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Computational Biology
Evaluation of KDR rs34231037 as a predictor of sunitinib efficacy in patients with metastatic renal cell carcinoma
Apr 21, 2017   Pharmacogenetics And Genomics
Apellániz-Ruiz M, Diekstra MH, Roldán JM, Boven E, Castellano D, Gelderblom H, Mathijssen RHJ, Swen JJ, Böhringer S, García-Donás J, Rini BI, Guchelaar HJ, Rodríguez-Antona C
Evaluation of KDR rs34231037 as a predictor of sunitinib efficacy in patients with metastatic renal cell carcinoma
Apr 21, 2017
Pharmacogenetics And Genomics
The identification of biomarkers able to predict clinical benefit from vascular endothelial growth factor receptor (VEGFR) tyrosine kinase inhibitors is urgently needed. Recently, Maitland and colleagues described an association between KDR-rs34231037 and soluble VEGFR2 levels as well as pazopanib pharmacodynamics. We investigated in a well-characterized series of metastatic clear cell renal cell carcinoma patients whether rs34231037 could influence sunitinib response. Clinical data and DNA were available from an international series of 276 patients. KDR-rs34231037 association with sunitinib response, clinical benefit, and progression-free survival was analyzed using logistic and Cox regression analyses. We found that G-allele carriers were over-represented among patients with clinical benefit during sunitinib treatment compared with those refractory to the treatment (odds ratio: 3.78; 95% confidence interval: 1.02-14.06; P=0.047, multivariable analysis). In conclusion, rs34231037 variant carriers seemed to have better sunitinib response than wild-type patients. Moreover, the association with tumor size reduction suggests that this single nucleotide polymorphism might also identify patients with successful tumor downsizing under anti-VEGFR therapy.
DNAproDB: an interactive tool for structural analysis of DNA-protein complexes
Apr 21, 2017   Nucleic Acids Research
Sagendorf JM, Berman HM, Rohs R
DNAproDB: an interactive tool for structural analysis of DNA-protein complexes
Apr 21, 2017
Nucleic Acids Research
Many biological processes are mediated by complex interactions between DNA and proteins. Transcription factors, various polymerases, nucleases and histones recognize and bind DNA with different levels of binding specificity. To understand the physical mechanisms that allow proteins to recognize DNA and achieve their biological functions, it is important to analyze structures of DNA-protein complexes in detail. DNAproDB is a web-based interactive tool designed to help researchers study these complexes. DNAproDB provides an automated structure-processing pipeline that extracts structural features from DNA-protein complexes. The extracted features are organized in structured data files, which are easily parsed with any programming language or viewed in a browser. We processed a large number of DNA-protein complexes retrieved from the Protein Data Bank and created the DNAproDB database to store this data. Users can search the database by combining features of the DNA, protein or DNA-protein interactions at the interface. Additionally, users can upload their own structures for processing privately and securely. DNAproDB provides several interactive and customizable tools for creating visualizations of the DNA-protein interface at different levels of abstraction that can be exported as high quality figures. All functionality is documented and freely accessible at http://dnaprodb.usc.edu. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
Role of the Ion Channel Extracellular Collar in AMPA Receptor Gating
Apr 22, 2017   Scientific Reports
Yelshanskaya MV, Mesbahi-Vasey S, Kurnikova MG, Sobolevsky AI
Role of the Ion Channel Extracellular Collar in AMPA Receptor Gating
Apr 22, 2017
Scientific Reports
AMPA subtype ionotropic glutamate receptors mediate fast excitatory neurotransmission and are implicated in numerous neurological diseases. Ionic currents through AMPA receptor channels can be allosterically regulated via different sites on the receptor protein. We used site-directed mutagenesis and patch-clamp recordings to probe the ion channel extracellular collar, the binding region for noncompetitive allosteric inhibitors. We found position and substitution-dependent effects for introduced mutations at this region on AMPA receptor gating. The results of mutagenesis suggested that the transmembrane domains M1, M3 and M4, which contribute to the ion channel extracellular collar, undergo significant relative displacement during gating. We used molecular dynamics simulations to predict an AMPA receptor open state structure and rationalize the results of mutagenesis. We conclude that the ion channel extracellular collar plays a distinct role in gating and represents a hub for powerful allosteric modulation of AMPA receptor function that can be used for developing novel therapeutics.
