bluuebunny/crossref_metadata_2025_split huggingface dataset:
ACE2 is the critical in vivo receptor for SARS-CoV-2 in a novel COVID-19 mouse model with TNF- and IFNγ-driven immunopathology
Authors: Gawish Riem , Starkl Philipp , Pimenov Lisabeth , Hladik Anastasiya , Lakovits Karin , Oberndorfer Felicitas , Cronin Shane J.F. , Ohradanova-Repic Anna , Wirnsberger Gerald , Agerer Benedikt , Endler Lukas , Capraz Tümay , Perthold Jan W. , Hagelkruys Astrid , Montserrat Nuria , Mirazimi Ali , Boon Louis , Stockinger Hannes , Bergthaler Andreas , Oostenbrink Chris , Penninger Josef M. , Knapp Sylvia 
Published: August 2021

SummaryDespite tremendous progress in the understanding of COVID-19, mechanistic insight into immunological, disease-driving factors remains limited. We generated maVie16, a mouse-adapted SARS-CoV-2, by serial passaging of a human isolate. In silico modelling revealed how Spike mutations of maVie16 enhanced interaction with murine ACE2. MaVie16 induced profound pathology in BALB/c and C57BL/6 mice and the resulting mouse COVID-19 (mCOVID-19) replicated critical aspects of human disease, including early lymphopenia, pulmonary immune cell infiltration, pneumonia and specific adaptive immunity. Inhibition of the proinflammatory cytokines IFNγ and TNF substantially reduced immunopathology. Importantly, genetic ACE2-deficiency completely prevented mCOVID-19 development. Finally, inhalation therapy with recombinant ACE2 fully protected mice from mCOVID-19, revealing a novel and efficient treatment. Thus, we here present maVie16 as a new tool to model COVID-19 for the discovery of new therapies and show that disease severity is determined by cytokine-driven immunopathology and critically dependent on ACE2 in vivo.Key pointsThe mouse-adapted SARS-CoV-2 strain maVie16 causes fatal disease in BALB/c mice and substantial inflammation, pneumonia and immunity in C57BL/6 miceTNFα/IFNγ blockade ameliorates maVie16-induced immunopathologyMaVie16 infection depends on ACE2 and soluble ACE2 inhalation can prevent disease
Evaluating the impact ofin silicopredictors on clinical variant classification
Authors: Wilcox Emma H. , Sarmady Mahdi , Wulf Bryan , Wright Matt W. , Rehm Heidi L. , Biesecker Leslie G. , Abou Tayoun Ahmad N. 
Published: August 2021

AbstractBackgroundIn silicoevidence is important to consider when interpreting genetic variants. According to the ACMG/AMP,in silicoevidence is applied at the supporting strength level using the PP3 and BP4 criteria, for pathogenic and benign evidence, respectively. While PP3 has been determined to be one of the most commonly applied criteria, less is known about the effect of these two criteria on variant classification outcomes.MethodsIn this study, a total of 727 missense variants curated by Clinical Genome Resource (ClinGen) Variant Curation Expert Panels (VCEPs) were analyzed to determine how often PP3 and BP4 were applied and how often they influenced final variant classifications. The current categorical system of variant classification was compared with a point-based system being developed by the ClinGen Sequence Variant Interpretation Working Group. In addition, the performance of fourin silicotools (REVEL, VEST, FATHMM, and MPC) was assessed by using a gold set of 237 variants (classified as benign or pathogenic independent of PP3 or BP4) to calculate pathogenicity likelihood ratios.ResultsCollectively, the PP3 and BP4 criteria were applied by ClinGen VCEPs to 55% of missense variants in this data set. Removingin silicocriteria from variants where they were originally applied caused variants to change classification from pathogenic to likely pathogenic (14%), likely pathogenic to variant of uncertain significance (VUS) (24%), or likely benign to VUS (64%). The proportion of downgrades with the categorical classification system was similar to that of the point-based system, though the latter resolved borderline classifications. REVEL and VEST performed at a level consistent with moderate strength towards either benign or pathogenic evidence, while FATHMM performed at the supporting level.ConclusionsOverall, this study demonstrates thatin silicocriteria PP3 and BP4 are commonly applied in variant classification and often affect the final classification. Our results suggest that when sufficient thresholds forin silicopredictors are established, PP3 and BP4 may be appropriate to use at a moderate strength. However, further calibration with larger datasets is needed to optimize the performance of currentin silicotools given the impact they have on clinical variant classification.
OTUs clustering should be avoided for defining oral microbiome
Authors: Regueira-Iglesias A , Vázquez-González L , Balsa-Castro C , Blanco-Pintos T , Arce VM , Carreira MJ , Tomás I 
Published: August 2021

