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Find video protocols related to scientific articles indexed in Pubmed.
Mechismo: predicting the mechanistic impact of mutations and modifications on molecular interactions.
Nucleic Acids Res.
PUBLISHED: 11-14-2014
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Systematic interrogation of mutation or protein modification data is important to identify sites with functional consequences and to deduce global consequences from large data sets. Mechismo (mechismo.russellab.org) enables simultaneous consideration of thousands of 3D structures and biomolecular interactions to predict rapidly mechanistic consequences for mutations and modifications. As useful functional information often only comes from homologous proteins, we benchmarked the accuracy of predictions as a function of protein/structure sequence similarity, which permits the use of relatively weak sequence similarities with an appropriate confidence measure. For protein-protein, protein-nucleic acid and a subset of protein-chemical interactions, we also developed and benchmarked a measure of whether modifications are likely to enhance or diminish the interactions, which can assist the detection of modifications with specific effects. Analysis of high-throughput sequencing data shows that the approach can identify interesting differences between cancers, and application to proteomics data finds potential mechanistic insights for how post-translational modifications can alter biomolecular interactions.
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Revised risk estimation and treatment stratification of low- and intermediate-risk neuroblastoma patients by integrating clinical and molecular prognostic markers.
Clin. Cancer Res.
PUBLISHED: 09-19-2014
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Purpose: To optimize neuroblastoma treatment stratification, we aimed at developing a novel risk estimation system by integrating gene expression-based classification and established prognostic markers. Material and Methods: Gene expression profiles were generated from 709 neuroblastoma specimens using customized 4x44K microarrays. Classification models were built using 75 tumors with contrasting courses of disease. Validation was performed in an independent test set (n=634) by Kaplan-Meier estimates and Cox regression analyses. Results: The best-performing classifier predicted patient outcome with an accuracy of 0.95 (sensitivity 0.93, specificity 0.97) in the validation cohort. The highest potential clinical value of this predictor was observed for current low-risk patients (LR: 5-year EFS 0.84±0.02 vs 0.29±0.10; 5-year OS 0.99±0.01vs 0.76±0.11; both p<0.001) and intermediate-risk patients (IR: 5-year EFS 0.88±0.06 vs 0.41±0.10; 5-year OS 1.0 vs 0.70±0.09; both p<0.001). In multivariate Cox regression models for LR/IR patients the classifier outperformed risk assessment of the current German trial NB2004 (EFS: HR 5.07, 95%-CI 3.20-8.02, OS: HR 25.54, 95%-CI 8.40-77.66; both p<0.001). Based on these findings, we propose to integrate the classifier into a revised risk stratification system for LR/IR patients. According to this system, we identified novel subgroups with poor outcome (5-year EFS 0.19±0.08; 5-year OS 0.59±0.1), for whom we propose intensified treatment, and with beneficial outcome (5-year EFS 0.87±0.05; 5-year OS 1.0), who may benefit from treatment de-escalation. Conclusion: Combination of gene expression-based classification and established prognostic markers improves risk estimation of LR/IR neuroblastoma patients. We propose to implement our revised treatment stratification system in a prospective clinical trial.
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Data-derived modeling characterizes plasticity of MAPK signaling in melanoma.
PLoS Comput. Biol.
PUBLISHED: 09-04-2014
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The majority of melanomas have been shown to harbor somatic mutations in the RAS-RAF-MEK-MAPK and PI3K-AKT pathways, which play a major role in regulation of proliferation and survival. The prevalence of these mutations makes these kinase signal transduction pathways an attractive target for cancer therapy. However, tumors have generally shown adaptive resistance to treatment. This adaptation is achieved in melanoma through its ability to undergo neovascularization, migration and rearrangement of signaling pathways. To understand the dynamic, nonlinear behavior of signaling pathways in cancer, several computational modeling approaches have been suggested. Most of those models require that the pathway topology remains constant over the entire observation period. However, changes in topology might underlie adaptive behavior to drug treatment. To study signaling rearrangements, here we present a new approach based on Fuzzy Logic (FL) that predicts changes in network architecture over time. This adaptive modeling approach was used to investigate pathway dynamics in a newly acquired experimental dataset describing total and phosphorylated protein signaling over four days in A375 melanoma cell line exposed to different kinase inhibitors. First, a generalized strategy was established to implement a parameter-reduced FL model encoding non-linear activity of a signaling network in response to perturbation. Next, a literature-based topology was generated and parameters of the FL model were derived from the full experimental dataset. Subsequently, the temporal evolution of model performance was evaluated by leaving time-defined data points out of training. Emerging discrepancies between model predictions and experimental data at specific time points allowed the characterization of potential network rearrangement. We demonstrate that this adaptive FL modeling approach helps to enhance our mechanistic understanding of the molecular plasticity of melanoma.
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Characterizing protein interactions employing a genome-wide siRNA cellular phenotyping screen.
PLoS Comput. Biol.
PUBLISHED: 09-01-2014
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Characterizing the activating and inhibiting effect of protein-protein interactions (PPI) is fundamental to gain insight into the complex signaling system of a human cell. A plethora of methods has been suggested to infer PPI from data on a large scale, but none of them is able to characterize the effect of this interaction. Here, we present a novel computational development that employs mitotic phenotypes of a genome-wide RNAi knockdown screen and enables identifying the activating and inhibiting effects of PPIs. Exemplarily, we applied our technique to a knockdown screen of HeLa cells cultivated at standard conditions. Using a machine learning approach, we obtained high accuracy (82% AUC of the receiver operating characteristics) by cross-validation using 6,870 known activating and inhibiting PPIs as gold standard. We predicted de novo unknown activating and inhibiting effects for 1,954 PPIs in HeLa cells covering the ten major signaling pathways of the Kyoto Encyclopedia of Genes and Genomes, and made these predictions publicly available in a database. We finally demonstrate that the predicted effects can be used to cluster knockdown genes of similar biological processes in coherent subgroups. The characterization of the activating or inhibiting effect of individual PPIs opens up new perspectives for the interpretation of large datasets of PPIs and thus considerably increases the value of PPIs as an integrated resource for studying the detailed function of signaling pathways of the cellular system of interest.
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Estimating the activity of transcription factors by the effect on their target genes.
Bioinformatics
PUBLISHED: 08-28-2014
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Understanding regulation of transcription is central for elucidating cellular regulation. Several statistical and mechanistic models have come up the last couple of years explaining gene transcription levels using information of potential transcriptional regulators as transcription factors (TFs) and information from epigenetic modifications. The activity of TFs is often inferred by their transcription levels, promoter binding and epigenetic effects. However, in principle, these methods do not take hard-to-measure influences such as post-transcriptional modifications into account.
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Identification of regulatory networks in HSCs and their immediate progeny via integrated proteome, transcriptome, and DNA Methylome analysis.
Cell Stem Cell
PUBLISHED: 08-21-2014
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In this study, we present integrated quantitative proteome, transcriptome, and methylome analyses of hematopoietic stem cells (HSCs) and four multipotent progenitor (MPP) populations. From the characterization of more than 6,000 proteins, 27,000 transcripts, and 15,000 differentially methylated regions (DMRs), we identified coordinated changes associated with early differentiation steps. DMRs show continuous gain or loss of methylation during differentiation, and the overall change in DNA methylation correlates inversely with gene expression at key loci. Our data reveal the differential expression landscape of 493 transcription factors and 682 lncRNAs and highlight specific expression clusters operating in HSCs. We also found an unexpectedly dynamic pattern of transcript isoform regulation, suggesting a critical regulatory role during HSC differentiation, and a cell cycle/DNA repair signature associated with multipotency in MPP2 cells. This study provides a comprehensive genome-wide resource for the functional exploration of molecular, cellular, and epigenetic regulation at the top of the hematopoietic hierarchy.
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Non-rigid multi-frame registration of cell nuclei in live cell fluorescence microscopy image data.
Med Image Anal
PUBLISHED: 08-11-2014
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The analysis of the motion of subcellular particles in live cell microscopy images is essential for understanding biological processes within cells. For accurate quantification of the particle motion, compensation of the motion and deformation of the cell nucleus is required. We introduce a non-rigid multi-frame registration approach for live cell fluorescence microscopy image data. Compared to existing approaches using pairwise registration, our approach exploits information from multiple consecutive images simultaneously to improve the registration accuracy. We present three intensity-based variants of the multi-frame registration approach and we investigate two different temporal weighting schemes. The approach has been successfully applied to synthetic and live cell microscopy image sequences, and an experimental comparison with non-rigid pairwise registration has been carried out.
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circlize Implements and enhances circular visualization in R.
Bioinformatics
PUBLISHED: 06-14-2014
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Circular layout is an efficient way for the visualization of huge amounts of genomic information. Here we present the circlize package, which provides an implementation of circular layout generation in R as well as an enhancement of available software. The flexibility of this package is based on the usage of low-level graphics functions such that self-defined high-level graphics can be easily implemented by users for specific purposes. Together with the seamless connection between the powerful computational and visual environment in R, circlize gives users more convenience and freedom to design figures for better understanding genomic patterns behind multi-dimensional data.
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Genetic variants in apoptosis-related genes associated with colorectal hyperplasia.
Genes Chromosomes Cancer
PUBLISHED: 04-21-2014
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Deregulation of apoptosis is a frequent alteration in early benign lesions of the colon mucosa and is thought to be a major contributor to tumor progression and cancer. Single nucleotide polymorphisms (SNPs) within apoptosis-related genes could affect apoptotic responses and their identification might provide a basis to assess individual risk for development of early lesions. To investigate a possible association between genetic polymorphisms and the occurrence of hyperplastic polyps (HP), we developed a custom DNA chip assay for 1,536 SNPs in the coding and flanking regions of 826 genes with known functional roles in apoptosis or apoptosis-associated (e.g., stress-related) pathways. During a first round of screening, genotypes were determined for 272 endoscopy patients harboring hyperplastic colorectal polyps and for 512 sex and aged-matched controls. A set of 14 candidate SNPs associated with HP (P?