Low-cost, Low-bias and Low-input RNA-seq with High Experimental Verifiability based on Semiconductor Sequencing
Apr 22, 2017   Scientific Reports
Mai Z, Xiao C, Jin J, Zhang G
Low-cost, Low-bias and Low-input RNA-seq with High Experimental Verifiability based on Semiconductor Sequencing
Apr 22, 2017
Scientific Reports
Low-input RNA-seq is powerful to represent the gene expression profiles with limited number of cells, especially when single-cell variations are not the aim. However, pre-amplification-based and molecule index-based library construction methods boost bias or require higher throughput. Here we demonstrate a simple, low-cost, low-bias and low-input RNA-seq with ion torrent semiconductor sequencing (LIEA RNA-seq). We also developed highly accurate and error-tolerant spliced mapping algorithm FANSe2splice to accurately map the single-ended reads to the reference genome with better experimental verifiability than the previous spliced mappers. Combining the experimental and computational advancements, our solution is comparable with the bulk mRNA-seq in quantification, reliably detects splice junctions and minimizes the bias with much less mappable reads.
Toward a direct and scalable identification of reduced models for categorical processes
Apr 22, 2017   Proceedings Of The National Academy Of Sciences Of The United States Of America
Gerber S, Horenko I
Toward a direct and scalable identification of reduced models for categorical processes
Apr 22, 2017
Proceedings Of The National Academy Of Sciences Of The United States Of America
The applicability of many computational approaches is dwelling on the identification of reduced models defined on a small set of collective variables (colvars). A methodology for scalable probability-preserving identification of reduced models and colvars directly from the data is derived-not relying on the availability of the full relation matrices at any stage of the resulting algorithm, allowing for a robust quantification of reduced model uncertainty and allowing us to impose a priori available physical information. We show two applications of the methodology: (i) to obtain a reduced dynamical model for a polypeptide dynamics in water and (ii) to identify diagnostic rules from a standard breast cancer dataset. For the first example, we show that the obtained reduced dynamical model can reproduce the full statistics of spatial molecular configurations-opening possibilities for a robust dimension and model reduction in molecular dynamics. For the breast cancer data, this methodology identifies a very simple diagnostics rule-free of any tuning parameters and exhibiting the same performance quality as the state of the art machine-learning applications with multiple tuning parameters reported for this problem.
Automated quantitative characterisation of retinal vascular leakage and microaneurysms in ultra-widefield fluorescein angiography
Apr 22, 2017   The British Journal Of Ophthalmology
Ehlers JP, Wang K, Vasanji A, Hu M, Srivastava SK
Automated quantitative characterisation of retinal vascular leakage and microaneurysms in ultra-widefield fluorescein angiography
Apr 22, 2017
The British Journal Of Ophthalmology
Ultra-widefield fluorescein angiography (UWFA) is an emerging imaging modality used to characterise pathology in the retinal vasculature such as microaneurysms (MAs) and vascular leakage. Despite its potential value for diagnosis and disease surveillance, objective quantitative assessment of retinal pathology by UWFA is currently limited because it requires laborious manual segmentation by trained human graders. In this report, we describe a novel fully automated software platform, which segments MAs and leakage areas in native and dewarped UWFA images with retinal vascular disease. Comparison of the algorithm with human grader-generated gold standards demonstrated significant strong correlations for MA and leakage areas (intraclass correlation coefficient (ICC)=0.78-0.87 and ICC=0.70-0.86, respectively, p=2.1×10-7 to 3.5×10-10 and p=7.8×10-6 to 1.3×10-9, respectively). These results suggest the algorithm performs similarly to human graders in MA and leakage segmentation and may be of significant utility in clinical and research settings. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Molecular cloning and functional characterization of duck nucleotide-binding oligomerization domain 1 (NOD1)
Apr 22, 2017   Developmental And Comparative Immunology
Li H, Jin H, Li Y, Liu D, Foda MF, Jiang Y, Luo R
Molecular cloning and functional characterization of duck nucleotide-binding oligomerization domain 1 (NOD1)
Apr 22, 2017
Developmental And Comparative Immunology
Nucleotide-binding oligomerization domain 1 (NOD1) is an imperative cytoplasmic pattern recognition receptor (PRR) and considered as a key member of the NOD-like receptor (NLR) family which plays a critical role in innate immunity through sensing microbial components derived from bacterial peptidoglycan. In the current study, the full-length of duck NOD1 (duNOD1) cDNA from duck embryo fibroblasts (DEFs) was cloned. Multiple sequence alignment and phylogenetic analysis demonstrated that duNOD1 exhibited a strong evolutionary relationship with chicken and rock pigeon NOD1. Tissue-specific expression analysis showed that duNOD1 was widely distributed in various organs, with the highest expression observed in the liver. Furthermore, duNOD1 overexpression induced NF-κB activation in DEFs and the CARD domain is crucial for duNOD1-mediated NF-κB activation. In addition, silencing the duNOD1 decreased the activity of NF-κB in DEFs stimulated by iE-DAP. Overexpression of duNOD1 significantly increased the expression of TNF-α, IL-6, and RANTES in DEFs. These findings highlight the crucial role of duNOD1 as an intracellular sensor in duck innate immune system. Copyright © 2017. Published by Elsevier Ltd.
