bluuebunny/crossref_metadata_2025_split huggingface dataset:
A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin
Authors: Santos Sean M. , Hartman John L. 
Published: January 2019

AbstractBackgroundSaccharomyces cerevisiaerepresses respiration in the presence of adequate glucose, mimicking the Warburg effect, termed aerobic glycolysis. We conducted yeast phenomic experiments to characterize differential doxorubicin-gene interaction, in the context of respirationvs.glycolysis. The resulting systems level biology about doxorubicin cytotoxicity, including the influence of the Warburg effect, was integrated with cancer pharmacogenomics data to identify potentially causal correlations between differential gene expression and anti-cancer efficacy.MethodsQuantitative high-throughput cell array phenotyping (Q-HTCP) was used to measure cell proliferation phenotypes (CPPs) of the yeast gene knockout/knockdown library, treated with escalating doxorubicin concentrations in fermentable and non-fermentable media. Doxorubicin-gene interaction was quantified by departure of the observed and expected phenotypes for the doxorubicin-treated mutant strain, with respect to phenotypes for the untreated mutant strain and both the treated and untreated reference strain. Recursive expectation-maximization clustering (REMc) and Gene Ontology-based analyses of interactions were used to identify functional biological modules that buffer doxorubicin cytotoxicity, and to characterize their Warburg-dependence. Yeast phenomic data was applied to cancer cell line pharmacogenomics data to predict differential gene expression that causally influences the anti-tumor efficacy, and potentially the anthracycline-associated host toxicity, of doxorubicin.ResultsDoxorubicin cytotoxicity was greater with respiration, suggesting the Warburg effect can influence therapeutic efficacy. Accordingly, doxorubicin drug-gene interaction was more extensive with respiration, including increased buffering by cellular processes related to chromatin organization, protein folding and modification, translation reinitiation, spermine metabolism, and fatty acid beta-oxidation. Pathway enrichment was less notable for glycolysis-specific buffering. Cellular processes exerting influence relatively independently, with respect to Warburg status, included homologous recombination, sphingolipid homeostasis, telomere tethering at nuclear periphery, and actin cortical patch localization. Causality for differential gene expression associated with doxorubicin cytotoxicity in tumor cells was predicted within the biological context of the phenomic model.ConclusionsWarburg status influences the genetic requirements to buffer doxorubicin toxicity. Yeast phenomics provides an experimental platform to model the complexity of gene interaction networks that influence human disease phenotypes, as in this example of chemotherapy response. High-resolution, systems level yeast phenotyping is useful to predict the biological influence of functional variation on disease, offering the potential to fundamentally advance precision medicine.
Siliplant1 (Slp1) protein precipitates silica in sorghum silica cells
Authors: Kumar Santosh , Adiram-Filiba Nurit , Blum Shula , Sanchez-Lopez Javier Arturo , Tzfadia Oren , Omid Ayelet , Volpin Hanne , Heifetz Yael , Goobes Gil , Elbaum Rivka 
Published: January 2019

SummarySilicon is absorbed by plant roots as silicic acid. The acid moves with the transpiration stream to the shoot, and mineralizes as silica. In grasses, leaf epidermal cells called silica cells deposit silica in most of their volume by unknown mechanism.Using bioinformatics tools, we identified a previously uncharacterized protein in sorghum (Sorghum bicolor), which we named Siliplant1 (Slp1). Silica precipitation activity in vitro, expression profile, and activity in precipitating biosilica in vivo were characterized.Slp1 is a basic protein with seven repeat units rich in proline, lysine, and glutamic acid. A short peptide, repeating five times in the protein precipitated silica in vitro at a biologically relevant silicic acid concentration. Raman and NMR spectroscopies showed that the peptide attached the silica through lysine amine groups, forming a mineral-peptide open structure. We found Slp1 expression in immature leaf and inflorescence tissues. In the immature leaf active silicification zone, Slp1 was localized to the cytoplasm or near cell boundaries of silica cells. It was packed in vesicles and secreted to the paramural space. Transient overexpression of Slp1 in sorghum resulted in ectopic silica deposition in all leaf epidermal cell types.Our results show that Slp1 precipitates silica in sorghum silica cells.
Spontaneously emerging patterns in human visual cortex and their functional connectivity are linked to the patterns evoked by visual stimuli
Authors: Kim DoHyun , Livne Tomer , Metcalf Nicholas V. , Corbetta Maurizio , Shulman Gordon L. 
Published: January 2019

