Integrating domain similarity to improve protein complexes identification in TAP-MS data

Background

Detecting protein complexes in protein-protein interaction (PPI) networks plays an important role in improving our understanding of the dynamic of cellular organisation. However, protein interaction data generated by high-throughput experiments such as yeast-two-hybrid (Y2H) and tandem affinity-purification/mass-spectrometry (TAP-MS) are characterised by the presence of a significant number of false positives and false negatives. In recent years there has been a growing trend to incorporate diverse domain knowledge to support large-scale analysis of PPI networks.

Methods

This paper presents a new algorithm, by incorporating Gene Ontology (GO) based semantic similarities, to detect protein complexes from PPI networks generated by TAP-MS. By taking co-complex relations in TAP-MS data into account, TAP-MS PPI networks are modelled as bipartite graph, where bait proteins consist of one set of nodes and prey proteins are on the other. Similarities between pairs of bait proteins are computed by considering both the topological features and GO-driven semantic similarities. Bait proteins are then grouped in to sets of clusters based on their pair-wise similarities to produce a set of 'seed' clusters. An expansion process is applied to each 'seed' cluster to recruit prey proteins which are significantly associated with the same set of bait proteins. Thus, completely identified protein complexes are then obtained.

Results

The proposed algorithm has been applied to real TAP-MS PPI networks. Fifteen quality measures have been employed to evaluate the quality of generated protein complexes. Experimental results show that the proposed algorithm has greatly improved the accuracy of identifying complexes and outperformed several state-of-the-art clustering algorithms. Moreover, by incorporating semantic similarity, the proposed algorithm is more robust to noises in the networks.

     

M-Finder: Uncovering functionally associated proteins from interactome data integrated with GO annotations

Background

Protein-protein interactions (PPIs) play a key role in understanding the mechanisms of cellular processes. The availability of interactome data has catalyzed the development of computational approaches to elucidate functional behaviors of proteins on a system level. Gene Ontology (GO) and its annotations are a significant resource for functional characterization of proteins. Because of wide coverage, GO data have often been adopted as a benchmark for protein function prediction on the genomic scale.

Results

We propose a computational approach, called M-Finder, for functional association pattern mining. This method employs semantic analytics to integrate the genome-wide PPIs with GO data. We also introduce an interactive web application tool that visualizes a functional association network linked to a protein specified by a user. The proposed approach comprises two major components. First, the PPIs that have been generated by high-throughput methods are weighted in terms of their functional consistency using GO and its annotations. We assess two advanced semantic similarity metrics which quantify the functional association level of each interacting protein pair. We demonstrate that these measures outperform the other existing methods by evaluating their agreement to other biological features, such as sequence similarity, the presence of common Pfam domains, and core PPIs. Second, the information flow-based algorithm is employed to discover a set of proteins functionally associated with the protein in a query and their links efficiently. This algorithm reconstructs a functional association network of the query protein. The output network size can be flexibly determined by parameters.

Conclusions

M-Finder provides a useful framework to investigate functional association patterns with any protein. This software will also allow users to perform further systematic analysis of a set of proteins for any specific function. It is available online at http://bionet.ecs.baylor.edu/mfinder

     

Rapid sampling of local minima in protein energy surface and effective reduction through a multi-objective filter

Background

Many problems in protein modeling require obtaining a discrete representation of the protein conformational space as an ensemble of conformations. In ab-initio structure prediction, in particular, where the goal is to predict the native structure of a protein chain given its amino-acid sequence, the ensemble needs to satisfy energetic constraints. Given the thermodynamic hypothesis, an effective ensemble contains low-energy conformations which are similar to the native structure. The high-dimensionality of the conformational space and the ruggedness of the underlying energy surface currently make it very difficult to obtain such an ensemble. Recent studies have proposed that Basin Hopping is a promising probabilistic search framework to obtain a discrete representation of the protein energy surface in terms of local minima. Basin Hopping performs a series of structural perturbations followed by energy minimizations with the goal of hopping between nearby energy minima. This approach has been shown to be effective in obtaining conformations near the native structure for small systems. Recent work by us has extended this framework to larger systems through employment of the molecular fragment replacement technique, resulting in rapid sampling of large ensembles.

