bluuebunny/crossref_metadata_2025_split huggingface dataset:
Swimming direction of the glass catfish is responsive to magnetic stimulation
Authors: Hunt Ryan D. , Ashbaugh Ryan C. , Reimers Mark , Udpa Lalita , De Jimenez Gabriela Saldana , Moore Michael , Gilad Assaf A. , Pelled Galit 
Published: August 2020

AbstractSeveral marine species have developed a magnetic perception that is essential for navigation and detection of prey and predators. One of these species is the transparent glass catfish that contains an ampullary organ dedicated to sense magnetic fields. Here we examine the behavior of the glass catfish in response to static magnetic fields which will provide valuable insight on function of this magnetic response. By utilizing state of the art animal tracking software and artificial intelligence approaches, we quantified the effects of magnetic fields on the swimming direction of glass catfish. The results demonstrate that glass catfish placed in a radial arm maze, consistently swim away from magnetic fields over 20 µT and show adaptability to changing magnetic field direction and location.
SEMplMe: A tool for integrating DNA methylation effects in transcription factor binding affinity predictions
Authors: Nishizaki Sierra S. , Boyle Alan P. 
Published: August 2020

AbstractMotivationAberrant DNA methylation in transcription factor binding sites has been shown to lead to anomalous gene regulation that is strongly associated with human disease. However, the majority of methylation-sensitive positions within transcription factor binding sites remain unknown. Here we introduce SEMplMe, a computational tool to generate predictions of the effect of methylation on transcription factor binding strength in every position within a transcription factor’s motif.ResultsSEMplMe uses ChIP-seq and whole genome bisulfite sequencing to predict effects of methylation within binding sites. SEMplMe validates known methylation sensitive and insensitive positions within a binding motif, identifies cell type specific transcription factor binding driven by methylation, and outperforms SELEX-based predictions for CTCF. These predictions can be used to identify aberrant sites of DNA methylation contributing to human disease.Availability and ImplementationSEMplMe is available fromhttps://github.com/Boyle-Lab/SEMplMe.Contactapboyle@umich.eduSupplementary InformationSupplementary data are available atBioinformaticsonline.
Sub-optimal Discontinuous Current-Clamp switching rates lead to deceptive mouse neuronal firing
Authors: Manuel Marin 
Published: August 2020

AbstractIntracellular recordings using sharp microelectrodes often rely on a technique called Discontinuous Current-Clamp to accurately record the membrane potential while injecting current through the same microelectrode. It is well known that a poor choice of DCC switching rate can lead to under-or over-estimation of the cell potential, however, its effect on the cell firing is rarely discussed. Here, we show that sub-optimal switching rates lead to an overestimation of cell excitability. We performed intracellular recordings of mouse spinal motoneurons and recorded their firing in response to pulses and ramps of current in Bridge and DCC mode at various switching rates. We demonstrate that using an incorrect (too low) DCC frequency leads not only to an underestimation of the input resistance, but also, paradoxically, to an artificial overestimation of the firing of these cells: neurons fire at lower current, and at higher frequencies than at higher DCC rates, or than the same neuron recorded in Bridge mode. These effects are dependent on the membrane time constant of the recorded cell, and special care needs to be taken in large cells with very short time constants. Our work highlights the importance of choosing an appropriate DCC switching rate to obtain not only accurate membrane potential readings but also an accurate representation of the firing of the cell.Significance StatementDiscontinuous Current-Clamp is a technique often used during intracellular recordings in vivo. However, incorrect usage of this technique can lead to incorrect interpretations. Poor choice of the DCC switching rate can lead to under- or over-estimation of the cell potential. In addition, we show here that sub-optimal switching rates lead to an overestimation of the cell excitability.
Bisbee: A proteomics validated analysis package for detecting differential splicing, identifying splice outliers, and predicting splice event protein effects
Authors: Halperin Rebecca F. , Hegde Apurva , Lang Jessica D. , Raupach Elizabeth A. ,   C4RCD Research Group, Legendre Christophe , Liang Winnie S. , LoRusso Patricia M. , Sekulic Aleksandar , Sosman Jeffrey A. , Trent Jeffrey M. , Rangasamy Sampathkumar , Pirrotte Patrick , Schork Nicholas J. 
Published: August 2020

