bluuebunny/crossref_metadata_2025_split huggingface dataset:
CIAlign - A highly customisable command line tool to clean, interpret and visualise multiple sequence alignments
Authors: Tumescheit Charlotte , Firth Andrew E. , Brown Katherine 
Published: September 2020

AbstractBackgroundThroughout biology, multiple sequence alignments (MSAs) form the basis of much investigation into biological features and relationships. These alignments are at the heart of many bioinformatics analyses. However, sequences in MSAs are often incomplete or very divergent, which leads to poorly aligned regions or large gaps in alignments. This slows down computation and can impact conclusions without being biologically relevant. Therefore, cleaning the alignment by removing these regions can substantially improve analyses. Manual editing of MSAs is very widespread but is time-consuming and difficult to reproduce.ResultsWe present a comprehensive, user-friendly MSA trimming tool with multiple visualisation options. Our highly customisable command line tool aims to give intervention power to the user by offering various options, and outputs graphical representations of the alignment before and after processing to give the user a clear overview of what has been removed.The main functionalities of the tool include removing regions of low coverage due to insertions, removing gaps, cropping poorly aligned sequence ends and removing sequences that are too divergent or too short. The thresholds for each function can be specified by the user and parameters can be adjusted to each individual MSA. CIAlign is designed with an emphasis on solving specific and common alignment problems and on providing transparency to the user.ConclusionCIAlign effectively removes problematic regions and sequences from MSAs and provides novel visualisation options. This tool can be used to refine alignments for further analysis and processing. The tool is aimed at anyone who wishes to automatically clean up parts of an MSA and those requiring a new, accessible way of visualising large MSAs.
SARS-CoV-2 protein Nsp1 alters actomyosin cytoskeleton and phenocopies arrhythmogenic cardiomyopathy-related PKP2 mutant
Authors: Márquez-López Cristina , Roche-Molina Marta , García-Quintáns Nieves , Sacristán Silvia , Siniscalco David , González-Guerra Andrés , Camafeita Emilio , Lytvyn Mariya , Guillen María I. , Sanz-Rosa David , Martín-Pérez Daniel , Sánchez-Ramos Cristina , García Ricardo , Bernal Juan A. 
Published: September 2020

AbstractMutations in desmosomalPlakophilin-2 (PKP2)are the most prevalent drivers of arrhythmogenic cardiomyopathy (ACM) and a common cause of sudden cardiac death in young athletes. However, partner proteins that elucidate PKP2 cellular mechanism to understand cardiac dysfunction in ACM are mostly unknown. Here we identify the actin-based motor proteins Myh9 and Myh10 as key PKP2 interactors, and demonstrate that the expression of the ACM-related PKP2 mutant R735X alters actin fiber organization and cell mechanical stiffness. We also show that SARS-CoV-2 Nsp1 protein acts similarly to this known pathogenic R735X mutant, altering the actomyosin component distribution on cardiac cells. Our data reveal that the viral Nsp1 hijacks PKP2 into the cytoplasm and mimics the effect of delocalized R735X mutant. These results demonstrate that cytoplasmic PKP2, wildtype or mutant, induces the collapse of the actomyosin network, since shRNA-PKP2knockdown maintains the cell structure, validating a critical role of PKP2 localization in the regulation of actomyosin architecture. The fact that Nsp1 and PKP2 mutant R735X share similar phenotypes also suggests that direct SARS-CoV-2 heart infection could induce a transient ACM-like disease in COVID-19 patients, which may contribute to right ventricle dysfunction, observed in patients with poor survival prognosis.HighlightsThe specific cardiac isoform Plakophilin-2a (PKP2) interacts with Myh9 and Myh10.PKP2 delocalization alters actomyosin cytoskeleton component organization. SARS-CoV-2 Nsp1 protein hijacks PKP2 from the desmosome into the soluble fraction where it is downregulated.Viral Nsp1 collapses the actomyosin cytoskeleton and phenocopies the arrhythmogenic cardiomyopathy-related mutant R735X.
Identification of hsa-miR-106a-5p as an impact agent on promotion of multiple sclerosis using multi-step data analysis
Authors: Rahimirad Samira , Navaderi Mohammad , Alaei Shokoofeh , Sanati Mohammad Hossein 
Published: September 2020