Methods

This paper investigates the algorithmic components in Basin Hopping to both understand and control their effect on the sampling of near-native minima. Realizing that such an ensemble is reduced before further refinement in full ab-initio protocols, we take an additional step and analyze the quality of the ensemble retained by ensemble reduction techniques. We propose a novel multi-objective technique based on the Pareto front to filter the ensemble of sampled local minima.

Results and conclusions

We show that controlling the magnitude of the perturbation allows directly controlling the distance between consecutively-sampled local minima and, in turn, steering the exploration towards conformations near the native structure. For the minimization step, we show that the addition of Metropolis Monte Carlo-based minimization is no more effective than a simple greedy search. Finally, we show that the size of the ensemble of sampled local minima can be effectively and efficiently reduced by a multi-objective filter to obtain a simpler representation of the probed energy surface.

     

B-cell depletion in SLE: clinical and trial experience with rituximab and ocrelizumaband implications for study design

B cells are believed to be central to the disease process in systemic lupuserythematosus (SLE), making them a target for new therapeutic intervention. In recentyears there have been many publications regarding the experience in SLE of B-celldepletion utilising rituximab, an anti-CD20 mAb that temporarily depletes B cells,reporting promising results in uncontrolled open studies and in routine clinical use.However, the two large randomised controlled trials in extra-renal lupus (EXPLORERstudy) and lupus nephritis (LUNAR study) failed to achieve their primary endpoints.Based on the clinical experience with rituximab this failure was somewhat unexpectedand raised a number of questions and concerns, not only into the true level ofbenefit of B-cell depletion in a broad population but also how to test the true levelof effectiveness of an investigational agent as we seek to improve the design oftherapeutic trials in SLE. A better understanding of what went wrong in these trialsis essential to elucidate the underlying reasons for the disparate observations notedin open studies and controlled trials. In this review, we focus on various factorsthat may affect the ability to accurately and confidently establish the level oftreatment effect of the investigational agent, in this case rituximab, in the twostudies and explore hurdles faced in the randomised controlled trials investigatingthe efficacy of ocrelizumab, the humanised anti-CD20 mAb, in SLE. Further, based onthe lessons learned from the clinical trials, we make suggestions that could beimplemented in future clinical trial design to overcome the hurdles faced.     

HMPAS: Human Membrane Protein Analysis System

Background

Membrane proteins perform essential roles in diverse cellular functions and are regarded as major pharmaceutical targets. The significance of membrane proteins has led to the developing dozens of resources related with membrane proteins. However, most of these resources are built for specific well-known membrane protein groups, making it difficult to find common and specific features of various membrane protein groups.

Methods

We collected human membrane proteins from the dispersed resources and predicted novel membrane protein candidates by using ortholog information and our membrane protein classifiers. The membrane proteins were classified according to the type of interaction with the membrane, subcellular localization, and molecular function. We also made new feature dataset to characterize the membrane proteins in various aspects including membrane protein topology, domain, biological process, disease, and drug. Moreover, protein structure and ICD-10-CM based integrated disease and drug information was newly included. To analyze the comprehensive information of membrane proteins, we implemented analysis tools to identify novel sequence and functional features of the classified membrane protein groups and to extract features from protein sequences.

Results

We constructed HMPAS with 28,509 collected known membrane proteins and 8,076 newly predicted candidates. This system provides integrated information of human membrane proteins individually and in groups organized by 45 subcellular locations and 1,401 molecular functions. As a case study, we identified associations between the membrane proteins and diseases and present that membrane proteins are promising targets for diseases related with nervous system and circulatory system. A web-based interface of this system was constructed to facilitate researchers not only to retrieve organized information of individual proteins but also to use the tools to analyze the membrane proteins.

