bluuebunny/crossref_metadata_2025_split huggingface dataset:
A new paradigm for personal protection against ticks: efficacy of spatial repellents to reduce host seeking activities in three major tick species of medical importance
Authors: Siegel Eric L. , Olivera Marcos , Roig Esteban Martinez , Perry Melynda , Li Andrew Y. , D’hers Sebastián , Elman Noel M. , Rich Stephen M. 
Published: May 2022

AbstractAddressing the prevalence of tick-borne disease requires robust chemical options as an integral component of Integrative Vector Management (IVM) program. Spatial repellency is a novel concept in tick bite prevention. To date, there is no standard for the evaluation of spatial repellency against ticks, despite the speculated value of volatilized chemicals in control systems. This study reports a novel vertical climb assay that was specifically created for the quantitative evaluation of spatial repellency in ticks. Controlled release devices (CRDs) were used to control the dispersion of multiple Active Ingredients (AIs) transfluthrin, metofluthrin, nootkatone, and DEET against adult females of three medically important tick species: Dermacentor variabilis, Amblyomma americanum, and Ixodes scapularis. Results of our study indicate significant associations between AI exposure and changing in tick climbing behavior when compared controls in the absence of the AI, from several perspectives, including changes in tick movement velocity, displacement, detachment, and rate of successful vertical climbing. Metofluthrin and transfluthrin caused strong reductions in host seeking activities against D. variabilis and A. americanum, while both demonstrated slightly weaker effects against I. scapularis. Further work is planned to evaluate spatial repellency in ticks in more natural environments and assess their potential in future tick control programs.
Comprehensive benchmark and architectural analysis of deep learning models for Nanopore sequencing basecalling
Authors: Pagès-Gallego Marc , de Ridder Jeroen 
Published: May 2022

AbstractNanopore-based DNA sequencing relies on basecalling the electric current signal. Basecalling requires neural networks to achieve competitive accuracies. To improve sequencing accuracy further, new models are continuously proposed. However, benchmarking is currently not standardized, and evaluation metrics and datasets used are defined on a per publication basis, impeding progress in the field. To standardize the process of benchmarking, we unified existing benchmarking datasets and defined a rigorous set of evaluation metrics. We benchmarked the latest seven basecaller models and analyzed their deep learning architectures. Our results show that overall Bonito has the best architecture for basecalling. We find, however, that species bias in training can have a large impact on performance. Our comprehensive evaluation of 90 novel architecture demonstrates that different models excel at reducing different types of errors and using RNNs (LSTM) and a CRF decoder are the main drivers of high performing models.
Pig manure treatment strategies for mitigating the spread of antibiotic resistance
Authors: Zalewska Magdalena , Błażejewska Aleksandra , Czapko Agnieszka , Popowska Magdalena 
Published: May 2022

AbstractOne of the most important public health challenges facing the world today is that posed by antibiotic resistance. Many pathogenic antibiotic-resistant bacteria and their antibiotic resistance genes, usually located on mobile genetic elements, are frequently present in the faeces of farm animals. To prevent the possibility of antimicrobial resistance transfer to the environment, these faeces should undergo treatment before being used as natural fertilizer. The two strategies for processing pig manure proposed in this study, viz. storage (most commonly used for livestock manure today) and composting, are cheap and do not require special tools or technologies. The present study examines the changes in the physicochemical properties of treated manure, in the microbiome, through metagenomic sequencing, and in the resistome, using the SmartChip Real-time PCR system compared to raw manure. This is the first such comprehensive analysis performed on the same batch of manure. Our results suggest that while none of the processes completely eliminates the environmental risk, composting results in a faster and more pronounced reduction of mobile genetic elements harbouring antibiotic resistance genes, including those responsible for multi-drug resistance. The physicochemical parameters of the treated manure are comparable after both processes; however, composting resulted in significantly higher organic matter. Overall, it appears that the composting process can be an efficient strategy for mitigating the spread of antibiotic resistance in the environment and reducing the risk of its transfer to agricultural crops and hence, the food chain. It also provides the organic matter necessary for humus formation, and increases the sorption properties of the soil and the micro and macro elements necessary for plant growth, which in turn translates into increased soil productivity.HighlightsThe changes in microbial population composition correlate with changes in specific antibiotic-resistance genes and mobile genetic elements in the studied populations.Positive correlations have been demonstrated between microbial phyla and genes coding the multi-drug resistance mechanismCo-occurrence networks showed positive correlations between antibiotic-resistance genes and mobile genetic elementsThe composting strategy was most efficient at reducing microbial loads, antibiotic resistance genes and mobile genetic elements.Composted manure can be part of a natural, safe soil fertilization strategy.
Nature-Inspired Chemical Probes for in-cell Labeling of Lipidized RNA and Identification of New Regulatory Enzymes
Authors: Zhou Hongling , Li Yuanyuan , Zhang Jingwen , Wang Li , Zheng Ya Ying , Begley Thomas J. , Sheng Jia , Wang Rui 
Published: May 2022

