bluuebunny/crossref_metadata_2025_split huggingface dataset:
Zika virus replicates in skeletal muscle contributing to peripheral viral amplification prior to reach neural tissue
Authors: Gavino-Leopoldino Daniel , Figueiredo Camila Menezes , Barcellos Letícia Gonçalves , da Silva Mariana Oliveira Lopes , Bernardino Araújo Suzana Maria , da Silva Neris Rômulo Leão , Miranda Laryssa Daniele , Ladislau Leandro , Benjamim Claudia Farias , Da Poain Andrea Thompson , Clarke Julia Rosauro , Figueiredo Claudia Pinto , Assunção-Miranda Iranaia 
Published: March 2020

AbstractZika virus (ZIKV) infections are still a worldwide concern due to the severity of neurological outcomes. ZIKV neurotropism is well characterized, but peripheral tissue could be sites of viral amplification, contributing to endothelial-barrier crossing and access to peripheral nerves. During acute and late phases of infection, ZIKV can be detected in several body fluids, eyes, testis and vagina. However, the importance of initial replication sites for the establishment of infection and viral spread remain unknown. Here we demonstrated that ZIKV replicates primarily in human muscle precursor cells, resulting in cell death and inhibition of myogenesis. ZIKV also replicates in fetal muscle after maternal transmission and in infected neonate mice, inducing lesions and inflammation. Muscle was an important site of viral amplification, sustaining higher peripheral viral loads than liver and spleen. In addition, ZIKV showed rapid and sustained replication kinetics in muscle even before replication in the neural tissues, persisting until 16 days post infection. Our results highlight the importance of muscle in ZIKV pathogenesis as a peripheral site of viral amplification which may contribute to ZIKV reaching neural structures.Author SummaryZika Virus (ZIKV) neurotropism and its deleterious effects on central nervous system have been well characterized. But, investigations of the initial replication sites for the establishment of infection and viral spread to neural tissues remain under explored. Here we demonstrated that ZIKV replicates primarily in human skeletal muscle precursor cells, resulting in cell death and disrupted myogenesis. ZIKV also replicates in muscle of fetus and neonate mice inducing muscle damage and inflammation. Muscle replication occurs before amplification in peripheral nerves and brain, contributing to the increase of peripheral ZIKV load and dissemination. In addition, ZIKV RNA still been detected in skeletal muscle at late stages of infection. Overall, our findings showed that skeletal muscle is involved in ZIKV pathogenesis, contributing to a broader understanding of ZIKV infection. Thus, opens new aspects in the investigation of the long-term consequence of early infection.
Inhibition of the SUV4-20 H1 histone methyltransferase increases frataxin expression in Friedreich’s ataxia patient cells
Authors: Vilema-Enríquez G , Quinlan R , Kilfeather P , Mazzone R , Saqlain S , del Molino del Barrio I , Donato A , Corda G , Li F , Vedadi M , Németh AH , Brennan PE , Wade-Martins R 
Published: March 2020

AbstractThe molecular mechanisms of reduced frataxin (FXN) expression in Friedreich’s ataxia (FRDA) are linked to epigenetic modification of theFXNlocus caused by the disease-associated GAA expansion. Here, we identify that SUV4-20 histone methyltransferases, specifically SUV4-20 H1, play an important role in the regulation ofFXNexpression and represent a novel therapeutic target. Using a humanFXN-GAA-Luciferase repeat expansion genomic DNA reporter model of FRDA, we screened the Structural Genomics Consortium epigenetic probe collection. We found that pharmacological inhibition of the SUV4-20 methyltransferases by the tool compound A-196 increased the expression ofFXNby approximately 1.5-fold in the reporter cell line and in several FRDA cell lines and patient-derived primary peripheral blood mononuclear cells. SUV4-20 inhibition was accompanied by a reduction in H4K20me2 and H4K20me3 and an increase in H4K20me1, but only modest (1.4–7.8%) perturbation in genome-wide expression was observed. Finally, based on the structural activity relationship and crystal structure of A-196, novel small molecule A-196 analogues were synthesized and shown to give a 20-fold increase in potency for increasingFXNexpression. Overall, our results suggest that histone methylation is important in the regulation ofFXNexpression, and highlight SUV4-20 H1 as a potential novel therapeutic target for FRDA.
One leaf for all: Chemical traits of single leaves measured at the leaf surface using Near infrared-reflectance spectroscopy (NIRS)
Authors: Bon Matteo Petit , Böhner Hanna , Kaino Sissel , Moe Torunn , Bråthen Kari Anne 
Published: March 2020