Cardiac computed tomography-derived myocardial mass at risk using the Voronoi-based segmentation algorithm: A histological validation study
Apr 22, 2017   Journal Of Cardiovascular Computed Tomography
Ide S, Sumitsuji S, Yamaguchi O, Sakata Y
Cardiac computed tomography-derived myocardial mass at risk using the Voronoi-based segmentation algorithm: A histological validation study
Apr 22, 2017
Journal Of Cardiovascular Computed Tomography
Myocardial mass at risk (MMAR) is an important predictor of adverse cardiac events in patients with ischemic heart disease. This study aims to validate the accuracy of MMAR calculated from cardiac computed tomography (CCT) data using the Voronoi-based segmentation algorithm in comparison with actual MMAR measured on ex-vivo swine hearts prepared by injecting a dye into the coronary arteries. Fifteen extracted swine hearts had India ink injected into one of the major coronary arteries. Subsequently, all coronary arteries manually injected with methylcellulose-based iohexiol-370 were imaged by 16-row CT. The ventricles were cross-sectioned perpendicularly to the long axis of the left ventricle (LV). The stained area and the total LV area of individual slices were measured, and actual MMAR was calculated as the ratio of the LV volume with the disc-summation method. CT-based MMAR of each coronary artery was calculated automatically with the Voronoi-based segmentation algorithm. The results were compared using Pearson's correlation coefficient. The median value of CT-based MMAR was 50.8% for the left anterior descending artery (LAD), 36.6% for the left circumflex artery (LCX), and 23.0% for the right coronary artery (RCA). Actual MMAR was 49.8% for LAD, 32.2% for LCX, and 25.9% for RCA. CT-based MMAR was significantly related to actual MMAR (r = 0.92, p = 0.02 for LAD; r = 0.96, p = 0.009 for LCX; r = 0.96, p = 0.009 for RCA). CT-based MMAR obtained by Voronoi-based segmentation algorithm reliably estimates actual MMAR measured on ex-vivo swine hearts. Copyright © 2017 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.
Genome-wide identification and analysis of the Populus trichocarpa TIFY gene family
Apr 21, 2017   Plant Physiology And Biochemistry : PPB
Wang Y, Pan F, Chen D, Chu W, Liu H, Xiang Y
Genome-wide identification and analysis of the Populus trichocarpa TIFY gene family
Apr 21, 2017
Plant Physiology And Biochemistry : PPB
The plant-specific TIFY proteins are widely present in land plants and play the important roles in the regulation of plant stress-responses. In this study, we carried out a bioinformatics analysis of TIFY genes in Populus trichocarpa by determining the phylogenetic relationship, chromosomal location and gene structure and expression profiles analysis under stresses. The 24 TIFY genes were identified and classified into four subfamilies (ZML, JAZ, PPD and TIFY). The 24 TIFY genes were irregularly located on 13 of the 19 chromosomes; ten gene pairs were involved in large-scale interchromosomal segmental duplication events; we identified 17 collinear TIFY gene pairs in the Populus trichocarpa genome. Numerous abiotic stress cis-elements were widely found in the promoter regions. Analysis of the Ka/Ks ratios indicated that the paralogs of the PtTIFY family principally underwent purifying selection. Microarray data and qRT-PCR analysis revealed that 24 PtTIFY genes were differentially expressed in various tissues. Quantitative real-time RT-PCR analysis of TIFY genes expression in response to salt, JA hormones and low-temperature stress revealed their stress-responses profiles. The results of this study provided valuable information for further exploration of the TIFY gene family in Populus trichocarpa. Copyright © 2017. Published by Elsevier Masson SAS.
