Current Proteomics - Volume 11, Issue 4, 2014

Development of a transgenic animal model always is followed by extensive characterization steps. Here, we intended to test and optimize a fast screening method to get general findings about the differential protein composition in the heart of wild type (WT) and transgenic (TG) mice. Therefore, we developed a protocol for magnetic bead-based separation (MB) combined with Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDITOF MS) for protein profiling in plasma and cardiac tissue from TG and WT mice. We studied tissues from mice with cardiac specific overexpression of the catalytic subunit of PP2A, a model system for cardiac hypertrophy. EDTA-plasma or an extract of homogenized cardiac tissue (or skeletal muscle as control) were fractionated by hydrophobic interaction (MB-HIC C8) or weak cation exchange (MB-WCX) chromatography. MALDI-TOF MS spectra were generated in the mass range of m/z 1000-80000 using different matrices. The number of mass signals in the cardiac tissue extract was critically dependent on the use of the homogenization buffer, the residual blood contamination, and the surface modification of the magnetic beads. We noted different profiles in cardiac homogenates from WT compared to TG. As a control, the profile in skeletal muscle was not different between WT and TG. The results indicate that proteome profiling using MB-based sample preparation combined with MALDI-TOF MS is suitable for the proteome profiling in cardiac tissue of transgenic mice.

Proteins are the second largest portion of a cell after water, playing a wide variety of key roles in the cellular activities. Due to low-efficiency in determining protein functions, however, accurately and cost-effectively identifying functions of a protein is still one of major challenge in the post-genomics era. In an attempt to close this gap, we presented a novel neighborhood model to predict protein functions from protein-protein interaction data. The new method takes into consideration functions of directly interacting proteins as well as ones of indirectly interacting proteins, and also weighted interactions. The jackknife test on 4662 proteins in the S.cerevisiae shows that our method outperforms other two neighborhood models: the neighbor counting method and Chi-square method. The experimental results also show that the functional information of indirectly interacting proteins are greatly decayed to infer protein function, and the function categories involving interactions are predicted with higher accuracy than those not involving interactions.

The water buffalo is a native species in Asia, and is considered to be a work animal. But because of an inherent defect, it has a low reproductive efficiency. This study presents research on the proteome of the water buffalo testis, a better understanding of which is very important for reproduction. 1-D SDS-PAGE and Reverse Phase Liquid chromatography mass spectrum (RPLC-MS/MS) were utilized, and 1383 proteins in water buffalo testis were identified. Bioinformatics analysis indicated that 26 proteins take part in testis-specific processes which could be crucial for testis functions. Some of these proteins take part in oxidative phosphorylation, which is a significant enrichment pathway for producing energy for the cell reproduction, division and androgen generation. There are some antioxidant proteins identified which can provide protection against the action of reactive oxygen species (ROS). This broad view of the proteins in water buffalo testis will provide a reference for future research on improving the water buffalo’s reproductive efficiency.

The purpose of this research work was to investigate whether such a workflow including the phosphoproteins enriched by affinity purification, isolated and quantified by two-dimensional difference gel electrophoresis, the differential protein spots identified by mass spectrometry, was suitable to dissect the intact phosphoprotein profile that mediated cell signaling pathways. Endothelial cells with or without vascular endothelial growth factor (VEGF) induction were used in the experiment. The accidental error introduced by enrichment column was assayed by control-to-control 2D-DIGE analysis and the efficiency of the workflow was tested by control-to-sample 2D-DIGE analysis. The data indicated that a high level of accidental error was introduced by different phosphoprotein enrichment columns and could be reduced by slowing down the flow rate of the mobile phase at the expense of sensitivity and specificity of enrichment column. Dephosphorylation did not occur for most high abundance phosphoproteins based on the sensitivity of 2D-DIGE detection. The advantage of this workflow was that multiple phosphorylated proteins could be visualized on the 2D-gel directly, but DIGE minimal label only quantified the limited high or medium abundance phosphoproteins. The sensitivity and accuracy of 2D-DIGE measurement were still not good enough to dissect the intact phosphoprotein profile that involved in cell signal pathway. Consequently, phosphoproteomic laboratory workflow based on phosphoproteins enrichment strategy combined with 2D-DIGE quantification does not have enough sensitivity and accuracy to dissect the intact phosphoprotein profile that mediated cell signaling pathways. Low abundance and ionization of the phosphopeptides are the main reasons that lead to the failure of protein identification even if the phosphoproteins were enriched.