AbstractRNA modifications play pivotal roles in numerous cellular processes and human diseases. In addition to well-studied methyl-based modifications, hydrophobic prenyl-modifications have also been found in many RNA species. Here we report two chemical labeling strategies for tagging lipid-modified RNAs by taking advantage of a natural SelU-mediated tRNA geranylation process and the special reactivity of prenyl-groups. We synthesized a series of ‘clickable’ geranyl-pyrophosphate analogs and identified two candidates for indirect RNA labeling using a two-step process,azidation-and-click-tagging offluorescent dyes, namely ACT-Flu. We also developed a directmetabolicincorporation andbiorthogonal tagging (MIBT-Tag) method based on the Ene-ligation of prenyl-groups. Both methods have been successfully applied to in-cell RNA labeling and the identification of new proteins associated with the geranylation process through proteomic and bioinformatic studies. These biochemical toolsets enable furtherin vivoapplications to study prenylation pathways and monitor their status in both healthy and diseased cells.
Rtapas: An R package to assess cophylogenetic signal between two evolutionary histories
Authors: Llaberia-Robledillo Mar , Lucas-Lledó J. Ignacio , Pérez-Escobar Oscar Alejandro , Krasnov Boris R. , Balbuena Juan Antonio 
Published: May 2022

ABSTRACTCophylogeny represents a framework to understand how ecological and evolutionary process influence lineage diversification. However, linking patterns to mechanisms remains a major challenge. The recently developed Random Tanglegram Partitions provides a directly interpretable statistic to quantify the strength of cophylogenetic signal, maps onto a tanglegram the contribution to phylogenetic signal of individual host-symbiont associations, and can incorporate phylogenetic uncertainty into estimation of cophylogenetic signal. We introduce Rtapas (v1.2), an R package to perform Random Tanglegram Partitions. Rtapas applies a given global-fit method to random partial tanglegrams of a fixed size to identify the associations, terminals, and nodes that maximize phylogenetic congruence. Rtapas extends the original implementation with a new algorithm that tests phylogenetic incongruence and adds ParaFit, a method designed to test for topological congruence between two phylogenies using patristic distances, to the list of global-fit methods than can be applied. Rtapas can particularly cater for the need for causal inference in cophylogeny as demonstrated herein using to two real-world systems. One involves assessing topological (in)congruence between phylogenies produced with different DNA markers and identifying the particular associations that contribute most to topological incongruence, whereas the other implies analyzing the evolutionary histories of symbiont partners in a large dataset. Rtapas facilitates and speeds up cophylogenetic analysis, as it can handle large phylogenies reducing computational time, and is directly applicable to any scenario that may show phylogenetic congruence (or incongruence).
Simulating structurally variable Nuclear Pore Complexes for Microscopy
Authors: Theiss Maria , Hériché Jean-Karim , Russell Craig , Helekal David , Soppitt Alisdair , Ries Jonas , Ellenberg Jan , Brazma Alvis , Uhlmann Virginie 
Published: May 2022