ABSTRACTThis in silico investigation aimed to: 1) evaluate a set of primer pairs with high coverage, including those most commonly used in the literature, to find the different oral species with 16S rRNA gene amplicon similarity/identity (ASI) values ≥97%; and 2) identify oral species that may be erroneously clustered in the same operational taxonomic unit (OTU) and ascertain whether they belong to distinct genera or other higher taxonomic ranks.Thirty-nine primer pairs were employed to obtain amplicon sequence variants (ASVs) from the complete genomes of 186 bacterial and 135 archaeal species. For each primer, ASVs without mismatches were aligned using BLASTN and their similarity values were obtained. Finally, we selected ASVs from different species with an ASI value ≥97% that were covered 100% by the query sequences. For each primer, the percentage of species-level coverage with no ASI≥97% (SC-NASI≥97%) was calculated.Based on the SC-NASI≥97% values, the best primer pairs were OP_F053-KP_R020 for bacteria (65.05%), KP_F018-KP_R002 for archaea (51.11%), and OP_F114-KP_R031 for bacteria and archaea together (52.02%). Eighty percent of the oral-bacteria and oralarchaea species shared an ASI≥97% with at least one other taxa, including Campylobacter, Rothia, Streptococcus, and Tannerella, which played conflicting roles in the oral microbiota. Moreover, around a quarter and a third of these two-by-two similarity relationships were between species from different bacteria and archaea genera, respectively. Furthermore, even taxa from distinct families, orders, and classes could be grouped in the same cluster.Consequently, irrespective of the primer pair used, OTUs constructed with a 97% similarity provide an inaccurate description of oral-bacterial and oral-archaeal species, greatly affecting microbial diversity parameters. As a result, clustering by OTUs impacts the credibility of the associations between some oral species and certain health and disease conditions. This limits significantly the comparability of the microbial diversity findings reported in oral microbiome literature.
On the relationships between rarity, uniqueness, distinctiveness, originality and functional/phylogenetic diversity
Authors: Pavoine Sandrine , Ricotta Carlo 
Published: August 2021

ABSTRACTRarity reflects the low abundance of a species while distinctiveness reflects its quality of being easy to recognize because it has unique functional characteristics and/or an isolated phylogenetic position. As such, the assemblage-level rarity of a species’ functional and phylogenetic characteristics (that we name ‘effective originality’) results from both the rarity and the distinctiveness of this species. The functional and phylogenetic diversity of an assemblage then results from a compromise between the abundances and the effective originalities of the species it contains. Although the distinctiveness of a species itself depends on the abundance of the other species in the assemblage, distinctiveness indices that are available in the ecological literature scarcely consider abundance data. We develop a unifying framework that demonstrates the direct connections between measures of diversity, rarity, distinctiveness and effective originality. While developing our framework, we discovered a family of distinctiveness indices that permit a full control of the influence one wants to give to the strict uniqueness of a species (=its smallest functional or phylogenetic distance to another species in the assemblage). Illustrating our framework with bat phylogenetic diversity along a disturbance gradient in Mexico, we show how each component of rarity, distinctiveness and originality can be controlled to obtain efficient indicators for conservation. Overall our framework is aimed to improve conservation actions directed towards highly diverse areas and/or towards species whose loss would considerably decrease biodiversity by offering flexible quantitative tools where the influence of abundant versus rare, and ordinary versus original, species is understood and controlled.
Regulation of sexually dimorphic abdominal courtship behaviors in Drosophila by the Tlx/tailless-like nuclear receptor, Dissatisfaction
Authors: Duckhorn Julia C. , Cande Jessica , Metkus Mary C. , Song Hyeop , Altamirano Sofia , Stern David L. , Shirangi Troy R. 
Published: August 2021