Lyme disease is caused by the spirochete Borrelia burgdorferi which enters into the skin by feeding ticks, mainly Ixodes species. Spread of the pathogen into the blood results in various symptoms. Because some individuals do not show any symptom following the infection, it is very difficult to diagnose the infection caused by this spirochete. When a proper treatment is not provided, this infection subsequently evolves to severe neurologic, joint, skin and cardiac abnormalities. Outer surface protein A (OspA) from B. burgdorferi has been the considered for the development of vaccine against Lyme disease. Even though the native form of OspA antigen is an active vaccine, some side effects are associated with it. For instance musculoskeletal arthritis in humans and severe, destructive osteoarthropathy in hamsters are the major sides effects detected in vaccinated animals. C-terminal region of OspA antigen has been suggested to be used alone as a second generation vaccine because all anti-OspA antibodies responsible for blocking Borrelia bind to Cterminal region only. In the present study an attempt is made to truncate N-terminal region of OspA antigen followed by modeling the interaction between truncated homology modelled antigen with native antibody using in silico approaches. The 3D models of full length OspA antigen as well as of all its truncated forms have been predicted through homology modeling approach. Docking of homology remodelled structure onto the native antibody (1FJ1_AB) was successful. MD simulation for 10ns was used for calculating the binding free energy of four selected antigen-antibody models under explicit solvent conditions.

Under the environmental stress condition, protein folding or refolding has become an important issue for the survival of any microorganism. In majority of bacteria, such as Escherichia coli, temperature downshift leads to a transient arrest of cell growth, which results in inhibition of general protein synthesis. However, syntheses of a number of proteins, called cold-shock proteins are induced under these conditions. These proteins minimize secondary structure folding and acts as DNA or RNA chaperons. In the present study, to understand the mechanism of CSPs and to identify the key residues involved in nucleic acid binding, we generated homology model of cold shock protein homologs from CspB to CspI of Escherichia coli using Modeler 9v1. The modeled homologs were docked with potential ligand and protein-ligand interactions were studied using program, GLIDE. Docking results revealed that several basic and aromatic amino acid residues are conserved on the ligand binding surface of CSP homolog and aromatic residues that are essentially required for nucleic acid binding, also play important role in protein stability and protein folding inhibition.

Recent developments in bioinformatics have highlighted the importance of protein structure prediction for which information about structure classes forms the foundation and plays an important role in the prediction of protein folds and tertiary structure. The majority of previous researches have focused on only four protein classes in the Structure Classification of Proteins (SCOP) database. In this paper, we focused mainly on finding the best performing prediction method using SCOP—extended (SCOPe, Release 2.03; previously known as version 1.75C in SCOP), which contains seven major protein classes, including all-α proteins, all-β proteins, α/β proteins, α+β proteins, multi-domain proteins, membrane and cell surface proteins and peptides, and small proteins. The framework that we developed consists of two stages: in the first stage we used a hybrid frequency method for feature extraction from a SCOPe dataset, and in the second stage, we calculated an effective parameter (number of trees) for the Random Forest Classifier. Our computational results on the SCOPe dataset demonstrate the efficiency and effectiveness of our model that generated predictions with an accuracy of 88%, which is much higher than the accuracies reported in previous studies. These encouraging results may be helpful for future research on protein structure and protein fold prediction. Our codes are available in http://datamining.xmu.edu.cn/~zhaoxuewei/PSP.