bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unlocking the genomic taxonomy of theProchlorococcuscollective
Authors: Tschoeke Diogo , Vidal Livia , Campeão Mariana , Salazar Vinícius W. , Swings Jean , Thompson Fabiano , Thompson Cristiane 
Published: March 2020

ABSTRACTProchlorococcusis the most abundant photosynthetic prokaryote on our planet. The extensive ecological literature on theProchlorococcuscollective (PC) is based on the assumption that it comprises one single genus comprising the speciesProchlorococcus marinus, containing itself a collective of ecotypes. Ecologists adopt the distributed genome hypothesis of an open pan-genome to explain the observed genomic diversity and evolution patterns of the ecotypes within PC. Novel genomic data for the PC prompted us to revisit this group, applying the current methods used in genomic taxonomy. As a result, we were able to distinguish the five genera:Prochlorococcus, Eurycolium, Prolificoccus, ThaumococcusandRiococcus. The novel genera have distinct genomic and ecological attributes.
Histone modifications during the life cycle of the brown algaEctocarpus
Authors: Bourdareau Simon , Tirichine Leila , Lombard Bérangère , Loew Damarys , Scornet Delphine , Wu Yue , Coelho Susana M. , Cock J. Mark 
Published: March 2020

AbstractBackgroundBrown algae evolved complex multicellularity independently of the animal and land plant lineages and are the third most developmentally complex phylogenetic group on the planet. An understanding of developmental processes in this group is expected to provide important insights into the evolutionary events necessary for the emergence of complex multicellularity. Here we have focused on mechanisms of epigenetic regulation involving post-translational modifications (PTMs) of histone proteins.ResultsA total of 47 histone PTMs were identified, including a novel mark H2AZR38me1, butEctocarpuslacks both H3K27me3 and the major polycomb complexes. ChIP-seq identified PTMs associated with transcription start sites (TSSs) and gene bodies of active genes, and with transposons. H3K79me2 exhibited an unusual pattern, often marking large genomic regions spanning several genes. TSSs of closely spaced divergently transcribed gene pairs shared a common nucleosome depleted region and exhibited shared histone PTM peaks. Overall, patterns of histone PTMs were stable through the life cycle. Analysis of histone PTMs at generation-biased genes identified a correlation between the presence of specific chromatin marks and the level of gene expression.ConclusionsThe overview of histone PTMs in the brown algae presented here will provide a foundation for future studies aimed at understanding the role of chromatin modifications in the regulation of brown algal genomes.
Studying the dynamics of the gut microbiota using metabolically stable isotopic labeling and metaproteomics
Authors: Smyth Patrick , Zhang Xu , Ning Zhibin , Mayne Janice , Moore Jasmine I , Walker Krystal , Lavallée-Adam Mathieu , Figeys Daniel 
Published: March 2020

AbstractBackgroundThe gut microbiome and its metabolic processes are dynamic systems. Surprisingly, our understanding of gut microbiome dynamics is limited. Here we report a metaproteomic workflow that involves protein stable isotope probing (protein-SIP) and identification and quantification of partially labeled peptides. We also developed a package, which we call MetaProfiler, that corrects for false identifications and performs phylogenetic and time series analysis for the study of gut microbiome functional dynamics.ResultsFrom the stool sample of five mice that were fed with15N hydrolysate fromRalstonia eutropha, we identified 15,297 non-redundant unlabeled peptides of which 10,839 of their heavy counterparts were quantified. These peptides revealed incorporation profiles over time that were different between and within taxa, as well as between and within clusters of orthologous groups (COGs).ConclusionsOur study helps unravel the complex dynamics of protein synthesis and bacterial dynamics in the mouse microbiome.AvailabilityMetaProfiler and the bioinformatic pipeline are available athttps://github.com/psmyth94/MetaProfiler.git.
Who reviews for predatory journals? A study on reviewer characteristics
Authors: Severin Anna , Strinzel Michaela , Egger Matthias , Domingo Marc , Barros Tiago 
Published: March 2020