AbstractSexually dimorphic courtship behaviors in Drosophila melanogaster develop from the activity of the sexual differentiation genes, doublesex (dsx) and fruitless (fru), functioning with other regulatory factors that have received little attention. The dissatisfaction gene (dsf) encodes an orphan nuclear receptor homologous to vertebrate Tlx and Drosophila tailless that is critical for the development of several aspects of female- and male-specific sexual behaviors. Here, we report the pattern of dsf expression in the central nervous system and show that the activity of sexually dimorphic abdominal interneurons that co-express dsf and dsx is necessary and sufficient for vaginal plate opening in virgin females, ovipositor extrusion in mated females, and abdominal curling in males during courtship. We find that dsf activity results in different neuroanatomical outcomes in females and males, promoting and suppressing, respectively, female development and function of these neurons depending upon the sexual state of dsx expression. We posit that dsf and dsx interact to specify sex differences in the neural circuitry for dimorphic abdominal behaviors.
Does the evolution of division of labour require accelerating returns from individual specialisation?
Authors: Cooper Guy Alexander , Frost Hadleigh , Liu Ming , West Stuart Andrew 
Published: August 2021

AbstractRecent theory has overturned the assumption that accelerating returns from individual specialisation are required to favour the evolution of division of labour. Yanni et al. (2020) showed that topologically constrained groups, where cells cooperate with only direct neighbours such as for filaments or branching growths, can evolve a reproductive division of labour even with diminishing returns from individual specialisation. We developed a conceptual framework and specific models to investigate the factors that can favour the initial evolution of reproductive division of labour. We found that selection for division of labour in topologically constrained groups: (1) is not a single mechanism to favour division of labour – depending upon details of the group structure, division of labour can be favoured for different reasons; (2) always involves an efficiency benefit at the level of group fitness; and (3) requires a mechanism of coordination to determine which individuals perform which tasks. Given that such coordination is unlikely to evolve before division of labour, this limits the extent to which topological constraints could have favoured the initial evolution of division of labour. We conclude by suggesting experimental designs that could determine why division of labour is favoured in the natural world.
Intraguild predation does not necessarily have negative effects on pest biological control: insights from a multiple consumer–multiple resource food web population model
Authors: Costa Michel Iskin da S. , dos Anjos Lucas 
Published: August 2021

AbstractWe develop a food web population dynamical based on an experimental pest biocontrol setup consisting of thrips and aphids (pests) being consumed by two agentsMacrolophus pygmaeusandOrius laevigatus, and withO. laevigatusbeing an intraguild predator ofM. pygmaeus. By means of numerical simulations, we show that pest biocontrol disruption can be avoided depending on initial population densities of pests and agents, despite the intraguild predation (IGP) ofO. laevigatusuponM. pygmaeus. This possible avoidance of pest biocontrol disruption is in accordance with the referred experimental setup and moreover, the proposed model corroborates the importance of initial densities of pests and agents in the determination of the failure or success of pest biocontrol found in this and other biocontrol experimental setups.
Molecular Changes in Prader-Willi Syndrome Neurons Reveals Clues About Increased Autism Susceptibility
Authors: Victor A. Kaitlyn , Donaldson Martin , Johnson Daniel , Miller Winston , Reiter Lawrence T. 
Published: August 2021