AbstractThe leaf is an essential unit for measures of plant ecological traits. Yet, measures of plant chemical traits are often achieved by merging several leaves, masking potential foliar variation within and among plant individuals. This is also the case with cost-effective measures derived using Near-infrared reflectance spectroscopy (NIRS). The calibration models developed for converting NIRS spectral information to chemical traits are typically based on spectra from merged and milled leaves. In this study we ask if such calibration models can be applied to spectra derived from whole leaves, providing measures of chemical traits of single leaves.We sampled cohorts of single leaves from different biogeographic regions, growth forms, species and phenological stages in order to include variation in leaf and chemical traits. For each cohort we first sampled NIRS-spectra from each whole, single leaf, including leaf sizes down to Ø 4 mm (the minimum area of our NIRS application). Next, we merged, milled and tableted the leaves and sampled spectra from the cohort as a tablet. We applied arctic-alpine calibration models to all spectra and derived chemical traits. Finally, we evaluated the performance of the models in predicting chemical traits of whole, single leaves by comparing the traits derived at the level of leaves to that of the tablets.We found that the arctic-alpine calibration models can successfully be applied to single, whole leaves for measures of Nitrogen (R2=0.88, RMSE=0.824), Phosphorus (R2=0.65, RMSE=0.081), and Carbon (R2=0.78, RMSE=2.199) content. For Silicon content we found the method acceptable when applied to Silicon-rich growth forms (R2=0.67, RMSE=0.677). We found a considerable variation in chemical trait values among leaves within the cohorts.This time- and cost-efficient NIRS-application provides non-destructive measures of a set of chemical traits in single, whole leaves, including leaves of small sizes. The application can facilitate research into the scales of variability of chemical traits and include intraindividual variation. Potential trade-offs among chemical traits and other traits within the leaf unit can be identified and be related to ecological processes. In sum this NIRS-application can facilitate further ecological understanding of the role of leaf chemical traits.
A second hybrid-binding domain modulates the activity of Drosophila ribonuclease H1
Authors: González de Cózar Jose M. , Carretero-Junquera Maria , Ciesielski Grzegorz L. , Miettinen Sini M. , Varjosalo Markku , Kaguni Laurie S. , Dufour Eric , Jacobs Howard T. 
Published: March 2020

ABSTRACTIn eukaryotes, ribonuclease H1 (RNase H1) is involved in the processing and removal of RNA/DNA hybrids in both nuclear and mitochondrial DNA. The enzyme comprises a C-terminal catalytic domain and an N-terminal hybrid-binding domain (HBD), separated by a linker of variable length, which in Drosophila melanogaster (Dm) is exceptionally long, 115 amino acids. Molecular modeling predicted this extended linker to fold into a structure similar to the conserved HBD. We measured catalytic activity and substrate binding by EMSA and biolayer interferometry, using a deletion series of protein variants. Both the catalytic domain and the conserved HBD were required for high-affinity binding to heteroduplex substrates, whilst loss of the novel HBD led to a ∼90% drop in K[cat] with a decreased K[M], and a large increase in the stability of the RNA/DNA hybrid-enzyme complex. The findings support a bipartite binding model for the enzyme, whereby the second HBD facilitates dissociation of the active site from the product, allowing for processivity. We used shotgun proteomics to identify protein partners of the enzyme involved in mediating these effects. Single-stranded DNA-binding proteins from both the nuclear and mitochondrial compartments, respectively RpA-70 and mtSSB, were prominently detected by this method. However, we were not able to document direct interactions between mtSSB and Dm RNase H1 when co-overexpressed in S2 cells, or functional interactions in vitro. Further studies are needed to determine the exact reaction mechanism of Dm RNase H1, the nature of its interaction with mtSSB and the role of the second HBD in both.
Changes within neural population codes can be inferred from psychophysical threshold studies
Authors: Hays Jason , Soto Fabian A. 
Published: March 2020