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Engineering light-inducible nuclear localization signals for precise spatiotemporal control of protein dynamics in living cells.
Nat Commun
PUBLISHED: 04-14-2014
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The function of many eukaryotic proteins is regulated by highly dynamic changes in their nucleocytoplasmic distribution. The ability to precisely and reversibly control nuclear translocation would, therefore, allow dissecting and engineering cellular networks. Here we develop a genetically encoded, light-inducible nuclear localization signal (LINuS) based on the LOV2 domain of Avena sativa phototropin 1. LINuS is a small, versatile tag, customizable for different proteins and cell types. LINuS-mediated nuclear import is fast and reversible, and can be tuned at different levels, for instance, by introducing mutations that alter AsLOV2 domain photo-caging properties or by selecting nuclear localization signals (NLSs) of various strengths. We demonstrate the utility of LINuS in mammalian cells by controlling gene expression and entry into mitosis with blue light.
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Recurrent RHOA mutations in pediatric Burkitt lymphoma treated according to the NHL-BFM protocols.
Genes Chromosomes Cancer
PUBLISHED: 04-11-2014
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Burkitt lymphoma (BL) is the most frequent B-cell lymphoma in childhood. Genetically, it is characterized by the presence of an IG-MYC translocation which is supposed to be an initiating but not sufficient event in Burkitt lymphomagenesis. In a recent whole-genome sequencing study of four cases, we showed that the gene encoding the ras homolog family member A (RHOA) is recurrently mutated in pediatric BL. Here, we analyzed RHOA by Sanger sequencing in a cohort of 101 pediatric B-cell lymphoma patients treated according to Non-Hodgkin's Lymphoma Berlin-Frankfurt-Münster (NHL-BFM) study protocols. Among the 78 BLs in this series, an additional five had RHOA mutations resulting in a total incidence of 7/82 (8.5%) with c.14G>A (p.R5Q) being present in three cases. Modeling the mutational effect suggests that most of them inactivate the RHOA protein. Thus, deregulation of RHOA by mutation is a recurrent event in Burkitt lymphomagenesis in children.
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An RNAi screen identifies KIF15 as a novel regulator of the endocytic trafficking of integrin.
J. Cell. Sci.
PUBLISHED: 03-21-2014
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?2?1 integrin is one of the most important collagen-binding receptors, and it has been implicated in numerous thrombotic and immune diseases. ?2?1 integrin is a potent tumour suppressor, and its downregulation is associated with increased metastasis and poor prognosis in breast cancer. Currently, very little is known about the mechanism that regulates the cell-surface expression and trafficking of ?2?1 integrin. Here, using a quantitative fluorescence-microscopy-based RNAi assay, we investigated the impact of 386 cytoskeleton-associated or -regulatory genes on ?2 integrin endocytosis and found that 122 of these affected the intracellular accumulation of ?2 integrin. Of these, 83 were found to be putative regulators of ?2 integrin trafficking and/or expression, with no observed effect on the internalization of epidermal growth factor (EGF) or transferrin. Further interrogation and validation of the siRNA screen revealed a role for KIF15, a microtubule-based molecular motor, as a significant inhibitor of the endocytic trafficking of ?2 integrin. Our data suggest a novel role for KIF15 in mediating plasma membrane localization of the alternative clathrin adaptor Dab2, thus impinging on pathways that regulate ?2 integrin internalization.
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Decoding the regulatory landscape of medulloblastoma using DNA methylation sequencing.
Nature
PUBLISHED: 03-20-2014
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Epigenetic alterations, that is, disruption of DNA methylation and chromatin architecture, are now acknowledged as a universal feature of tumorigenesis. Medulloblastoma, a clinically challenging, malignant childhood brain tumour, is no exception. Despite much progress from recent genomics studies, with recurrent changes identified in each of the four distinct tumour subgroups (WNT-pathway-activated, SHH-pathway-activated, and the less-well-characterized Group 3 and Group 4), many cases still lack an obvious genetic driver. Here we present whole-genome bisulphite-sequencing data from thirty-four human and five murine tumours plus eight human and three murine normal controls, augmented with matched whole-genome, RNA and chromatin immunoprecipitation sequencing data. This comprehensive data set allowed us to decipher several features underlying the interplay between the genome, epigenome and transcriptome, and its effects on medulloblastoma pathophysiology. Most notable were highly prevalent regions of hypomethylation correlating with increased gene expression, extending tens of kilobases downstream of transcription start sites. Focal regions of low methylation linked to transcription-factor-binding sites shed light on differential transcriptional networks between subgroups, whereas increased methylation due to re-normalization of repressed chromatin in DNA methylation valleys was positively correlated with gene expression. Large, partially methylated domains affecting up to one-third of the genome showed increased mutation rates and gene silencing in a subgroup-specific fashion. Epigenetic alterations also affected novel medulloblastoma candidate genes (for example, LIN28B), resulting in alternative promoter usage and/or differential messenger RNA/microRNA expression. Analysis of mouse medulloblastoma and precursor-cell methylation demonstrated a somatic origin for many alterations. Our data provide insights into the epigenetic regulation of transcription and genome organization in medulloblastoma pathogenesis, which are probably also of importance in a wider developmental and disease context.
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Intra- and interdimeric caspase-8 self-cleavage controls strength and timing of CD95-induced apoptosis.
Sci Signal
PUBLISHED: 03-13-2014
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Apoptosis in response to the ligand CD95L (also known as Fas ligand) is initiated by caspase-8, which is activated by dimerization and self-cleavage at death-inducing signaling complexes (DISCs). Previous work indicated that the degree of substrate cleavage by caspase-8 determines whether a cell dies or survives in response to a death stimulus. To determine how a death ligand stimulus is effectively translated into caspase-8 activity, we assessed this activity over time in single cells with compartmentalized probes that are cleaved by caspase-8 and used multiscale modeling to simultaneously describe single-cell and population data with an ensemble of single-cell models. We derived and experimentally validated a minimal model in which cleavage of caspase-8 in the enzymatic domain occurs in an interdimeric manner through interaction between DISCs, whereas prodomain cleavage sites are cleaved in an intradimeric manner within DISCs. Modeling indicated that sustained membrane-bound caspase-8 activity is followed by transient cytosolic activity, which can be interpreted as a molecular timer mechanism reflected by a limited lifetime of active caspase-8. The activation of caspase-8 by combined intra- and interdimeric cleavage ensures weak signaling at low concentrations of CD95L and strongly accelerated activation at higher ligand concentrations, thereby contributing to precise control of apoptosis.
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Dissecting the contribution of actin and vimentin intermediate filaments to mechanical phenotype of suspended cells using high-throughput deformability measurements and computational modeling.
J Biomech
PUBLISHED: 02-28-2014
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Mechanical cell properties play an important role in many basic biological functions, including motility, adhesion, proliferation and differentiation. There is a growing body of evidence that the mechanical cell phenotype can be used for detection and, possibly, treatment of various diseases, including cancer. Understanding of pathological mechanisms requires investigation of the relationship between constitutive properties and major structural components of cells, i.e., the nucleus and cytoskeleton. While the contribution of actin und microtubules to cellular rheology has been extensively studied in the past, the role of intermediate filaments has been scarcely investigated up to now. Here, for the first time we compare the effects of drug-induced disruption of actin and vimentin intermediate filaments on mechanical properties of suspended NK cells using high-throughput deformability measurements and computational modeling. Although, molecular mechanisms of actin and vimentin disruption by the applied cytoskeletal drugs, Cytochalasin-D and Withaferin-A, are different, cell softening in both cases can be attributed to reduction of the effective density and stiffness of filament networks. Our experimental data suggest that actin and vimentin deficient cells exhibit, in average, 41% and 20% higher deformability in comparison to untreated control. 3D Finite Element simulation is performed to quantify the contribution of cortical actin and perinuclear vimentin to mechanical phenotype of the whole cell. Our simulation provides quantitative estimates for decreased filament stiffness in drug-treated cells and predicts more than two-fold increase of the strain magnitude in the perinuclear vimentin layer of actin deficient cells relatively to untreated control. Thus, the mechanical function of vimentin becomes particularly essential in motile and proliferating cells that have to dynamically remodel the cortical actin network. These insights add functional cues to frequently observed overexpression of vimentin in diverse types of cancer and underline the role of vimentin targeting drugs, such as Withaferin-A, as a potent cancerostatic supplement.
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Genome sequencing of SHH medulloblastoma predicts genotype-related response to smoothened inhibition.
Cancer Cell
PUBLISHED: 02-13-2014
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Smoothened (SMO) inhibitors recently entered clinical trials for sonic-hedgehog-driven medulloblastoma (SHH-MB). Clinical response is highly variable. To understand the mechanism(s) of primary resistance and identify pathways cooperating with aberrant SHH signaling, we sequenced and profiled a large cohort of SHH-MBs (n = 133). SHH pathway mutations involved PTCH1 (across all age groups), SUFU (infants, including germline), and SMO (adults). Children >3 years old harbored an excess of downstream MYCN and GLI2 amplifications and frequent TP53 mutations, often in the germline, all of which were rare in infants and adults. Functional assays in different SHH-MB xenograft models demonstrated that SHH-MBs harboring a PTCH1 mutation were responsive to SMO inhibition, whereas tumors harboring an SUFU mutation or MYCN amplification were primarily resistant.
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Creating functional engineered variants of the single-module non-ribosomal peptide synthetase IndC by T domain exchange.