Conclusions

HMPAS provides comprehensive information about human membrane proteins including specific features of certain membrane protein groups. In this system, user can acquire the information of individual proteins and specified groups focused on their conserved sequence features, involved cellular processes, and diseases. HMPAS may contribute as a valuable resource for the inference of novel cellular mechanisms and pharmaceutical targets associated with the human membrane proteins. HMPAS is freely available at http://fcode.kaist.ac.kr/hmpas.

     

The use of proton pump inhibitors in treating and preventing NSAID-induced mucosal damage

NSAIDs are prescribed widely but have rare serious gastrointestinal side effects. More recently, adverse cardiovascular effects of these drugs have also been recognized, leading to the withdrawal of some agents and continuing uncertainty about the best approach for patients requiring NSAID therapy. Proton pump inhibitors (PPIs) provide potent and long-lasting inhibition of gastric acid secretion and have proven efficacy in healing NSAID-associated ulcers, including those with continued exposure to NSAIDs. PPIs have also shown efficacy in reducing the risk of ulcerations due to NSAID use compared with NSAIDs alone in randomized controlled trials (RCTs) where endoscopic ulcers are used as the primary endpoint, albeit a surrogate marker for clinical ulcers and complications. Large RCT outcome trials comparing patients exposed to NSAIDs with and without PPI co-therapy have not been performed, but adequately powered RCTs in high-risk patients demonstrate that PPI + nonselective NSAID provides similar rates of symptomatic ulcer recurrence rates as the use of a cyclooxygenase (COX)-2 selective inhibitor. A RCT in high-risk patients with previous ulcer complications supports the additive bene3 t of two risk-reducing strategies, as ulcer complication recurrence was eliminated in high-risk patients who were given a COX-2 selective agent with a PPI. Helicobacter pylori, an independent risk factor for ulcers, should be sought out and eradicated in patients at increased gastrointestinal risk, typically those with an ulcer history. Following H. pylori eradication, however, patients remain at risk and co-therapy with a PPI is recommended. NSAID medication selection should consider both the individual patients' gastrointestinal and cardiovascular risks.     

The use of H2 antagonists in treating and preventing NSAID-induced mucosal damage

Pain affects the quality of life for millions of individuals and is a major reason for healthcare utilization. As populations age, medical personnel will need to manage more and more patients suffering from pain associated with degenerative and inflammatory musculoskeletal disorders. Nonsteroidal anti-inflammatory drugs (NSAIDs) are an effective treatment for both acute and chronic musculoskeletal pain; however, their use is associated with potentially significant gastrointestinal (GI) toxicity. Guidelines suggest various strategies to prevent problems in those at risk for NSAID-associated GI complications. In this article, we review the data supporting one such strategy - the use of histamine type-2 receptor antagonists (H2RAs) - for the prevention of GI adverse events in NSAID users. Older studies suggest that high-dose H2RAs are effective in preventing upper GI ulcers and dyspepsia. This suggestion was recently confirmed during clinical trials with a new ibuprofen/famotidine combination that reduced the risk of ulcers by 50% compared with ibuprofen alone.     

Ion-current-based Proteomic Profiling of the Retina in a Rat Model of Smith-Lemli-Opitz Syndrome

