2,819 research outputs found
Improved prediction of RNA secondary structure by integrating the free energy model with restraints derived from experimental probing data.
PublishedEvaluation StudiesJournal ArticleResearch Support, Non-U.S. Gov'tRecently, several experimental techniques have emerged for probing RNA structures based on high-throughput sequencing. However, most secondary structure prediction tools that incorporate probing data are designed and optimized for particular types of experiments. For example, RNAstructure-Fold is optimized for SHAPE data, while SeqFold is optimized for PARS data. Here, we report a new RNA secondary structure prediction method, restrained MaxExpect (RME), which can incorporate multiple types of experimental probing data and is based on a free energy model and an MEA (maximizing expected accuracy) algorithm. We first demonstrated that RME substantially improved secondary structure prediction with perfect restraints (base pair information of known structures). Next, we collected structure-probing data from diverse experiments (e.g. SHAPE, PARS and DMS-seq) and transformed them into a unified set of pairing probabilities with a posterior probabilistic model. By using the probability scores as restraints in RME, we compared its secondary structure prediction performance with two other well-known tools, RNAstructure-Fold (based on a free energy minimization algorithm) and SeqFold (based on a sampling algorithm). For SHAPE data, RME and RNAstructure-Fold performed better than SeqFold, because they markedly altered the energy model with the experimental restraints. For high-throughput data (e.g. PARS and DMS-seq) with lower probing efficiency, the secondary structure prediction performances of the tested tools were comparable, with performance improvements for only a portion of the tested RNAs. However, when the effects of tertiary structure and protein interactions were removed, RME showed the highest prediction accuracy in the DMS-accessible regions by incorporating in vivo DMS-seq data.National Key Basic Research Program of China [2012CB316503]; National High-Tech Research and Development Program of China [2014AA021103]; National Natural Science Foundation of China [31271402]; Tsinghua University Initiative Scientific Research Program [2014z21045]; Hong Kong Research Grants Council Early Career Scheme [419612 to K.Y.]; National Science Foundation [1339282 to D.H.M.]; Computing Platform of the National Protein Facilities (Tsinghua University). Funding for open access charge: National Natural Science Foundation of China [31271402]
Mild autonomic dysfunction in primary Sjögren's syndrome: a controlled study
Introduction The aim of this study was to compare cardiovascular autonomic nervous system function in patients with primary Sjögren's syndrome (pSS) with that in control individuals, and to correlate the findings with autonomic symptoms and the presence of exocrine secretory dysfunction. Methods Twenty-seven female patients with pSS and 25 control individuals completed the COMPASS (Composite Autonomic Symptom Scale) self-reported autonomic symptom questionnaire. Beat-to-beat heart rate and blood pressure data in response to five standard cardiovascular reflex tests were digitally recorded using a noninvasive finger pressure cuff and heart rate variability was analyzed by Fourier spectral analysis. Analysis was performed by analysis of variance (ANOVA), multivariate ANOVA and repeated measures ANOVA, as indicated. Factor analysis was utilized to detect relationships between positive autonomic symptoms in pSS patients. Results Multiple, mild autonomic disturbances were observed in pSS patients relating to decreased heart rate variability, decreased blood pressure variability and increased heart rate, which were most evident in response to postural change. There was a strong trend toward an association between decreased heart rate variability and increased severity of the secretomotor, orthostatic, bladder, gastroparesis and constipation self-reported autonomic symptom cluster identified in pSS patients. This symptom cluster was also associated with fatigue and reduced unstimulated salivary flow, and therefore may be an important component of the clinical spectrum of this disease. Conclusion There was evidence of mild autonomic dysfunction in pSS as measured with both cardiovascular reflex testing and self-reported symptoms. Pathogenic autoantibodies targeting M3 muscarinic receptors remain a strong candidate for the underlying pathophysiology, but practical assays for the detection of this autoantibody remain elusive.Fin ZJ Cai, Sue Lester, Tim Lu, Helen Keen, Karyn Boundy, Susanna M Proudman, Anne Tonkin and Maureen Rischmuelle
Identification of Colletotrichum species associated with anthracnose disease of coffee in Vietnam
Colletotrichum gloeosporioides, C. acutatum, C. capsici and C. boninense associated with anthracnose disease on coffee (Coffea spp.) in Vietnam were identified based on morphology and DNA analysis. Phylogenetic analysis of DNA sequences from the internal transcribed spacer region of nuclear rDNA and a portion of mitochondrial small subunit rRNA were concordant and allowed good separation of the taxa. We found several Colletotrichum isolates of unknown species and their taxonomic position remains unresolved. The majority of Vietnamese isolates belonged to C. gloeosporioides and they grouped together with the coffee berry disease (CBD) fungus, C. kahawae. However, C. kahawae could be distinguished from the Vietnamese C. gloeosporioides isolates based on ammonium tartrate utilization, growth rate and pathogenictity. C. gloeosporioides isolates were more pathogenic on detached green berries than isolates of the other species, i.e. C. acutatum, C capsici and C. boninense. Some of the C. gloeosporioides isolates produced slightly sunken lesion on green berries resembling CBD symptoms but it did not destroy the bean. We did not find any evidence of the presence of C. kahawae in Vietnam
RNAstructure: software for RNA secondary structure prediction and analysis