AbstractMultiple Sclerosis (MS) is a chronic, demyelinating disease in which the neuron myelin sheath is disrupted and leading to signal transductions disabilities. The evidence demonstrated that gene expression patterns and their related regulating factors are the most critical agents in Multiple Sclerosis demyelinating process. A miRNA is a small non-coding RNA which functions in post-transcriptional regulation of gene expression. Identification of specific miRNA dysregulation patterns in multiple sclerosis blood samples compared to healthy control can be used as a diagnostic and prognostic agent. Through the literature review and bioinformatics analysis, it was found that the hsa-miR-106a-5p can be considered as a significant MS pathogenic factor, which seems has an abnormal expression pattern in patients’ blood. Experimental validation using Real-Time PCR assay was carried to verifying the miR-106a-5p expression in Multiple Sclerosis and healthy control blood samples. The obtained results proved the miR-106a dysregulation in MS patients. The expression levels of miR-106a-5p were significantly down-regulated (Fold change=0.44) in patient blood samples compared to controls (p=0.059). Our study suggested that miR-106a-5p may have a biomarker potential to the diagnosis of MS patients based on its dysregulation patterns in Multiple Sclerosis blood.
Ligation bias is a major contributor to nonstoichiometric abundances of secondary siRNAs and impacts analyses of microRNAs
Authors: Baldrich Patricia , Tamim Saleh , Mathioni Sandra , Meyers Blake 
Published: September 2020

ABSTRACTPlant small RNAs are a diverse and complex set of molecules, ranging in length from 21 to 24 nt, involved in a wide range of essential biological processes. High-throughput sequencing is used for the discovery and quantification of small RNAs. However, several biases can occur during the preparation of small RNA libraries, especially using low input RNA. We used two stages of maize anthers to evaluate the performance of seven commercially-available methods for small RNA library construction, using different RNA input amounts. We show that when working with plant material, library construction methods have differing capabilities to capture small RNAs, and that different library construction methods provide better results when applied to the detection of microRNAs, phasiRNAs, or tRNA-derived fragment. We also observed that ligation bias occurs at both ends of miRNAs and phasiRNAs, suggesting that the biased compositions observed in small RNA populations, including nonstoichiometric levels of phasiRNAs within a locus, may reflect a combination of biological and technical influences.
CROssBAR: Comprehensive Resource of Biomedical Relations with Deep Learning Applications and Knowledge Graph Representations
Authors: Doğan Tunca , Atas Heval , Joshi Vishal , Atakan Ahmet , Rifaioglu Ahmet Sureyya , Nalbat Esra , Nightingale Andrew , Saidi Rabie , Volynkin Vladimir , Zellner Hermann , Cetin-Atalay Rengul , Martin Maria , Atalay Volkan 
Published: September 2020

AbstractSystemic analysis of available large-scale biological and biomedical data is critical for developing novel and effective treatment approaches against both complex and infectious diseases. Owing to the fact that different sections of the biomedical data is produced by different organizations/institutions using various types of technologies, the data are scattered across individual computational resources, without any explicit relations/connections to each other, which greatly hinders the comprehensive multi-omics-based analysis of data. We aimed to address this issue by constructing a new biological and biomedical data resource, CROssBAR, a comprehensive system that integrates large-scale biomedical data from various resources and store them in a new NoSQL database, enrich these data with deep-learning-based prediction of relations between numerous biomedical entities, rigorously analyse the enriched data to obtain biologically meaningful modules and display them to users via easy-to-interpret, interactive and heterogenous knowledge graph (KG) representations within an open access, user-friendly and online web-service athttps://crossbar.kansil.org. As a use-case study, we constructed CROssBAR COVID-19 KGs (available at:https://crossbar.kansil.org/covid_main.php) that incorporate relevant virus and host genes/proteins, interactions, pathways, phenotypes and other diseases, as well as known and completely new predicted drugs/compounds. Our COVID-19 graphs can be utilized for a systems-level evaluation of relevant virus-host protein interactions, mechanisms, phenotypic implications and potential interventions.
Contrasting beta diversity and functional composition of aquatic insect communities across local to regional scales in Amazonian streams
Authors: Nicacio Gilberto , Cunha Erlane José , Hamada Neusa , Juen Leandro 
Published: September 2020