Smith-Lemli-Opitz syndrome (SLOS) is one of the most common recessive human disorders and is characterized by multiple congenital malformations as well as neurosensory and cognitive abnormalities. A rat model of SLOS has been developed that exhibits progressive retinal degeneration and visual dysfunction; however, the molecular events underlying the degeneration and dysfunction remain poorly understood. Here, we employed a well-controlled, ion-current-based approach to compare retinas from the SLOS rat model to retinas from age- and sex-matched control rats (n = 5/group). Retinas were subjected to detergent extraction and subsequent precipitation and on-pellet-digestion procedures and then were analyzed on a long, heated column (75 cm, with small particles) with a 7-h gradient. The high analytical reproducibility of the overall proteomics procedure enabled reliable expression profiling. In total, 1,259 unique protein groups, ∼40% of which were membrane proteins, were quantified under highly stringent criteria, including a peptide false discovery rate of 0.4%, with high quality ion-current data (e.g. signal-to-noise ratio ≥ 10) obtained independently from at least two unique peptides for each protein. The ion-current-based strategy showed greater quantitative accuracy and reproducibility over a parallel spectral counting analysis. Statistically significant alterations of 101 proteins were observed; these proteins are implicated in a variety of biological processes, including lipid metabolism, oxidative stress, cell death, proteolysis, visual transduction, and vesicular/membrane transport, consistent with the features of the associated retinal degeneration in the SLOS model. Selected targets were further validated by Western blot analysis and correlative immunohistochemistry. Importantly, although photoreceptor cell death was validated by TUNEL analysis, Western blot and immunohistochemical analyses suggested a caspase-3-independent pathway. In total, these results provide compelling new evidence implicating molecular changes beyond the initial defect in cholesterol biosynthesis in this retinal degeneration model, and they might have broader implications with respect to the pathobiological mechanism underlying SLOS.Smith-Lemli-Opitz syndrome (SLOS)¹ is an autosomal recessive disorder associated with subnormal growth and failure to thrive, mental retardation and neurosensory deficits, and multiple congenital anomalies, including dysmorphologies (1, 2). Early epidemiological studies estimated the incidence of SLOS as 1 in 20,000 to 1 in 60,000 live births, primarily among Caucasians (1, 2). However, more recent studies suggest that the SLOS carrier frequency is ∼1 in 30 to 1 in 50; this predicts a much higher actual disease frequency, ranging from 1 in 1,590 to 1 in 17,000 (3, 4), making SLOS the fourth most common autosomal recessive human disease (after cystic fibrosis, phenylketonuria, and hemochromatosis). Mutation of the DHCR7 gene is the intrinsic cause of SLOS; this gene encodes the enzyme DHCR7 (3β-hydroxysterol-Δ7-reductase, a.k.a. 7-dehydrocholesterol reductase; EC1.3.1.21), which catalyzes the final step in the cholesterol biosynthetic pathway, reducing the Δ7 double bond and thus converting 7-dehydrocholesterol (7DHC) to cholesterol (4, 5). As a consequence, markedly reduced levels of cholesterol and aberrantly elevated levels of the cholesterol precursor 7DHC (and its epimer, 8DHC) are observed in the majority of affected SLOS patients (6, 7). Therefore, the clinical suspicion of SLOS is confirmed by elevated 7DHC in plasma or tissues, typically demonstrated via chromatographic methods (e.g. HPLC or GC/MS) (8, 9).Visual capacity may become compromised in SLOS patients because of a variety of congenital or postnatal pathologies, such as cataracts, aniridia, corneal endothelium defects, sclerocornea, electrophysiological defects in the retina, optic nerve abnormalities, or other ophthalmologic problems (10, 11). We currently lack full knowledge of the exact pathobiological mechanism underlying SLOS, but additional insights may be afforded by studies employing a rodent model of the disease in which rats are treated with AY9944 (trans-1,4-bis[2-chlorobenzylaminomethyl] cyclohexane dihydrochloride), a relatively selective inhibitor of DHCR7 (12–14). We previously described progressive retinal degeneration in this rat model of SLOS, which is characterized by the shortening of retinal rod outer segments, pyknosis and thinning of the outer nuclear layer (ONL) of the retina (which contains the photoreceptor nuclei), and accumulation of membranous/lipid inclusions in the retinal pigment epithelium (RPE) (12, 13). Reduced rod outer segment membrane fluidity, primarily caused by a dramatic (30 to 40 mol%) decline in docosahexaenoic acid (22:6, n3) levels relative to age-matched controls, also was observed in the SLOS rat model by three postnatal months (15, 16). Retinal function and sterol steady-state in the same rat model of SLOS can be partially rescued using a high-cholesterol diet (2% by weight), although histological degeneration of the retina still occurs (17). However, the molecular mechanisms that underlie the observed electrophysiological defects in the retina, the accumulation of membranous/lipid inclusions in the RPE, the shortening of retinal rod outer segments, and the initiation of ONL pyknosis in the SLOS rat model remain poorly understood. Therefore, a comprehensive profiling of the retinal proteomes of AY9944-treated versus age-matched untreated control rats may contribute to further understanding of the underlying mechanisms responsible for the retinopathy associated with the SLOS model and, by extension, the human disease.Nevertheless, extensive and reliable expression profiling of the retinal proteome remains a prominent challenge, owing to the need to quantify data from multiple animals and a high percentage of integral membrane and membrane-associated proteins (18, 19). Label-free approaches can compare multiple replicates (20–22) with quantitative accuracy comparable to that attained with stable isotope-labeling methods (23–25). However, in order to achieve reliable relative quantification, highly quantitative and reproducible sample preparation and LC/MS analysis are required for relatively large-scale sample cohorts.In the present study, we performed a reproducible, well-controlled, ion-current-based comparative proteomic analysis of the retinas from AY9944-treated versus age/sex-matched control rats (n = 5 animals per group). A high-concentration detergent mixture was used for the efficient extraction of proteins from retinas, and samples then underwent a reproducible precipitation/on-pellet-digestion procedure and long-column, 7-h nano-LC-MS analysis. These approaches ensured extensive comparative analysis of retina samples with 10 animals. The preparative and analytical procedures were carefully optimized and controlled to ensure optimal reproducibility. Two label-free approaches, the ion-current-based method and a spectral counting method, were compared in parallel. The altered proteins were subjected to functional annotation, and selected groups of proteins of interest were further validated by means of Western blot and correlative immunohistochemical analysis.     