AbstractMotivationThe Nuclear Pore Complex (NPC) is the only passageway for macromolecules between nucleus and cytoplasm, and one of localization microscopy’s most important reference standards: it is massive and stereotypically arranged. The average architecture of NPC proteins has been resolved with pseudo-atomic precision, however observed NPC heterogeneities evidence a high degree of divergence from this average. Single Molecule Localization Microscopy (SMLM) images NPCs at protein-level resolution, whereupon image analysis software studies NPC variability. However the true picture of NPC variability is unknown. In quantitative image analysis experiments, it is thus difficult to distinguish intrinsically high SMLM noise from true variability of the underlying structure.ResultsWe introduce CIR4MICS (“ceramics”, Configurable, Irregular Rings FOR MICroscopy Simulations), a pipeline that creates artificial datasets of structurally variable synthetic NPCs based on architectural models of the true NPC. Users can select one or more N- or C-terminally tagged NPC proteins, and simulate a wide range of geometric variations. We also represent the NPC as a spring-model such that arbitrary deforming forces, of user-defined magnitudes, simulate irregularly shaped variations. We provide an open-source simulation pipeline, as well as reference datasets of simulated human NPCs. Accompanying ground truth annotations allow to test the capabilities of image analysis software and facilitate a side-by-side comparison with real data. We demonstrate this by synthetically replicating a geometric analysis of real NPC radii and reveal that a wide range of simulated variability parameters can lead to observed results. Our simulator is therefore valuable to benchmark and develop image analysis methods, as well as to inform experimentalists about the requirements of hypothesis-driven imaging studies.AvailabilityCode:https://github.com/uhlmanngroup/cir4mics. Simulated data is available at BioStudies (Accession number S-BSST1058).Contacttheiss@ebi.ac.ukSupplementary informationSupplementary data are available at
Structure Activity Relationship of the Stem Peptide in Sortase A mediated Ligation from Staphylococcus aureus
Authors: Apostolos Alexis J. , Kelly Joey J. , Ongwae George G. , Pires Marcos M. 
Published: May 2022

AbstractThe surfaces of most Gram-positive bacterial cells, including that of Staphylococcus aureus (S. aureus), are heavily decorated with proteins that coordinate cellular interactions with the extracellular space. In S. aureus, sortase A is the principal enzyme responsible for covalently anchoring proteins, which display the sorting signal LPXTG, onto the peptidoglycan (PG) matrix. Considerable efforts have been made to understand the role of this signal peptide in the sortase-mediated reaction. In contrast, much less is known about how the primary structure of the other substrate involved in the reaction (PG stem peptide) could impact sortase activity. To assess the sortase activity, a library of synthetic analogs of the stem peptide that mimic naturally existing variations found in the S. aureus PG primary sequence were evaluated. Using a combination of two unique assays, we showed that there is broad tolerability of substrate variations that are effectively processed by sortase A. While some of these stem peptide derivatives are naturally found in mature PG, they are not known to be present in the PG precursor, lipid II. These results suggest that sortase A could process both lipid II and mature PG as acyl-acceptor strands, which has not been previously described.
CRISPR/Cas9-Mediated Excision of ALS/FTD-Causing Hexanucleotide Repeat Expansion in C9ORF72 rescues major disease mechanisms in vivo and in vitro
Authors: Meijboom Katharina E. , Abdallah Abbas , Fordham Nicholas P. , Nagase Hiroko , Rodriguez Tomás , Kraus Carolyn , Gendron Tania F. , Krishnan Gopinath , Esanov Rustam , Andrade Nadja S. , Rybin Matthew J. , Ramic Melina , Stephens Zachary D. , Edraki Alireza , Blackwood Meghan T. , Kahriman Aydan , Henninger Nils , Kocher Jean-Pierre A. , Benatar Michael , Brodsky Michael H. , Petrucelli Leonard , Gao Fen-Biao , Sontheimer Erik J. , Brown Robert H. , Zeier Zane , Mueller Christian 
Published: May 2022