Mol Biosyst
PUBLISHED: 01-25-2014
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Non-ribosomal peptide synthetases (NRPSs) are enzymes that catalyze ribosome-independent production of small peptides, most of which are bioactive. NRPSs act as peptide assembly lines where individual, often interconnected modules each incorporate a specific amino acid into the nascent chain. The modules themselves consist of several domains that function in the activation, modification and condensation of the substrate. NRPSs are evidently modular, yet experimental proof of the ability to engineer desired permutations of domains and modules is still sought. Here, we use a synthetic-biology approach to create a small library of engineered NRPSs, in which the domain responsible for carrying the activated amino acid (T domain) is exchanged with natural or synthetic T domains. As a model system, we employ the single-module NRPS IndC from Photorhabdus luminescens that produces the blue pigment indigoidine. As chassis we use Escherichia coli. We demonstrate that heterologous T domain exchange is possible, even for T domains derived from different organisms. Interestingly, substitution of the native T domain with a synthetic one enhanced indigoidine production. Moreover, we show that selection of appropriate inter-domain linker regions is critical for functionality. Taken together, our results extend the engineering avenues for NRPSs, as they point out the possibility of combining domain sequences coming from different pathways, organisms or from conservation criteria. Moreover, our data suggest that NRPSs can be rationally engineered to control the level of production of the corresponding peptides. This could have important implications for industrial and medical applications.
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Network topology-based detection of differential gene regulation and regulatory switches in cell metabolism and signaling.
BMC Syst Biol
PUBLISHED: 01-14-2014
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Common approaches to pathway analysis treat pathways merely as lists of genes disregarding their topological structures, that is, ignoring the genes' interactions on which a pathway's cellular function depends. In contrast, PathWave has been developed for the analysis of high-throughput gene expression data that explicitly takes the topology of networks into account to identify both global dysregulation of and localized (switch-like) regulatory shifts within metabolic and signaling pathways. For this purpose, it applies adjusted wavelet transforms on optimized 2D grid representations of curated pathway maps.
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Enhancer hijacking activates GFI1 family oncogenes in medulloblastoma.
Nature
PUBLISHED: 01-12-2014
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Medulloblastoma is a highly malignant paediatric brain tumour currently treated with a combination of surgery, radiation and chemotherapy, posing a considerable burden of toxicity to the developing child. Genomics has illuminated the extensive intertumoral heterogeneity of medulloblastoma, identifying four distinct molecular subgroups. Group 3 and group 4 subgroup medulloblastomas account for most paediatric cases; yet, oncogenic drivers for these subtypes remain largely unidentified. Here we describe a series of prevalent, highly disparate genomic structural variants, restricted to groups 3 and 4, resulting in specific and mutually exclusive activation of the growth factor independent 1 family proto-oncogenes, GFI1 and GFI1B. Somatic structural variants juxtapose GFI1 or GFI1B coding sequences proximal to active enhancer elements, including super-enhancers, instigating oncogenic activity. Our results, supported by evidence from mouse models, identify GFI1 and GFI1B as prominent medulloblastoma oncogenes and implicate 'enhancer hijacking' as an efficient mechanism driving oncogene activation in a childhood cancer.
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Genome sequencing: a systematic review of health economic evidence.
Health Econ Rev
PUBLISHED: 10-24-2013
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Recently the sequencing of the human genome has become a major biological and clinical research field. However, the public health impact of this new technology with focus on the financial effect is not yet to be foreseen. To provide an overview of the current health economic evidence for genome sequencing, we conducted a thorough systematic review of the literature from 17 databases. In addition, we conducted a hand search. Starting with 5 520 records we ultimately included five full-text publications and one internet source, all focused on cost calculations. The results were very heterogeneous and, therefore, difficult to compare. Furthermore, because the methodology of the publications was quite poor, the reliability and validity of the results were questionable. The real costs for the whole sequencing workflow, including data management and analysis, remain unknown. Overall, our review indicates that the current health economic evidence for genome sequencing is quite poor. Therefore, we listed aspects that needed to be considered when conducting health economic analyses of genome sequencing. Thereby, specifics regarding the overall aim, technology, population, indication, comparator, alternatives after sequencing, outcomes, probabilities, and costs with respect to genome sequencing are discussed. For further research, at the outset, a comprehensive cost calculation of genome sequencing is needed, because all further health economic studies rely on valid cost data. The results will serve as an input parameter for budget-impact analyses or cost-effectiveness analyses.
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Tagmentation-based whole-genome bisulfite sequencing.
Nat Protoc
PUBLISHED: 09-26-2013
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Epigenetic modifications such as carbon 5 methylation of the cytosine base in a CpG dinucleotide context are involved in the onset and progression of human diseases. A comprehensive understanding of the role of genome-wide DNA methylation patterns, the methylome, requires quantitative determination of the methylation states of all CpG sites in a genome. So far, analyses of the complete methylome by whole-genome bisulfite sequencing (WGBS) are rare because of the required large DNA quantities, substantial bioinformatic resources and high sequencing costs. Here we describe a detailed protocol for tagmentation-based WGBS (T-WGBS) and demonstrate its reliability in comparison with conventional WGBS. In T-WGBS, a hyperactive Tn5 transposase fragments the DNA and appends sequencing adapters in a single step. T-WGBS requires not more than 20 ng of input DNA; hence, the protocol allows the comprehensive methylome analysis of limited amounts of DNA isolated from precious biological specimens. The T-WGBS library preparation takes 2 d.
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Inflammation-mediated skin tumorigenesis induced by epidermal c-Fos.
Genes Dev.
PUBLISHED: 09-12-2013
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Skin squamous cell carcinomas (SCCs) are the second most prevalent skin cancers. Chronic skin inflammation has been associated with the development of SCCs, but the contribution of skin inflammation to SCC development remains largely unknown. In this study, we demonstrate that inducible expression of c-fos in the epidermis of adult mice is sufficient to promote inflammation-mediated epidermal hyperplasia, leading to the development of preneoplastic lesions. Interestingly, c-Fos transcriptionally controls mmp10 and s100a7a15 expression in keratinocytes, subsequently leading to CD4 T-cell recruitment to the skin, thereby promoting epidermal hyperplasia that is likely induced by CD4 T-cell-derived IL-22. Combining inducible c-fos expression in the epidermis with a single dose of the carcinogen 7,12-dimethylbenz(a)anthracene (DMBA) leads to the development of highly invasive SCCs, which are prevented by using the anti-inflammatory drug sulindac. Moreover, human SCCs display a correlation between c-FOS expression and elevated levels of MMP10 and S100A15 proteins as well as CD4 T-cell infiltration. Our studies demonstrate a bidirectional cross-talk between premalignant keratinocytes and infiltrating CD4 T cells in SCC development. Therefore, targeting inflammation along with the newly identified targets, such as MMP10 and S100A15, represents promising therapeutic strategies to treat SCCs.
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Mining quasi-bicliques from HIV-1-human protein interaction network: a multiobjective biclustering approach.
IEEE/ACM Trans Comput Biol Bioinform
PUBLISHED: 08-10-2013
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In this work, we model the problem of mining quasi-bicliques from weighted viral-host protein-protein interaction network as a biclustering problem for identifying strong interaction modules. In this regard, a multiobjective genetic algorithm-based biclustering technique is proposed that simultaneously optimizes three objective functions to obtain dense biclusters having high mean interaction strengths. The performance of the proposed technique has been compared with that of other existing biclustering methods on an artificial data. Subsequently, the proposed biclustering method is applied on the records of biologically validated and predicted interactions between a set of HIV-1 proteins and a set of human proteins to identify strong interaction modules. For this, the entire interaction information is realized as a bipartite graph. We have further investigated the biological significance of the obtained biclusters. The human proteins involved in the strong interaction module have been found to share common biological properties and they are identified as the gateways of viral infection leading to various diseases. These human proteins can be potential drug targets for developing anti-HIV drugs.
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Efficient Keratinocyte Differentiation Strictly Depends on JNK-Induced Soluble Factors in Fibroblasts.
J. Invest. Dermatol.
PUBLISHED: 07-25-2013
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Previous studies demonstrated that fibroblast-derived and JUN-dependent soluble factors play a crucial role on keratinocyte proliferation and differentiation during cutaneous wound healing. Furthermore, mice with a deficiency in Jun N-terminal kinases, JNK1 or JNK2, showed impaired skin development and delayed wound closure. To decipher the role of dermal JNK in keratinocyte behavior during these processes we employed a heterologous co-culture model combining primary human keratinocytes and murine fibroblasts. While co-cultured JNK1/JNK2-deficient fibroblasts did not affect keratinocyte proliferation, temporal monitoring of the transcriptome of differentiating keratinocytes revealed that efficient keratinocyte differentiation not only requires the support by fibroblast-derived soluble factors but critically depends on JNK1 and JNK2 signaling in these cells. Moreover, we showed that the repertoire of fibroblast transcripts encoding secreted proteins is severely disarranged upon loss of JNK under the co-culture conditions applied. Finally, our data demonstrate that efficient keratinocyte terminal differentiation requires constant presence of JNK-dependent and fibroblast-derived soluble factors. Taken together, our results imply that mesenchymal JNK plays a pivotal role in the paracrine crosstalk between dermal fibroblasts and epidermal keratinocytes during wound healing.Journal of Investigative Dermatology accepted article preview online, 16 December 2013. doi:10.1038/jid.2013.535.
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Integrative DNA methylation and gene expression analysis in high-grade soft tissue sarcomas.
Genome Biol.
PUBLISHED: 06-24-2013
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High-grade soft tissue sarcomas are a heterogeneous, complex group of aggressive malignant tumors showing mesenchymal differentiation. Recently, soft tissue sarcomas have increasingly been classified on the basis of underlying genetic alterations; however, the role of aberrant DNA methylation in these tumors is not well understood and, consequently, the usefulness of methylation-based classification is unclear.
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Hypermutation of the inactive X chromosome is a frequent event in cancer.