AbstractThe function of spontaneous brain activity is an important issue in neuroscience. Here we test the hypothesis that patterns of spontaneous activity code representational patterns evoked by stimuli and tasks. We compared in human visual cortex multi-vertex patterns of spontaneous activity to patterns evoked by ecological visual stimuli (faces, bodies, scenes) and low-level visual features (e.g. phase-scrambled faces). Specifically, we identified regions that preferred particular stimulus categories during localizer scans (e.g. extra-striate body area for bodies), measured multi-vertex patterns for each category during event-related task scans, and then correlated over vertices these stimulus-evoked patterns to the pattern measured on each frame of resting-state scans. The mean correlation coefficient was essentially zero for all regions/stimulus categories, indicating that resting multi-vertex patterns were not biased toward particular stimulus-evoked patterns. However, the spread of correlation coefficients between stimulus-evoked and resting patterns, i.e. both positive and negative, was significantly greater for the preferred stimulus category of an ROI (e.g. body category in body-preferring ROIs). The relationship between spontaneous and stimulus-evoked multi-vertex patterns also governed the temporal correlation or functional connectivity of patterns of spontaneous activity between individual regions (pattern-based functional connectivity). Resting patterns related to an object category fluctuated preferentially between ROIs preferring the same category, and patterns related to different categories fluctuated independently within their respective preferred ROIs (e.g. body- and scene-related multi-vertex patterns within body- and scene-preferring ROIs). These results support the general proposal that spontaneous multi-vertex activity patterns are linked to stimulus-evoked patterns, consistent with a representational function for spontaneous activity.
Recognizing off-sample mass spectrometry images with machine and deep learning
Authors: Ovchinnikova Katja , Kovalev Vitaly , Stuart Lachlan , Alexandrov Theodore 
Published: January 2019

AbstractMotivationImaging mass spectrometry (imaging MS) is a powerful technology for revealing localizations of hundreds of molecules in tissue sections. However, imaging MS data is polluted with off-sample ions caused by caused by sample preparation, particularly by the MALDI matrix application. The presence of the off-sample ion images confounds and hinders metabolite identification and downstream analysis.ResultsWe created a high-quality gold standard of 23238 manually tagged ion images from 87 public datasets from the METASPACE knowledge base. We developed several machine and deep learning methods for recognizing off-sample ion images. Deep residual learning performed the best with the F1 score of 0.97. Spatio-molecular biclustering method achieved the F1 scores of 0.96 and 0.93 in semi- and fully-automated scenarios, respectively. Molecular co-localization method achieved the F1 score of 0.90. We investigated the clusters of the DHB matrix, the most common MALDI matrix, and characterized parameters of a clusters combinatorial model. This work addresses an important issue in imaging MS and illustrates how public data, modern web technologies, and machine and deep learning open novel avenues in imaging MS.Availability and ImplementationData and source code are available at: https://github.com/metaspace2020/offsample.Contacttheodore.alexandrov@embl.de
Kinesin-5 promotes microtubule nucleation and assembly by stabilizing a lattice-competent conformation of tubulin
Authors: Chen Geng-Yuan , Asenjo Ana B. , Chen Yalei , Mascaro Jake , Arginteanu David F. J. , Sosa Hernando , Hancock William O. 
Published: January 2019