AbstractBackgroundPrader-Willi syndrome (PWS) is a neurodevelopmental disorder characterized by hormonal dysregulation, obesity, intellectual disability, and behavioral problems. Most PWS cases are caused by paternal interstitial deletions of 15q11.2-q13.1, while a smaller number of cases are caused by chromosome 15 maternal uniparental disomy (PW-UPD). Children with PW-UPD are at higher risk for developing autism spectrum disorder (ASD) than the neurotypical population. In this study, we used expression analysis of PW-UPD neurons to try to identify the molecular cause for increased autism risk.MethodsDental pulp stem cells (DPSC) from neurotypical control and PWS subjects were differentiated to neurons for mRNA sequencing. Significantly differentially expressed transcripts among all groups were identified. Downstream protein analysis including immunocytochemistry and immunoblots were performed to confirm the transcript level data and pathway enrichment findings.ResultsWe identified 9 transcripts outside of the PWS critical region (15q11.2-q13.1) that may contribute to core PWS phenotypes. Moreover, we discovered a global reduction in mitochondrial transcripts in the PW-UPD +ASD group. We also found decreased mitochondrial abundance along with mitochondrial aggregates in the cell body and neural projections of +ASD neurons.LimitationsDPSC derived neuronal cultures used here were immature (3 weeks old), while important for studying the development of the disorder, it will be critical to confirm these mitochondrial defects in more mature neurons or postmortem brain tissue. Our PW-UPD -ASD group included only females, but the sample size in downstream image analysis was increased to include males for the analysis of mitochondrial phenotypes. The ASD diagnostic tool we use is the Social Communication Questionnaire (SCQ), which has been used extensively, but is not the gold standard for ASD diagnosis.ConclusionsThe 9 transcripts we identified common to all PWS subtypes may reveal PWS specific defects during neurodevelopment. Importantly, we found a global reduction in mitochondrial transcripts in PW-UPD +ASD neurons versus control and other PWS subtypes. We then confirmed mitochondrial defects in neurons from individuals with PWS at the cellular level. Quantification of this phenotype supports our hypothesis that the increased incidence of ASD in PW-UPD subjects may arise from mitochondrial defects in developing neurons.
Acetylation regulates the oligomerization state and activity of RNase J, the major ribonuclease of Helicobacter pylori
Authors: Tejada-Arranz Alejandro , Bouilloux-Lafont Maxime , Pei Xue-Yuan , Douché Thibaut , Matondo Mariette , Williams Allison , Raynal Bertrand , Luisi Ben F , De Reuse Hilde 
Published: August 2021

AbstractIn Helicobacter pylori, post-transcriptional regulation strongly relies on the activity of an RNA degradosome, composed of the essential ribonuclease RNase J and the DEAD-box RNA helicase RhpA. Here, we describe post-translational modifications of this protein complex that affect its activity. Cell-extracted RNase J is acetylated on multiple residues, one of which, K649, strongly impacts RNase J oligomerization, which in turn influences ribonuclease activity. Corroborating the link between oligomerization and activity, mutations targeting K649 and other residues affect the dimerization and in vitro activity of RNase J. Our crystal structure of RNase J reveals three loops that gate access to the active site and rationalizes how oligomerization state influences activity. The acetylated residues of RNase J are important for H. pylori morphology, highlighting that the modifications affect the RNase J cellular function. We propose acetylation as a regulatory level controlling the activity of RNase J and the H. pylori RNA degradosome.
Predictive Modeling of Multiplex Chemical Phenomics for Novel Cells and Patients: Applied to Personalized Alzheimer’s Disease Drug Repurposing
Authors: Liu Qiao , Qiu Yue , Xie Lei 
Published: August 2021

AbstractChemical phenomics which measures multiplex chemical-induced phenotypic response of cells or patients, particularly dose-dependent transcriptomics and drug-response curves, provides new opportunities forin silicomechanism-driven phenotype-based drug discovery. However, state-of-the-art computational methods only focus on predicting a single phenotypic readout and are less successful in screening compounds for novel cells or individual patients. We designed a new deep learning model, MultiDCP, to enable high-throughput compound screening based on multiplex chemical phenomics for the first time, and further expand the scope of chemical phenomics to unexplored cells and patients. The novelties of MultiDCP lie in a multi-task learning framework with a novel knowledge-driven autoencoder to integrate incoherent labeled and unlabeled omics data, and a teacher-student training strategy to exploit unreliable data. MultiDCP significantly outperforms the state-of-the-art for novel cell lines. The predicted chemical transcriptomics demonstrate a stronger predictive power than noisy experimental data for downstream tasks. We applied MultiDCP to repurpose individualized drugs for Alzheimer’s disease, suggesting that MultiDCP is a potentially powerful tool for personalized medicine.
Visual evoked feedforward-feedback travelling waves organize neural activity across the cortical hierarchy in mice
Authors: Aggarwal Adeeti , Brennan Connor , Luo Jennifer , Chung Helen , Contreras Diego , Kelz Max B. , Proekt Alex 
Published: August 2021