<p>Abstract</p> <p>Background</p> <p>To understand an RNA sequence's mechanism of action, the structure must be known. Furthermore, target RNA structure is an important consideration in the design of small interfering RNAs and antisense DNA oligonucleotides. RNA secondary structure prediction, using thermodynamics, can be used to develop hypotheses about the structure of an RNA sequence.</p> <p>Results</p> <p>RNAstructure is a software package for RNA secondary structure prediction and analysis. It uses thermodynamics and utilizes the most recent set of nearest neighbor parameters from the Turner group. It includes methods for secondary structure prediction (using several algorithms), prediction of base pair probabilities, bimolecular structure prediction, and prediction of a structure common to two sequences. This contribution describes new extensions to the package, including a library of C++ classes for incorporation into other programs, a user-friendly graphical user interface written in JAVA, and new Unix-style text interfaces. The original graphical user interface for Microsoft Windows is still maintained.</p> <p>Conclusion</p> <p>The extensions to RNAstructure serve to make RNA secondary structure prediction user-friendly. The package is available for download from the Mathews lab homepage at <url>http://rna.urmc.rochester.edu/RNAstructure.html</url>.</p
Bioconjugates of Glucose Oxidase and Gold Nanorods Based on Electrostatic Interaction with Enhanced Thermostability
Bioconjugates made up of an enzyme and gold nanorods (GNRs) were fabricated by electrostatic interactions (layer-by-layer method, LBL) between anionic glucose oxidase (GOD) and positively charged GNRs. The assembled processes were monitored by UV–Vis spectra, zeta potential measurements, and transmission electron microscopy. The enzyme activity assays of the obtained bioconjugates display a relatively enhanced thermostability behavior in contrast with that of free enzyme. Free GOD in solution only retains about 22% of its relative activity at 90 °C. Unexpectedly, the immobilized GOD on GNRs still retains about 39.3% activity after the same treatment. This work will be of significance for the biologic enhancement using other kinds of anisotropic nanostructure and suggests a new way of enhancing enzyme thermostability using anisotropic metal nanomaterials
From Nonspecific DNA–Protein Encounter Complexes to the Prediction of DNA–Protein Interactions
©2009 Gao, Skolnick. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.doi:10.1371/journal.pcbi.1000341DNA–protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA–protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA–protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA–protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA–protein interaction modes exhibit some similarity to specific DNA–protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Ca deviation from native is up to 5 Å from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA–protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein
Tripeptide tyroserleutide plus doxorubicin: therapeutic synergy and side effect attenuation
<p>Abstract</p> <p>Background</p> <p>Tripeptide tyroserleutide (YSL) is a novel small molecule anti-tumor polypeptide that has been shown to inhibit the growth of human liver cancer cells. In this study, we investigated the effects of YSL plus doxorubicin on the growth of human hepatocellular carcinoma BEL-7402 cells that had been transplanted into nude mice.</p> <p>Methods</p> <p>Nude mice bearing human hepatocellular carcinoma BEL-7402 tumors were treated with successive intraperitoneal injections of saline; low-, mid-, or high-dose doxorubicin; or low-, mid-, or high-dose doxorubicin plus YSL. Effects on the weight and volume of the tumors were evaluated.</p> <p>Results</p> <p>Co-administration of YSL and high-dose doxorubicin (6 mg/kg every other day) prolonged the survival time of tumor-bearing mice as compared to high-dose doxorubicin alone. As well, the anti-tumor effects of mid- and low-dose doxorubicin (2 and 0.7 mg/kg every other day, respectively) were enhanced when supplemented with YSL; the tumor growth inhibition rates for YSL plus doxorubicin were greater than the inhibition rates for the same dosages of doxorubicin alone. The combination of YSL and doxorubicin decreased chemotherapy-associated weight loss, leukocyte depression, and heart, liver, and kidney damage as compared to doxorubicin alone.</p> <p>Conclusion</p> <p>The combination of YSL plus doxorubicin enhances the anti-tumor effect and reduces the side effects associated with doxorubicin chemotherapy.</p
MysiRNA-designer: a workflow for efficient siRNA design
The design of small interfering RNA (siRNA) is a multi factorial problem that has gained the attention of many researchers in the area of therapeutic and functional genomics. MysiRNA score was previously introduced that improves the correlation of siRNA activity prediction considering state of the art algorithms. In this paper, a new program, MysiRNA-Designer, is described which integrates several factors in an automated work-flow considering mRNA transcripts variations, siRNA and mRNA target accessibility, and both near-perfect and partial off-target matches. It also features the MysiRNA score, a highly ranked correlated siRNA efficacy prediction score for ranking the designed siRNAs, in addition to top scoring models Biopredsi, DISR, Thermocomposition21 and i-Score, and integrates them in a unique siRNA score-filtration technique. This multi-score filtration layer filters siRNA that passes the 90% thresholds calculated from experimental dataset features. MysiRNA-Designer takes an accession, finds conserved regions among its transcript space, finds accessible regions within the mRNA, designs all possible siRNAs for these regions, filters them based on multi-scores thresholds, and then performs SNP and off-target filtration. These strict selection criteria were tested against human genes in which at least one active siRNA was designed from 95.7% of total genes. In addition, when tested against an experimental dataset, MysiRNA-Designer was found capable of rejecting 98% of the false positive siRNAs, showing superiority over three state of the art siRNA design programs. MysiRNA is a freely accessible (Microsoft Windows based) desktop application that can be used to design siRNA with a high accuracy and specificity. We believe that MysiRNA-Designer has the potential to play an important role in this area
Differential Dynamics of Transposable Elements during Long-Term Diploidization of Nicotiana Section Repandae (Solanaceae) Allopolyploid Genomes
PubMed ID: 23185607This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
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