SummaryBesides sliding apart antiparallel microtubules during spindle elongation, the mitotic kinesin-5, Eg5 promotes microtubule polymerization, emphasizing its importance in mitotic spindle length control. Here, we characterize the Eg5 microtubule polymerase mechanism by assessing motor-induced changes in the longitudinal and lateral tubulin-tubulin bonds that form the microtubule lattice. Isolated Eg5 motor domains promote microtubule nucleation, growth and stability. Eg5 binds preferentially to microtubules over free tubulin, and colchicine-like inhibitors that stabilize the bent conformation of tubulin allosterically inhibit Eg5 binding, consistent with a model in which Eg5 induces a curved-to-straight transition in tubulin. Domain swap experiments establish that the family-specific Loop11, which resides near the nucleotide-sensing Switch-II domain, is necessary and sufficient for the polymerase activity of Eg5. Thus, we propose a microtubule polymerase mechanism in which Eg5 at the plus-end promotes a curved-to-straight transition in tubulin that enhances lateral bond formation and thereby promotes microtubule growth and stability.
Cross-talk of cellulose and mannan perception pathways leads to inhibition of cellulase production in several filamentous fungi
Authors: Hassan Lara , Lin Liangcai , Sorek Hagit , Goudoulas Thomas , Germann Natalie , Tian Chaoguang , Benz J. Philipp 
Published: January 2019

AbstractIt is essential for microbes to acquire information about their environment. Fungi use soluble degradation products of plant cell wall components to understand the substrate composition they grow on. Individual signaling pathways have been well described. However, the interconnections between pathways remain poorly understood. In the present work, we provide evidence of “confusion” due to cross-talk between the perception pathways for cellulose and the hemicellulose mannan in several filamentous fungi, leading to the inhibition of cellulase expression. We used the functional genomics tools available forNeurospora crassato investigate this signaling overlap at the molecular level. Cross-talk and competitive inhibition could be identified both during uptake by cellodextrin transporters and intracellularly. Importantly, the overlap is independent of CRE-1-mediated catabolite repression. These results provide novel insights into the regulatory networks of lignocellulolytic fungi and will contribute to the rational optimization of fungal enzyme production for efficient plant biomass depolymerization and utilization.
A hypomorphic allele of telomerase reverse transcriptase uncovers the minimal functional length of telomeres in Arabidopsis
Authors: Watson J. Matthew , Trieb Johanna , Troestl Martina , Renfrew Kyle , Mandakova Terezie , Shippen Dorothy E. , Riha Karel 
Published: January 2019

AbstractDespite the essential requirement of telomeric DNA for genome stability, the length of telomere tracts between species differs by up to four orders of magnitude, raising the question of the minimal length of telomeric DNA necessary for proper function. Here we address this question using a hypomorphic allele of the telomerase catalytic subunit, TERT. We show that although this construct partially restored telomerase activity to a tert mutant, telomeres continued to shorten over several generations, ultimately stabilizing at a bimodal size distribution. Telomeres on two chromosome arms were maintained at a length of 1kb, while the remaining telomeres were maintained at 400 bp. The longest telomeres identified in this background were also significantly longer in wild type populations, suggesting cis-acting elements on these arms either promote telomerase processivity or recruitment. Genetically disrupting telomerase processivity in this background resulted in immediate lethality. Thus, telomeres of 400 bp are both necessary and sufficient for Arabidopsis viability. As this length is the estimated minimal length for t-loop formation, our data suggest that telomeres long enough to form a t-loop constitute the minimal functional length.
Epigenetic deregulation of lamina-associated domains in Hutchinson-Gilford Progeria Syndrome
Authors: Köhler Florian , Bormann Felix , Raddatz Günter , Gutekunst Julian , Musch Tanja , Lyko Frank , Rodríguez-Paredes Manuel 
Published: January 2019

AbstractHutchinson-Gilford Progeria Syndrome (HGPS) is a progeroid disease characterized by the early onset of some classically age-related phenotypes including arthritis, loss of body fat and hair and atherosclerosis. Cells from affected individuals express a mutant version of the nuclear envelope protein Lamin A (termed Progerin) and have previously been shown to exhibit prominent chromatin changes. Here, we identify epigenetic deregulation of lamina-associated domains (LADs) as a central feature in the molecular pathology of HGPS. Using ATAC-see/-seq and Infinium MethylationEPIC BeadChip-mediated DNA methylation profiling, we demonstrate that dermal fibroblasts from HGPS patients exhibit both chromatin accessibility and DNA methylation changes that are enriched in LADs. Importantly, we further show that these epigenetic alterations are associated with HGPS-specific gene expression changes. Together, our results establish a central involvement of LADs in the epigenetic deregulation of HGPS and provide novel insight into the molecular changes associated with the disease.
SEMA4C is a novel target to limit osteosarcoma growth, progression, and metastasis
Authors: Smeester Branden A. , Slipek Nicholas J. , Pomeroy Emily J. , Bomberger Heather E. , Shamsan Ghaidan A. , Peterson Joseph J. , Crosby Margaret R. , Draper Garrett M. , Becklin Kelsie L. , Rahrmann Eric P. , McCarthy James B. , Odde David J. , Wood David K. , Largaespada David A. , Moriarity Branden S. 
Published: January 2019

