bluuebunny/crossref_metadata_2025_split huggingface dataset:
Isolation of a natural DNA virus ofDrosophila melanogaster, and characterisation of host resistance and immune responses
Authors: Palmer William H. , Medd Nathan , Beard Philippa M. , Obbard Darren J. 
Published: November 2017

AbstractDrosophila melanogasterhas played a key role in our understanding of invertebrate immunity. However, both functional and evolutionary studies of host-virus interaction inDrosophilahave been limited by a dearth of native virus isolates. In particular, despite a long history of virus research, DNA viruses ofD. melanogasterhave only recently been described, and none have been available for experimental study. Here we report the isolation and comprehensive characterisation of Kallithea virus, a large double-stranded DNA virus, and the first DNA virus to have been reported from wild populations ofD. melanogaster. We find that Kallithea virus infection is costly for adult flies, reaching high titres in both sexes and disproportionately reducing survival in males and movement and late fecundity in females. Using theDrosophilaGenetic Reference Panel, we quantify host genetic variance for virus-induced mortality and viral titre and identify candidate host genes that may underlie this variation, includingCdc42-interacting protein 4. Using full transcriptome sequencing of infected males and females, we examine the transcriptional response of flies to Kallithea virus infection, and describe differential regulation of virus-responsive genes. This work establishes Kallithea virus as a new tractable model to study the natural interaction betweenD. melanogasterand DNA viruses, and we hope it will serve as a basis for future studies of immune responses to DNA viruses in insects.Author SummaryThe fruit flyDrosophila melanogasteris a useful model species to study host-virus interaction and innate immunity. However, few natural viruses ofDrosophilahave been available for experiments, and no natural DNA viruses ofDrosophila melanogasterhave been available at all. Although infecting flies with viruses from other insects has been useful to uncover general immune mechanisms, viruses that naturally infect wild flies could help us to learn more about the coevolutionary process, and more about the genes that underlie the host-virus interaction. Here we present an isolate of a DNA virus (named Kallithea Virus) that naturally infects the model speciesDrosophila melanogasterin the wild. We describe the basic biology of infection by this virus, finding that both male and females flies die from infection, but females are more tolerant of infection than males, while laying lay fewer eggs than uninfected females. We quantify genetic variation for virus resistance in the flies, and we use RNA sequencing to see which genes are expressed in male and female flies in response to infection. These results will form the basis for further research to understand how insects defend themselves against infection by DNA viruses, and how DNA viruses can overcome antiviral defence.
Widespread ancient whole genome duplications in Malpighiales coincide with Eocene global climatic upheaval
Authors: Cai Liming , Xi Zhenxiang , Amorim André M. , Sugumaran M. , Rest Joshua S. , Liu Liang , Davis Charles C. 
Published: November 2017