Cell
PUBLISHED: 04-27-2013
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Mutation is a fundamental process in tumorigenesis. However, the degree to which the rate of somatic mutation varies across the human genome and the mechanistic basis underlying this variation remain to be fully elucidated. Here, we performed a cross-cancer comparison of 402 whole genomes comprising a diverse set of childhood and adult tumors, including both solid and hematopoietic malignancies. Surprisingly, we found that the inactive X chromosome of many female cancer genomes accumulates on average twice and up to four times as many somatic mutations per megabase, as compared to the individual autosomes. Whole-genome sequencing of clonally expanded hematopoietic stem/progenitor cells (HSPCs) from healthy individuals and a premalignant myelodysplastic syndrome (MDS) sample revealed no X chromosome hypermutation. Our data suggest that hypermutation of the inactive X chromosome is an early and frequent feature of tumorigenesis resulting from DNA replication stress in aberrantly proliferating cells.
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Recurrent somatic alterations of FGFR1 and NTRK2 in pilocytic astrocytoma.
Nat. Genet.
PUBLISHED: 03-26-2013
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Pilocytic astrocytoma, the most common childhood brain tumor, is typically associated with mitogen-activated protein kinase (MAPK) pathway alterations. Surgically inaccessible midline tumors are therapeutically challenging, showing sustained tendency for progression and often becoming a chronic disease with substantial morbidities. Here we describe whole-genome sequencing of 96 pilocytic astrocytomas, with matched RNA sequencing (n = 73), conducted by the International Cancer Genome Consortium (ICGC) PedBrain Tumor Project. We identified recurrent activating mutations in FGFR1 and PTPN11 and new NTRK2 fusion genes in non-cerebellar tumors. New BRAF-activating changes were also observed. MAPK pathway alterations affected all tumors analyzed, with no other significant mutations identified, indicating that pilocytic astrocytoma is predominantly a single-pathway disease. Notably, we identified the same FGFR1 mutations in a subset of H3F3A-mutated pediatric glioblastoma with additional alterations in the NF1 gene. Our findings thus identify new potential therapeutic targets in distinct subsets of pilocytic astrocytoma and childhood glioblastoma.
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Signatures of mutational processes in human cancer.
Nature
PUBLISHED: 03-24-2013
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All cancers are caused by somatic mutations; however, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here we analysed 4,938,362 mutations from 7,042 cancers and extracted more than 20 distinct mutational signatures. Some are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are confined to a single cancer class. Certain signatures are associated with age of the patient at cancer diagnosis, known mutagenic exposures or defects in DNA maintenance, but many are of cryptic origin. In addition to these genome-wide mutational signatures, hypermutation localized to small genomic regions, kataegis, is found in many cancer types. The results reveal the diversity of mutational processes underlying the development of cancer, with potential implications for understanding of cancer aetiology, prevention and therapy.
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SplicingCompass: differential splicing detection using RNA-seq data.
Bioinformatics
PUBLISHED: 02-28-2013
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Alternative splicing is central for cellular processes and substantially increases transcriptome and proteome diversity. Aberrant splicing events often have pathological consequences and are associated with various diseases and cancer types. The emergence of next-generation RNA sequencing (RNA-seq) provides an exciting new technology to analyse alternative splicing on a large scale. However, algorithms that enable the analysis of alternative splicing from short-read sequencing are not fully established yet and there are still no standard solutions available for a variety of data analysis tasks.
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Secretory meningiomas are defined by combined KLF4 K409Q and TRAF7 mutations.
Acta Neuropathol.
PUBLISHED: 01-28-2013
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Meningiomas are among the most frequent intracranial tumors. The secretory variant of meningioma is characterized by glandular differentiation, formation of intracellular lumina and pseudopsammoma bodies, expression of a distinct pattern of cytokeratins and clinically by pronounced perifocal brain edema. Here we describe whole-exome sequencing analysis of DNA from 16 secretory meningiomas and corresponding constitutional tissues. All secretory meningiomas invariably harbored a mutation in both KLF4 and TRAF7. Validation in an independent cohort of 14 secretory meningiomas by Sanger sequencing or derived cleaved amplified polymorphic sequence (dCAPS) assay detected the same pattern, with KLF4 mutations observed in a total of 30/30 and TRAF7 mutations in 29/30 of these tumors. All KLF4 mutations were identical, affected codon 409 and resulted in a lysine to glutamine exchange (K409Q). KLF4 mutations were not found in 89 non-secretory meningiomas, 267 other intracranial tumors including gliomas, glioneuronal tumors, pituitary adenomas and metastases, 59 peripheral nerve sheath tumors and 52 pancreatic tumors. TRAF7 mutations were restricted to the WD40 domains. While KLF4 mutations were exclusively seen in secretory meningiomas, TRAF7 mutations were also observed in 7/89 (8 %) of non-secretory meningiomas. KLF4 and TRAF7 mutations were mutually exclusive with NF2 mutations. In conclusion, our findings suggest an essential contribution of combined KLF4 K409Q and TRAF7 mutations in the genesis of secretory meningioma and demonstrate a role for TRAF7 alterations in other non-NF2 meningiomas.
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Integrative genomic analyses reveal an androgen-driven somatic alteration landscape in early-onset prostate cancer.
Cancer Cell
PUBLISHED: 01-03-2013
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Early-onset prostate cancer (EO-PCA) represents the earliest clinical manifestation of prostate cancer. To compare the genomic alteration landscapes of EO-PCA with "classical" (elderly-onset) PCA, we performed deep sequencing-based genomics analyses in 11 tumors diagnosed at young age, and pursued comparative assessments with seven elderly-onset PCA genomes. Remarkable age-related differences in structural rearrangement (SR) formation became evident, suggesting distinct disease pathomechanisms. Whereas EO-PCAs harbored a prevalence of balanced SRs, with a specific abundance of androgen-regulated ETS gene fusions including TMPRSS2:ERG, elderly-onset PCAs displayed primarily non-androgen-associated SRs. Data from a validation cohort of > 10,000 patients showed age-dependent androgen receptor levels and a prevalence of SRs affecting androgen-regulated genes, further substantiating the activity of a characteristic "androgen-type" pathomechanism in EO-PCA.
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Decision-tree based model analysis for efficient identification of parameter relations leading to different signaling States.
PLoS ONE
PUBLISHED: 01-01-2013
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In systems biology, a mathematical description of signal transduction processes is used to gain a more detailed mechanistic understanding of cellular signaling networks. Such models typically depend on a number of parameters that have different influence on the model behavior. Local sensitivity analysis is able to identify parameters that have the largest effect on signaling strength. Bifurcation analysis shows on which parameters a qualitative model response depends. Most methods for model analysis are intrinsically univariate. They typically cannot consider combinations of parameters since the search space for such analysis would be too large. This limitation is important since activation of a signaling pathway often relies on multiple rather than on single factors. Here, we present a novel method for model analysis that overcomes this limitation. As input to a model defined by a system of ordinary differential equations, we consider parameters for initial chemical species concentrations. The model is used to simulate the system response, which is then classified into pre-defined classes (e.g., active or not active). This is combined with a scan of the parameter space. Parameter sets leading to a certain system response are subjected to a decision tree algorithm, which learns conditions that lead to this response. We compare our method to two alternative multivariate approaches to model analysis: analytical solution for steady states combined with a parameter scan, and direct Lyapunov exponent (DLE) analysis. We use three previously published models including a model for EGF receptor internalization and two apoptosis models to demonstrate the power of our approach. Our method reproduces critical parameter relations previously obtained by both steady-state and DLE analysis while being more generally applicable and substantially less computationally expensive. The method can be used as a general tool to predict multivariate control strategies for pathway activation and to suggest strategies for drug intervention.
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Coverage bias and sensitivity of variant calling for four whole-genome sequencing technologies.
PLoS ONE
PUBLISHED: 01-01-2013
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The emergence of high-throughput, next-generation sequencing technologies has dramatically altered the way we assess genomes in population genetics and in cancer genomics. Currently, there are four commonly used whole-genome sequencing platforms on the market: Illuminas HiSeq2000, Life Technologies SOLiD 4 and its completely redesigned 5500xl SOLiD, and Complete Genomics technology. A number of earlier studies have compared a subset of those sequencing platforms or compared those platforms with Sanger sequencing, which is prohibitively expensive for whole genome studies. Here we present a detailed comparison of the performance of all currently available whole genome sequencing platforms, especially regarding their ability to call SNVs and to evenly cover the genome and specific genomic regions. Unlike earlier studies, we base our comparison on four different samples, allowing us to assess the between-sample variation of the platforms. We find a pronounced GC bias in GC-rich regions for Life Technologies platforms, with Complete Genomics performing best here, while we see the least bias in GC-poor regions for HiSeq2000 and 5500xl. HiSeq2000 gives the most uniform coverage and displays the least sample-to-sample variation. In contrast, Complete Genomics exhibits by far the smallest fraction of bases not covered, while the SOLiD platforms reveal remarkable shortcomings, especially in covering CpG islands. When comparing the performance of the four platforms for calling SNPs, HiSeq2000 and Complete Genomics achieve the highest sensitivity, while the SOLiD platforms show the lowest false positive rate. Finally, we find that integrating sequencing data from different platforms offers the potential to combine the strengths of different technologies. In summary, our results detail the strengths and weaknesses of all four whole-genome sequencing platforms. It indicates application areas that call for a specific sequencing platform and disallow other platforms. This helps to identify the proper sequencing platform for whole genome studies with different application scopes.
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Normalizing for individual cell population context in the analysis of high-content cellular screens.
BMC Bioinformatics
PUBLISHED: 09-14-2011
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High-content, high-throughput RNA interference (RNAi) offers unprecedented possibilities to elucidate gene function and involvement in biological processes. Microscopy based screening allows phenotypic observations at the level of individual cells. It was recently shown that a cells population context significantly influences results. However, standard analysis methods for cellular screens do not currently take individual cell data into account unless this is important for the phenotype of interest, i.e. when studying cell morphology.
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Enhancers regulate progression of development in mammalian cells.
Nucleic Acids Res.