AbstractSemaphorins, specifically type IV, are important regulators of axonal guidance and have been increasingly implicated in poor prognoses in a number of different solid cancers. In conjunction with their cognate PLXNB family receptors, type IV members have been increasingly shown to mediate oncogenic functions necessary for tumor development and malignant spread. In this study, we investigated the role of semaphorin 4C (SEMA4C) in osteosarcoma growth, progression, and metastasis. We investigated the expression and localization of SEMA4C in primary osteosarcoma patient tissues and its tumorigenic functions in these malignancies. We demonstrate that overexpression of SEMA4C promotes properties of cellular transformation, while RNAi knockdown of SEMA4C promotes adhesion and reduces cellular proliferation, colony formation, migration, wound healing, tumor growth, and lung metastasis. These phenotypic changes were accompanied by reductions in activated AKT signaling, G1 cell cycle delay, and decreases in expression of mesenchymal marker genes SNAI1, SNAI2, and TWIST1. Lastly, monoclonal antibody blockade of SEMA4C in vitro mirrored that of the genetic studies. Together, our results indicate a multi-dimensional oncogenic role for SEMA4C in metastatic osteosarcoma and more importantly that SEMA4C has actionable clinical potential.
Geometric control of frequency modulation of cAMP oscillations due to Ca2+-bursts in dendritic spines
Authors: Ohadi D. , Rangamani P. 
Published: January 2019

ABSTRACTThe spatiotemporal regulation of cAMP and its dynamic interactions with other second messengers such as calcium are critical features of signaling specificity required for neuronal development and connectivity. cAMP is known to contribute to long-term potentiation and memory formation by controlling the formation and regulation of dendritic spines. Despite the recent advances in biosensing techniques for monitoring spatiotemporal cAMP dynamics, the underlying molecular mechanisms that attribute to the subcellular modulation of cAMP remain unknown. In the present work, we model the spatio-temporal dynamics of calcium-induced cAMP signaling pathway in dendritic spines. Using a 3D reaction-diffusion model, we investigate the effect of different spatial characteristics of cAMP dynamics that may be responsible for subcellular regulation of cAMP concentrations. Our model predicts that the volume-to-surface ratio of the spine, regulated through the spine head size, spine neck size, and the presence of physical barriers (spine apparatus) is an important regulator of cAMP dynamics. Furthermore, localization of the enzymes responsible for the synthesis and degradation of cAMP in different compartments also modulates the oscillatory patterns of cAMP through exponential relationships. Our findings shed light on the significance of complex geometric and localization relationships for cAMP dynamics in dendritic spines.
β-catenin has an ancestral role in cell fate specification but not cell adhesion
Authors: Salinas-Saavedra Miguel , Wikramanayake Athula H. , Martindale Mark Q 
Published: January 2019

AbstractThe ß-catenin protein has two major known functions in animal cells. It keeps epithelial tissue homeostasis by its connection with Adherens Junctions (AJ), and it serves as a transcriptional cofactor along with Lef/Tcf to enter the nucleus and regulate target genes of the Wnt/ß-catenin (cWnt) signaling pathway. To assess the ancestral role of ß-catenin during development we examined its distribution and function in the ctenophoreMnemiopsis leidyi(one of the earliest branching animal phyla) by using ctenophore-specific antibodies and mRNA injection. We found that ß-catenin protein never localizes to cell-cell contacts during embryogenesis as it does in other metazoans, most likely because ctenophore-cadherins do not have the cytoplasmic domain required for interaction with the catenin proteins. Downregulation of zygoticMlß-catenin signaling led to the loss of endodermal and mesodermal tissues indicating that nuclear ß-catenin may have a deep role in germ-layer evolution. Our results indicate that the ancestral role for ß-catenin was in the cell-fate specification and not in cell adhesion and also further emphasizes the critical role of this protein in the evolution of tissue layers in metazoans.
Computation of stationary distributions in stochastic models of cellular processes with molecular memory
Authors: Zhang Jiajun , Zhou Tianshou 
Published: January 2019