ABSTRACTBackgroundWhile the characteristics of scholars who publish in predatory journals are relatively well-understood, nothing is known about the scholars who review for these journals. We aimed to answer the following questions: Can we observe patterns of reviewer characteristics for scholars who review for predatory journals and for legitimate journals? Second, how are reviews for potentially predatory journals distributed globally?MethodsWe matched random samples of 1,000 predatory journals and 1,000 legitimate journals of the Cabells Scholarly Analytics’ journal lists with the Publons database of review reports, using the Jaro-Winkler string metric. For reviewers of matched reviews, we descriptively analysed meta-data on reviewing and publishing behaviour.ResultsWe matched 183,743 unique Publons reviews that were claimed by 19,598 reviewers. 6,077 reviews were conducted for 1160 unique predatory journals (3.31% of all reviews). 177,666 were claimed for 6,403 legitimate journals (96.69% of all reviews). The vast majority of scholars either never or only occasionally submitted reviews for predatory journals to Publons (89.96% and 7.55% of all reviewers, respectively). Smaller numbers of scholars claimed reviews predominantly or exclusively for predatory journals (0.26% and 0.35% of all reviewers, respectively). The two latter groups of scholars are of younger academic age and have fewer publications and fewer reviews than the first two groups of scholars.Developing regions feature larger shares of reviews for predatory reviews than developed regions.ConclusionThe characteristics of scholars who review for potentially predatory journals resemble those of authors who publish their work in these outlets. In order to combat potentially predatory journals, stakeholders will need to adopt a holistic approach that takes into account the entire research workflow.
Visualizing protein-protein interactions in plants by rapamycin-dependent delocalization
Authors: Winkler Joanna , Mylle Evelien , De Meyer Andreas , Pavie Benjamin , Merchie Julie , Grones Peter , Van Damme Daniël 
Published: March 2020

ABSTRACTIdentifying protein-protein interactions (PPI) is crucial for understanding biological processes. Many PPI tools are available, yet only some function within the context of a plant cell. Narrowing down even further, only a few tools allow complex multi-protein interactions to be visualized. Here, we present a conditionalin vivoPPI tool for plant research that meets these criteria. Knocksideways in plants (KSP) is based on the ability of rapamycin to alter the localization of a bait protein and its interactors via the heterodimerization of FKBP and FRB domains. KSP is inherently free from many limitations of other PPI systems. Thisin vivotool does not require spatial proximity of the bait and prey fluorophores and it is compatible with a broad range of fluorophores. KSP is also a conditional tool and therefore the visualization of the proteins in the absence of rapamycin acts as an internal control. We used KSP to confirm previously identified interactions inNicotiana benthamianaleaf epidermal cells. Furthermore, the scripts that we generated allow the interactions to be quantified at high throughput. Finally, we demonstrate that KSP can easily be used to visualize complex multi-protein interactions. KSP is therefore a versatile tool with unique characteristics and applications that complements other plant PPI methods.
A Data-driven Surrogate Model for Work Computation of a Periodically Forced Half-Sarcomere
Authors: Rudy Samuel H. , Williams C. David , Kutz J. Nathan , Daniel Thomas L. 
Published: March 2020