PUBLISHED: 07-23-2011
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During development and differentiation of an organism, accurate gene regulation is central for cells to maintain and balance their differentiation processes. Transcriptional interactions between cis-acting DNA elements such as promoters and enhancers are the basis for precise and balanced transcriptional regulation. We identified modules of combinations of binding sites in proximal and distal regulatory regions upstream of all transcription start sites (TSSs) in silico and applied these modules to gene expression time-series of mouse embryonic development and differentiation of human stem cells. In addition to tissue-specific regulation controlled by combinations of transcription factors (TFs) binding at promoters, we observed that in particular the combination of TFs binding at promoters together with TFs binding at the respective enhancers regulate highly specifically temporal progression during development: whereas 40% of TFs were specific for time intervals, 79% of TF pairs and even 97% of promoter-enhancer modules showed specificity for single time intervals of the human stem cells. Predominantly SP1 and E2F contributed to temporal specificity at promoters and the forkhead (FOX) family of TFs at enhancer regions. Altogether, we characterized three classes of TFs: with binding sites being enriched at the TSS (like SP1), depleted at the TSS (like FOX), and rather uniformly distributed.
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Proteomic bronchiolitis obliterans syndrome risk monitoring in lung transplant recipients.
Transplantation
PUBLISHED: 07-01-2011
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Obliterative bronchiolitis poses a primary obstacle for long-term survival of lung transplant recipients and manifests clinically as bronchiolitis obliterans syndrome (BOS). Establishing a molecular level screening method to detect BOS-related proteome changes before its diagnosis by forced expiratory volume surrogate marker criteria was the main objective of this study.
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RIP: the regulatory interaction predictor--a machine learning-based approach for predicting target genes of transcription factors.
Bioinformatics
PUBLISHED: 06-20-2011
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Understanding transcriptional gene regulation is essential for studying cellular systems. Identifying genome-wide targets of transcription factors (TFs) provides the basis to discover the involvement of TFs and TF cooperativeness in cellular systems and pathogenesis.
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Integration of activating and inhibitory receptor signaling by regulated phosphorylation of Vav1 in immune cells.
Sci Signal
PUBLISHED: 06-03-2011
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Natural killer (NK) cells are effector cells of the immune system whose activation is carefully regulated by the interplay of signals from activating and inhibitory receptors. Signals from activating receptors induce phosphorylation of the guanine nucleotide exchange factor Vav1, whereas those from inhibitory receptors lead to the dephosphorylation of Vav1 by the Src homology 2 domain-containing protein tyrosine phosphatase 1 (SHP-1). Here, we used mathematical modeling and experiments with NK cells to gain insight into this integration of positive and negative signals at a molecular level. Our data showed a switch-like regulation of Vav1 phosphorylation, the extent of which correlated with the cytotoxic activity of NK cells. Comparison of our experimental results with the predictions that we derived from an ensemble of 72 mathematical models showed that a physical association between Src family kinases and activating receptors on NK cells was essential to generate the cytotoxic response. Our data support a central role for Vav1 in determining the cytotoxic activity of NK cells and provide insight into the molecular mechanism of the integration of positive and negative signals during lymphocyte activation.
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Negative feedback in the bone morphogenetic protein 4 (BMP4) synexpression group governs its dynamic signaling range and canalizes development.
Proc. Natl. Acad. Sci. U.S.A.
PUBLISHED: 06-01-2011
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What makes embryogenesis a robust and canalized process is an important question in developmental biology. A bone morphogenetic protein (BMP) morphogen gradient plays a key role in embryonic development, and we are beginning to understand how the self-regulating properties of its signaling circuitry ensure robust embryonic patterning. An unexplored question is why the BMP signaling circuit is organized as a modular synexpression group, with a prevalence of feedback inhibitors. Here, we provide evidence from direct experimentation and mathematical modeling that the synexpressed feedback inhibitors BAMBI, SMAD6, and SMAD7 (i) expand the dynamic BMP signaling range essential for proper embryonic patterning and (ii) reduce interindividual phenotypic and molecular variability in Xenopus embryos. Thereby, negative feedback linearizes signaling responses and confers robust patterning, thus promoting canalized development. The presence of negative feedback inhibitors in other growth factor synexpression groups suggests that these properties may constitute a general principle.
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Probing compressibility of the nuclear interior in wild-type and lamin deficient cells using microscopic imaging and computational modeling.
J Biomech
PUBLISHED: 05-31-2011
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Mechanical properties of the cell nucleus play an important role in maintaining the integrity of the genome and controlling the cellular force balance. Irregularities in these properties have been related to disruption of a variety of force-dependent processes in the cell, such as migration, division, growth or differentiation. Characterizing mechanical properties of the cell nucleus in situ and relating these parameters to cellular phenotypes remain challenging tasks, as conventional micromanipulation techniques do not allow direct probing of intracellular structures. Here, we present a framework based on light microscopic imaging and automated mechanical modeling that enables characterization of the compressibility of the nuclear interior in situ. Based entirely on optical methods, our approach does not require application of destructive or contacting techniques and it enables measurements of a significantly larger number of cells. Compressibility, in this paper represented by Poissons ratio ?, is determined by fitting a numerical model to experimentally observed time series of microscopic images of fluorescent cell nuclei in which bleached patterns are introduced. In a proof-of-principle study, this framework was applied to estimate ? in wild type cells and cells lacking important structural proteins of the nuclear envelope (LMNA(-/-)). Based on measurements of a large number of cells, our study revealed distinctive changes in compressibility of the nuclear interior between these two cell types. Our method allows an automated, contact-free estimation of mechanical properties of intracellular structures. Combined with knockdown and overexpression screens, it paves the way towards a high-throughput measurement of intracellular mechanical properties in functional phenotyping screens.
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Herpesviral replication compartments move and coalesce at nuclear speckles to enhance export of viral late mRNA.
Proc. Natl. Acad. Sci. U.S.A.
PUBLISHED: 05-09-2011
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The role of the intranuclear movement of chromatin in gene expression is not well-understood. Herpes simplex virus forms replication compartments (RCs) in infected cell nuclei as sites of viral DNA replication and late gene transcription. These structures develop from small compartments that grow in size, move, and coalesce. Quantitative analysis of RC trajectories, derived from 4D images, shows that most RCs move by directed motion. Directed movement is impaired in the presence of actin and myosin inhibitors as well as a transcription inhibitor. In addition, RCs coalesce at and reorganize nuclear speckles. Lastly, distinct effects of actin and myosin inhibitors on viral gene expression suggest that RC movement is not required for transcription, but rather, movement results in the bridging of transcriptionally active RCs with nuclear speckles to form structures that enhance export of viral late mRNAs.
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Comparative transcriptome profiling of amyloid precursor protein family members in the adult cortex.
BMC Genomics
PUBLISHED: 03-24-2011
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The ?-amyloid precursor protein (APP) and the related ?-amyloid precursor-like proteins (APLPs) undergo complex proteolytic processing giving rise to several fragments. Whereas it is well established that A? accumulation is a central trigger for Alzheimers disease, the physiological role of APP family members and their diverse proteolytic products is still largely unknown. The secreted APPs? ectodomain has been shown to be involved in neuroprotection and synaptic plasticity. The ?-secretase-generated APP intracellular domain (AICD) functions as a transcriptional regulator in heterologous reporter assays although its role for endogenous gene regulation has remained controversial.
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Concurrent detection of autolysosome formation and lysosomal degradation by flow cytometry in a high-content screen for inducers of autophagy.
BMC Biol.
PUBLISHED: 02-16-2011
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Autophagy mediates lysosomal degradation of cytosolic components. Recent work has associated autophagic dysfunction with pathologies, including cancer and cardiovascular disease. To date, the identification of clinically-applicable drugs that modulate autophagy has been hampered by the lack of standardized assays capable of precisely reporting autophagic activity.
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Bronchoalveolar lavage fluid of lung cancer patients: mapping the uncharted waters using proteomics technology.
Lung Cancer
PUBLISHED: 01-20-2011
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The search for proteome-level markers of non-small cell lung cancer (NSCLC) has been mainly limited to serum or cell line screening approaches up to this point. We would like to demonstrate by this proof-of-principle study investigating bronchoalveolar lavage fluid samples from a cohort of NSCLC and control patients, that this readily available biofluid might be a more suitable source for discovering clinically usable NSCLC biomarkers.
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Recruitment and activation of a lipid kinase by hepatitis C virus NS5A is essential for integrity of the membranous replication compartment.
Cell Host Microbe
PUBLISHED: 01-18-2011
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Hepatitis C virus (HCV) is a major causative agent of chronic liver disease in humans. To gain insight into host factor requirements for HCV replication, we performed a siRNA screen of the human kinome and identified 13 different kinases, including phosphatidylinositol-4 kinase III alpha (PI4KIII?), as being required for HCV replication. Consistent with elevated levels of the PI4KIII? product phosphatidylinositol-4-phosphate (PI4P) detected in HCV-infected cultured hepatocytes and liver tissue from chronic hepatitis C patients, the enzymatic activity of PI4KIII? was critical for HCV replication. Viral nonstructural protein 5A (NS5A) was found to interact with PI4KIII? and stimulate its kinase activity. The absence of PI4KIII? activity induced a dramatic change in the ultrastructural morphology of the membranous HCV replication complex. Our analysis suggests that the direct activation of a lipid kinase by HCV NS5A contributes critically to the integrity of the membranous viral replication complex.
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Artesunate activates mitochondrial apoptosis in breast cancer cells via iron-catalyzed lysosomal reactive oxygen species production.
