Predicting beta-turns in proteins using support vector machines with fractional polynomials

Background

β-turns are secondary structure type that have essential role in molecular recognition, protein folding, and stability. They are found to be the most common type of non-repetitive structures since 25% of amino acids in protein structures are situated on them. Their prediction is considered to be one of the crucial problems in bioinformatics and molecular biology, which can provide valuable insights and inputs for the fold recognition and drug design.

Results

We propose an approach that combines support vector machines (SVMs) and logistic regression (LR) in a hybrid prediction method, which we call (H-SVM-LR) to predict β-turns in proteins. Fractional polynomials are used for LR modeling. We utilize position specific scoring matrices (PSSMs) and predicted secondary structure (PSS) as features. Our simulation studies show that H-SVM-LR achieves Qtotal of 82.87%, 82.84%, and 82.32% on the BT426, BT547, and BT823 datasets respectively. These values are the highest among other β-turns prediction methods that are based on PSSMs and secondary structure information. H-SVM-LR also achieves favorable performance in predicting β-turns as measured by the Matthew's correlation coefficient (MCC) on these datasets. Furthermore, H-SVM-LR shows good performance when considering shape strings as additional features.

Conclusions

In this paper, we present a comprehensive approach for β-turns prediction. Experiments show that our proposed approach achieves better performance compared to other competing prediction methods.

     

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.

     

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.     

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.     

Isolation of Novel Afipia septicemium and Identification of Previously Unknown Bacteria Bradyrhizobium sp. OHSU_III from Blood of Patients with Poorly Defined Illnesses

Cultures previously set up for isolation of mycoplasmal agents from blood of patients with poorly-defined illnesses, although not yielding positive results, were cryopreserved because of suspicion of having low numbers of unknown microbes living in an inactive state in the broth. We re-initiated a set of 3 cultures for analysis of the "uncultivable" or poorly-grown microbes using NGS technology. Broth of cultures from 3 blood samples, submitted from OHSU between 2000 and 2004, were inoculated into culture flasks containing fresh modified SP4 medium and kept at room temperature (RT), 30°C and 35°C. The cultures showing evidence of microbial growth were expanded and subjected to DNA analysis by genomic sequencing using Illumina MiSeq. Two of the 3 re-initiated blood cultures kept at RT after 7–8 weeks showed evidence of microbial growth that gradually reached into a cell density with detectable turbidity. The microbes in the broth when streaked on SP4 agar plates produced microscopic colonies in ∼ 2 weeks. Genomic studies revealed that the microbes isolated from the 2 blood cultures were a novel Afipia species, tentatively named Afipia septicemium. Microbes in the 3^rd culture (OHSU_III) kept at RT had a limited level of growth and could not reach a plateau with high cell density. Genomic sequencing identified the microbe in the culture as a previously unknown species of Bradyrhizobium bacteria. This study reports on the isolation of novel Afipia and Bradyrhizobium species. Isolation of Bradyrhizobium species bacteria has never been reported in humans. The study also reveals a previously unrecognized nature of hematogenous infections by the 2 unique groups of Bradyrhizobiaceae. Our studies show that improvement of culture system plus effective use of NGS technology can facilitate findings of infections by unusual microbes in patients having poorly-defined, sometimes mysterious illnesses.     

Quantitative and Temporal Control of Oxygen Microenvironment at the Single Islet Level

Simultaneous oxygenation and monitoring of glucose stimulus-secretion coupling factors in a single technique is critical for modeling pathophysiological states of islet hypoxia, especially in transplant environments. Standard hypoxic chamber techniques cannot modulate both stimulations at the same time nor provide real-time monitoring of glucose stimulus-secretion coupling factors. To address these difficulties, we applied a multilayered microfluidic technique to integrate both aqueous and gas phase modulations via a diffusion membrane. This creates a stimulation sandwich around the microscaled islets within the transparent polydimethylsiloxane (PDMS) device, enabling monitoring of the aforementioned coupling factors via fluorescence microscopy. Additionally, the gas input is controlled by a pair of microdispensers, providing quantitative, sub-minute modulations of oxygen between 0-21%. This intermittent hypoxia is applied to investigate a new phenomenon of islet preconditioning. Moreover, armed with multimodal microscopy, we were able to look at detailed calcium and K_ATP channel dynamics during these hypoxic events. We envision microfluidic hypoxia, especially this simultaneous dual phase technique, as a valuable tool in studying islets as well as many ex vivo tissues.     