AbstractMuscle force generation follows from molecular scale interactions that drive macroscopic behaviors and macroscopic processes that influence those at the molecular scale. A particuarly challenging issue is that models at the molecular level of organization are often quite difficult to apply to larger spatial scales. This is particularly true of moleuclar models driven by Monte-Carlo simulations. This challenge of multiscale dynamics requires methods to extract reduced order behaviors from detailed high-dimensional simulations. In this work we present a novel deterministic simulation method yielding accurate predictions of force-length behaviors of contracting muscle sarcomeres undergoing periodic length changes (work loops). The model maintains interpretability by tracking macroscopic state variables throughout the simulation while using data-driven representations of dynamics. Parameters of the data-driven dynamics are learned from trajectories from Monte-Carlo simulations of a half-sarcomere. Our method significantly reduces computational cost by tracking the state of the sarcomere in a course grained set of variables while maintaining accurate prediction of macroscopic level observables and time series for course grained variables. This allows for rapid sampling of the model’s output and builds towards the ability to scale to multiple-sarcomere simulations.Author SummaryWe develop a data-driven surrogate model for the dynamics of the half-sarcomere. This model achieves the same behavior with respect to force traces as more sophisticated Monte Carlo models at a substantially lower computational cost. The model is built by finding a course grained description of the full state space of the Monte Carlo simulation and learning dynamical models on the course grained space. Data-driven representations of the dynamics in the course grained space are trained using data from the full model. Data-driven models for forcing are also learned, and the result fed back into the dynamics. In doing so, the model seeks to replicate the effects of filament compliance on macro scale dynamics without explicitly tracking micro scale features. We withhold some input parameter regimes and demonstrate accurate reconstruction of course grained state and force traces using the data-driven model and given only knowledge of the initial condition and input. This work allows for faster computation of the forcing behavior of the half-sarcomere, as well as consistent representations of the course grained state variables. It is therefore promising as a step towards multi-sarcomere or even tissue scale models of skeletal muscle.
D-Retro Inverso (DRI) Amylin and the Stability of Amylin Fibrils
Authors: Pandey Preeti , Nguyen Natalie , Hansmann Ulrich H.E. 
Published: March 2020

AbstractMotivated by the role that amylin aggregates pay in type-II diabetes, we compare the stability of regular amylin fibrils with the stability of fibrils where L-amino acid chains are replaced by D-Retro Inverso (DRI) amylin,i.e., peptides where the sequence of amino acids is reversed, and at the same time the L-amino acids are replaced by their mirror images. Our molecular dynamics simulations show that despite leading to only marginal difference in fibril structure and stability, aggregating DRI-amylin peptides have different pattern of contacts and hydrogen bonding. Because of these differences does DRI-amylin, when interacting with regular (L) amylin, alter the elongation process and lowers the stability of hybrid amylin fibrils. Our results suggest not only a potential use of DRI-amylin as inhibitor of amylin fibril-formation, but points also to the possibility of using insertion of DRI-proteins in L-assemblies as a way to probe the role of certain kinds of hydrogen bonds in supra-molecular assemblies or aggregates.
A simple, scalable approach to building a cross-platform transcriptome atlas
Authors: Angel Paul W , Rajab Nadia , Deng Yidi , Pacheco Chris M , Chen Tyrone , Lê Cao Kim-Anh , Choi Jarny , Wells Christine A 
Published: March 2020

ABSTRACTGene expression atlases have transformed our understanding of the development, composition and function of human tissues. New technologies promise improved cellular or molecular resolution, and have led to the identification of new cell types, or better defined cell states. But as new technologies emerge, information derived on old platforms becomes obsolete. We demonstrate that it is possible to combine a large number of different profiling experiments summarised from dozens of laboratories and representing hundreds of donors, to create an integrated molecular map of human tissue. As an example, we combine 850 samples from 38 platforms to build an integrated atlas of human blood cells. We achieve robust and unbiased cell type clustering using a variance partitioning method, selecting genes with low platform bias relative to biological variation. Other than an initial rescaling, no other transformation to the primary data is applied through batch correction or renormalisation. Additional data, including single-cell datasets, can be projected for comparison, classification and annotation. The resulting atlas provides a multi-scaled approach to visualise and analyse the relationships between sets of genes and blood cell lineages, including the maturation and activation of leukocytes in vivo and in vitro.In allowing for data integration across hundreds of studies, we address a key reproduciblity challenge which is faced by any new technology. This allows us to draw on the deep phenotypes and functional annotations that accompany traditional profiling methods, and provide important context to the high cellular resolution of single cell profiling. Here, we have implemented the blood atlas in the open access Stemformatics.org platform, drawing on its extensive collection of curated transcriptome data. The method is simple, scalable and amenable for rapid deployment in other biological systems or computational workflows.Graphical abstractRecursive approach to generating a multi-scaled atlas. Top panel: The method integrates data from all cell types in the Stemformatics database, and shows clear division of samples into global categories of stromal, pluripotent or blood (inset) cell types. Bottom panel: Integration of only the blood cell subsets provides a blood atlas. Projection of external samples (green) onto the blood atlas. Samples are coloured by curated annotations derived from the original studies, and can be viewed atStemformatics.org
ZNF423 orthologs are highly constrained in vertebrates but show domain-level plasticity across invertebrate lineages
Authors: Hamilton Bruce A. 
Published: March 2020