AbstractAncient whole genome duplications (WGDs) are important in eukaryotic genome evolution, and are especially prominent in plants. Recent genomic studies from large vascular plant clades, including ferns, gymnosperms, and angiosperms suggest that WGDs may represent a crucial mode of speciation. Moreover, numerous WGDs have been dated to events coinciding with major episodes of global and climatic upheaval, including the mass extinction at the KT boundary (~65 Ma) and during more recent intervals of global aridification in the Miocene (~10-5 Ma). These findings have led to the hypothesis that polyploidization may buffer lineages against the negative consequences of such disruptions. Here, we explore WGDs in the large, and diverse flowering plant clade Malpighiales using a combination of transcriptomes and complete genomes from 42 species. We conservatively identify 22 ancient WGDs, widely distributed across Malpighiales subclades. Our results provide strong support for the hypothesis that WGD is an important mode of speciation in plants. Importantly, we also identify that these events are clustered around the Eocene-Paleocene Transition (~54 Ma), during which time the planet was warmer and wetter than any period in the Cenozoic. These results establish that the Eocene Climate Optimum represents another, previously unrecognized, period of prolific WGDs in plants, and lends support to the hypothesis that polyploidization promotes adaptation and enhances plant survival during major episodes of global change. Malpighiales, in particular, may have been particularly influenced by these events given their predominance in the tropics where Eocene warming likely had profound impacts owing to the relatively tight thermal tolerances of tropical organisms.Significance StatementWhole genome duplications (WGDs) are hypothesized to generate adaptive variations during episodes of climate change and global upheaval. Using large-scale phylogenomic assessments, we identify an impressive 22 ancient WGDs in the large, tropical flowering plant clade Malpighiales. This supports growing evidence that ancient WGDs are far more common than has been thought. Additionally, we identify that WGDs are clustered during a narrow window of time, ~54 Ma, when the climate was warmer and more humid than during any period in the last ~65 Ma. This lends support to the hypothesis that WGDs are associated with surviving climatic upheavals, especially for tropical organisms like Malpighiales, which have tight thermal tolerances.
SAFE-clustering: Single-cell Aggregated (From Ensemble) Clustering for Single-cell RNA-seq Data
Authors: Yang Yuchen , Huh Ruth , Culpepper Houston W. , Lin Yuan , Love Michael I. , Li Yun 
Published: November 2017

ABSTRACTMotivationAccurately clustering cell types from a mass of heterogeneous cells is a crucial first step for the analysis of single-cell RNA-seq (scRNA-Seq) data. Although several methods have been recently developed, they utilize different characteristics of data and yield varying results in terms of both the number of clusters and actual cluster assignments.ResultsHere, we present SAFE-clustering, Single-cell Aggregated (From Ensemble) clustering, a flexible, accurate and robust method for clustering scRNA-Seq data. SAFE-clustering takes as input, results from multiple clustering methods, to build one consensus solution. SAFE-clustering currently embeds four state-of-the-art methods, SC3, CIDR, Seurat and t-SNE + k-means; and ensembles solutions from these four methods using three hypergraph-based partitioning algorithms. Extensive assessment across 12 datasets with the number of clusters ranging from 3 to 14, and the number of single cells ranging from 49 to 32,695 showcases the advantages of SAFE-clustering in terms of both cluster number (18.9 - 50.0% reduction in absolute deviation to the truth) and cluster assignment (on average 28.9% improvement, and up to 34.5% over the best of the four methods, measured by adjusted rand index). Moreover, SAFE-clustering is computationally efficient to accommodate large datasets, taking <10 minutes to process 28,733 cells.Availability and implementationSAFE-clustering, including source codes and tutorial, is free available on the web at http://yunliweb.its.unc.edu/safe/.Contactyunli@med.unc.eduSupplementary informationSupplementary data are available at Bioinformatics online.
Targeting stromal remodeling and cancer stem cell plasticity to overcome chemoresistance in triple negative breast cancer
Authors: Cazet Aurélie S. , Hui Mun N. , Elsworth Benjamin L. , Wu Sunny Z. , Roden Daniel , Chan Chia-Ling , Skhinas Joanna N. , Collot Raphaël , Yang Jessica , Harvey Kate , Johan M. Zahied , Cooper Caroline , Nair Radhika , Herrmann David , McFarland Andrea , Deng Nian-Tao , Ruiz-Borrego Manuel , Rojo Federico , Trigo José M. , Bezares Susana , Caballero Rosalía , Lim Elgene , Timpson Paul , O’Toole Sandra , Watkins D. Neil , Cox Thomas R. , Samuel Michael , Martín Miguel , Swarbrick Alexander 
Published: November 2017