AbstractA hexanucleotide repeat expansion (HRE) consisting of GGGGCC24+ in the C9ORF72 gene is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Both are fatal neurodegenerative diseases with no current approved treatments that significantly slow disease progression or extend life expectancy. Several hypotheses have emerged to explain how this HRE causes neuronal death, including C9ORF72 haploinsufficiency, sequestration of RNA-binding proteins in the nucleus, and production of dipeptide repeat proteins. In the present study we used a CRISPR/Cas9 gene-editing approach to remove the HRE from the C9ORF72 genomic locus, designing guide RNAs (gRNAs) flanking the HRE, and delivered Cas9 and gRNAs using adeno-associated virus serotype 9 (AAV9) vectors. Here, we demonstrate successful excision of the HRE in C9ORF72 in primary cortical neurons and brains of three mouse models containing the C9ORF72 expanded HRE (ranging from 500-600 repeats) as well as in patient-derived iPSC motor neurons and brain organoids (450 repeats). This resulted in a reduction of RNA foci, poly-dipeptides and haploinsufficiency, the major hallmarks of C9-ALS/FTD, making this an extremely attractive therapeutic approach to these diseases.
INSISTC: Incorporating Network Structure Information for Single-Cell Type Classification
Authors: Zheng Hansi , Wang Saidi , Li Xiaoman , Hu Haiyan 
Published: May 2022

AbstractMotivationUncovering gene regulatory mechanisms in individual cells can provide insight into cell heterogeneity and function. Recent accumulated single-cell RNA sequencing data have made it possible to analyze gene regulation at single-cell resolution. On the other hand, understanding cell-type-specific gene regulation can also assist in more accurate cell type and state identification. Computational approaches utilizing gene regulatory relationships for single-cell type classification are under development. Methods pioneering in integrating gene regulatory mechanism discovery with cell-type classification encounter challenges such as how to accurately determine gene regulatory relation-ships and how to incorporate gene regulatory network structure into consideration.ResultsWe developed a computational method to incorporate gene regulatory network structure information for single-cell type classification (INSISTC). INSISTC is capable of identifying cell-type-specific gene regulatory mechanisms while performing single cell type classification. Tested on three mouse scRNA-Seq datasets, including thousands of single-cell samples, INSISTC demonstrated its accuracy in cell type classification and its potential for providing insight into molecular mechanisms specific to individual cells. In comparison with the alternative methods, INSISTC demonstrated its complementary performance for gene regulation interpretation.Availabilityhttps://hulab.ucf.edu/research/projects/INSISTC/Contacthaihu@cs.ucf.eduorxiaoman@mail.ucf.eduSupplementary informationSupplementary data are available at xxxxxx online.
Adaptation-proof SARS-CoV-2 vaccine design
Authors: Vishweshwaraiah Yashavantha L. , Hnath Brianna , Rackley Brendan , Wang Jian , Gontu Abhinay , Chandler Morgan , Afonin Kirill A. , Kuchipudi Suresh V. , Christensen Neil , Yennawar Neela H. , Dokholyan Nikolay V. 
Published: May 2022

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) surface spike glycoprotein - a major antibody target - is critical for virus entry via engagement of human angiotensin-converting enzyme 2 (ACE2) receptor. Despite successes with existing vaccines and therapies that primarily target the receptor binding domain (RBD) of the spike protein, the susceptibility of RBD to mutations provides escape routes for the SARS-CoV-2 from neutralizing antibodies. On the other hand, structural conservation in the spike protein can be targeted to reduce escape mutations and achieve broad protection. Here, we designed candidate stable immunogens that mimic surface features of selected conserved regions of spike protein through ‘epitope grafting,’ in which we present the target epitope topology on diverse heterologous scaffolds that can structurally accommodate the spike epitopes. Structural characterization of the epitope-scaffolds showed stark agreement with our computational models and target epitopes. The sera from mice immunized with engineered designs display epitope-scaffolds and spike binding activity. We also demonstrated the utility of the designed epitope-scaffolds in diagnostic applications. Taken all together, our study provides important methodology for targeting the conserved, non-RBD structural motifs of spike protein for SARS-CoV-2 epitope vaccine design and demonstrates the potential utility of ‘epitope grafting’ in rational vaccine design.
Bayesian statistics improves biological interpretability of metabolomics data from human cohorts
Authors: Brydges Christopher , Che Xiaoyu , Lipkin W. Ian , Fiehn Oliver 
Published: May 2022