Structural and Functional Analysis of a β2-Adrenergic Receptor Complex with GRK5
Apr 21, 2017   Cell
Komolov KE, Du Y, Duc NM, Betz RM, Rodrigues JPGLM, Leib RD, Patra D, Skiniotis G, Adams CM, Dror RO, Chung KY, Kobilka BK, Benovic JL
Structural and Functional Analysis of a β2-Adrenergic Receptor Complex with GRK5
Apr 21, 2017
Cell
The phosphorylation of agonist-occupied G-protein-coupled receptors (GPCRs) by GPCR kinases (GRKs) functions to turn off G-protein signaling and turn on arrestin-mediated signaling. While a structural understanding of GPCR/G-protein and GPCR/arrestin complexes has emerged in recent years, the molecular architecture of a GPCR/GRK complex remains poorly defined. We used a comprehensive integrated approach of cross-linking, hydrogen-deuterium exchange mass spectrometry (MS), electron microscopy, mutagenesis, molecular dynamics simulations, and computational docking to analyze GRK5 interaction with the β2-adrenergic receptor (β2AR). These studies revealed a dynamic mechanism of complex formation that involves large conformational changes in the GRK5 RH/catalytic domain interface upon receptor binding. These changes facilitate contacts between intracellular loops 2 and 3 and the C terminus of the β2AR with the GRK5 RH bundle subdomain, membrane-binding surface, and kinase catalytic cleft, respectively. These studies significantly contribute to our understanding of the mechanism by which GRKs regulate the function of activated GPCRs. PAPERCLIP. Copyright © 2017 Elsevier Inc. All rights reserved.
Genetic analysis of α-synuclein 3' untranslated region and its corresponding microRNAs in relation to Parkinson's compared to dementia with Lewy bodies
Apr 21, 2017   Alzheimer's & Dementia : The Journal Of The Alzheimer's Association
Tagliafierro L, Glenn OC, Zamora ME, Beach TG, Woltjer RL, Lutz MW, Chiba-Falek O
Genetic analysis of α-synuclein 3' untranslated region and its corresponding microRNAs in relation to Parkinson's compared to dementia with Lewy bodies
Apr 21, 2017
Alzheimer's & Dementia : The Journal Of The Alzheimer's Association
The α-synuclein (SNCA) gene has been implicated in the etiology of Parkinson's disease (PD) and dementia with Lewy bodies (DLB). A computational analysis of SNCA 3' untranslated region to identify potential microRNA (miRNA) binding sites and quantitative real-time PCR to determine their expression in isogenic induced pluripotent stem cell-derived dopaminergic and cholinergic neurons as a model of PD and DLB, respectively, were performed. In addition, we performed a deep sequencing analysis of the SNCA 3' untranslated region of autopsy-confirmed cases of PD, DLB, and normal controls, followed by genetic association analysis of the identified variants. We identified four miRNA binding sites and observed a neuronal-type-specific expression profile for each miRNA in the different isogenic induced pluripotent stem cell-derived dopaminergic and cholinergic neurons. Furthermore, we found that the short structural variant rs33988309 poly-T was moderately associated with DLB but not with PD. We suggest that the regulation of SNCA expression through miRNAs is neuronal-type-specific expression. Furthermore, genetic variability in the SNCA gene may contribute to synucleinopathies in a pathology-specific manner. Copyright © 2017. Published by Elsevier Inc.
Programmatic access to bioinformatics tools from EMBL-EBI update: 2017
Apr 21, 2017   Nucleic Acids Research
Chojnacki S, Cowley A, Lee J, Foix A, Lopez R
Programmatic access to bioinformatics tools from EMBL-EBI update: 2017
Apr 21, 2017
Nucleic Acids Research
Since 2009 the EMBL-EBI provides free and unrestricted access to several bioinformatics tools via the user's browser as well as programmatically via Web Services APIs. Programmatic access to these tools, which is fundamental to bioinformatics, is increasingly important as more high-throughput data is generated, e.g. from proteomics and metagenomic experiments. Access is available using both the SOAP and RESTful approaches and their usage is reviewed regularly in order to ensure that the best, supported tools are available to all users. We present here an update describing the latest enhancement to the Job Dispatcher APIs as well as the governance under it. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
A method for learning a sparse classifier in the presence of missing data for high-dimensional biological datasets
Apr 21, 2017   Bioinformatics (Oxford, England)
Severson K, Monian B, Christopher Love J, Braatz RD
A method for learning a sparse classifier in the presence of missing data for high-dimensional biological datasets
Apr 21, 2017
Bioinformatics (Oxford, England)
This work addresses two common issues in building classification models for biological or medical studies: learning a sparse model, where only a subset of a large number of possible predictors is used, and training in the presence of missing data. This work focuses on supervised generative binary classification models, specifically linear discriminant analysis (LDA). The parameters are determined using an expectation maximization algorithm to both address missing data and introduce priors to promote sparsity. The proposed algorithm, expectation-maximization sparse discriminant analysis (EM-SDA), produces a sparse LDA model for datasets with and without missing data. : EM-SDA is tested via simulations and case studies. In the simulations, EM-SDA is compared to nearest shrunken centroids (NSC) and sparse discriminant analysis (SDA) with k-nearest neighbors for imputation for varying mechanism and amount of missing data. In three case studies using published biomedical data, the results are compared to NSC and SDA models with four different types of imputation, all of which are common approaches in the field. EM-SDA is more accurate and sparse than competing methods both with and without missing data in most of the experiments. Furthermore, the EM-SDA results are mostly consistent between the missing and full cases. Biological relevance of the resulting models, as quantified via a literature search, is also presented. A Matlab implementation published under GNU GPL v.3 license is available at http://web.mit.edu/braatzgroup/links.html. braatz@mit.edu. Supplementary data are available at Bioinformatics online.