AbstractThe use of population encoding models has come to dominate the study of human visual neuroscience, serving as a primary tool for making inferences about neural code changes based on indirect measurements. A popular approach in computational neuroimaging is to use such models to obtain estimates of neural population responses via inverted encoding modeling. Recent research suggests that this approach may be prone to identifiability problems, with multiple mechanisms of encoding change producing similar changes in the estimated population responses. Psychophysical data might be able to provide additional constraints to infer the encoding change mechanism underlying some behavior of interest. However, computational work aimed at determining to what extent different mechanisms can be differentiated using psychophysics is lacking. Here, we used simulation to explore exactly which of a number of changes in neural population codes could be differentiated from observed changes in psychophysical thresholds. Eight mechanisms of encoding change were under study, chosen because they have been proposed in the previous literature as mechanisms for improved task performance (e.g., due to attention or learning): specific and nonspecific gain, specific and nonspecific tuning, specific suppression, specific suppression plus gain, and inward and outward tuning shifts. We simulated psychophysical thresholds as a function of both external noise (TvN curves) or stimulus value (TvS curves) for a number of variations of each one of the models. With the exception of specific gain and specific tuning, all studied mechanisms produced qualitatively different patterns of change in the TvN and TvS curves, suggesting that psychophysical studies can be used as a complement to inverted encoding modeling, and provide strong constraints on inferences based on the latter. We use our results to provide recommendations for interested researchers and to re-interpret previous psychophysical data in terms of mechanisms of encoding change.
CryoDRGN: Reconstruction of heterogeneous structures from cryo-electron micrographs using neural networks
Authors: Zhong Ellen D. , Bepler Tristan , Berger Bonnie , Davis Joseph H. 
Published: March 2020

AbstractCryo-EM single-particle analysis has proven powerful in determining the structures of rigid macromolecules. However, many protein complexes are flexible and can change conformation and composition as a result of functionally-associated dynamics. Such dynamics are poorly captured by current analysis methods. Here, we present cryoDRGN, an algorithm that for the first time leverages the representation power of deep neural networks to efficiently reconstruct highly heterogeneous complexes and continuous trajectories of protein motion. We apply this tool to two synthetic and three publicly available cryo-EM datasets, and we show that cryoDRGN provides an interpretable representation of structural heterogeneity that can be used to identify discrete states as well as continuous conformational changes. This ability enables cryoDRGN to discover previously overlooked structural states and to visualize molecules in motion.
Tracking bacterial lineages in complex and dynamic environments with applications to growth control and persistence
Authors: Bakshi Somenath , Leoncini Emanuele , Baker Charles , Cañas-Duarte Silvia J. , Okumus Burak , Paulsson Johan 
Published: March 2020

AbstractAs bacteria transition from exponential to stationary phase they change greatly in size, morphology, growth and expression-profiles. These responses also vary between individual cells, but it has proven difficult to track cell lineages along the growth curve to determine the progression of events or correlations between how individual cells enter and exit dormancy. We developed a platform for tracking >105parallel cell lineages in dense and changing cultures, independently validating that the imaged cells closely track batch populations. Initial applications show that for bothEscherichia coliandBacillus subtilis, growth changes from an ‘adder’ mode in exponential phase to mixed ‘adders-timers’ entering stationary phase, and then a near-perfect ‘sizer’ upon exit – creating broadly distributed cell sizes in stationary phase but rapidly returning to narrowly distributed sizes upon exit. Furthermore, cells that undergo more divisions entering stationary phase suffer reduced survival after long periods of dormancy but are the only cells observed that persist against antibiotics.
SARS-CoV-2 exhibits intra-host genomic plasticity and low-frequency polymorphic quasispecies
Authors: Karamitros Timokratis , Papadopoulou Gethsimani , Bousali Maria , Mexias Anastasios , Tsiodras Sotiris , Mentis Andreas 
Published: March 2020