AbstractHere we present a novel statistical approach to splicing outlier and differential splicing detection, implemented in a software package called Bisbee. We leverage Bisbee’s prediction of protein level effects to benchmark using matched RNAseq and mass spectrometry data from normal tissues. Bisbee exhibits improved sensitivity and specificity over existing approaches. We applied Bisbee to confirm a pathogenic splicing event in a rare disease and to identify tumor-specific splice isoforms associated with an oncogenic splice factor mutation. We also identified common tumor associated splice isoforms replicated in an independent dataset, demonstrating the utility of Bisbee in discovering disease relevant splice variants.
Predicting identity-preserving object transformations across the human ventral visual stream
Authors: Mocz Viola , Vaziri-Pashkam Maryam , Chun Marvin , Xu Yaoda 
Published: August 2020

AbstractIn everyday life, we have no trouble recognizing and categorizing objects as they change in position, size, and orientation in our visual fields. This phenomenon is known as object invariance. Previous fMRI research suggests that higher-level object processing regions in the human lateral occipital cortex may link object responses from different affine states (i.e. size and viewpoint) through a general linear mapping function with the learned mapping capable of predicting responses of novel objects. In this study, we extended this approach to examine the mapping for both Euclidean (e.g. position and size) and non-Euclidean (e.g. image statistics and spatial frequency) transformations across the human ventral visual processing hierarchy, including areas V1, V2, V3, V4, ventral occipitotemporal cortex (VOT), and lateral occipitotemporal cortex (LOT). The predicted pattern generated from a linear mapping could capture a significant amount, but not all, of the variance of the true pattern across the ventral visual pathway. The derived linear mapping functions were not entirely category independent as performance was better for the categories included in the training. Moreover, prediction performance was not consistently better in higher than lower visual regions, nor were there notable differences between Euclidean and non-Euclidean transformations. Together, these findings demonstrate a near-orthogonal representation of object identity and non-identity features throughout the human ventral visual processing pathway, with the non-identity features largely untangled from the identity features early in the visual processing.Significance StatementPresently we still do not fully understand how object identity and non-identity (e.g. position, size) information are simultaneously represented in the primate ventral visual system to form invariant representations. Previous work suggests that the human lateral occipital cortex may be linking different affine states of object representations through general linear mapping functions. Here we show that across the entire human ventral processing pathway, we could link object responses in different states of non-identity transformations through linear mapping functions for both Euclidean and non-Euclidean transformations. These mapping functions are not identity-independent, suggesting that object identity and non-identity features are represented in a near, rather than a completely, orthogonal manner.
Intercellular Arc signaling regulates vasodilation
Authors: Barragan-Iglesias Paulino , de la Peña June Bryan , Lou Tzu-Fang , Loerch Sarah , Kunder Nikesh , Shukla Tarjani , Basavarajappa Lokesh , Song Jane , Megat Salim , Moy Jamie K. , Wanghzou Andi , Ray Pradipta R. , Shepherd Jason , Hoyt Kenneth , Steward Oswald , Price Theodore J. , Campbell Zachary T. 
Published: August 2020

ABSTRACTInjury responses require communication between different cell types in the skin. Sensory neurons contribute to inflammation and can secrete signaling molecules that affect non-neuronal cells. Despite the pervasive role of translational regulation in nociception, the contribution of activity-dependent protein synthesis to inflammation is not well understood. To address this problem, we examined the landscape of nascent translation in DRG neurons treated with inflammatory mediators using ribosome profiling. We identified the activity-dependent gene, Arc, as a target of privileged translationin vitroandin vivo. Inflammatory cues promote local translation of Arc in the skin. Arc deficient mice display exaggerated paw temperatures and vasodilation in response to an inflammatory challenge. Since Arc has recently been shown to be released from neurons in extracellular vesicles, we hypothesized that intercellular Arc signaling regulates the inflammatory response in skin. We found that the excessive thermal responses and vasodilation observed in Arc defective mice are rescued by injection of Arc-containing extracellular vesicles into the skin. Our findings suggest that activity-dependent production of Arc in afferent fibers regulates neurogenic inflammation through intercellular signaling.HIGHLIGHTSRibosome profiling identifies Arc as a target of activity-dependent translationArc is present in the DRG, spinal cord, and skinInduced Arc biosynthesis in skin requires the presence of afferent fibersArc-deficient mice have exaggerated inflammation that is rescued by Arc-containing extracellular vesicles
Hydroxychloroquine: mechanism of action inhibiting SARS-CoV2 entry
Authors: Yuan Zixuan , Pavel Mahmud Arif , Wang Hao , Hansen Scott B. 
Published: August 2020