Bayesian Phylogeography of Crimean-Congo Hemorrhagic Fever Virus in Europe

Crimean-Congo hemorrhagic fever (CCHF) is a zoonosis mainly transmitted by ticks that causes severe hemorrhagic fever and has a mortality rate of 5-60%. The first outbreak of CCHF occurred in the Crimean peninsula in 1944-45 and it has recently emerged in the Balkans and eastern Mediterranean. In order to reconstruct the origin and pathway of the worldwide dispersion of the virus at global and regional (eastern European) level, we investigated the phylogeography of the infection by analysing 121 publicly available CCHFV S gene sequences including two recently characterised Albanian isolates. The spatial and temporal phylogeny was reconstructed using a Bayesian Markov chain Monte Carlo approach, which estimated a mean evolutionary rate of 2.96 x 10^-4 (95%HPD=1.6 and 4.7 x 10^-4) substitutions/site/year for the analysed fragment. All of the isolates segregated into seven highly significant clades that correspond to the known geographical clades: in particular the two new isolates from northern Albania clustered significantly within the Europe 1 clade. Our phylogeographical reconstruction suggests that the global CCHFV clades originated about one thousand years ago from a common ancestor probably located in Africa. The virus then spread to Asia in the XV century and entered Europe on at least two occasions: the first in the early 1800s, when a still circulating but less or non-pathogenic virus emerged in Greece and Turkey, and the second in the early 1900s, when a pathogenic CCHFV strain began to spread in eastern Europe. The most probable location for the origin of this European clade 1 was Russia, but Turkey played a central role in spreading the virus throughout Europe. Given the close proximity of the infected areas, our data suggest that the movement of wild and domestic ungulates from endemic areas was probably the main cause of the dissemination of the virus in eastern Europe.     

Multiple Sclerosis in the Mount Etna Region: Possible Role of Volcanogenic Trace Elements

Background

Trace elements have been hypothesised to be involved in the pathogenesis of Multiple Sclerosis and volcanic degassing is the major natural sources of trace elements. Both incidence of Multiple Sclerosis in Catania and volcanic activity of Mount Etna have been significantly increased during the last 30 years. Due to prevailing trade winds direction, volcanic gases from Etna summit craters are mostly blown towards the eastern and southern sectors of the volcano.

Objective

To evaluate the possible association between Multiple Sclerosis and exposure to volcanogenic trace elements.

Methods

We evaluated prevalence and incidence of Multiple Sclerosis in four communities (47,234 inhabitants) located in the eastern flank and in two communities (52,210 inhabitants) located in the western flank of Mount Etna, respectively the most and least exposed area to crater gas emissions.

Results

A higher prevalence was found in the population of the eastern flank compared to the population of the western one (137.6/100,000 versus 94.3/100,000; p-value 0.04). We found a borderline significantly higher incidence risk during the incidence study period (1980–2009) in the population of the eastern flank 4.6/100,000 (95% CI 3.1–5.9), compared with the western population 3.2/100,000 (95% CI 2.4–4.2) with a RR of 1.41 (95% CI 0.97–2.05; p-value 0.06). Incidence risks have increased over the time in both populations reaching a peak of 6.4/100,000 in the eastern flank and of 4.4/100.000 in the western flank during 2000–2009.

Conclusion

We found a higher prevalence and incidence of Multiple Sclerosis among populations living in the eastern flank of Mount Etna. According to our data a possible role of TE cannot be ruled out as possible co-factor in the MS pathogenesis. However larger epidemiological study are needed to confirm this hypothesis.