Quantification of hypoxia-related gene expression as a potential approach for clinical outcome prediction in breast cancer
Apr 21, 2017   PloS One
El Guerrab A, Cayre A, Kwiatkowski F, Privat M, Rossignol JM, Rossignol F, Penault-Llorca F, Bignon YJ
Quantification of hypoxia-related gene expression as a potential approach for clinical outcome prediction in breast cancer
Apr 21, 2017
PloS One
Breast cancers are solid tumors frequently characterized by regions with low oxygen concentrations. Cellular adaptations to hypoxia are mainly determined by "hypoxia inducible factors" that mediate transcriptional modifications involved in drug resistance and tumor progression leading to metastasis and relapse occurrence. In this study, we investigated the prognostic value of hypoxia-related gene expression in breast cancer. A systematic review was conducted to select a set of 45 genes involved in hypoxia signaling pathways and breast tumor progression. Gene expression was quantified by RT-qPCR in a retrospective series of 32 patients with invasive ductal carcinoma. Data were analyzed in relation to classical clinicopathological criteria and relapse occurrence. Coordinated overexpression of selected genes was observed in high-grade and HER2+ tumors. Hierarchical cluster analysis of gene expression significantly segregated relapsed patients (p = 0.008, Chi2 test). All genes (except one) were up-regulated and six markers were significantly expressed in tumors from recurrent patients. The expression of this 6-gene set was used to develop a basic algorithm for identifying recurrent patients according to a risk score of relapse. Analysis of Kaplan-Meier relapse-free survival curves allowed the definition of a threshold score of 2 (p = 0.021, Mantel-Haenszel test). The risk of recurrence was increased by 40% in patients with a high score. In addition to classical prognostic factors, we showed that hypoxic markers have potential prognostic value for outcome and late recurrence prediction, leading to improved treatment decision-making for patients with early-stage invasive breast cancer. It will be necessary to validate the clinical relevance of this prognostic approach through independent studies including larger prospective patient cohorts.
Genomic data for 78 chickens from 14 populations
Apr 21, 2017   GigaScience
Li D, Che T, Chen B, Tian S, Zhou X,   . . . . . .   , Yang M, Zhou R, Li R, Zhu Q, Li M
Genomic data for 78 chickens from 14 populations
Apr 21, 2017
GigaScience
Since the domestication of the red jungle fowls ( Gallus gallus ) (dating back to ∼10,000 B.P.) in Asia, domestic chickens ( Gallus gallus domesticus ) have been subjected to the combined effects of natural selection and human-driven artificial selection; this has resulted in marked phenotypic diversity in a number of traits, including behavior, body composition, egg production and skin color. Population genomic variations through diversifying selection have not been fully investigated. The whole genomes of 78 domestic chickens were sequenced to an average of 18-fold coverage for each bird. By combining this data with publicly available genomes of 5 wild red jungle fowls and 8 Xishuangbanna game fowls, we conducted a comprehensive comparative genomics analysis of 91 chickens from 17 populations. After aligning ∼21.30 gigabases (Gb) of high quality data from each individual to the reference chicken genome, we identified ∼6.44 million (M) SNPs for each population. These SNPs included 1.10 M novel SNPs in 17 populations that were absent in the current chicken dbSNP (Build 145) entries. The current data is important for population genetics and further studies in chicken, and will serve as a valuable resource for investigating diversifying selection and candidate genes for selective breeding in chicken.