J. Biol. Chem.
PUBLISHED: 12-13-2010
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The antimalarial agent artesunate (ART) activates programmed cell death (PCD) in cancer cells in a manner dependent on the presence of iron and the generation of reactive oxygen species. In malaria parasites, ART cytotoxicity originates from interactions with heme-derived iron within the food vacuole. The analogous digestive compartment of mammalian cells, the lysosome, similarly contains high levels of redox-active iron and in response to specific stimuli can initiate mitochondrial apoptosis. We thus investigated the role of lysosomes in ART-induced PCD and determined that in MCF-7 breast cancer cells ART activates lysosome-dependent mitochondrial outer membrane permeabilization. ART impacted endolysosomal and autophagosomal compartments, inhibiting autophagosome turnover and causing perinuclear clustering of autophagosomes, early and late endosomes, and lysosomes. Lysosomal iron chelation blocked all measured parameters of ART-induced PCD, whereas lysosomal iron loading enhanced death, thus identifying lysosomal iron as the lethal source of reactive oxygen species upstream of mitochondrial outer membrane permeabilization. Moreover, lysosomal inhibitors chloroquine and bafilomycin A1 reduced ART-activated PCD, evidencing a requirement for lysosomal function during PCD signaling. ART killing did not involve activation of the BH3-only protein, Bid, yet ART enhanced TNF-mediated Bid cleavage. We additionally demonstrated the lysosomal PCD pathway in T47D and MDA-MB-231 breast cancer cells. Importantly, non-tumorigenic MCF-10A cells resisted ART-induced PCD. Together, our data suggest that ART triggers PCD via engagement of distinct, interconnected PCD pathways, with hierarchical signaling from lysosomes to mitochondria, suggesting a potential clinical use of ART for targeting lysosomes in cancer treatment.
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Large-scale in silico modeling of metabolic interactions between cell types in the human brain.
Nat. Biotechnol.
PUBLISHED: 11-21-2010
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Metabolic interactions between multiple cell types are difficult to model using existing approaches. Here we present a workflow that integrates gene expression data, proteomics data and literature-based manual curation to model human metabolism within and between different types of cells. Transport reactions are used to account for the transfer of metabolites between models of different cell types via the interstitial fluid. We apply the method to create models of brain energy metabolism that recapitulate metabolic interactions between astrocytes and various neuron types relevant to Alzheimers disease. Analysis of the models identifies genes and pathways that may explain observed experimental phenomena, including the differential effects of the disease on cell types and regions of the brain. Constraint-based modeling can thus contribute to the study and analysis of multicellular metabolic processes in the human tissue microenvironment and provide detailed mechanistic insight into high-throughput data analysis.
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An integrated genome research network for studying the genetics of alcohol addiction.
Addict Biol
PUBLISHED: 11-03-2010
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Alcohol drinking is highly prevalent in many cultures and contributes to the global burden of disease. In fact, it was shown that alcohol constitutes 3.2% of all worldwide deaths in the year 2006 and is linked to more than 60 diseases, including cancers, cardiovascular diseases, liver cirrhosis, neuropsychiatric disorders, injuries and foetal alcohol syndrome. Alcoholism, which has been proven to have a high genetic load, is one potentially fatal consequence of chronic heavy alcohol consumption, and may be regarded as one of the most prevalent neuropsychiatric diseases afflicting our society today. The aim of the integrated genome research network Genetics of Alcohol Addiction--which is a German inter-/trans-disciplinary life science consortium consisting of molecular biologists, behavioural pharmacologists, system biologists with mathematicians, human geneticists and clinicians--is to better understand the genetics of alcohol addiction by identifying and validating candidate genes and molecular networks involved in the aetiology of this pathology. For comparison, addictive behaviour to other drugs of abuse (e.g. cocaine) is studied as well. Here, we present an overview of our research consortium, the current state of the art on genetic research in the alcohol field, and list finally several of our recently published research highlights. As a result of our scientific efforts, better insights into the molecular and physiological processes underlying addictive behaviour will be obtained, new targets and target networks in the addicted brain will be defined, and subsequently, novel and individualized treatment strategies for our patients will be delivered.
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Nonrigid registration of 2-D and 3-D dynamic cell nuclei images for improved classification of subcellular particle motion.
IEEE Trans Image Process
PUBLISHED: 09-13-2010
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The observed motion of subcellular particles in fluorescence microscopy image sequences of live cells is generally a superposition of the motion and deformation of the cell and the motion of the particles. Decoupling the two types of movements to enable accurate classification of the particle motion requires the application of registration algorithms. We have developed an intensity-based approach for nonrigid registration of multichannel microscopy image sequences of cell nuclei. First, based on 3-D synthetic images we demonstrate that cell nucleus deformations change the observed motion types of particles and that our approach allows to recover the original motion. Second, we have successfully applied our approach to register 2-D and 3-D real microscopy image sequences. A quantitative experimental comparison with previous approaches for nonrigid registration of cell microscopy has also been performed.
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Analyzing the regulation of metabolic pathways in human breast cancer.
BMC Med Genomics
PUBLISHED: 09-10-2010
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Tumor therapy mainly attacks the metabolism to interfere the tumors anabolism and signaling of proliferative second messengers. However, the metabolic demands of different cancers are very heterogeneous and depend on their origin of tissue, age, gender and other clinical parameters. We investigated tumor specific regulation in the metabolism of breast cancer.
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Detecting host factors involved in virus infection by observing the clustering of infected cells in siRNA screening images.
Bioinformatics
PUBLISHED: 09-09-2010
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Detecting human proteins that are involved in virus entry and replication is facilitated by modern high-throughput RNAi screening technology. However, hit lists from different laboratories have shown only little consistency. This may be caused by not only experimental discrepancies, but also not fully explored possibilities of the data analysis. We wanted to improve reliability of such screens by combining a population analysis of infected cells with an established dye intensity readout.
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Model-based dissection of CD95 signaling dynamics reveals both a pro- and antiapoptotic role of c-FLIPL.
J. Cell Biol.
PUBLISHED: 08-11-2010
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Cellular FADD-like interleukin-1beta-converting enzyme inhibitory proteins (c-FLIPs; isoforms c-FLIP long [c-FLIP(L)], c-FLIP short [c-FLIP(S)], and c-FLIP Raji [c-FLIP(R)]) regulate caspase-8 activation and death receptor (DR)-induced apoptosis. In this study, using a combination of mathematical modeling, imaging, and quantitative Western blots, we present a new mathematical model describing caspase-8 activation in quantitative terms, which highlights the influence of c-FLIP proteins on this process directly at the CD95 death-inducing signaling complex. We quantitatively define how the stoichiometry of c-FLIP proteins determines sensitivity toward CD95-induced apoptosis. We show that c-FLIP(L) has a proapoptotic role only upon moderate expression in combination with strong receptor stimulation or in the presence of high amounts of one of the short c-FLIP isoforms, c-FLIP(S) or c-FLIP(R). Our findings resolve the present controversial discussion on the function of c-FLIP(L) as a pro- or antiapoptotic protein in DR-mediated apoptosis and are important for understanding the regulation of CD95-induced apoptosis, where subtle differences in c-FLIP concentrations determine life or death of the cells.
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Phenocopy--a strategy to qualify chemical compounds during hit-to-lead and/or lead optimization.
PLoS ONE
PUBLISHED: 06-23-2010
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A phenocopy is defined as an environmentally induced phenotype of one individual which is identical to the genotype-determined phenotype of another individual. The phenocopy phenomenon has been translated to the drug discovery process as phenotypes produced by the treatment of biological systems with new chemical entities (NCE) may resemble environmentally induced phenotypic modifications. Various new chemical entities exerting inhibition of the kinase activity of Transforming Growth Factor ? Receptor I (TGF-?R1) were qualified by high-throughput RNA expression profiling. This chemical genomics approach resulted in a precise time-dependent insight to the TGF-? biology and allowed furthermore a comprehensive analysis of each NCEs off-target effects. The evaluation of off-target effects by the phenocopy approach allows a more accurate and integrated view on optimized compounds, supplementing classical biological evaluation parameters such as potency and selectivity. It has therefore the potential to become a novel method for ranking compounds during various drug discovery phases.
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Tracking and quantitative analysis of dynamic movements of cells and particles.
Cold Spring Harb Protoc
PUBLISHED: 06-03-2010
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Understanding complex cellular processes requires investigating the underlying mechanisms within a spatiotemporal context. Although cellular processes are dynamic in nature, most studies in molecular cell biology are based on fixed specimens, for example, using immunocytochemistry or fluorescence in situ hybridization (FISH). However, breakthroughs in fluorescence microscopy imaging techniques, in particular, the discovery of green fluorescent protein (GFP) and its spectral variants, have facilitated the study of a wide range of dynamic processes by allowing nondestructive labeling of target structures in living cells. In addition, the tremendous improvements in spatial and temporal resolution of light microscopes now allow cellular processes to be analyzed in unprecedented detail. These state-of-the-art imaging technologies, however, provide a huge amount of digital image data. To cope with the enormous amount of image data and to extract reproducible as well as quantitative information, computer-based image analysis is required. In this article, we describe methods for computer-based analysis of multidimensional live cell microscopy images and their application to study the dynamics of cells and particles. First, we sketch a general workflow for quantitative analysis of live cell images. Then, we detail computational methods for automatic image analysis comprising image preprocessing, segmentation, registration, tracking, and classification. We conclude with a discussion of quantitative analysis and systems biology.
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Computational identification of signalling pathways in Plasmodium falciparum.
Infect. Genet. Evol.
PUBLISHED: 05-10-2010
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Malaria is one of the worlds most common and serious diseases causing death of about 3 million people each year. Its most severe occurrence is caused by the protozoan Plasmodium falciparum. Reports have shown that the resistance of the parasite to existing drugs is increasing. Therefore, there is a huge and urgent need to discover and validate new drug or vaccine targets to enable the development of new treatments for malaria. The ability to discover these drug or vaccine targets can only be enhanced from our deep understanding of the detailed biology of the parasite, for example how cells function and how proteins organize into modules such as metabolic, regulatory and signal transduction pathways. It has been noted that the knowledge of signalling transduction pathways in Plasmodium is fundamental to aid the design of new strategies against malaria. This work uses a linear-time algorithm for finding paths in a network under modified biologically motivated constraints. We predicted several important signalling transduction pathways in Plasmodium falciparum. We have predicted a viable signalling pathway characterized in terms of the genes responsible that may be the PfPKB pathway recently elucidated in Plasmodium falciparum. We obtained from the FIKK family, a signal transduction pathway that ends up on a chloroquine resistance marker protein, which indicates that interference with FIKK proteins might reverse Plasmodium falciparum from resistant to sensitive phenotype. We also proposed a hypothesis that showed the FIKK proteins in this pathway as enabling the resistance parasite to have a mechanism for releasing chloroquine (via an efflux process). Furthermore, we also predicted a signalling pathway that may have been responsible for signalling the start of the invasion process of Red Blood Cell (RBC) by the merozoites. It has been noted that the understanding of this pathway will give insight into the parasite virulence and will facilitate rational vaccine design against merozoites invasion. And we have a host of other predicted pathways, some of which have been used in this work to predict the functionality of some proteins.