AbstractWe investigated how components of beta diversity (i.e., the turnover and nestedness and functional compositional) aquatic insect assemblages change among sites and are influenced by environmental and spatial drivers. For this, we analyzed beta-diversity and functional composition of Ephemeroptera, Plecoptera, and Trichoptera in 16 streams in two Amazonian basins with distinct environmental conditions (the Carajás and Tapajós regions). We performed Multiple regression on dissimilarity matrices (MRM) and Procrustes analysis to test spatial and environmental influences on the taxonomic and functional composition of communities. Community dissimilarity was most related to variations in geographic distance and topography, which highlighted the environmental distances shaping the communities. Variation in functional composition could be mostly attributed to the replacement of species by those with similar traits, indicating trait convergence among communities. Environmental predictors best-explained species replacement and trait congruence within and between the regions evaluated. In summary, among communities with different taxonomic compositions, the high species replacement observed appears to be leading them to have similar community structure, with species having the same functional composition, even in communities separated by both small and large geographic distances.
GP96 drives exacerbation of secondary bacterial pneumonia following influenza A virus infection
Authors: Sumitomo Tomoko , Nakata Masanobu , Nagase Satoshi , Takahara Yuki , Honda-Ogawa Mariko , Mori Yasushi , Yamaguchi Masaya , Okamoto Shigefumi , Kawabata Shigetada 
Published: September 2020

AbstractInfluenza A virus (IAV) infection predisposes the host to secondary bacterial pneumonia, known as a major cause of morbidity and mortality during influenza epidemics. Analysis of interactions between IAV-infected human epithelial cells andStreptococcus pneumoniaerevealed that infected cells ectopically exhibited the endoplasmic reticulum chaperon GP96 on the surface. Importantly, efficient pneumococcal adherence to epithelial cells was imparted by interactions with extracellular GP96 and integrin αV, with the surface expression mediated by GP96 chaperone activity. Furthermore, abrogation of adherence was gained by chemical inhibition or genetic knockout of GP96, as well as addition of RGD peptide. Direct binding of extracellular GP96 and pneumococci was shown to be mediated by pneumococcal oligopeptide permease components. Additionally, IAV infection induced activation of calpains and Snail1, which are responsible for degradation and transcriptional repression of junctional proteins in the host, respectively, indicating increased bacterial translocation across the epithelial barrier. Notably, treatment of IAV-infected mice with the GP96 inhibitor enhanced pneumococcal clearance from lung tissues and ameliorated lung pathology. Taken together, the present findings indicate a viral-bacterial synergy in relation to disease progression and suggest a paradigm for developing novel therapeutic strategies tailored to inhibit pneumococcal colonization in an IAV-infected respiratory tract.
COPB2haploinsufficiency causes a coatopathy with osteoporosis and developmental delay
Authors: Marom Ronit , Burrage Lindsay C. , Clément Aurélie , Blanco-Sánchez Bernardo , Venditti Rossella , Jain Mahim , Grafe Ingo , Scott Daryl A. , Rosenfeld Jill A. , Sutton V. Reid , Shinawi Marwan , Mirzaa Ghayda , DeVile Catherine , Roberts Rowenna , Calder Alistair D , Allgrove Jeremy , Lanza Denise G. , Li Xiaohui , Joeng Kyu Sang , Lee Yi-Chien , Song I-Wen , Sliepka Joseph M. , Batkovskyte Dominyka , Jin Zixue , Dawson Brian C. , Chen Shan , Chen Yuqing , Jiang Ming-Ming , Munivez Elda M. , Tran Alyssa A. , Emrick Lisa T. , Murdock David R. , Hanchard Neil A. , Zapata Gladys E. , Mehta Nitesh R. , Weis Mary Ann , Kuzawa Cole , Scott Abbey , Tremp Brenna A. , Phillips Jennifer B. , Wegner Jeremy , Taylor-Miller Tashunka , Gibbs Richard A. , Muzny Donna M. , Jhangiani Shalini N. , Stottmann Rolf W. , Dickinson Mary E. , Seavitt John R. , Heaney Jason D. , Eyre David R. , Ambrose Catherine G. ,   Undiagnosed Diseases Network Monte Westerfield, De Matteis Maria Antonella , Lee Brendan 
Published: September 2020