AbstractBackgroundUnivariate analyses of metabolomics data currently follow a frequentist approach, using p-values to reject a null-hypothesis. However, the usability ofp-values is plagued by many misconceptions and inherent pitfalls. We here propose the use of Bayesian statistics to quantify evidence supporting different hypotheses and discriminate between the null hypothesis versus lack of statistical power.MethodsWe use metabolomics data from three independent human cohorts that studied plasma signatures of subjects with myalgic encephalomyelitis / chronic fatigue syndrome (ME/CFS). Data are publicly available, covering 84-197 subjects in each study with 562-888 identified metabolites of which 777 were common between two studies, and 93 compounds reported in all three studies. By comparing results from classic multiple regression against Bayesian multiple regression we show how Bayesian statistics incorporates results from one study as ‘prior information’ into the next study, thereby improving the overall assessment of the likelihood of finding specific differences between plasma metabolite levels and disease outcomes in ME/CFS.ResultsWhereas using classic statistics and Benjamini-Hochberg FDR-corrections, study 1 detected 18 metabolic differences, study 2 detected no differences. Using Bayesian statistics on the same data, we found a high likelihood that 97 compounds were altered in concentration in study 2, after using the results of study 1 as prior distributions. These findings included lower levels of peroxisome-produced ether-lipids, higher levels of long chain, unsaturated triacylglycerides, and the presence of exposome compounds that are explained by difference in diet and medication between healthy subjects and ME/CFS patients. Although study 3 reported only 92 reported compounds in common with the other two studies, these major differences were confirmed. We also found that prostaglandin F2alpha, a lipid mediator of physiological relevance, was significantly reduced in ME/CFS patients across all three studies.ConclusionsThe use of Bayesian statistics led to biological conclusions from metabolomic data that were not found through the frequentist analytical approaches more commonly employed. We propose that Bayesian statistics to be highly useful for studies with similar research designs if similar metabolomic assays are used.
EDGE2: advancing the prioritisation of threatened evolutionary history for conservation action
Authors: Gumbs Rikki , Gray Claudia L. , Böhm Monika , Burfield Ian J. , Couchman Olivia R. , Faith Daniel P. , Forest Félix , Hoffmann Michael , Isaac Nick J. B. , Jetz Walter , Mace Georgina M. , Mooers Arne O. , Safi Kamran , Scott Oenone , Steel Mike , Tucker Caroline M. , Pearse William D. , Owen Nisha R. , Rosindell James 
Published: May 2022

AbstractThe global biodiversity crisis threatens the natural world and its capacity to provide benefits to humans into the future. The conservation of evolutionary history, captured by the measure phylogenetic diversity (PD), is linked to the maintenance of these benefits and future options. The Evolutionarily Distinct and Globally Endangered (EDGE) metric has, since 2007, been used to identify species for conservation action that embody large amounts of threatened evolutionary history. In 2017, we convened a workshop to update the EDGE metric to incorporate advances in the field of phylogenetically-informed conservation. Building on that workshop, we devised the metric ‘EDGE2’, which we present here. EDGE2 uses a modular, tiered approach to provide priority rankings—and associated measures of uncertainty in both phylogenetic and extinction risk data—for all species in a clade. EDGE2 takes into account the extinction risk of closely-related species to better reflect the contribution a species is expected to make to overall PD in the future. We applied EDGE2 to the world’s mammals to identify an updated list of priority EDGE species and compare the results with the original EDGE approach. Despite similarity in the priority lists produced between EDGE and EDGE2, EDGE2 places greater priority on species with fewer close relatives on the Tree of Life. As we approach a crossroads for global biodiversity policy, EDGE2 exemplifies how academic and applied conservation biologists can collaborate to guide effective priority-setting to conserve the most irreplaceable components of biodiversity upon which humanity depends.