AbstractZNF423encodes 30 C2H2 zinc fingers that bind DNA and a variety of lineage- and signal-dependent transcription factors.ZNF423genetic variants are proposed to cause neurodevelopmental and ciliopathy-related disorders in humans. Mouse models show midline brain defects, including cerebellar vermis hypoplasia, and defects in adipogenesis. Here I show strong protein sequence constraint among 165 vertebrate orthologs. In contrast, orthologs from invertebrate lineages, spanning larger time intervals, show substantial differences in zinc finger number, arrangement, and identity. A terminal zinc finger cluster common among other lineages was independently lost in vertebrates and insects. Surprisingly, a moderately-constrained non-C2H2 sequence with potential to form a C4-class zinc finger is a previously-unrecognized conserved feature of nearly all identified homologs. These results highlight evolutionary dynamics of a likely signal integration node across species with distinct developmental strategies and body plans. Functions of the newly identified C4-like sequence and lineage-specific fingers remain to be studied.
Mechanisms of γ-Secretase Activation and Substrate Processing
Authors: Bhattarai Apurba , Devkota Sujan , Bhattarai Sanjay , Wolfe Michael S. , Miao Yinglong 
Published: March 2020

AbstractAmyloid β-peptide, the principal component of characteristic cerebral plaques of Alzheimer’s disease (AD), is produced through intramembrane proteolysis of the amyloid precursor protein (APP) by γ-secretase. Despite the importance in pathogenesis of AD, the mechanisms of intramembrane proteolysis and substrate processing by γ-secretase remain poorly understood. Here, complementary all-atom simulations using a robust Gaussian accelerated molecular dynamics (GaMD) method and biochemical experiments were combined to investigate substrate processing of wildtype and mutant APP by γ-secretase. The GaMD simulations captured spontaneous activation of γ-secretase, with hydrogen bonded catalytic aspartates and water poised for proteolysis of APP at the ε cleavage site. Furthermore, GaMD simulations revealed that familial AD mutations I45F and T48P enhanced the initial ε cleavage between residues Leu49-Val50, while M51F mutation shifted the ε cleavage site to the amide bond between Thr48-Leu49. Detailed analysis of the GaMD simulations allowed us to identify distinct low-energy conformational states of γ-secretase, different secondary structures of the wildtype and mutant APP substrate, and important active-site sub-pockets for catalytic function of the enzyme. The simulation findings were highly consistent with experimental analyses of APP proteolytic products using mass spectrometry and western blotting. Taken together, the GaMD simulations and biochemical experiments have enabled us to elucidate the mechanisms of γ-secretase activation and substrate processing, which should facilitate rational computer-aided drug design targeting this functionally important enzyme.
Noise-correlation is Modulated by Reward Expectation in the Primary Motor Cortex Bilaterally During Manual and Observational Tasks in Primates
Authors: Moore Brittany , Khang Sheng , Francis Joseph Thachil 
Published: March 2020

AbstractReward modulation is represented in the motor cortex (M1) and could be used to implement more accurate decoding models to improve brain computer interfaces (BCIs) (Zhao et al. 2018). Analyzing trial-to-trial noise-correlations between neural units in the presence of rewarding (R) and non-rewarding (NR) stimuli adds to our understanding of cortical network dynamics. We utilized Pearson’s correlation coefficient to measure shared variability between simultaneously recorded units (32 – 112) and found significantly higher noise-correlation and positive correlation between the populations’ signal- and noise-correlation during NR trials as compared to R trials. This pattern is evident in data from two non-human primates (NHPs) during single-target center out reaching tasks, both manual and action observation versions. We conducted mean matched noise-correlation analysis in order to decouple known interactions between event triggered firing rate changes and neural correlations. Isolated reward discriminatory units demonstrated stronger correlational changes than units unresponsive to reward firing rate modulation, however the qualitative response was similar, indicating correlational changes within the network as a whole can serve as another information channel to be exploited by BCIs that track the underlying cortical state, such as reward expectation, or attentional modulation. Reward expectation and attention in return can be utilized with reinforcement learning towards autonomous BCI updating.
Investigating the effect of glycaemic traits on the risk of psychiatric illness using Mendelian randomisation
Authors: Adams Danielle M. , Reay William R. , Geaghan Michael P. , Cairns Murray J. 
Published: March 2020