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Identifying essential genes in bacterial metabolic networks with machine learning methods.
BMC Syst Biol
PUBLISHED: 05-03-2010
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Identifying essential genes in bacteria supports to identify potential drug targets and an understanding of minimal requirements for a synthetic cell. However, experimentally assaying the essentiality of their coding genes is resource intensive and not feasible for all bacterial organisms, in particular if they are infective.
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Identification of the Rage-dependent gene regulatory network in a mouse model of skin inflammation.
BMC Genomics
PUBLISHED: 04-21-2010
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In the past, molecular mechanisms that drive the initiation of an inflammatory response have been studied intensively. However, corresponding mechanisms that sustain the expression of inflammatory response genes and hence contribute to the establishment of chronic disorders remain poorly understood. Recently, we provided genetic evidence that signaling via the receptor for advanced glycation end products (Rage) drives the strength and maintenance of an inflammatory reaction. In order to decipher the mode of Rage function on gene transcription levels during inflammation, we applied global gene expression profiling on time-resolved samples of mouse back skin, which had been treated with the phorbol ester TPA, a potent inducer of skin inflammation.
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International network of cancer genome projects.
, Thomas J Hudson, Warwick Anderson, Axel Artez, Anna D Barker, Cindy Bell, Rosa R Bernabé, M K Bhan, Fabien Calvo, Iiro Eerola, Daniela S Gerhard, Alan Guttmacher, Mark Guyer, Fiona M Hemsley, Jennifer L Jennings, David Kerr, Peter Klatt, Patrik Kolar, Jun Kusada, David P Lane, Frank Laplace, Lu Youyong, Gerd Nettekoven, Brad Ozenberger, Jane Peterson, T S Rao, Jacques Remacle, Alan J Schafer, Tatsuhiro Shibata, Michael R Stratton, Joseph G Vockley, Koichi Watanabe, Huanming Yang, Matthew M F Yuen, Bartha M Knoppers, Martin Bobrow, Anne Cambon-Thomsen, Lynn G Dressler, Stephanie O M Dyke, Yann Joly, Kazuto Kato, Karen L Kennedy, Pilar Nicolás, Michael J Parker, Emmanuelle Rial-Sebbag, Carlos M Romeo-Casabona, Kenna M Shaw, Susan Wallace, Georgia L Wiesner, Nikolajs Zeps, Peter Lichter, Andrew V Biankin, Christian Chabannon, Lynda Chin, Bruno Clément, Enrique De Alava, Françoise Degos, Martin L Ferguson, Peter Geary, D Neil Hayes, Amber L Johns, Arek Kasprzyk, Hidewaki Nakagawa, Robert Penny, Miguel A Piris, Rajiv Sarin, Aldo Scarpa, Marc van de Vijver, P Andrew Futreal, Hiroyuki Aburatani, Mònica Bayés, David D L Botwell, Peter J Campbell, Xavier Estivill, Sean M Grimmond, Ivo Gut, Martin Hirst, Carlos Lopez-Otin, Partha Majumder, Marco Marra, John D McPherson, Zemin Ning, Xose S Puente, Yijun Ruan, Hendrik G Stunnenberg, Harold Swerdlow, Victor E Velculescu, Richard K Wilson, Hong H Xue, Liu Yang, Paul T Spellman, Gary D Bader, Paul C Boutros, Paul Flicek, Gad Getz, Roderic Guigo, Guangwu Guo, David Haussler, Simon Heath, Tim J Hubbard, Tao Jiang, Steven M Jones, Qibin Li, Nuria López-Bigas, Ruibang Luo, Lakshmi Muthuswamy, B F Francis Ouellette, John V Pearson, Víctor Quesada, Benjamin J Raphael, Chris Sander, Terence P Speed, Lincoln D Stein, Joshua M Stuart, Jon W Teague, Yasushi Totoki, Tatsuhiko Tsunoda, Alfonso Valencia, David A Wheeler, Honglong Wu, Shancen Zhao, Guangyu Zhou, Mark Lathrop, Gilles Thomas, Teruhiko Yoshida, Myles Axton, Chris Gunter, Linda J Miller, Junjun Zhang, Syed A Haider, Jianxin Wang, Christina K Yung, Anthony Cros, Anthony Cross, Yong Liang, Saravanamuttu Gnaneshan, Jonathan Guberman, Jack Hsu, Don R C Chalmers, Karl W Hasel, Terry S H Kaan, William W Lowrance, Tohru Masui, Laura Lyman Rodriguez, Catherine Vergely, David D L Bowtell, Nicole Cloonan, Anna deFazio, James R Eshleman, Dariush Etemadmoghadam, Brooke B Gardiner, Brooke A Gardiner, James G Kench, Robert L Sutherland, Margaret A Tempero, Nicola J Waddell, Peter J Wilson, Steve Gallinger, Ming-Sound Tsao, Patricia A Shaw, Gloria M Petersen, Debabrata Mukhopadhyay, Ronald A DePinho, Sarah Thayer, Kamran Shazand, Timothy Beck, Michelle Sam, Lee Timms, Vanessa Ballin, Youyong Lu, Jiafu Ji, Xiuqing Zhang, Feng Chen, Xueda Hu, Qi Yang, Geng Tian, Lianhai Zhang, Xiaofang Xing, Xianghong Li, Zhenggang Zhu, Yingyan Yu, Jun Yu, Jörg Tost, Paul Brennan, Ivana Holcatova, David Zaridze, Alvis Brazma, Lars Egevard, Egor Prokhortchouk, Rosamonde Elizabeth Banks, Mathias Uhlén, Juris Viksna, Fredrik Ponten, Konstantin Skryabin, Ewan Birney, Ake Borg, Anne-Lise Børresen-Dale, Carlos Caldas, John A Foekens, Sancha Martin, Jorge S Reis-Filho, Andrea L Richardson, Christos Sotiriou, Giles Thoms, Laura van't Veer, Daniel Birnbaum, Hélène Blanché, Pascal Boucher, Sandrine Boyault, Jocelyne D Masson-Jacquemier, Iris Pauporté, Xavier Pivot, Anne Vincent-Salomon, Eric Tabone, Charles Theillet, Isabelle Treilleux, Paulette Bioulac-Sage, Thomas Decaens, Dominique Franco, Marta Gut, Didier Samuel, Jessica Zucman-Rossi, Roland Eils, Benedikt Brors, Jan O Korbel, Andrey Korshunov, Pablo Landgraf, Hans Lehrach, Stefan Pfister, Bernhard Radlwimmer, Guido Reifenberger, Michael D Taylor, Christof von Kalle, Partha P Majumder, Paolo Pederzoli, Rita A Lawlor, Massimo Delledonne, Alberto Bardelli, Thomas Gress, David Klimstra, Giuseppe Zamboni, Yusuke Nakamura, Satoru Miyano, Akihiro Fujimoto, Elias Campo, Silvia de Sanjosé, Emili Montserrat, Marcos Gonzalez-Díaz, Pedro Jares, Heinz Himmelbauer, Heinz Himmelbaue, Sílvia Beà, Samuel Aparicio, Douglas F Easton, Francis S Collins, Carolyn C Compton, Eric S Lander, Wylie Burke, Anthony R Green, Stanley R Hamilton, Olli P Kallioniemi, Timothy J Ley, Edison T Liu, Brandon J Wainwright.
Nature
PUBLISHED: 04-16-2010
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The International Cancer Genome Consortium (ICGC) was launched to coordinate large-scale cancer genome studies in tumours from 50 different cancer types and/or subtypes that are of clinical and societal importance across the globe. Systematic studies of more than 25,000 cancer genomes at the genomic, epigenomic and transcriptomic levels will reveal the repertoire of oncogenic mutations, uncover traces of the mutagenic influences, define clinically relevant subtypes for prognosis and therapeutic management, and enable the development of new cancer therapies.
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PathWave: discovering patterns of differentially regulated enzymes in metabolic pathways.
Bioinformatics
PUBLISHED: 03-24-2010
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Gene expression profiling by microarrays or transcript sequencing enables observing the pathogenic function of tumors on a mesoscopic level.
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Omic data from evolved E. coli are consistent with computed optimal growth from genome-scale models.
Mol. Syst. Biol.
PUBLISHED: 03-18-2010
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After hundreds of generations of adaptive evolution at exponential growth, Escherichia coli grows as predicted using flux balance analysis (FBA) on genome-scale metabolic models (GEMs). However, it is not known whether the predicted pathway usage in FBA solutions is consistent with gene and protein expression in the wild-type and evolved strains. Here, we report that >98% of active reactions from FBA optimal growth solutions are supported by transcriptomic and proteomic data. Moreover, when E. coli adapts to growth rate selective pressure, the evolved strains upregulate genes within the optimal growth predictions, and downregulate genes outside of the optimal growth solutions. In addition, bottlenecks from dosage limitations of computationally predicted essential genes are overcome in the evolved strains. We also identify regulatory processes that may contribute to the development of the optimal growth phenotype in the evolved strains, such as the downregulation of known regulons and stringent response suppression. Thus, differential gene and protein expression from wild-type and adaptively evolved strains supports observed growth phenotype changes, and is consistent with GEM-computed optimal growth states.
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Comparison of normalization methods for Illumina BeadChip HumanHT-12 v3.