ABSTRACTThe cellular and molecular basis of stromal cell recruitment, activation and crosstalk in carcinomas is poorly understood, limiting the development of targeted anti-stromal therapies. In mouse models of triple negative breast cancer (TNBC), Hh ligand produced by neoplastic cells reprogrammed cancer-associated fibroblast (CAF) gene expression, driving tumor growth and metastasis. Hh-activated CAFs upregulated expression of FGF5 and production of fibrillar collagen, leading to FGFR and FAK activation in adjacent neoplastic cells, which then acquired a stem-like, drug-resistant phenotype. Treatment with smoothened inhibitors (SMOi) reversed these phenotypes. Stromal treatment of TNBC patient-derived xenograft (PDX) models with SMOi downregulated the expression of cancer stem cell markers and sensitized tumors to docetaxel, leading to markedly improved survival and reduced metastatic burden. In the phase I clinical trial EDALINE, 3 of 12 patients with metastatic TNBC derived clinical benefit from combination therapy with the SMOi Sonidegib and docetaxel chemotherapy, with one patient experiencing a complete response. Markers of pathway activity correlated with response. These studies identify Hh signaling to CAFs as a novel mediator of cancer stem cell plasticity and an exciting new therapeutic target in TNBC.SIGNIFICANCECompared to other breast cancer subtypes, TNBCs are associated with significantly worse patient outcomes. Standard of care systemic treatment for patients with non-BRCA1/2 positive TNBC is cytotoxic chemotherapy. However, the failure of 70% of treated TNBCs to attain complete pathological response reflects the relative chemoresistance of these tumors. New therapeutic strategies are needed to improve patient survival and quality of life. Here, we provide new insights into the dynamic interactions between heterotypic cells within a tumor. Specifically, we establish the mechanisms by which CAFs define cancer cell phenotype and demonstrate that the bidirectional CAF-cancer cell crosstalk can be successfully targeted in mice and humans using anti-stromal therapy.
Male parental investment reflects the level of partner contributions and brood value in tree swallows
Authors: Lendvai Ádám Z. , Akçay Çağlar , Stanback Mark , Haussmann Mark F. , Moore Ignacio T. , Bonier Frances 
Published: November 2017

AbstractBiparental care presents an interesting case of cooperation and conflict between unrelated individuals. Several models have been proposed to explain how parents should respond to changes in each other’s parental care to maximize their own fitness, predicting no change, partial compensation, or matching effort as a response. Here, we present an experiment in tree swallows (Tachycineta bicolor) in which we increased the parental care of females by presenting them, but not their mates, with additional nestling begging calls using automated playbacks. We performed this experiment in two populations differing in future breeding opportunities and thus the intensity of conflict over current parental care. We found that in response to a temporary increase in female parental effort, males in the northern population with lower sexual conflict matched the increased effort, whereas males in the southern population did not. We also found that increases in parental care during playbacks were driven by the females (i.e., females initiated the increased effort and their mates followed them) in the northern population but not the southern population. These results support the idea that with incomplete information about the brood value and need, cues or signals from the partner might become important in coordinating parental care.
Biophysical models reveal the relative importance of transporter proteins and impermeant anions in chloride homeostasis
Authors: Düsterwald Kira M. , Currin Christopher B. , Burman Richard J. , Akerman Colin J. , Kay Alan R. , Raimondo Joseph V. 
Published: November 2017

AbstractFast synaptic inhibition in the nervous system depends on the transmembrane flux of Cl− ions based on the neuronal Cl− driving force. Established theories regarding the determinants of Cl− driving force have recently been questioned. Here we present biophysical models of Cl− homeostasis using the pump-leak model. Using numerical and novel analytic solutions, we demonstrate that the Na+/K+-ATPase, ion conductances, impermeant anions, electrodiffusion, water fluxes and cation-chloride cotransporters (CCCs) play roles in setting the Cl− driving force. Our models, together with experimental validation, show that while impermeant anions can contribute to setting [Cl−]i in neurons, they have a negligible effect on the driving force for Cl− locally and cell-wide. In contrast, we demonstrate that CCCs are well-suited for modulating Cl− driving force and hence inhibitory signalling in neurons. Our findings reconcile recent experimental findings and provide a framework for understanding the interplay of different chloride regulatory processes in neurons.
Ennet: construction of potential cancer-driving networks based on somatic enhancer mutations only
Authors: Cui Ya , Niu Yiwei , Teng Xueyi , Wang Dan , Luo Huaxia , Zhang Peng , Wu Wei , He Shunmin , Luo Jianjun , Chen Runsheng 
Published: November 2017