ABSTRACTIn December 2019, an outbreak of atypical pneumonia (Coronavirus disease 2019 - COVID-19) associated with a novel coronavirus (SARS-CoV-2) was reported in Wuhan city, Hubei province, China. The outbreak was traced to a seafood wholesale market and human to human transmission was confirmed. The rapid spread and the death toll of the new epidemic warrants immediate intervention. The intra-host genomic variability of SARS-CoV-2 plays a pivotal role in the development of effective antiviral agents and vaccines, but also in the design of accurate diagnostics.We analyzed NGS data derived from clinical samples of three Chinese patients infected with SARS-CoV-2, in order to identify small- and large-scale intra-host variations in the viral genome. We identified tens of low- or higher-frequency single nucleotide variations (SNVs) with variable density across the viral genome, affecting 7 out of 10 protein-coding viral genes. The majority of these SNVs corresponded to missense changes. The annotation of the identified SNVs but also of all currently circulating strain variations revealed colocalization of intra-host but also strain specific SNVs with primers and probes currently used in molecular diagnostics assays. Moreover, we de-novo assembled the viral genome, in order to isolate and validate intra-host structural variations and recombination breakpoints. The bioinformatics analysis disclosed genomic rearrangements over poly-A / poly-U regions located in ORF1ab and spike (S) gene, including a potential recombination hot-spot within S gene.Our results highlight the intra-host genomic diversity and plasticity of SARS-CoV-2, pointing out genomic regions that are prone to alterations. The isolated SNVs and genomic rearrangements, reflect the intra-patient capacity of the polymorphic quasispecies, which may arise rapidly during the outbreak, allowing immunological escape of the virus, offering resistance to anti-viral drugs and affecting the sensitivity of the molecular diagnostics assays.
Hierarchical progressive learning of cell identities in single-cell data
Authors: Michielsen Lieke , Reinders Marcel J.T. , Mahfouz Ahmed 
Published: March 2020

AbstractSupervised methods are increasingly used to identify cell populations in single-cell data. Yet, current methods are limited in their ability to learn from multiple datasets simultaneously, are hampered by the annotation of datasets at different resolutions, and do not preserve annotations when retrained on new datasets. The latter point is especially important as researchers cannot rely on downstream analysis performed using earlier versions of the dataset. Here, we presentscHPL, a hierarchical progressive learning method which allows continuous learning from single-cell data by leveraging the different resolutions of annotations across multiple datasets to learn and continuously update a classification tree. We evaluate the classification and tree learning performance using simulated as well as real datasets and show thatscHPLcan successfully learn known cellular hierarchies from multiple datasets while preserving the original annotations.scHPLis available athttps://github.com/lcmmichielsen/hierarchicalprogressivelearning.
Whole-organism behavioral profiling reveals a role for dopamine in state-dependent motor program coupling inC. elegans
Authors: Cermak Nathan , Yu Stephanie K. , Clark Rebekah , Huang Yung-Chi , Flavell Steven W. 
Published: March 2020

AbstractAnimal behaviors are commonly organized into long-lasting states that coordinately impact the generation of diverse motor outputs such as feeding, locomotion, and grooming. However, the neural mechanisms that coordinate these diverse motor programs remain poorly understood. Here, we examine how the distinct motor programs of the nematodeC. elegansare coupled together across behavioral states. We describe a new imaging platform that permits automated, simultaneous quantification of each of the mainC. elegansmotor programs over hours or days. Analysis of these whole-organism behavioral profiles shows that the motor programs coordinately change as animals switch behavioral states. Utilizing genetics, optogenetics, and calcium imaging, we identify a new role for dopamine in coupling locomotion and egg-laying together across states. These results provide new insights into how the diverse motor programs throughout an organism are coordinated and suggest that neuromodulators like dopamine can couple motor circuits together in a state-dependent manner.
A New High-throughput Screening (HiTS) Method for Phages – Enabling Crude Isolation and Fast Identification of Diverse Phages with Therapeutic Potential
Authors: Olsen Nikoline S. , Hendriksen Niels Bohse , Hansen Lars H. , Kot Witold 
Published: March 2020