ABSTRACTHydroxychloroquine (HCQ) has been proposed in the treatment of SARS-coronavirus 2 (SARS-CoV-2) infection, albeit with much controversy.In vitro, HCQ effectively inhibits viral entry, but its use in the clinic has been hampered by conflicting results. A better understanding of HCQ’s mechanism of actionsin vitrois needed to resolve these conflicts. Recently, anesthetics were shown to disrupt ordered monosialotetrahexosylganglioside1 (GM1) lipid rafts. These same lipid rafts recruit the SARS-CoV-2 surface receptor angiotensin converting enzyme 2 (ACE2) to an endocytic entry point, away from phosphatidylinositol 4,5 bisphosphate (PIP2) domains. Here we employed super resolution imaging of cultured mammalian cells to show HCQ directly perturbs GM1 lipid rafts and inhibits the ability of ACE2 receptor to associate with the endocytic pathway. HCQ also disrupts PIP2domains and their ability to cluster and sequester ACE2. Similarly, the antibiotic erythromycin inhibits viral entry and both HCQ and erythromycin decrease the antimicrobial host defense peptide amyloid beta in cultured cells. We conclude HCQ is an anesthetic-like compound that disrupts GM1 lipid rafts similar to anesthetics. The disruption likely decreases viral clustering at both endocytic and putative PIP2entry points.KEY POINTSQuestion:What is the molecular basis for antiviral activity of hydroxychloroquine?Findings:Hydroxychloroquine disrupt lipid rafts similar to general anesthetics.Meaning:Since lipids cluster ACE2 and facilitate viral entry, hydroxychloroquine appears to inhibit viral entry by disrupting the lipid clustering of the SARS-CoV2 receptor.
Genome-wide predictions of genetic redundancy inArabidopsis thaliana
Authors: Cusack Siobhan A. , Wang Peipei , Moore Bethany M. , Meng Fanrui , Conner Jeffrey K. , Krysan Patrick J. , Lehti-Shiu Melissa D. , Shiu Shin-Han 
Published: August 2020

ABSTRACTGenetic redundancy refers to a situation where an individual with a loss-of-function mutation in one gene (single mutant) does not show an apparent phenotype until one or more paralogs are also knocked out (double/higher-order mutant). Previous studies have identified some characteristics common among redundant gene pairs, but a predictive model of genetic redundancy incorporating a wide variety of features has not yet been established. In addition, the relative importance of these characteristics for genetic redundancy remains unclear. Here, we establish machine learning models for predicting whether a gene pair is likely redundant or not in the model plantArabidopsis thaliana. Benchmark gene pairs were classified based on six feature categories: functional annotations, evolutionary conservation including duplication patterns and mechanisms, epigenetic marks, protein properties including post-translational modifications, gene expression, and gene network properties. The definition of redundancy, data transformations, feature subsets, and machine learning algorithms used affected model performance significantly. Among the most important features in predicting gene pairs as redundant were having a paralog(s) from recent duplication events, annotation as a transcription factor, downregulation during stress conditions, and having similar expression patterns under stress conditions. Predictions were then tested using phenotype data withheld from model building and validated using well-characterized, redundant and nonredundant gene pairs. This genetic redundancy model sheds light on characteristics that may contribute to long-term maintenance of paralogs that are seemingly functionally redundant, and will ultimately allow for more targeted generation of functionally informative double mutants, advancing functional genomic studies.
Maternalschistosomiasisimpairs offspring IL-4 production and B cell expansion
Authors: Cortes-Selva Diana , Gibbs Lisa , Ready Andrew , Ekiz H. Atakan , Rajwa Bartek , Fairfax Keke C. 
Published: August 2020