AbstractWhole genome sequencing technology has facilitated the discovery of a large number of somatic mutations in enhancers (SMEs), whereas the utility of SMEs in tumorigenesis has not been fully explored. Here we present Ennet, a method to comprehensively investigate SMEs enriched networks (SME-networks) in cancer by integrating SMEs, enhancer-gene interactions and gene-gene interactions. Using Ennet, we performed a pan-cancer analysis in 2004 samples from 8 cancer types and found many well-known cancer drivers were involved in the SME-networks, includingESR1,SMAD3,MYC,EGFR,BCL2andPAX5. Meanwhile, Ennet also identified many new networks with less characterization but have potentially important roles in cancer, including a large SME-network in medulloblastoma (MB), which contains genes enriched in the glutamate receptor and neural development pathways. Interestingly, SME-networks are specific across cancer types, and the vast majority of the genes identified by Ennet have few mutations in gene bodies. Collectively, our work suggests that using enhancer-only somatic mutations can be an effective way to discover potential cancer-driving networks. Ennet provides a new perspective to explore new mechanisms for tumor progression from SMEs.
Deconstructing Procedural Memory: Different Learning Trajectories and Consolidation of Sequence and Statistical Learning
Authors: Simor Peter , Zavecz Zsofia , Horváth Kata , Éltető Noémi , Török Csenge , Pesthy Orsolya , Gombos Ferenc , Janacsek Karolina , Nemeth Dezso 
Published: November 2017

AbstractProcedural learning is a fundamental cognitive function that facilitates efficient processing of and automatic responses to complex environmental stimuli. Here, we examined training-dependent and off-line changes of two sub-processes of procedural learning: namely, sequence learning and statistical learning. Whereas sequence learning requires the acquisition of order-based relationships between the elements of a sequence, statistical learning is based on the acquisition of probabilistic associations between elements. Seventy-eight healthy young adults (58 females and 20 males) completed the modified version of the Alternating Serial Reaction Time task that was designed to measure Sequence and Statistical Learning simultaneously. After training, participants were randomly assigned to one of three conditions: active wakefulness, quiet rest, or daytime sleep. We examined off-line changes in Sequence and Statistical Learning as well as further improvements after extended practice. Performance in Sequence Learning increased during training, while Statistical Learning plateaued relatively rapidly. After the off-line period, both the acquired sequence and statistical knowledge was preserved, irrespective of the vigilance state (awake, quiet rest or sleep). Sequence Learning further improved during extended practice, while Statistical Learning did not. Moreover, within the sleep group, cortical oscillations and sleep spindle parameters showed differential associations with Sequence and Statistical Learning. Our findings can contribute to a deeper understanding of the dynamic changes of multiple parallel learning and consolidation processes that occur during procedural memory formation.
Identifying Crohn’s disease signal from variome analysis
Authors: Wang Yanran , Astrakhan Yuri , Petersen Britt-Sabina , Schreiber Stefan , Franke Andre , Bromberg Yana 
Published: November 2017