AbstractModeling stochastic dynamics of intracellular processes has long rested on Markovian (i.e., memoryless) hypothesis. However, many of these processes are non-Markovian (i.e., memorial) due to, e.g., small reaction steps involved in synthesis or degradation of a macroscopic molecule. When interrogating aspects of a cellular network by experimental measurements (e.g., by singlemolecule and single-cell measurement technologies) of network components, a key need is to develop efficient approaches to simulate and compute joint distributions of these components. To cope with this computational challenge, we develop two efficient algorithms: stationary generalized Gillespie algorithm and stationary generalized finite state projection, both being established based on a stationary generalized chemical master equation. We show how these algorithms can be combined in a streamlined procedure for evaluation of non-Markovian effects in a general cellular network. Stationary distributions are evaluated in two models of constitutive and bursty gene expressions as well as a model of genetic toggle switch, each considering molecular memory. Our approach significantly expands the capability of stochastic simulation to investigate gene regulatory network dynamics, which has the potential to advance both understanding of molecular systems biology and design of synthetic circuits.Author summaryCellular systems are driven by interactions between subsystems via time-stamped discrete events, involving numerous components and reaction steps and spanning several time scales. Such biochemical reactions are subject to inherent noise due to the small numbers of molecules. Also, they could involve several small steps, creating a memory between individual events. Delineating these molecular stochasticity and memory of biomolecular networks are continuing challenges for molecular systems biology. We present a novel approach to compute the probability distribution in stochastic models of cellular processes with molecular memory based on stationary generalized chemical master equation. We map a stochastic system with memory onto a Markovian model with effective reaction propensity functions. This formulation enables us to efficiently develop algorithms under the Markovian framework, and thus systematically analyze how molecular memories regulate stochastic behaviors of biomolecular networks. Here we propose two representative algorithms: stationary generalized Gillespie algorithm and stationary generalized finite state projection algorithm. The former generate realizations with Monte Carlo simulation, but the later compute approximations of the probability distribution by solving a truncated version of stochastic process. Our approach is demonstrated by applying it to three different examples from systems biology: generalized birth-death process, a stochastic toggle switch model, and a 3-stage gene expression model.
Emotions as core building blocks of an experience
Authors: Bastiaansen Marcel , Lub Xander Dennis , Mitas Ondrej , Jung Timothy Hyungsoo , Ascenção Mário Passos , Han Dai-In , Moilanen Teemu , Smit Bert , Strijbosch Wim 
Published: January 2019

PurposeThis paper aims to stimulate the discussion in the fields of hospitality, tourism and leisure on what exactly constitutes “an experience” and how to measure it; the authors unpack the experience construct into its core constituent elements, namely, emotions.Design/methodology/approachThe paper reviews insights from psychology and cognitive neuroscience that define experiences as a fine-grained temporal succession of emotions that occur during an experiential episode. Limitations of current methods for measuring experiences are discussed, after which biometric and neuroscientific methods are reviewed that are optimally geared toward measuring emotions, as they occur during an experience with fine temporal detail.FindingsAn overview is presented of the available studies within the fields of hospitality, tourism and leisure that use these methodologies. These studies show that using these methodologies provides a fruitful methodological approach to measuring experiences in real time.Practical implicationsCompanies are constantly seeking to create memorable experiences for their customers. The proposed research methodologies allow companies to get a more fine-grained image of what impacts customers over the course of their experience and to actively integrate the use of emotions into creating experiences, as emotions are key to making them memorable.Originality/valueThe paper sketches the contours of a rapidly emerging framework that unpacks memorable experiences into their constituent element – emotions. It is proposed that this will contribute to a deeper understanding of how consumers experience offerings in the hospitality, tourism and leisure industry.