AbstractCoatomer complexes function in the sorting and trafficking of proteins between subcellular organelles. Pathogenic variants in coatomer subunits or associated factors have been reported in multi-systemic disorders, i.e., coatopathies, that can affect the skeletal and central nervous systems. We have identified loss-of-function variants inCOPB2, a component of the coatomer complex I (COPI), in individuals presenting with osteoporosis, fractures and developmental delay of variable severity. Because the role of COPB2 in bone has not been characterized, we studied the effect ofCOPB2deficiency on skeletal development in mice and zebrafish.Copb2+/−mice showed low bone mass and decreased bone strength. In zebrafish, larvae carrying acopb2heterozygous frameshift variant showed delayed mineralization.copb2-null embryos showed endoplasmic reticulum (ER) and Golgi disorganization, and embryonic lethality.COPB2siRNA-treated fibroblasts showed delayed collagen trafficking with retention of type I collagen in the ER and Golgi, and altered distribution of Golgi markers. Our data suggest thatCOPB2haploinsufficiency leads to disruption of intracellular collagen trafficking and osteoporosis, which may improve with ascorbic acid supplementation. This work highlights the role of COPI complex as a critical regulator of bone mass and identifies a new form of coatopathy due toCOPB2deficiency.
Sustained attention and spatial attention distinctly influence long-term memory encoding
Authors: deBettencourt Megan T. , Williams Stephanie D. , Vogel Edward K. , Awh Edward 
Published: September 2020

AbstractOur attention is critically important for what we remember. Prior measures of the relationship between attention and memory, however, have largely treated “attention” as a monolith. Here, across three experiments, we provide evidence for two dissociable aspects of attention that influence encoding into long-term memory. Using spatial cues together with a sensitive continuous report procedure, we find that long-term memory response error is affected by both trial-by-trial fluctuations of sustained attention and prioritization via covert spatial attention. Furthermore, using multivariate analyses of EEG, we track both sustained attention and spatial attention prior to stimulus onset. Intriguingly, even during moments of low sustained attention, there is no decline in the representation of the spatially attended location, showing that these two aspects of attention have robust but independent effects on long term memory encoding. Finally, sustained and spatial attention predicted distinct variance in long-term memory performance across individuals. That is, the relationship between attention and long-term memory suggests a composite model, wherein distinct attentional subcomponents influence encoding into long-term memory. These results point towards a taxonomy of the distinct attentional processes that constrain our memories.
Dragonfly visual neurons selectively attend to features in naturalistic scenes
Authors: Evans BJE , Fabian JM , O’Carroll DC , Wiederman SD 
Published: September 2020