AbstractBackgroundAfter many years of concentrated research efforts, the exact cause of Crohn’s disease remains unknown. Its accurate diagnosis, however, helps in management and even preventing the onset of disease. Genome-wide association studies have identified 140 loci associated with CD, but these carry very small log odds ratios and are uninformative for diagnoses.ResultsHere we describe a machine learning method – AVA,Dx (Analysis of Variation for Association with Disease) – that uses whole exome sequencing data to make predictions of CD status. Using the person-specific variation in these genes from a panel of only 111 individuals, we built disease-prediction models informative of previously undiscovered disease genes. In this panel, our models differentiate CD patients from healthy controls with 71% precision and 73% recall at the default cutoff. By additionally accounting for batch effects, we are also able to predict individual CD status for previously unseen individuals from a separate CD study (84% precision, 73% recall).ConclusionsLarger training panels and additional features, including regulatory variants and environmental factors, e.g. human-associated microbiota, are expected to improve model performance. However, current results already position AVA,Dx as both an effective method for highlighting pathogenesis pathways and as a simple Crohn’s disease risk analysis tool, which can improve clinical diagnostic time and accuracy.
Prefrontal D1 dopamine-receptor neurons and delta resonance in interval timing
Authors: Kim Young-Cho , Narayanan Nandakumar S. 
Published: November 2017

AbstractConsiderable evidence has shown that prefrontal neurons expressing D1-type dopamine receptors (D1DRs) are critical for working memory, flexibility, and timing. This line of work predicts that frontal neurons expressing D1DRs mediate cognitive processing. During timing tasks, one form this cognitive processing might take is time-dependent ramping activity — monotonic changes in firing rate over time. Thus, we hypothesized the prefrontal D1DR+ neurons would strongly exhibited time-dependent ramping during interval timing. We tested this idea using an interval-timing task in which we used optogenetics to tag D1DR+ neurons in the mouse medial frontal cortex (MFC). While 23% of MFC D1DR+ neurons exhibited ramping, this was significantly less than untagged MFC D1DR+ neurons. By contrast, MFC D1DR+ neurons had strong delta-frequency (1-4 Hz) coherence with other MFC ramping neurons. This coherence was phase-locked to cue onset and was strongest early in the interval. To test the significance of these interactions, we optogenetically stimulated MFC D1DR+ neurons early vs. late in the interval. We found that 2-Hz stimulation early in the interval was particularly effective in rescuing timing-related behavioral performance deficits in dopamine-depleted animals. These findings provide insight into MFC networks and have relevance for disorders such as Parkinson’s disease and schizophrenia.Significance StatementPrefrontal D1DRs are involved in cognitive processing and cognitive dysfunction in human diseases such as Parkinson’s disease and schizophrenia. We use optogenetics to identify these neurons, as well as neurons that are putatively connected to MFC D1DR+ neurons. We study these neurons in detail during an elementary cognitive task. These data could have relevance for cognitive deficits for Parkinson’s disease, schizophrenia, and other diseases involving frontal dopamine.
Knockdown of endogenous circulating C1 inhibitor induces neurovascular impairment, neuroinflammation and cognitive decline
Authors: Farfara Dorit , Feierman Emily , Richards Allison , Revenko Alexey S. , MacLeod Robert A. , Norris Erin H. , Strickland Sidney 
Published: November 2017

AbstractPlasma proteins and activated immune cells are known contributors of vascular brain disorders. However, the mechanisms and routes involved are still unclear. In order to understand the cross-talk between plasma proteins and the brain, we knocked down circulating C1 inhibitor (C1INH) in wild-type (WT) mice using antisense-oligonucleotide (ASO) technique and examined the brain. C1INH is a plasma protein inhibitor of vascular inflammation induced by activation of the kallikrein-kinin system (KKS) and the complement system. This knockdown induced the activation of the KKS but spared the activation of the classical complement system. Activation of the KKS induced an upregulation of the bradykinin pathway in the periphery and the brain, resulting in hypotension. Blood-brain barrier (BBB) permeability, plasma protein extravasations, activated glial cells and elevated levels of IL-1beta, IL-6, TNF-alpha, and iNOS were detected in brains of C1INH ASO treated mice. Infiltrating innate immune cells were evident, entering the brain through the lateral ventricle walls and the neurovascular units. The mice showed normal motor functions, however, cognition was impaired. Altogether, our results highlight the important role of regulated plasma-C1INH as a gatekeeper of the neurovascular system. Thus, manipulation of C1INH in neurovascular disorders might be therapeutically beneficial.