Hybrid de novo genome assembly of the Chinese herbal fleabane Erigeron breviscapus
Apr 21, 2017   GigaScience
Yang J, Zhang G, Zhang J, Liu H, Chen W, Wang X, Li Y, Dong Y, Yang S
Hybrid de novo genome assembly of the Chinese herbal fleabane Erigeron breviscapus
Apr 21, 2017
GigaScience
The plants in the Erigeron genus of the Compositae (Asteraceae) family are commonly called fleabanes, possibly due to the belief that certain chemicals in these plants repel fleas. In the traditional Chinese medicine, Erigeron breviscapus , which is native to China, was widely used in the treatment of cerebrovascular disease. A handful of bioactive compounds, including scutellarin, 3,5-dicaffeoylquinic acid, and 3,4-dicaffeoylquinic acid, have been isolated from the plant. With the purpose of finding novel medicinal compounds and understanding their biosynthetic pathways, we propose to sequence the genome of E. breviscapus . We assembled the highly heterozygous E. breviscapus genome using a combination of PacBio single-molecular real-time sequencing method and next-generation sequencing method on the Illumina HiSeq platform. The final draft genome is approximately 1.2 Gb, with the contig and scaffold N50 sizes of 18.8 kb and 31.5 kb, respectively. Further analyses predicted 37,504 protein-coding genes in the E. breviscapus genome, and 8,172 shared gene families among Compositae species. The E. breviscapus genome provides a valuable resource for the investigation of novel bioactive compounds in this Chinese herb.
Long non-coding RNA exchange during the oocyte-to-embryo transition in mice
Apr 21, 2017   DNA Research : An International Journal For Rapid Publication Of Reports On Genes And Genomes
Karlic R, Ganesh S, Franke V, Svobodova E, Urbanova J, Suzuki Y, Aoki F, Vlahovicek K, Svoboda P
Long non-coding RNA exchange during the oocyte-to-embryo transition in mice
Apr 21, 2017
DNA Research : An International Journal For Rapid Publication Of Reports On Genes And Genomes
Diabetes mellitus as the major risk factor for mucormycosis in Mexico: Epidemiology, diagnosis, and outcomes of reported cases
Apr 21, 2017   Medical Mycology
Corzo-León DE, Chora-Hernández LD, Rodríguez-Zulueta AP, Walsh TJ
Diabetes mellitus as the major risk factor for mucormycosis in Mexico: Epidemiology, diagnosis, and outcomes of reported cases
Apr 21, 2017
Medical Mycology
Mucormycosis is an emerging infectious disease with high rates of associated mortality and morbidity. Little is known about the characteristics of mucormycosis or entomophthoromycosis occurring in Mexico. A search strategy was performed of literature published in journals found in available databases and theses published online at Universidad Nacional Autónoma de México (UNAM) library website reporting clinical cases or clinical case series of mucormycosis and entomophthoromycosis occurring in Mexico between 1982 and 2016. Among the 418 cases identified, 72% were diabetic patients, and sinusitis accounted for 75% of the reported cases. Diabetes mellitus was not a risk factor for entomophthoromycosis. Mortality rate was 51% (125/244). Rhizopus species were the most frequent isolates (59%, 148/250). Amphotericin B deoxycholate was used in 89% of cases (204/227), while surgery and antifungal management as combined treatment was used in 90% (172/191). In diabetic individuals, this combined treatment approach was associated with a higher probability of survival (95% vs 66%, OR = 0.1, 95% CI, 0.02-0.43' P = .002). The most common complications were associated with nephrotoxicity and prolonged hospitalization due to IV antifungal therapy. An algorithm is proposed to establish an early diagnosis of rhino-orbital cerebral (ROC) mucormycosis based on standardized identification of warning signs and symptoms and performing an early direct microbiological exam and histopathological identification through a multidisciplinary medical and surgical team. In summary, diabetes mellitus was the most common risk factor for mucormycosis in Mexico; combined antifungal therapy and surgery in ROC mucormycosis significantly improved survival. © The Author 2017. Published by Oxford University Press on behalf of The International Society for Human and Animal Mycology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Deep Mining Heterogeneous Networks of Biomedical Linked Data to Predict Novel Drug-Target Associations
Apr 21, 2017   Bioinformatics (Oxford, England)
Zong N, Kim H, Ngo V, Harismendy O
Deep Mining Heterogeneous Networks of Biomedical Linked Data to Predict Novel Drug-Target Associations
Apr 21, 2017
Bioinformatics (Oxford, England)