AbstractBacteriophage therapy and application of phages as biocontrol in plant production and food processing, all necessitates acquisition of suitable phages. Depending on purpose, the selection criteria of phage characteristics include lifestyle (lytic/lysogenic), host range, physical stability and absence of unwanted genetic traits such as integrases, antibiotic resistance or bacterial virulence factors. The exclusivity of antibiotic resistant clinical infections and possible development of phage-resistance instigates a need to continually build sizeable phage libraries and also be able to rapidly isolate and characterise novel phages of specified bacterial hosts. Current methods for phage isolation are both laborious and time consuming, suitable only for the isolation of a limited number of phages. Thus, we developed theHigh-ThroughputScreening(HITS) method for phages for fast isolation and identification of potentially hundreds of distinct phages against single hosts. This scalable method enables screening of hundreds of samples, in multiple simultaneous setups with varying parameters increasing the likelihood of isolating multiple distinct phages specific for the given conditions. The efficiency of the method is emphasised by our screening of 200 environmental samples, resulting in the identification of an abundance of unique phage species lytic toEscherichia coli, Salmonella Enterica, Enterococcus faecalisandPseudomonas aeruginosa.
Scientometric correlates of high-quality reference lists in ecological papers
Authors: Mammola Stefano , Fontaneto Diego , Martínez Alejandro , Chichorro Filipe 
Published: March 2020

AbstractIt is said that the quality of a scientific publication is as good as the science it cites, but the properties of high-quality reference lists have never been numerically quantified. We examined seven numerical characteristics of reference lists of 50,878 primary research articles published in 17 ecological journals between 1997 and 2017. Over this 20-years period, there have been significant changes in reference lists’ properties. On average, more recent ecological papers have longer reference lists, cite more high Impact Factor papers, and fewer non-journal publications. Furthermore, we show that highly cited papers across the ecology literature have longer reference lists, cite more recent and impactful papers, and account for more self-citations. Conversely, the proportion of ‘classic’ papers and non-journal publications cited, as well as the temporal range of the reference list, have no significant influence on articles’ citations. From this analysis, we distill a recipe for crafting impactful reference lists.
Evolutionary analysis of LP3 gene family in conifers: an ASR homolog
Authors: Lecoy Jonathan , García-Gil MR 
Published: March 2020

AbstractDrought has long been established as a major environmental stress for plants which have in turn developed several coping strategies, ranging from physiological to molecular mechanisms. LP3; a homolog of the Abscisic Acid, Stress and Ripening (ASR) gene was first detected in tomato; and has been shown to be present in four different isoforms in loblolly pine called LP3-0, LP3-1, LP3-2 and LP3-3. While ASR has already been extensively studied notably in tomato, the same cannot be said of LP3. Like ASR, the different LP3 isoforms have been shown to be upregulated in response to water deficit stress and to also act as transcription factors for genes likely involved in hexose transport. In this study we have investigated the evolutionary history of LP3 gene family, with the aim of relating it to that of ASR from a phylogenetic perspective and comparing the differences in selective pressure and codon usage. Phylogenetic analyses of different LP3 homologs compared to ASR show that LP3 is less divergent across species than ASR and that even when comparing the different sub-sections of the gene the divergence rate of LP3 is lower than that of ASR. Analysis of different gene parameters showed that there were differences in GC1% and GC2% but not in total or GC3% content. All genes had a relatively high CAI value associated with a low to moderate ENC value, which is indicative of high translation efficiency found in highly expressed genes. Analysis of codon usage also showed that LP3 preferentially uses different codons than ASR. Selective pressure analysis across most of the LP3 and ASR genes used in this study showed that these genes were principally undergoing purifying selection, with the exception of LP3-3 which seems to be undergoing diversifying selection most probably due to the fact that it likely recently diverged from LP3-0. This study thus provides insight in how ASR and LP3 have diverged from each other while remaining homologous.