Nitrate signals determine the sensing of nitrogen through differential expression of genes involved in nitrogen uptake and assimilation in finger millet

In order to understand the molecular basis of high nitrogen use efficiency of finger millet, five genes (EcHNRT2, EcLNRT1, EcNADH-NR, EcGS, and EcFd-GOGAT) involved in nitrate uptake and assimilation were isolated using conserved primer approaches. Expression profiles of these five genes along with the previously isolated EcDof1 was studied under increased KNO₃ concentrations (0.15 to 1,500 μM) for 2 h as well as at 1.5 μM for 24 h in the roots and shoots of 25 days old nitrogen deprived two contrasting finger millet genotypes (GE-3885 and GE-1437) differing in grain protein content (13.76 and 6.15 %, respectively). Time kinetics experiment revealed that, all the five genes except EcHNRT2 in the leaves of GE-3885 were induced within 30 min of nitrate exposure indicating that there might be a greater nitrogen deficit in leaves and therefore quick transportation of nitrate signals to the leaves. Exposing the plants to increasing nitrate concentrations for 2 h showed that in roots of GE-3885, NR was strongly induced while GS was repressed; however, the pattern was found to be reversed in leaves of GE-1437 indicating that in GE-3885, most of the nitrate might be reduced in the roots but assimilated in leaves and vice-versa. Furthermore, compared with the low-protein genotype, expression of HNRT2 was strongly induced in both roots and shoots of high-protein genotype at the least nitrate concentration supplied. This further indicates that GE-3885 is a quick sensor of nitrogen compared with the low-protein genotype. Furthermore, expression of EcDof1 was also found to overlap the expression of NR, GS, and GOGAT indicating that Dof1 probably regulates the expression of these genes under different conditions by sensing the nitrogen fluctuations around the root zone.