaction and their effects have to be considered, such as predation, competition, mutualism and facilitation. Understanding the resulting interaction networks is a challenge in changing environments, e.g. to predict knock-on effects of invasive species and to understand how climate change impacts biodiversity. The elucidation of complex ecological systems with their interactions will benefit enormously from the development of new machine learning tools that aim to infer the structure of interaction networks from field data. In the present study, we propose a novel Bayesian regression and multiple changepoint model (BRAM) for reconstructing species interaction networks from observed species distributions. The model has been devised to allow robust inference in the presence of spatial autocorrelation and distributional heterogeneity. We have evaluated the model on simulated data that combines a trophic niche model with a stochastic population model on a 2-dimensional lattice, and we have compared the performance of our model with L1-penalized sparse regression (LASSO) and non-linear Bayesian networks with the BDe scoring scheme. In addition, we have applied our method to plant ground coverage data from the western shore of the Outer Hebrides with the objective to infer the ecological interactions. (C) 2012 Elsevier B.V. All rights reserved.