A heterogeneous network topology possessing abundant interactions between biomedical entities has yet to be utilized in similarity-based methods for predicting drug-target associations based on the array of varying features of drugs and their targets. Deep learning reveals features of vertices of a large network that can be adapted in accommodating the similarity-based solutions to provide a flexible method of drug-target prediction. We propose a similarity-based drug-target prediction method that enhances existing association discovery methods by using a topology-based similarity measure. DeepWalk, a deep learning method, is adopted in this study to calculate the similarities within Linked Tripartite Network (LTN), a heterogeneous network generated from biomedical linked datasets. This proposed method shows promising results for drug-target association prediction: 98.96% AUC ROC score with a 10-fold cross-validation and 99.25% AUC ROC score with a Monte Carlo cross-validation with LTN. By utilizing DeepWalk, we demonstrate that: (1) this method outperforms other existing topology-based similarity computation methods, (2) the performance is better for tripartite than with bipartite networks, and (3) the measure of similarity using network topology outperforms the ones derived from chemical structure (drugs) or genomic sequence (targets). Our proposed methodology proves to be capable of providing a promising solution for drug-target prediction based on topological similarity with a heterogeneous network, and may be readily re-purposed and adapted in the existing of similarity-based methodologies. The proposed method has been developed in JAVA and it is available, along with the data at the following URL: https://github.com/zongnansu1982/drug-target-prediction. nazong@ucsd.edu. Supplementary data are available at Bioinformatics online.
Capturing Non-Local Interactions by Long Short Term Memory Bidirectional Recurrent Neural Networks for Improving Prediction of Protein Secondary Structure, Backbone Angles, Contact Numbers, and Solvent Accessibility
Apr 21, 2017   Bioinformatics (Oxford, England)
Heffernan R, Yang Y, Paliwal K, Zhou Y
Capturing Non-Local Interactions by Long Short Term Memory Bidirectional Recurrent Neural Networks for Improving Prediction of Protein Secondary Structure, Backbone Angles, Contact Numbers, and Solvent Accessibility
Apr 21, 2017
Bioinformatics (Oxford, England)
The accuracy of predicting protein local and global structural properties such as secondary structure and solvent accessible surface area has been stagnant for many years because of the challenge of accounting for non-local interactions between amino acid residues that are close in three-dimensional structural space but far from each other in their sequence positions. All existing machine-learning techniques relied on a sliding window of 10-20 amino acid residues to capture some "short to intermediate" non-local interactions. Here, we employed Long Short Term Memory (LSTM) Bidirectional Recurrent Neural Networks (BRNNs) which are capable of capturing long range interactions without using a window. We showed that the application of LSTM-BRNN to the prediction of protein structural properties makes the most significant improvement for residues with the most long-range contacts (|i-j|>19) over a previous window-based, deep-learning method SPIDER2. Capturing long-range interactions allows the accuracy of three-state secondary structure prediction to reach 84% and the correlation coefficient between predicted and actual solvent accessible surface areas to reach 0.80, plus a reduction of 5%, 10%, 5%, and 10% in the mean absolute error for backbone ϕ ,Ψ, θ , and τ angles, respectively, from SPIDER2. More significantly, 27% of 182724 40-residue models directly constructed from predicted Cα atom-based θ and τ have similar structures to their corresponding native structures (6Å RMSD or less), which is 3% better than models built by ϕ and Ψ angles. We expect the method to be useful for assisting protein structure and function prediction. The method is available as a SPIDER3 server and standalone package at http://sparks-lab.org . yaoqi.zhou@griffith.edu.au , yuedong.yang@griffith.edu.au. Supplementary data are available at Bioinformatics online.
ClusPro PeptiDock: Efficient global docking of peptide recognition motifs using FFT
Apr 21, 2017   Bioinformatics (Oxford, England)
Porter KA, Xia B, Beglov D, Bohnuud T, Alam N, Schueler-Furman O, Kozakov D
ClusPro PeptiDock: Efficient global docking of peptide recognition motifs using FFT
Apr 21, 2017
Bioinformatics (Oxford, England)
We present an approach for the efficient docking of peptide motifs to their free receptor structures. Using a motif based search, we can retrieve structural fragments from the Protein Data Bank (PDB) that are very similar to the peptide's final, bound conformation. We use a Fast Fourier Transform (FFT) based docking method to quickly perform global rigid body docking of these fragments to the receptor. According to CAPRI peptide docking criteria, an acceptable conformation can often be found among the top-ranking predictions. The method is available as part of the protein-protein docking server ClusPro at https://peptidock.cluspro.org/nousername.php . Supplementary data are available at Bioinformatics online.