BMC Genomics
PUBLISHED: 03-09-2010
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Normalization of microarrays is a standard practice to account for and minimize effects which are not due to the controlled factors in an experiment. There is an overwhelming number of different methods that can be applied, none of which is ideally suited for all experimental designs. Thus, it is important to identify a normalization method appropriate for the experimental setup under consideration that is neither too negligent nor too stringent. Major aim is to derive optimal results from the underlying experiment. Comparisons of different normalization methods have already been conducted, none of which, to our knowledge, comparing more than a handful of methods.
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Dynamics within the CD95 death-inducing signaling complex decide life and death of cells.
Mol. Syst. Biol.
PUBLISHED: 03-09-2010
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This study explores the dilemma in cellular signaling that triggering of CD95 (Fas/APO-1) in some situations results in cell death and in others leads to the activation of NF-kappaB. We established an integrated kinetic mathematical model for CD95-mediated apoptotic and NF-kappaB signaling. Systematic model reduction resulted in a surprisingly simple model well approximating experimentally observed dynamics. The model postulates a new link between c-FLIP(L) cleavage in the death-inducing signaling complex (DISC) and the NF-kappaB pathway. We validated experimentally that CD95 stimulation resulted in an interaction of p43-FLIP with the IKK complex followed by its activation. Furthermore, we showed that the apoptotic and NF-kappaB pathways diverge already at the DISC. Model and experimental analysis of DISC formation showed that a subtle balance of c-FLIP(L) and procaspase-8 determines life/death decisions in a nonlinear manner. We present an integrated model describing the complex dynamics of CD95-mediated apoptosis and NF-kappaB signaling.
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The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.
Leming Shi, Gregory Campbell, Wendell D Jones, Fabien Campagne, Zhining Wen, Stephen J Walker, Zhenqiang Su, Tzu-Ming Chu, Federico M Goodsaid, Lajos Pusztai, John D Shaughnessy, André Oberthuer, Russell S Thomas, Richard S Paules, Mark Fielden, Bart Barlogie, Weijie Chen, Pan Du, Matthias Fischer, Cesare Furlanello, Brandon D Gallas, Xijin Ge, Dalila B Megherbi, W Fraser Symmans, May D Wang, John Zhang, Hans Bitter, Benedikt Brors, Pierre R Bushel, Max Bylesjo, Minjun Chen, Jie Cheng, Jing Cheng, Jeff Chou, Timothy S Davison, Mauro Delorenzi, Youping Deng, Viswanath Devanarayan, David J Dix, Joaquin Dopazo, Kevin C Dorff, Fathi Elloumi, Jianqing Fan, Shicai Fan, Xiaohui Fan, Hong Fang, Nina Gonzaludo, Kenneth R Hess, Huixiao Hong, Jun Huan, Rafael A Irizarry, Richard Judson, Dilafruz Juraeva, Samir Lababidi, Christophe G Lambert, Li Li, Yanen Li, Zhen Li, Simon M Lin, Guozhen Liu, Edward K Lobenhofer, Jun Luo, Wen Luo, Matthew N McCall, Yuri Nikolsky, Gene A Pennello, Roger G Perkins, Reena Philip, Vlad Popovici, Nathan D Price, Feng Qian, Andreas Scherer, Tieliu Shi, Weiwei Shi, Jaeyun Sung, Danielle Thierry-Mieg, Jean Thierry-Mieg, Venkata Thodima, Johan Trygg, Lakshmi Vishnuvajjala, Sue Jane Wang, Jianping Wu, Yichao Wu, Qian Xie, Waleed A Yousef, Liang Zhang, Xuegong Zhang, Sheng Zhong, Yiming Zhou, Sheng Zhu, Dhivya Arasappan, Wenjun Bao, Anne Bergstrom Lucas, Frank Berthold, Richard J Brennan, Andreas Buness, Jennifer G Catalano, Chang Chang, Rong Chen, Yiyu Cheng, Jian Cui, Wendy Czika, Francesca Demichelis, Xutao Deng, Damir Dosymbekov, Roland Eils, Yang Feng, Jennifer Fostel, Stephanie Fulmer-Smentek, James C Fuscoe, Laurent Gatto, Weigong Ge, Darlene R Goldstein, Li Guo, Donald N Halbert, Jing Han, Stephen C Harris, Christos Hatzis, Damir Herman, Jianping Huang, Roderick V Jensen, Rui Jiang, Charles D Johnson, Giuseppe Jurman, Yvonne Kahlert, Sadik A Khuder, Matthias Kohl, Jianying Li, Menglong Li, Quan-Zhen Li, Shao Li, Zhiguang Li, Jie Liu, Ying Liu, Zhichao Liu, Lu Meng, Manuel Madera, Francisco Martínez-Murillo, Ignacio Medina, Joseph Meehan, Kelci Miclaus, Richard A Moffitt, David Montaner, Piali Mukherjee, George J Mulligan, Padraic Neville, Tatiana Nikolskaya, Baitang Ning, Grier P Page, Joel Parker, R Mitchell Parry, Xuejun Peng, Ron L Peterson, John H Phan, Brian Quanz, Yi Ren, Samantha Riccadonna, Alan H Roter, Frank W Samuelson, Martin M Schumacher, Joseph D Shambaugh, Qiang Shi, Richard Shippy, Shengzhu Si, Aaron Smalter, Christos Sotiriou, Mat Soukup, Frank Staedtler, Guido Steiner, Todd H Stokes, Qinglan Sun, Pei-Yi Tan, Rong Tang, Zivana Težak, Brett Thorn, Marina Tsyganova, Yaron Turpaz, Silvia C Vega, Roberto Visintainer, Juergen von Frese, Charles Wang, Eric Wang, Junwei Wang, Wei Wang, Frank Westermann, James C Willey, Matthew Woods, Shujian Wu, Nianqing Xiao, Joshua Xu, Lei Xu, Lun Yang, Xiao Zeng, Jialu Zhang, Li Zhang, Min Zhang, Chen Zhao, Raj K Puri, Uwe Scherf, Weida Tong, Russell D Wolfinger, .
Nat. Biotechnol.
PUBLISHED: 03-02-2010
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Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.
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Bayesian statistical modelling of human protein interaction network incorporating protein disorder information.
BMC Bioinformatics
PUBLISHED: 01-25-2010
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We present a statistical method of analysis of biological networks based on the exponential random graph model, namely p2-model, as opposed to previous descriptive approaches. The model is capable to capture generic and structural properties of a network as emergent from local interdependencies and uses a limited number of parameters. Here, we consider one global parameter capturing the density of edges in the network, and local parameters representing each nodes contribution to the formation of edges in the network. The modelling suggests a novel definition of important nodes in the network, namely social, as revealed based on the local sociality parameters of the model. Moreover, the sociality parameters help to reveal organizational principles of the network. An inherent advantage of our approach is the possibility of hypotheses testing: a priori knowledge about biological properties of the nodes can be incorporated into the statistical model to investigate its influence on the structure of the network.
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Phenotypic profiling of the human genome by time-lapse microscopy reveals cell division genes.
Nature
PUBLISHED: 01-22-2010
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Despite our rapidly growing knowledge about the human genome, we do not know all of the genes required for some of the most basic functions of life. To start to fill this gap we developed a high-throughput phenotypic screening platform combining potent gene silencing by RNA interference, time-lapse microscopy and computational image processing. We carried out a genome-wide phenotypic profiling of each of the approximately 21,000 human protein-coding genes by two-day live imaging of fluorescently labelled chromosomes. Phenotypes were scored quantitatively by computational image processing, which allowed us to identify hundreds of human genes involved in diverse biological functions including cell division, migration and survival. As part of the Mitocheck consortium, this study provides an in-depth analysis of cell division phenotypes and makes the entire high-content data set available as a resource to the community.
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Automatic analysis of dividing cells in live cell movies to detect mitotic delays and correlate phenotypes in time.
Genome Res.
PUBLISHED: 10-01-2009
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Live-cell imaging allows detailed dynamic cellular phenotyping for cell biology and, in combination with small molecule or drug libraries, for high-content screening. Fully automated analysis of live cell movies has been hampered by the lack of computational approaches that allow tracking and recognition of individual cell fates over time in a precise manner. Here, we present a fully automated approach to analyze time-lapse movies of dividing cells. Our method dynamically categorizes cells into seven phases of the cell cycle and five aberrant morphological phenotypes over time. It reliably tracks cells and their progeny and can thus measure the length of mitotic phases and detect cause and effect if mitosis goes awry. We applied our computational scheme to annotate mitotic phenotypes induced by RNAi gene knockdown of CKAP5 (also known as ch-TOG) or by treatment with the drug nocodazole. Our approach can be readily applied to comparable assays aiming at uncovering the dynamic cause of cell division phenotypes.
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Prediction of small molecule binding property of protein domains with Bayesian classifiers based on Markov chains.
Comput Biol Chem
PUBLISHED: 09-25-2009
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Accurate computational methods that can help to predict biological function of a protein from its sequence are of great interest to research biologists and pharmaceutical companies. One approach to assume the function of proteins is to predict the interactions between proteins and other molecules. In this work, we propose a machine learning method that uses a primary sequence of a domain to predict its propensity for interaction with small molecules. By curating the Pfam database with respect to the small molecule binding ability of its component domains, we have constructed a dataset of small molecule binding and non-binding domains. This dataset was then used as training set to learn a Bayesian classifier, which should distinguish members of each class. The domain sequences of both classes are modelled with Markov chains. In a Jack-knife test, our classification procedure achieved the predictive accuracies of 77.2% and 66.7% for binding and non-binding classes respectively. We demonstrate the applicability of our classifier by using it to identify previously unknown small molecule binding domains. Our predictions are available as supplementary material and can provide very useful information to drug discovery specialists. Given the ubiquitous and essential role small molecules play in biological processes, our method is important for identifying pharmaceutically relevant components of complete proteomes. The software is available from the author upon request.
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JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

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