ABSTRACTData from observational studies have suggested an involvement of abnormal glycaemic regulation in the pathophysiology of psychiatric illness. This may be an attractive target for clinical intervention as glycaemia can be modulated by both lifestyle factors and pharmacological agents. However, observational studies are inherently confounded, and therefore causal relationships cannot be reliably established. We employed genetic variants rigorously associated with three glycaemic traits (fasting glucose, fasting insulin, and glycated haemoglobin) as instrumental variables in a two-sample Mendelian randomisation analysis to investigate the causal effect of these measures on the risk for eight psychiatric disorders. A significant protective effect of a unit increase in fasting insulin levels was observed for anorexia nervosa after the application of multiple testing correction (OR = 0.48 [95% CI: 0.33-0.71] – inverse-variance weighted estimate. The relationship between fasting insulin and anorexia nervosa was supported by a suite of sensitivity analyses, with no statistical evidence of instrument heterogeneity or horizontal pleiotropy. Further investigation is required to explore the relationship between insulin levels and anorexia.
Genome-centric portrait of the microbes’ cellulolytic competency
Authors: Wang Yubo , Li Liguan , Xia Yu , Ju Feng , Zhang Tong 
Published: March 2020

AbstractNeither the abundance of the exo/endoglucase GH modules nor the taxonomy affiliation is informative enough in inferring whether a genome is of a potential cellulolytic microbe or not. By interpreting the complete genomes of 2642 microbe strains whose phenotypes have been well documented, we are trying to reveal a more reliable genotype and phenotype correlation on the specific function niche of cellulose hydrolysis. By incorporating into the annotation approach an automatic recognition of the potential synergy machineries, a more reliable prediction on the corresponding microbes’ cellulolytic competency could be achieved. The potential cellulose hydrolyzing microbes could be categorized into 5 groups according to the varying synergy machineries among the carbohydrate active modules/genes annotated. Results of the meta-analysis on the 2642 genomes revealed that some cellulosome gene clusters were in lack of the surface layer homology module (SLH) and microbe strains annotated with such cellulosome gene clusters were not certainly cellulolytic. Hypothesized in this study was that cellulosome-independent genes harboring both the SLH module and the cellulose-binding carbohydrate binding module (CBM) were likely an alternative gene apparatus initiating the formation of the cellulose-enzyme-microbe (CEM) complexes; and their role is important especially for the cellulolytic anaerobes without cellulosome gene clusters.ImportanceIn the genome-centric prediction on the corresponding microbes’ cellulolytic activity, recognition of the synergy machineries that include but are not limited to the cellulosome gene clusters is equally important as the annotation of the individual carbohydrate active modules or genes. This is the first time that a pipeline was developed for an automatic recognition of the synergy among the carbohydrate active units annotated. With promising resolution and reliability, this pipeline should be a good add to the bioinformatic tools for the genome-centric interpretations on the specific function niche of cellulose hydrolysis.
Tilorone: A Broad-Spectrum Antiviral For Emerging Viruses
Authors: Ekins Sean , Madrid Peter B. 
Published: March 2020

AbstractTilorone is a 50-year-old synthetic small-molecule compound with antiviral activity that is proposed to induce interferon after oral administration. This drug is used as a broad-spectrum antiviral in several countries of the Russian Federation. We have recently described activityin vitroandin vivoagainst the Ebola Virus. After a broad screening of additional viruses, we now describein vitroactivity against Chikungunya virus (CHIK) and Middle Eastern Respiratory Syndrome Coronavirus (MERS-CoV).