MOST-Visualization: Software for producing automated textbook-style maps of genome-scale metabolic networks
Apr 21, 2017   Bioinformatics (Oxford, England)
Kelley JJ, Maor S, Kim MK, Lane A, Lun DS
MOST-Visualization: Software for producing automated textbook-style maps of genome-scale metabolic networks
Apr 21, 2017
Bioinformatics (Oxford, England)
Visualization of metabolites, reactions and pathways in genome-scale metabolic networks (GEMs) can assist in understanding cellular metabolism. Three attributes are desirable in software used for visualizing GEMs: 1. automation, since GEMs can be quite large; 2. production of understandable maps that provide ease in identification of pathways, reactions, and metabolites; and 3. visualization of the entire network to show how pathways are interconnected. No software currently exists for visualizing GEMs that satisfies all three characteristics, but MOST-Visualization, an extension of the software package MOST (Metabolic Optimization and Simulation Tool), satisfies (1), and by using a pre-drawn overview map of metabolism based on the Roche map satisfies (2) and comes close to satisfying (3). MOST is distributed for free on the GNU General Public License. The software and full documentation are available at http://most.ccib.rutgers.edu/ . dslun@rutgers.edu. Supplementary data are available at Bioinformatics online.
Mapping Genes for Calcium Signaling and Their Associated Human Genetic Disorders
Apr 21, 2017   Bioinformatics (Oxford, England)
Hörtenhuber M, Toledo EM, Smedler E, Arenas E, Malmersjö S, Louhivuori L, Uhlén P
Mapping Genes for Calcium Signaling and Their Associated Human Genetic Disorders
Apr 21, 2017
Bioinformatics (Oxford, England)
Signal transduction via calcium ions (Ca 2+ ) represents a fundamental signaling pathway in all eukaryotic cells. A large portion of the human genome encodes proteins used to assemble signaling systems that can transduce signals with diverse spatial and temporal dynamics. Here, we provide a map of all of the genes involved in Ca 2+ signaling and link these genes to human genetic disorders. Using Gene Ontology terms and genome databases, 1,805 genes were identified as regulators or targets of intracellular Ca 2+ signals. Associating these 1,805 genes with human genetic disorders uncovered 1,470 diseases with mutated "Ca 2+ genes". A network with scale-free properties appeared when the Ca 2+ genes were mapped to their associated genetic disorders. The Ca 2+ genome database is freely available at http://cagedb.uhlenlab.org and will foster studies of gene functions and genetic disorders associated with Ca 2+ signaling. per.uhlen@ki.se. Supplementary data are available at Bioinformatics online.
Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African ancestry anthropometry genetics consortium
Apr 21, 2017   PLoS Genetics
Ng MCY, Graff M, Lu Y, Justice AE, Mudgal P,   . . . . . .   , Bowden DW, Cupples LA, Haiman CA, Loos RJF, North KE
Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African ancestry anthropometry genetics consortium
Apr 21, 2017
PLoS Genetics
Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10-8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (
Probing protein flexibility reveals a mechanism for selective promiscuity
Apr 22, 2017   ELife
Pabon NA, Camacho CJ
Probing protein flexibility reveals a mechanism for selective promiscuity
Apr 22, 2017
ELife
Many eukaryotic regulatory proteins adopt distinct bound and unbound conformations, and use this structural flexibility to bind specifically to multiple partners. However, we lack an understanding of how an interface can select some ligands, but not others. Here, we present a molecular dynamics approach to identify and quantitatively evaluate the interactions responsible for this selective promiscuity. We apply this approach to the anti-cancer target PD-1 and its ligands PD-L1 and PD-L2. We discover that while unbound PD-1 exhibits a hard-to-drug hydrophilic interface, conserved specific triggers encoded in the cognate ligands activate a promiscuous binding pathway that reveals a flexible hydrophobic binding cavity. Specificity is then established by additional contacts that stabilize the PD-1 cavity into distinct bound-like modes. Collectively, our studies provide insight into the structural basis and evolution of multiple binding partners, and also suggest a biophysical approach to exploit innate binding pathways to drug seemingly undruggable targets.

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