SummaryMaternal helminth infections are a global public health concern and correlate with altered infant immune responses to some childhood immunizations, but a mechanistic understanding of how maternal helminth infection alters the cellular immune responses of offspring is lacking. Here we establish a model of maternalSchistosoma mansoniinfection in dual IL-4 reporter mice. We find that offspring born to mothers infected withS. mansonihave impaired production of IL-4 during homoeostasis, and following immunization with a Tetanus-Diphtheria vaccine. We identified that iNKT cells are the dominant source of IL-4 during early life homeostasis, and that diminished IL-4 production was associated with both reduced B cell and follicular dendritic cell responses. These defects were maintained long-term, affecting memory B and T cell responses. Single-cell RNASeq analysis of immunized offspring identified egg antigen-dependent reductions in B-cell cell cycle and proliferation-related genes. These data reveal that maternal infection leads to long-lasting defects in the cellular responses to heterologous antigens and provide vital insight into the influence of maternal infection on offspring immunity.
Transient delivery of A-C/EBP protein perturbs differentiation of 3T3-L1 cells and induces preadipocyte marker genes
Authors: Sharma Nishtha , Kaur Raminder , Yadav Binduma , Shah Koushik , Pandey Harshita , Choudhary Diksha , Jain Prateek , Aggarwal Aanchal , Vinson Charles , Rishi Vikas 
Published: August 2020

AbstractTransformation of committed 3T3-L1 preadipocytes to lipid-laden adipocytes involves timely appearance of numerous transcription factors (TFs), foremost among them C/EBPβ, is expressed during early phases of differentiation. Here we describe liposome-mediated protein transfection approach to rapidly downregulate C/EBPβ by A-C/EBP protein inhibitor. Signals from tagged A-C/EBP were observed in 3T3-L1 cells within 2hrs of protein inhibitor transfections whereas for gene transfection signals appeared in 48hrs. Following transient transfections, expression profiles of 24 marker genes belonging to pro- and anti-adipogenic, cell cycle, and preadipocytes pathways was analyzed. mRNA and protein expression profiles of adipocyte-marker genes showed lower expression in both A-C/EBP protein and gene transfected samples. Interestingly, for preadipocytes and cell fate determinant genes, striking differences were observed between protein and gene transfected samples. Preadipocyte differentiation factors Stat5a and Creb were downregulated in A-C/EBP protein samples. Five preadipocyte markers, namely,Pdgfrα, Pdgfrβ, Ly6A, CD34 Itgb1showed high expression in protein samples whereas onlyLy6AandCD34were expressed in gene transfected samples.PdgfrαandPdgfrβ, two known cell fate markers were expressed in protein transfected samples 5-days post-differentiation suggesting a possible reversal of differentiation. Our study provides evidences for the robust and efficient knockdown of C/EBPβ protein to understand time-dependent gene regulation during adipogenesis.
At least seven distinct rotavirus genotype constellations in bats with evidence of reassortment and zoonotic transmissions
Authors: Simsek Ceren , Corman Victor Max , Everling Hermann Ulrich , Lukashev Alexander N. , Rasche Andrea , Maganga Gael Darren , Binger Tabea , Jansen Daan , Beller Leen , Deboutte Ward , Gloza-Rausch Florian , Seebens-Hoyer Antje , Yordanov Stoian , Sylverken Augustina , Oppong Samuel , Sarkodie Yaw Adu , Vallo Peter , Leroy Eric M. , Bourgarel Mathieu , Yinda Kwe Claude , Van Ranst Marc , Drosten Christian , Drexler Jan Felix , Matthijnssens Jelle 
Published: August 2020