AbstractSensory processing is distributed among many brain regions that interact via feedforward and feedback signaling. It has been hypothesized that neuronal oscillations mediating feedforward and feedback interactions organize into travelling waves. However, stimulus evoked travelling waves of sufficient spatial scale have never been demonstrated directly. Here, we show that simple visual stimuli reliably evoke two traveling waves with spatial wavelengths that cover much of the cerebral hemisphere in awake mice. 30-50Hz feedforward waves arise in primary visual cortex (V1) and propagate rostrally, while 3-6Hz feedback waves originate in the association cortex and flow caudally. The phase of the feedback wave modulates the amplitude of the feedforward wave and synchronizes firing between V1 and parietal cortex. Altogether, these results provide direct experimental evidence that visual evoked travelling waves percolate through the cerebral cortex and coordinate neuronal activity across broadly distributed networks mediating visual processing.
Genomic style: yet another deep-learning approach to characterize bacterial genome sequences
Authors: Yoshimura Yuka , Hamada Akifumi , Augey Yohann , Akiyama Manato , Sakakibara Yasubumi 
Published: August 2021

AbstractMotivationBiological sequence classification is the most fundamental task in bioinformatics analysis. For example, in metagenome analysis, binning is a typical type of DNA sequence classification. In order to classify sequences, it is necessary to define sequence features. Thek-mer frequency, base composition, and alignment-based metrics are commonly used. In contrast, in the field of image recognition using machine learning, image classification is broadly divided into those based on shape and those based on style. A style matrix was introduced as a method of expressing the style of an image (e.g., color usage and texture).ResultsWe propose a novel sequence feature, called genomic style, inspired by image classification approaches, for classifying and clustering DNA sequences. As with the style of images, the DNA sequence is considered to have a genomic style unique to the bacterial species, and the style matrix concept is applied to the DNA sequence. Our main aim is to introduce the genomics style as yet another basic sequence feature for metagenome binning problem in replace of the most commonly used sequence featurek-mer frequency. Performance evaluations show that our method using style matrix achieves the superior accuracy than state-of-the-art binning tools based onk-mer frequency.
Domain Organization of Lentiviral and Betaretroviral Surface Envelope Glycoproteins Modeled with AlphaFold
Authors: Hötzel Isidro 
Published: August 2021

AbstractThe surface envelope glycoproteins of non-primate lentiviruses and betaretroviruses share sequence similarity with the inner proximal domain β-sandwich of the human immunodeficiency virus type 1 (HIV-1) gp120 glycoprotein that faces the transmembrane glycoprotein as well as patterns of cysteine and glycosylation site distribution that points to a similar two-domain organization in at least some lentiviruses. Here, high reliability models of the surface glycoproteins obtained with the AlphaFold algorithm are presented for the gp135 glycoprotein of the small ruminant caprine arthritis-encephalitis (CAEV) and visna lentiviruses and the betaretroviruses jaagsiekte sheep retrovirus (JSRV), mouse mammary tumor virus (MMTV) and consensus human endogenous retrovirus type K (HERV-K). The models confirm and extend the inner domain structural conservation in these viruses and identify two outer domains with a putative receptor binding site in the CAEV and visna virus gp135. The location of that site is consistent with patterns of sequence conservation and glycosylation site distribution in gp135. In contrast, a single domain is modeled for the JSRV, MMTV and HERV-K betaretrovirus envelope proteins that is highly conserved structurally in the proximal region and structurally diverse in apical regions likely to interact with cell receptors. The models presented here identify sites in small ruminant lentivirus and betaretrovirus envelope glycoproteins likely to be critical for virus entry and virus neutralization by antibodies and will facilitate their functional and structural characterization.ImportanceStructural information on the surface envelope proteins of lentiviruses and related betaretroviruses is critical to understand mechanisms of virus-host interactions. However, experimental determination of these structures has been challenging and only the structure of the human immunodeficiency virus type 1 gp120 has been determined. The advent of the AlphaFold artificial intelligence method for structure prediction allows high-quality modeling of the structures of small ruminant lentiviral and betaretroviral surface envelope proteins. The models are consistent with much of previously described experimental data, show regions likely to interact with receptors and identify domains that may be involved in mechanisms of antibody neutralization resistance in the small ruminant lentiviruses. The models will allow more precise design of mutants to further determine mechanisms of viral entry and immune evasion in this group of viruses and constructs for structure of these surface envelope proteins.