AbstractAerial predators, such as the dragonfly, determine the position and movement of their prey even when embedded in natural scenes. This task is likely supported by a group of optic lobe neurons with responses selective for moving targets of less than a few degrees. These Small Target Motion Detector (STMD) neurons are tuned to target velocity and show profound facilitation in responses to targets that move along continuous trajectories. When presented with a pair of targets, some STMDs competitively select one of the alternatives as if the other does not exist.Here we describe intracellular responses of STMD neurons to the visual presentation of many potential alternatives within cluttered environments comprised of natural scenes. We vary both target contrast and the background scene, across a range of target and background velocities. We find that background motion affects STMD responses indirectly, via the competitive selection of background features. We find that robust target discrimination is limited to scenarios when the target velocity is matched to, or greater than, background velocity. Furthermore, STMD target discriminability is modified by background direction. Backgrounds that move in the neuron’s anti-preferred direction result in the least performance degradation.Significance StatementBiological brains solve the difficult problem of visually detecting and tracking moving features in cluttered environments. We investigated this neuronal processing by recording intracellularly from dragonfly visual neurons that encode the motion of small moving targets subtending less than a few degrees (e.g. prey and conspecifics). However, dragonflies live in a complex visual environment where background features may interfere with tracking by reducing target contrast or providing competitive cues. We find that selective attention towards features drives much of the neuronal response, with background clutter competing with target stimuli for selection. Moreover, the velocity of features is an important component in determining the winner in these competitive interactions.
leADS: improved metabolic pathway inference based on active dataset subsampling
Authors: Basher Abdur Rahman M. A. , Nallan Aditi N. , McLaughlin Ryan J. , Anstett Julia , Hallam Steven J. 
Published: September 2020

AbstractMetabolic pathways are composed of reaction sequences catalyzed by enzymes. The set of reactions within and between cells comprises a reactome. Pathways and reactomes can be predicted from organismal or multi-organismal genomes using rule-based or machine learning methods. While machine learning methods overcome issues of probability and scale associated with rule-based methods, several complications remain that can degrade performance including inadequately labeled training data, missing feature information, and inherent imbalances in the distribution of pathways within a dataset. Here, we present leADS (multi-label learning based onactivedatasetsubsampling), a machine learning method, that uses subsampling to reduce the negative impact of training loss due to class imbalance. We demonstrate leADs performance using organismal and multi-organismal datasets in relation to other machine learning pathway prediction methods.Availability and implementationleADS is available under the GNU license at github.com/hallamlab/leADS. A wiki, including a tutorial, is available at github.com//hallamlab/leADS/wikiContactshallam@mail.ubc.ca
Fate of the M-phase-assembled centrioles during the cell cycle in theTP53;PCNT;CEP215-deleted cells
Authors: Jung Gee In , Rhee Kunsoo 
Published: September 2020

ABSTRACTCancer cells frequently include supernumerary centrioles. Here, we generatedTP53;PCNT;CEP215triple knockout cell lines and observed precocious separation and amplification of the centrioles at M phase. Many of the triple KO cells maintained supernumerary centrioles throughout the cell cycle. The M-phase-assembled centrioles lack an ability to function as templates for centriole assembly during S phase. They also lack an ability to organize microtubules in interphase. However, we found that a fraction of them acquired an ability to organize microtubules during M phase. Our works provide an example how supernumerary centrioles behave in dividing cells.
Mapping Brain-Behavior Space Relationships Along the Psychosis Spectrum
Authors: Ji Jie Lisa , Helmer Markus , Fonteneau Clara , Burt Joshua B. , Tamayo Zailyn , Demšar Jure , Adkinson Brendan , Savić Aleksandar , Preller Katrin H. , Moujaes Flora , Vollenweider Franz X. , Martin William J. , Repovš Grega , Murray John D. , Anticevic Alan 
Published: September 2020

AbstractDifficulties in advancing effective patient-specific therapies for psychiatric disorders highlight a need to develop a stable neurobiologically-grounded mapping between neural and symptom variation. This gap is particularly acute for psychosis-spectrum disorders (PSD). Here, in a sample of 436 cross-diagnostic PSD patients, we derived and replicated a dimensionality-reduced symptom space across hallmark psychopathology symptoms and cognitive deficits. In turn, these symptom axes mapped onto distinct, reproducible brain maps. Critically, we found that multivariate brain-behavior mapping techniques (e.g. canonical correlation analysis) do not produce stable results. Instead, we show that a univariate brain-behavioral space (BBS) can resolve stable individualized prediction. Finally, we show a proof-of-principle framework for relating personalized BBS metrics with molecular targets via serotonin and glutamate receptor manipulations and gene expression maps. Collectively, these results highlight a stable and data-driven BBS mapping across PSD, which offers an actionable path that can be iteratively optimized for personalized clinical biomarker endpoints.