ABSTRACTBats host many viruses pathogenic to humans, and increasing evidence suggests that Rotavirus A (RVA) also belongs to this list. Rotaviruses cause diarrheal disease in many mammals and birds, and their segmented genomes allow them to reassort and increase their genetic diversity. Eighteen out of 2,142 bat fecal samples (0.8%) collected from Europe, Central America and Africa were PCR-positive for RVA and 11 of those were fully characterized using viral metagenomics. Upon contrasting their genomes with publicly available data, at least 7 distinct bat RVA genotype constellations (GCs) were identified, including evidence of reassortments and 6 novel genotypes. Some of these constellations are spread across the world, whereas others appear to be geographically restricted. Our analyses also suggest that several unusual human and equine RVA strains might be of bat RVA origin, based on their phylogenetic clustering, despite varying levels of nucleotide sequence identities between them. Although SA11 is one of the most widely used reference strains for RVA research and forms the backbone of a reverse genetics system, its origin remained enigmatic. Remarkably, the majority of the genotypes of SA11-like strains were shared with Gabonese bat RVAs, suggesting a potential common origin. Overall, our findings suggest an underexplored genetic diversity of RVAs in bats, which is likely only the tip of the iceberg. Increasing contact between humans and bat wildlife will further increase the zoonosis risk, which warrants closer attention to these viruses.ImportanceThe increased research on bat coronaviruses after SARS-CoV and MERS-CoVallowed the very rapid identification of SARS-CoV-2. This is an excellent example of the importance of knowing viruses harbored by wildlife in general and bats in particular, for global preparedness against emerging viral pathogens. The current effort to characterize bat rotavirus strains from 3 continents shed light on the vast genetic diversity of rotaviruses and also hinted at a bat origin for several atypical rotaviruses in humans and animals, implying that zoonoses of bat rotaviruses might occur more frequently than currently realized.
The proteasome-related Connectase is a fast and specific protein ligase
Authors: Fuchs Adrian C. D. , Ammelburg Moritz , Martin Jörg , Hartmann Marcus D. , Lupas Andrei N. 
Published: August 2020

AbstractGenetic methods allow the recombinant production of any protein of interest, but yield the full-length construct in one step and are limited to native amino acids. For the “on demand” generation of chimeric, immobilized, fluorophore-conjugated or segmentally labeled proteins, these proteins must be modified using chemical1,2, (split) intein2,3, split domain4or enzymatic methods5. While each of these options comes with its own advantages and drawbacks, ligase enzymes are often used where small ligation motifs and good chemoselectivity are required. However, applications with the reference enzyme Sortase A are impeded by poor catalytic efficiencies, low substrate specificities and side reactions6,7. Here, we present the discovery of Connectase, a monomeric proteasome homolog that ligates substrates via a highly conserved KDPGA motif originally identified in methyltransferase A (MtrA), a key enzyme in archaeal methanogenesis. Connectase displays nanomolar affinity and thus great specificity for its substrates, allowing efficient protein-protein ligations even in complex solutions and at low substrate concentrations. Compared to an optimized Sortase variant, Connectase catalyzes such ligations at substantially higher rates, with higher yields but without detectable side reactions and thus presents a valuable new tool for protein conjugations.
Identifying causes of social evolution: The Price approach, contextual analysis, and multilevel selection
Authors: Thies Christoph , Watson Richard A. 
Published: August 2020

AbstractKin selection theory and multilevel selection theory are different approaches to explaining the evolution of social traits. The latter claims that it is useful to regard selection as a process that can occur on multiple levels of organisation such as the level of individuals and the level of groups. This is reflected in a decomposition of fitness into an individual component and a group component. However, the two major statistical tools to determine the coefficients of such a decomposition, the multilevel Price equation and contextual analysis, are inconsistent and may disagree on whether group selection is present. Here we show that the reason for the discrepancies is that underlying the multilevel Price equation and contextual analysis are two nonequivalent causal models for the generation of individual fitness effects (thus leaving different ‘remainders’ explained by group effects). While the multilevel Price equation assumes that the individual effect of a trait determines an individual’s relative success within a group, contextual analysis posits that the individual effect is context-independent. Since these different assumptions reflect claims about the causal structure of the system, the correct approach cannot be determined on general theoretical or statistical grounds but must be identified by experimental intervention. We outline interventions that reveal the underlying causal structure and thus facilitate choosing the appropriate approach. We note that the reductionist viewpoint of kin selection theory with its focus on the individual is immune to such inconsistency because it does not address causal structure with respect to levels of organisation. In contrast, our analysis of the two approaches to measuring group selection demonstrates that multilevel selection theory adds meaningful (falsifiable) causal structure to explain the sources of individual fitness and thereby constitutes a proper refinement of kin selection theory.